From cb52432159ecfea69c6df54be2cb56fd569f275f Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 8 Sep 2022 06:23:03 -0700 Subject: [PATCH 001/125] Added image classification implementation files and associated tests --- .../tasks/python/components/containers/BUILD | 10 + .../components/containers/classifications.py | 169 ++++++++++ mediapipe/tasks/python/test/vision/BUILD | 38 ++- .../test/vision/image_classification_test.py | 301 ++++++++++++++++++ mediapipe/tasks/python/vision/BUILD | 20 ++ .../python/vision/image_classification.py | 227 +++++++++++++ 6 files changed, 764 insertions(+), 1 deletion(-) create mode 100644 mediapipe/tasks/python/components/containers/classifications.py create mode 100644 mediapipe/tasks/python/test/vision/image_classification_test.py create mode 100644 mediapipe/tasks/python/vision/image_classification.py diff --git a/mediapipe/tasks/python/components/containers/BUILD b/mediapipe/tasks/python/components/containers/BUILD index 2bc951220..eb3acdd97 100644 --- a/mediapipe/tasks/python/components/containers/BUILD +++ b/mediapipe/tasks/python/components/containers/BUILD @@ -47,3 +47,13 @@ py_library( "//mediapipe/tasks/python/core:optional_dependencies", ], ) + +py_library( + name = "classifications", + srcs = ["classifications.py"], + deps = [ + ":category", + "//mediapipe/tasks/cc/components/containers:classifications_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) diff --git a/mediapipe/tasks/python/components/containers/classifications.py b/mediapipe/tasks/python/components/containers/classifications.py new file mode 100644 index 000000000..19c5decde --- /dev/null +++ b/mediapipe/tasks/python/components/containers/classifications.py @@ -0,0 +1,169 @@ +# Copyright 2022 The TensorFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Classifications data class.""" + +import dataclasses +from typing import Any, List, Optional + +from mediapipe.tasks.cc.components.containers import classifications_pb2 +from mediapipe.tasks.python.components.containers import category as category_module +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_ClassificationEntryProto = classifications_pb2.ClassificationEntry +_ClassificationsProto = classifications_pb2.Classifications +_ClassificationResultProto = classifications_pb2.ClassificationResult + + +@dataclasses.dataclass +class ClassificationEntry: + """List of predicted classes (aka labels) for a given classifier head. + + Attributes: + categories: The array of predicted categories, usually sorted by descending + scores (e.g. from high to low probability). + timestamp_ms: The optional timestamp (in milliseconds) associated to the + classification entry. This is useful for time series use cases, e.g., + audio classification. + """ + + categories: List[category_module.Category] + timestamp_ms: Optional[int] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ClassificationEntryProto: + """Generates a ClassificationEntry protobuf object.""" + return _ClassificationEntryProto( + categories=[category.to_pb2() for category in self.categories], + timestamp_ms=self.timestamp_ms) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, pb2_obj: _ClassificationEntryProto) -> 'ClassificationEntry': + """Creates a `ClassificationEntry` object from the given protobuf object.""" + return ClassificationEntry( + categories=[ + category_module.Category.create_from_pb2(category) + for category in pb2_obj.categories + ], + timestamp_ms=pb2_obj.timestamp_ms) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, ClassificationEntry): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class Classifications: + """Represents the classifications for a given classifier head. + + Attributes: + entries: A list of `ClassificationEntry` objects. + head_index: The index of the classifier head these categories refer to. + This is useful for multi-head models. + head_name: The name of the classifier head, which is the corresponding + tensor metadata name. + """ + + entries: List[ClassificationEntry] + head_index: int + head_name: str + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ClassificationsProto: + """Generates a Classifications protobuf object.""" + return _ClassificationsProto( + entries=[entry.to_pb2() for entry in self.entries], + head_index=self.head_index, + head_name=self.head_name) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _ClassificationsProto) -> 'Classifications': + """Creates a `Classifications` object from the given protobuf object.""" + return Classifications( + entries=[ + ClassificationEntry.create_from_pb2(entry) + for entry in pb2_obj.entries + ], + head_index=pb2_obj.head_index, + head_name=pb2_obj.head_name) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, Classifications): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class ClassificationResult: + """Contains one set of results per classifier head. + + Attributes: + classifications: A list of `Classifications` objects. + """ + + classifications: List[Classifications] + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ClassificationResultProto: + """Generates a ClassificationResult protobuf object.""" + return _ClassificationResultProto( + classifications=[ + classification.to_pb2() for classification in self.classifications + ]) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, pb2_obj: _ClassificationResultProto) -> 'ClassificationResult': + """Creates a `ClassificationResult` object from the given protobuf object.""" + return ClassificationResult( + classifications=[ + Classifications.create_from_pb2(classification) + for classification in pb2_obj.classifications + ]) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, ClassificationResult): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index bb495338d..a63c36b55 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -18,4 +18,40 @@ package(default_visibility = ["//mediapipe/tasks:internal"]) licenses(["notice"]) -# TODO: This test fails in OSS +py_test( + name = "object_detector_test", + srcs = ["object_detector_test.py"], + data = [ + "//mediapipe/tasks/testdata/vision:test_images", + "//mediapipe/tasks/testdata/vision:test_models", + ], + deps = [ + # build rule placeholder: numpy dep, + "//mediapipe/tasks/python/components/containers:bounding_box", + "//mediapipe/tasks/python/components/containers:category", + "//mediapipe/tasks/python/components/containers:detections", + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/test:test_util", + "//mediapipe/tasks/python/vision:object_detector", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + "@absl_py//absl/testing:parameterized", + ], +) + +py_test( + name = "image_classification_test", + srcs = ["image_classification_test.py"], + data = [ + "//mediapipe/tasks/testdata/vision:test_images", + "//mediapipe/tasks/testdata/vision:test_models", + ], + deps = [ + "//mediapipe/tasks/python/components/containers:category", + "//mediapipe/tasks/python/components/containers:classifications", + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/test:test_util", + "//mediapipe/tasks/python/vision:image_classification", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + "@absl_py//absl/testing:parameterized", + ], +) diff --git a/mediapipe/tasks/python/test/vision/image_classification_test.py b/mediapipe/tasks/python/test/vision/image_classification_test.py new file mode 100644 index 000000000..3650c547c --- /dev/null +++ b/mediapipe/tasks/python/test/vision/image_classification_test.py @@ -0,0 +1,301 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for image classifier.""" + +import enum + +from absl.testing import absltest +from absl.testing import parameterized + +from mediapipe.python._framework_bindings import image as image_module +from mediapipe.tasks.python.components.containers import category as category_module +from mediapipe.tasks.python.components.containers import classifications as classifications_module +from mediapipe.tasks.python.core import base_options as base_options_module +from mediapipe.tasks.python.test import test_util +from mediapipe.tasks.python.vision import image_classification +from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module + +_BaseOptions = base_options_module.BaseOptions +_Category = category_module.Category +_ClassificationEntry = classifications_module.ClassificationEntry +_Classifications = classifications_module.Classifications +_ClassificationResult = classifications_module.ClassificationResult +_Image = image_module.Image +_ImageClassifier = image_classification.ImageClassifier +_ImageClassifierOptions = image_classification.ImageClassifierOptions +_RUNNING_MODE = running_mode_module.VisionTaskRunningMode + +_MODEL_FILE = 'mobilenet_v2_1.0_224.tflite' +_IMAGE_FILE = 'burger.jpg' +_EXPECTED_CLASSIFICATION_RESULT = _ClassificationResult( + classifications=[ + _Classifications( + entries=[ + _ClassificationEntry( + categories=[ + _Category( + index=934, + score=0.7952049970626831, + display_name='', + category_name='cheeseburger'), + _Category( + index=932, + score=0.02732999622821808, + display_name='', + category_name='bagel'), + _Category( + index=925, + score=0.01933487318456173, + display_name='', + category_name='guacamole'), + _Category( + index=963, + score=0.006279350258409977, + display_name='', + category_name='meat loaf') + ], + timestamp_ms=0 + ) + ], + head_index=0, + head_name='probability') + ]) +_ALLOW_LIST = ['cheeseburger', 'guacamole'] +_DENY_LIST = ['cheeseburger'] +_SCORE_THRESHOLD = 0.5 +_MAX_RESULTS = 3 + + +class ModelFileType(enum.Enum): + FILE_CONTENT = 1 + FILE_NAME = 2 + + +class ImageClassifierTest(parameterized.TestCase): + + def setUp(self): + super().setUp() + self.test_image = test_util.read_test_image( + test_util.get_test_data_path(_IMAGE_FILE)) + self.model_path = test_util.get_test_data_path(_MODEL_FILE) + + def test_create_from_file_succeeds_with_valid_model_path(self): + # Creates with default option and valid model file successfully. + with _ImageClassifier.create_from_model_path(self.model_path) as classifier: + self.assertIsInstance(classifier, _ImageClassifier) + + def test_create_from_options_succeeds_with_valid_model_path(self): + # Creates with options containing model file successfully. + base_options = _BaseOptions(file_name=self.model_path) + options = _ImageClassifierOptions(base_options=base_options) + with _ImageClassifier.create_from_options(options) as classifier: + self.assertIsInstance(classifier, _ImageClassifier) + + def test_create_from_options_fails_with_invalid_model_path(self): + # Invalid empty model path. + with self.assertRaisesRegex( + ValueError, + r"ExternalFile must specify at least one of 'file_content', " + r"'file_name' or 'file_descriptor_meta'."): + base_options = _BaseOptions(file_name='') + options = _ImageClassifierOptions(base_options=base_options) + _ImageClassifier.create_from_options(options) + + def test_create_from_options_succeeds_with_valid_model_content(self): + # Creates with options containing model content successfully. + with open(self.model_path, 'rb') as f: + base_options = _BaseOptions(file_content=f.read()) + options = _ImageClassifierOptions(base_options=base_options) + classifier = _ImageClassifier.create_from_options(options) + self.assertIsInstance(classifier, _ImageClassifier) + + @parameterized.parameters( + (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), + (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) + def test_classify(self, model_file_type, max_results, + expected_classification_result): + # Creates classifier. + if model_file_type is ModelFileType.FILE_NAME: + base_options = _BaseOptions(file_name=self.model_path) + elif model_file_type is ModelFileType.FILE_CONTENT: + with open(self.model_path, 'rb') as f: + model_content = f.read() + base_options = _BaseOptions(file_content=model_content) + else: + # Should never happen + raise ValueError('model_file_type is invalid.') + + options = _ImageClassifierOptions( + base_options=base_options, max_results=max_results) + classifier = _ImageClassifier.create_from_options(options) + + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + # Comparing results. + self.assertEqual(image_result, expected_classification_result) + # Closes the classifier explicitly when the classifier is not used in + # a context. + classifier.close() + + @parameterized.parameters( + (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), + (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) + def test_classify_in_context(self, model_file_type, max_results, + expected_classification_result): + if model_file_type is ModelFileType.FILE_NAME: + base_options = _BaseOptions(file_name=self.model_path) + elif model_file_type is ModelFileType.FILE_CONTENT: + with open(self.model_path, 'rb') as f: + model_content = f.read() + base_options = _BaseOptions(file_content=model_content) + else: + # Should never happen + raise ValueError('model_file_type is invalid.') + + options = _ImageClassifierOptions( + base_options=base_options, max_results=max_results) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs object detection on the input. + image_result = classifier.classify(self.test_image) + # Comparing results. + self.assertEqual(image_result, expected_classification_result) + + def test_score_threshold_option(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(file_name=self.model_path), + score_threshold=_SCORE_THRESHOLD) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + classifications = image_result.classifications + + for classification in classifications: + for entry in classification.entries: + score = entry.categories[0].score + self.assertGreaterEqual( + score, _SCORE_THRESHOLD, + f'Classification with score lower than threshold found. ' + f'{classification}') + + def test_max_results_option(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(file_name=self.model_path), + max_results=_MAX_RESULTS) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + categories = image_result.classifications[0].entries[0].categories + + self.assertLessEqual( + len(categories), _MAX_RESULTS, 'Too many results returned.') + + def test_allow_list_option(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(file_name=self.model_path), + category_allowlist=_ALLOW_LIST) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + classifications = image_result.classifications + + for classification in classifications: + for entry in classification.entries: + label = entry.categories[0].category_name + self.assertIn(label, _ALLOW_LIST, + f'Label {label} found but not in label allow list') + + def test_deny_list_option(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(file_name=self.model_path), + category_denylist=_DENY_LIST) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + classifications = image_result.classifications + + for classification in classifications: + for entry in classification.entries: + label = entry.categories[0].category_name + self.assertNotIn(label, _DENY_LIST, + f'Label {label} found but in deny list.') + + def test_combined_allowlist_and_denylist(self): + # Fails with combined allowlist and denylist + with self.assertRaisesRegex( + ValueError, + r'`category_allowlist` and `category_denylist` are mutually ' + r'exclusive options.'): + options = _ImageClassifierOptions( + base_options=_BaseOptions(file_name=self.model_path), + category_allowlist=['foo'], + category_denylist=['bar']) + with _ImageClassifier.create_from_options(options) as unused_classifier: + pass + + def test_empty_classification_outputs(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(file_name=self.model_path), score_threshold=1) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + self.assertEmpty(image_result.classifications[0].entries[0].categories) + + def test_missing_result_callback(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(file_name=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM) + with self.assertRaisesRegex(ValueError, + r'result callback must be provided'): + with _ImageClassifier.create_from_options(options) as unused_classifier: + pass + + @parameterized.parameters((_RUNNING_MODE.IMAGE), (_RUNNING_MODE.VIDEO)) + def test_illegal_result_callback(self, running_mode): + + def pass_through(unused_result: _ClassificationResult): + pass + + options = _ImageClassifierOptions( + base_options=_BaseOptions(file_name=self.model_path), + running_mode=running_mode, + result_callback=pass_through) + with self.assertRaisesRegex(ValueError, + r'result callback should not be provided'): + with _ImageClassifier.create_from_options(options) as unused_classifier: + pass + + # @parameterized.parameters((0, _EXPECTED_CLASSIFICATION_RESULT), + # (1, _ClassificationResult(classifications=[]))) + # def test_classify_async_calls(self, threshold, expected_result): + # observed_timestamp_ms = -1 + # + # def check_result(result: _ClassificationResult, timestamp_ms: int): + # self.assertEqual(result, expected_result) + # self.assertLess(observed_timestamp_ms, timestamp_ms) + # self.observed_timestamp_ms = timestamp_ms + # + # options = _ImageClassifierOptions( + # base_options=_BaseOptions(file_name=self.model_path), + # running_mode=_RUNNING_MODE.LIVE_STREAM, + # max_results=4, + # score_threshold=threshold, + # result_callback=check_result) + # classifier = _ImageClassifier.create_from_options(options) + # for timestamp in range(0, 300, 30): + # classifier.classify_async(self.test_image, timestamp) + # classifier.close() + + +if __name__ == '__main__': + absltest.main() diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 7ff818610..7a27da179 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -36,3 +36,23 @@ py_library( "//mediapipe/tasks/python/vision/core:vision_task_running_mode", ], ) + +py_library( + name = "image_classification", + srcs = [ + "image_classification.py", + ], + deps = [ + "//mediapipe/python:_framework_bindings", + "//mediapipe/python:packet_creator", + "//mediapipe/python:packet_getter", + "//mediapipe/tasks/cc/components:classifier_options_py_pb2", + "//mediapipe/tasks/cc/vision/image_classification:image_classifier_options_py_pb2", + "//mediapipe/tasks/python/components/containers:classifications", + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/core:optional_dependencies", + "//mediapipe/tasks/python/core:task_info", + "//mediapipe/tasks/python/vision/core:base_vision_task_api", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + ], +) diff --git a/mediapipe/tasks/python/vision/image_classification.py b/mediapipe/tasks/python/vision/image_classification.py new file mode 100644 index 000000000..efe6aa11d --- /dev/null +++ b/mediapipe/tasks/python/vision/image_classification.py @@ -0,0 +1,227 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""MediaPipe image classifier task.""" + +import dataclasses +from typing import Callable, List, Mapping, Optional + +from mediapipe.python import packet_creator +from mediapipe.python import packet_getter +from mediapipe.python._framework_bindings import image as image_module +from mediapipe.python._framework_bindings import packet as packet_module +from mediapipe.python._framework_bindings import task_runner as task_runner_module +from mediapipe.tasks.cc.components import classifier_options_pb2 +from mediapipe.tasks.cc.vision.image_classification import image_classifier_options_pb2 +from mediapipe.tasks.python.components.containers import classifications as classifications_module +from mediapipe.tasks.python.core import base_options as base_options_module +from mediapipe.tasks.python.core import task_info as task_info_module +from mediapipe.tasks.python.core.optional_dependencies import doc_controls +from mediapipe.tasks.python.vision.core import base_vision_task_api +from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module + +_BaseOptions = base_options_module.BaseOptions +_ClassifierOptionsProto = classifier_options_pb2.ClassifierOptions +_ImageClassifierOptionsProto = image_classifier_options_pb2.ImageClassifierOptions +_RunningMode = running_mode_module.VisionTaskRunningMode +_TaskInfo = task_info_module.TaskInfo +_TaskRunner = task_runner_module.TaskRunner + +_CLASSIFICATION_RESULT_OUT_STREAM_NAME = 'classification_result_out' +_CLASSIFICATION_RESULT_TAG = 'CLASSIFICATION_RESULT' +_IMAGE_IN_STREAM_NAME = 'image_in' +_IMAGE_TAG = 'IMAGE' +_TASK_GRAPH_NAME = 'mediapipe.tasks.vision.ImageClassifierGraph' + + +@dataclasses.dataclass +class ImageClassifierOptions: + """Options for the image classifier task. + + Attributes: + base_options: Base options for the image classifier task. + running_mode: The running mode of the task. Default to the image mode. + Image classifier task has three running modes: + 1) The image mode for classifying objects on single image inputs. + 2) The video mode for classifying objects on the decoded frames of a + video. + 3) The live stream mode for classifying objects on a live stream of input + data, such as from camera. + display_names_locale: The locale to use for display names specified through + the TFLite Model Metadata. + max_results: The maximum number of top-scored classification results to + return. + score_threshold: Overrides the ones provided in the model metadata. Results + below this value are rejected. + category_allowlist: Allowlist of category names. If non-empty, detection + results whose category name is not in this set will be filtered out. + Duplicate or unknown category names are ignored. Mutually exclusive with + `category_denylist`. + category_denylist: Denylist of category names. If non-empty, detection + results whose category name is in this set will be filtered out. Duplicate + or unknown category names are ignored. Mutually exclusive with + `category_allowlist`. + result_callback: The user-defined result callback for processing live stream + data. The result callback should only be specified when the running mode + is set to the live stream mode. + """ + base_options: _BaseOptions + running_mode: _RunningMode = _RunningMode.IMAGE + display_names_locale: Optional[str] = None + max_results: Optional[int] = None + score_threshold: Optional[float] = None + category_allowlist: Optional[List[str]] = None + category_denylist: Optional[List[str]] = None + result_callback: Optional[ + Callable[[classifications_module.ClassificationResult], None]] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ImageClassifierOptionsProto: + """Generates an ImageClassifierOptions protobuf object.""" + base_options_proto = self.base_options.to_pb2() + base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True + + classifier_options_proto = _ClassifierOptionsProto( + display_names_locale=self.display_names_locale, + max_results=self.max_results, + score_threshold=self.score_threshold, + category_allowlist=self.category_allowlist, + category_denylist=self.category_denylist) + + return _ImageClassifierOptionsProto( + base_options=base_options_proto, + classifier_options=classifier_options_proto + ) + + +class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): + """Class that performs image classification on images.""" + + @classmethod + def create_from_model_path(cls, model_path: str) -> 'ImageClassifier': + """Creates an `ImageClassifier` object from a TensorFlow Lite model and the default `ImageClassifierOptions`. + + Note that the created `ImageClassifier` instance is in image mode, for + detecting objects on single image inputs. + + Args: + model_path: Path to the model. + + Returns: + `ImageClassifier` object that's created from the model file and the default + `ImageClassifierOptions`. + + Raises: + ValueError: If failed to create `ImageClassifier` object from the provided + file such as invalid file path. + RuntimeError: If other types of error occurred. + """ + base_options = _BaseOptions(file_name=model_path) + options = ImageClassifierOptions( + base_options=base_options, running_mode=_RunningMode.IMAGE) + return cls.create_from_options(options) + + @classmethod + def create_from_options(cls, + options: ImageClassifierOptions) -> 'ImageClassifier': + """Creates the `ImageClassifier` object from image classifier options. + + Args: + options: Options for the image classifier task. + + Returns: + `ImageClassifier` object that's created from `options`. + + Raises: + ValueError: If failed to create `ImageClassifier` object from + `ImageClassifierOptions` such as missing the model. + RuntimeError: If other types of error occurred. + """ + + def packets_callback(output_packets: Mapping[str, packet_module.Packet]): + classification_result_proto = packet_getter.get_proto( + output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]) + + classification_result = classifications_module.ClassificationResult([ + classifications_module.Classifications.create_from_pb2(classification) + for classification in classification_result_proto.classifications + ]) + options.result_callback(classification_result) + + task_info = _TaskInfo( + task_graph=_TASK_GRAPH_NAME, + input_streams=[':'.join([_IMAGE_TAG, _IMAGE_IN_STREAM_NAME])], + output_streams=[ + ':'.join([_CLASSIFICATION_RESULT_TAG, + _CLASSIFICATION_RESULT_OUT_STREAM_NAME]) + ], + task_options=options) + return cls( + task_info.generate_graph_config( + enable_flow_limiting=options.running_mode == + _RunningMode.LIVE_STREAM), options.running_mode, + packets_callback if options.result_callback else None) + + # TODO: Create an Image class for MediaPipe Tasks. + def classify( + self, + image: image_module.Image + ) -> classifications_module.ClassificationResult: + """Performs image classification on the provided MediaPipe Image. + + Args: + image: MediaPipe Image. + + Returns: + A classification result object that contains a list of classifications. + + Raises: + ValueError: If any of the input arguments is invalid. + RuntimeError: If image classification failed to run. + """ + output_packets = self._process_image_data( + {_IMAGE_IN_STREAM_NAME: packet_creator.create_image(image)}) + classification_result_proto = packet_getter.get_proto( + output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]) + + return classifications_module.ClassificationResult([ + classifications_module.Classifications.create_from_pb2(classification) + for classification in classification_result_proto.classifications + ]) + + def classify_async(self, image: image_module.Image, timestamp_ms: int) -> None: + """Sends live image data (an Image with a unique timestamp) to perform image + classification. + + This method will return immediately after the input image is accepted. The + results will be available via the `result_callback` provided in the + `ImageClassifierOptions`. The `detect_async` method is designed to process + live stream data such as camera input. To lower the overall latency, image + classifier may drop the input images if needed. In other words, it's not + guaranteed to have output per input image. The `result_callback` provides: + - A classification result object that contains a list of classifications. + - The input image that the image classifier runs on. + - The input timestamp in milliseconds. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input image in milliseconds. + + Raises: + ValueError: If the current input timestamp is smaller than what the image + classifier has already processed. + """ + self._send_live_stream_data({ + _IMAGE_IN_STREAM_NAME: + packet_creator.create_image(image).at(timestamp_ms) + }) From ec0c5f43412eb521f2d943ee6eef0423c95baf3c Mon Sep 17 00:00:00 2001 From: kinaryml Date: Sun, 11 Sep 2022 14:00:49 -0700 Subject: [PATCH 002/125] Code cleanup --- .../test/vision/image_classification_test.py | 25 ++------------ .../python/vision/image_classification.py | 33 +++---------------- 2 files changed, 6 insertions(+), 52 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_classification_test.py b/mediapipe/tasks/python/test/vision/image_classification_test.py index 3650c547c..a96eee6cb 100644 --- a/mediapipe/tasks/python/test/vision/image_classification_test.py +++ b/mediapipe/tasks/python/test/vision/image_classification_test.py @@ -124,7 +124,7 @@ class ImageClassifierTest(parameterized.TestCase): (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) def test_classify(self, model_file_type, max_results, - expected_classification_result): + expected_classification_result): # Creates classifier. if model_file_type is ModelFileType.FILE_NAME: base_options = _BaseOptions(file_name=self.model_path) @@ -152,7 +152,7 @@ class ImageClassifierTest(parameterized.TestCase): (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) def test_classify_in_context(self, model_file_type, max_results, - expected_classification_result): + expected_classification_result): if model_file_type is ModelFileType.FILE_NAME: base_options = _BaseOptions(file_name=self.model_path) elif model_file_type is ModelFileType.FILE_CONTENT: @@ -275,27 +275,6 @@ class ImageClassifierTest(parameterized.TestCase): with _ImageClassifier.create_from_options(options) as unused_classifier: pass - # @parameterized.parameters((0, _EXPECTED_CLASSIFICATION_RESULT), - # (1, _ClassificationResult(classifications=[]))) - # def test_classify_async_calls(self, threshold, expected_result): - # observed_timestamp_ms = -1 - # - # def check_result(result: _ClassificationResult, timestamp_ms: int): - # self.assertEqual(result, expected_result) - # self.assertLess(observed_timestamp_ms, timestamp_ms) - # self.observed_timestamp_ms = timestamp_ms - # - # options = _ImageClassifierOptions( - # base_options=_BaseOptions(file_name=self.model_path), - # running_mode=_RUNNING_MODE.LIVE_STREAM, - # max_results=4, - # score_threshold=threshold, - # result_callback=check_result) - # classifier = _ImageClassifier.create_from_options(options) - # for timestamp in range(0, 300, 30): - # classifier.classify_async(self.test_image, timestamp) - # classifier.close() - if __name__ == '__main__': absltest.main() diff --git a/mediapipe/tasks/python/vision/image_classification.py b/mediapipe/tasks/python/vision/image_classification.py index efe6aa11d..95381d78a 100644 --- a/mediapipe/tasks/python/vision/image_classification.py +++ b/mediapipe/tasks/python/vision/image_classification.py @@ -83,7 +83,8 @@ class ImageClassifierOptions: category_allowlist: Optional[List[str]] = None category_denylist: Optional[List[str]] = None result_callback: Optional[ - Callable[[classifications_module.ClassificationResult], None]] = None + Callable[[classifications_module.ClassificationResult], + None]] = None @doc_controls.do_not_generate_docs def to_pb2(self) -> _ImageClassifierOptionsProto: @@ -96,7 +97,8 @@ class ImageClassifierOptions: max_results=self.max_results, score_threshold=self.score_threshold, category_allowlist=self.category_allowlist, - category_denylist=self.category_denylist) + category_denylist=self.category_denylist + ) return _ImageClassifierOptionsProto( base_options=base_options_proto, @@ -198,30 +200,3 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): classifications_module.Classifications.create_from_pb2(classification) for classification in classification_result_proto.classifications ]) - - def classify_async(self, image: image_module.Image, timestamp_ms: int) -> None: - """Sends live image data (an Image with a unique timestamp) to perform image - classification. - - This method will return immediately after the input image is accepted. The - results will be available via the `result_callback` provided in the - `ImageClassifierOptions`. The `detect_async` method is designed to process - live stream data such as camera input. To lower the overall latency, image - classifier may drop the input images if needed. In other words, it's not - guaranteed to have output per input image. The `result_callback` provides: - - A classification result object that contains a list of classifications. - - The input image that the image classifier runs on. - - The input timestamp in milliseconds. - - Args: - image: MediaPipe Image. - timestamp_ms: The timestamp of the input image in milliseconds. - - Raises: - ValueError: If the current input timestamp is smaller than what the image - classifier has already processed. - """ - self._send_live_stream_data({ - _IMAGE_IN_STREAM_NAME: - packet_creator.create_image(image).at(timestamp_ms) - }) From 3fbb2b002bb6e4bc80fa62d7dc4d34d1df1fc287 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 21 Sep 2022 03:23:04 -0700 Subject: [PATCH 003/125] Added image segmenter implementation files --- mediapipe/python/BUILD | 2 + mediapipe/tasks/python/components/BUILD | 28 +++ .../python/components/segmenter_options.py | 78 +++++++ mediapipe/tasks/python/test/vision/BUILD | 38 +++- .../test/vision/image_segmenter_test.py | 118 ++++++++++ mediapipe/tasks/python/vision/BUILD | 19 ++ .../tasks/python/vision/image_segmenter.py | 205 ++++++++++++++++++ 7 files changed, 487 insertions(+), 1 deletion(-) create mode 100644 mediapipe/tasks/python/components/BUILD create mode 100644 mediapipe/tasks/python/components/segmenter_options.py create mode 100644 mediapipe/tasks/python/test/vision/image_segmenter_test.py create mode 100644 mediapipe/tasks/python/vision/image_segmenter.py diff --git a/mediapipe/python/BUILD b/mediapipe/python/BUILD index 3a4a90b44..331ee836c 100644 --- a/mediapipe/python/BUILD +++ b/mediapipe/python/BUILD @@ -86,6 +86,8 @@ cc_library( name = "builtin_task_graphs", deps = [ "//mediapipe/tasks/cc/vision/object_detector:object_detector_graph", + "//mediapipe/tasks/cc/vision/image_classification:image_classifier_graph", + "//mediapipe/tasks/cc/vision/image_segmenter:image_segmenter_graph", ], ) diff --git a/mediapipe/tasks/python/components/BUILD b/mediapipe/tasks/python/components/BUILD new file mode 100644 index 000000000..eb8714a93 --- /dev/null +++ b/mediapipe/tasks/python/components/BUILD @@ -0,0 +1,28 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Placeholder for internal Python strict library compatibility macro. + +package(default_visibility = ["//mediapipe/tasks:internal"]) + +licenses(["notice"]) + +py_library( + name = "segmenter_options", + srcs = ["segmenter_options.py"], + deps = [ + "//mediapipe/tasks/cc/components:segmenter_options_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) diff --git a/mediapipe/tasks/python/components/segmenter_options.py b/mediapipe/tasks/python/components/segmenter_options.py new file mode 100644 index 000000000..5b94a256d --- /dev/null +++ b/mediapipe/tasks/python/components/segmenter_options.py @@ -0,0 +1,78 @@ +# Copyright 2022 The TensorFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Segmenter options data class.""" + +import dataclasses +import enum +from typing import Any, Optional + +from mediapipe.tasks.cc.components import segmenter_options_pb2 +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_SegmenterOptionsProto = segmenter_options_pb2.SegmenterOptions + + +class OutputType(enum.Enum): + UNSPECIFIED = 0 + CATEGORY_MASK = 1 + CONFIDENCE_MASK = 2 + + +class Activation(enum.Enum): + NONE = 0 + SIGMOID = 1 + SOFTMAX = 2 + + +@dataclasses.dataclass +class SegmenterOptions: + """Options for segmentation processor. + Attributes: + output_type: The output mask type allows specifying the type of + post-processing to perform on the raw model results. + activation: Activation function to apply to input tensor. + """ + + output_type: Optional[OutputType] = OutputType.CATEGORY_MASK + activation: Optional[Activation] = Activation.NONE + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _SegmenterOptionsProto: + """Generates a protobuf object to pass to the C++ layer.""" + return _SegmenterOptionsProto( + output_type=self.output_type.value, + activation=self.activation.value + ) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, pb2_obj: _SegmenterOptionsProto) -> "SegmenterOptions": + """Creates a `SegmenterOptions` object from the given protobuf object.""" + return SegmenterOptions( + output_type=OutputType(pb2_obj.output_type), + activation=Activation(pb2_obj.output_type) + ) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + Args: + other: The object to be compared with. + Returns: + True if the objects are equal. + """ + if not isinstance(other, SegmenterOptions): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index bb495338d..403e00a37 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -18,4 +18,40 @@ package(default_visibility = ["//mediapipe/tasks:internal"]) licenses(["notice"]) -# TODO: This test fails in OSS +py_test( + name = "object_detector_test", + srcs = ["object_detector_test.py"], + data = [ + "//mediapipe/tasks/testdata/vision:test_images", + "//mediapipe/tasks/testdata/vision:test_models", + ], + deps = [ + # build rule placeholder: numpy dep, + "//mediapipe/tasks/python/components/containers:bounding_box", + "//mediapipe/tasks/python/components/containers:category", + "//mediapipe/tasks/python/components/containers:detections", + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/test:test_util", + "//mediapipe/tasks/python/vision:object_detector", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + "@absl_py//absl/testing:parameterized", + ], +) + +py_test( + name = "image_segmenter_test", + srcs = ["image_segmenter_test.py"], + data = [ + "//mediapipe/tasks/testdata/vision:test_images", + "//mediapipe/tasks/testdata/vision:test_models", + ], + deps = [ + # build rule placeholder: numpy dep, + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/test:test_util", + "//mediapipe/tasks/python/components:segmenter_options", + "//mediapipe/tasks/python/vision:image_segmenter", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + "@absl_py//absl/testing:parameterized", + ], +) diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py new file mode 100644 index 000000000..704b0fc57 --- /dev/null +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -0,0 +1,118 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for image segmenter.""" + +import enum + +from absl.testing import absltest +from absl.testing import parameterized +import numpy as np + +from mediapipe.python._framework_bindings import image as image_module +from mediapipe.tasks.python.components import segmenter_options +from mediapipe.tasks.python.core import base_options as base_options_module +from mediapipe.tasks.python.test import test_util +from mediapipe.tasks.python.vision import image_segmenter +from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module + +_BaseOptions = base_options_module.BaseOptions +_Image = image_module.Image +_OutputType = segmenter_options.OutputType +_Activation = segmenter_options.Activation +_ImageSegmenter = image_segmenter.ImageSegmenter +_ImageSegmenterOptions = image_segmenter.ImageSegmenterOptions +_RUNNING_MODE = running_mode_module.VisionTaskRunningMode + +_MODEL_FILE = 'deeplabv3.tflite' +_IMAGE_FILE = 'segmentation_input_rotation0.jpg' +_SEGMENTATION_FILE = 'segmentation_golden_rotation0.png' +_MASK_MAGNIFICATION_FACTOR = 10 +_MATCH_PIXELS_THRESHOLD = 0.01 + + +class ModelFileType(enum.Enum): + FILE_CONTENT = 1 + FILE_NAME = 2 + + +class ImageSegmenterTest(parameterized.TestCase): + + def setUp(self): + super().setUp() + self.test_image = test_util.read_test_image( + test_util.get_test_data_path(_IMAGE_FILE)) + self.model_path = test_util.get_test_data_path(_MODEL_FILE) + + def test_create_from_file_succeeds_with_valid_model_path(self): + # Creates with default option and valid model file successfully. + with _ImageSegmenter.create_from_model_path(self.model_path) as segmenter: + self.assertIsInstance(segmenter, _ImageSegmenter) + + def test_create_from_options_succeeds_with_valid_model_path(self): + # Creates with options containing model file successfully. + base_options = _BaseOptions(file_name=self.model_path) + options = _ImageSegmenterOptions(base_options=base_options) + with _ImageSegmenter.create_from_options(options) as segmenter: + self.assertIsInstance(segmenter, _ImageSegmenter) + + def test_create_from_options_fails_with_invalid_model_path(self): + # Invalid empty model path. + with self.assertRaisesRegex( + ValueError, + r"ExternalFile must specify at least one of 'file_content', " + r"'file_name' or 'file_descriptor_meta'."): + base_options = _BaseOptions(file_name='') + options = _ImageSegmenterOptions(base_options=base_options) + _ImageSegmenter.create_from_options(options) + + def test_create_from_options_succeeds_with_valid_model_content(self): + # Creates with options containing model content successfully. + with open(self.model_path, 'rb') as f: + base_options = _BaseOptions(file_content=f.read()) + options = _ImageSegmenterOptions(base_options=base_options) + segmenter = _ImageSegmenter.create_from_options(options) + self.assertIsInstance(segmenter, _ImageSegmenter) + + @parameterized.parameters( + (ModelFileType.FILE_NAME, 4), + (ModelFileType.FILE_CONTENT, 4)) + def succeeds_with_category_mask(self, model_file_type, max_results): + # Creates segmenter. + if model_file_type is ModelFileType.FILE_NAME: + base_options = _BaseOptions(file_name=self.model_path) + elif model_file_type is ModelFileType.FILE_CONTENT: + with open(self.model_path, 'rb') as f: + model_content = f.read() + base_options = _BaseOptions(file_content=model_content) + else: + # Should never happen + raise ValueError('model_file_type is invalid.') + + options = _ImageSegmenterOptions(base_options=base_options, + output_type=_OutputType.CATEGORY_MASK) + segmenter = _ImageSegmenter.create_from_options(options) + + # Performs image segmentation on the input. + image_result = segmenter.segment(self.test_image) + + # Comparing results. + print(image_result) + + # Closes the segmenter explicitly when the segmenter is not used in + # a context. + segmenter.close() + + +if __name__ == '__main__': + absltest.main() diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 7ff818610..ce59763d6 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -36,3 +36,22 @@ py_library( "//mediapipe/tasks/python/vision/core:vision_task_running_mode", ], ) + +py_library( + name = "image_segmenter", + srcs = [ + "image_segmenter.py", + ], + deps = [ + "//mediapipe/python:_framework_bindings", + "//mediapipe/python:packet_creator", + "//mediapipe/python:packet_getter", + "//mediapipe/tasks/cc/vision/image_segmenter/proto:image_segmenter_options_py_pb2", + "//mediapipe/tasks/python/components:segmenter_options", + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/core:optional_dependencies", + "//mediapipe/tasks/python/core:task_info", + "//mediapipe/tasks/python/vision/core:base_vision_task_api", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + ], +) diff --git a/mediapipe/tasks/python/vision/image_segmenter.py b/mediapipe/tasks/python/vision/image_segmenter.py new file mode 100644 index 000000000..ea40d85c1 --- /dev/null +++ b/mediapipe/tasks/python/vision/image_segmenter.py @@ -0,0 +1,205 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""MediaPipe image segmenter task.""" + +import dataclasses +from typing import Callable, List, Mapping, Optional + +from mediapipe.python import packet_creator +from mediapipe.python import packet_getter +from mediapipe.python._framework_bindings import image as image_module +from mediapipe.python._framework_bindings import packet as packet_module +from mediapipe.python._framework_bindings import task_runner as task_runner_module +from mediapipe.tasks.cc.vision.image_segmenter.proto import image_segmenter_options_pb2 +from mediapipe.tasks.python.components import segmenter_options +from mediapipe.tasks.python.core import base_options as base_options_module +from mediapipe.tasks.python.core import task_info as task_info_module +from mediapipe.tasks.python.core.optional_dependencies import doc_controls +from mediapipe.tasks.python.vision.core import base_vision_task_api +from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module + +_BaseOptions = base_options_module.BaseOptions +_ImageSegmenterOptionsProto = image_segmenter_options_pb2.ImageSegmenterOptions +_SegmenterOptions = segmenter_options.SegmenterOptions +_RunningMode = running_mode_module.VisionTaskRunningMode +_TaskInfo = task_info_module.TaskInfo +_TaskRunner = task_runner_module.TaskRunner + +_SEGMENTATION_OUT_STREAM_NAME = 'segmented_masks' +_SEGMENTATION_TAG = 'SEGMENTATION' +_GROUPED_SEGMENTATION_TAG = 'GROUPED_SEGMENTATION' +_IMAGE_IN_STREAM_NAME = 'image_in' +_IMAGE_OUT_STREAM_NAME = 'image_out' +_IMAGE_TAG = 'IMAGE' +_TASK_GRAPH_NAME = 'mediapipe.tasks.vision.ImageSegmenterGraph' + + +@dataclasses.dataclass +class ImageSegmenterOptions: + """Options for the image segmenter task. + + Attributes: + base_options: Base options for the image segmenter task. + running_mode: The running mode of the task. Default to the image mode. + Image segmenter task has three running modes: + 1) The image mode for detecting objects on single image inputs. + 2) The video mode for detecting objects on the decoded frames of a video. + 3) The live stream mode for detecting objects on a live stream of input + data, such as from camera. + output_type: Optional output mask type. + activation: Activation function to apply to input tensor. + result_callback: The user-defined result callback for processing live stream + data. The result callback should only be specified when the running mode + is set to the live stream mode. + """ + base_options: _BaseOptions + running_mode: _RunningMode = _RunningMode.IMAGE + output_type: Optional[segmenter_options.OutputType] = segmenter_options.OutputType.CATEGORY_MASK + activation: Optional[segmenter_options.Activation] = segmenter_options.Activation.NONE + result_callback: Optional[ + Callable[[List[image_module.Image], image_module.Image, int], + None]] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ImageSegmenterOptionsProto: + """Generates an ImageSegmenterOptions protobuf object.""" + base_options_proto = self.base_options.to_pb2() + base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True + + segmenter_options = _SegmenterOptions( + output_type=self.output_type, + activation=self.activation + ) + + return _ImageSegmenterOptionsProto( + base_options=base_options_proto, + segmenter_options=segmenter_options.to_pb2() + ) + + +class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): + """Class that performs image segmentation on images.""" + + @classmethod + def create_from_model_path(cls, model_path: str) -> 'ImageSegmenter': + """Creates an `ImageSegmenter` object from a TensorFlow Lite model and the default `ImageSegmenterOptions`. + + Note that the created `ImageSegmenter` instance is in image mode, for + performing image segmentation on single image inputs. + + Args: + model_path: Path to the model. + + Returns: + `ImageSegmenter` object that's created from the model file and the default + `ImageSegmenterOptions`. + + Raises: + ValueError: If failed to create `ImageSegmenter` object from the provided + file such as invalid file path. + RuntimeError: If other types of error occurred. + """ + base_options = _BaseOptions(file_name=model_path) + options = ImageSegmenterOptions( + base_options=base_options, running_mode=_RunningMode.IMAGE) + return cls.create_from_options(options) + + @classmethod + def create_from_options(cls, + options: ImageSegmenterOptions) -> 'ImageSegmenter': + """Creates the `ImageSegmenter` object from image segmenter options. + + Args: + options: Options for the image segmenter task. + + Returns: + `ImageSegmenter` object that's created from `options`. + + Raises: + ValueError: If failed to create `ImageSegmenter` object from + `ImageSegmenterOptions` such as missing the model. + RuntimeError: If other types of error occurred. + """ + + def packets_callback(output_packets: Mapping[str, packet_module.Packet]): + if output_packets[_IMAGE_OUT_STREAM_NAME].is_empty(): + return + segmentation_result = packet_getter.get_proto_list( + output_packets[_SEGMENTATION_OUT_STREAM_NAME]) + image = packet_getter.get_image(output_packets[_IMAGE_OUT_STREAM_NAME]) + timestamp = output_packets[_IMAGE_OUT_STREAM_NAME].timestamp + options.result_callback(segmentation_result, image, timestamp) + + task_info = _TaskInfo( + task_graph=_TASK_GRAPH_NAME, + input_streams=[':'.join([_IMAGE_TAG, _IMAGE_IN_STREAM_NAME])], + output_streams=[ + ':'.join([_SEGMENTATION_TAG, _SEGMENTATION_OUT_STREAM_NAME]), + ':'.join([_IMAGE_TAG, _IMAGE_OUT_STREAM_NAME]) + ], + task_options=options) + return cls( + task_info.generate_graph_config( + enable_flow_limiting=options.running_mode == + _RunningMode.LIVE_STREAM), options.running_mode, + packets_callback if options.result_callback else None) + + # TODO: Create an Image class for MediaPipe Tasks. + def segment(self, + image: image_module.Image) -> List[image_module.Image]: + """Performs the actual segmentation task on the provided MediaPipe Image. + + Args: + image: MediaPipe Image. + + Returns: + A segmentation result object that contains a list of segmentation masks + as images. + + Raises: + ValueError: If any of the input arguments is invalid. + RuntimeError: If object detection failed to run. + """ + output_packets = self._process_image_data( + {_IMAGE_IN_STREAM_NAME: packet_creator.create_image(image)}) + segmentation_result = packet_getter.get_proto_list( + output_packets[_SEGMENTATION_OUT_STREAM_NAME]) + return segmentation_result + + # def segment_async(self, image: image_module.Image, timestamp_ms: int) -> None: + # """Sends live image data (an Image with a unique timestamp) to perform image segmentation. + # + # This method will return immediately after the input image is accepted. The + # results will be available via the `result_callback` provided in the + # `ImageSegmenterOptions`. The `segment_async` method is designed to process + # live stream data such as camera input. To lower the overall latency, image + # segmenter may drop the input images if needed. In other words, it's not + # guaranteed to have output per input image. The `result_callback` provides: + # - A segmentation result object that contains a list of segmentation masks + # as images. + # - The input image that the image segmenter runs on. + # - The input timestamp in milliseconds. + # + # Args: + # image: MediaPipe Image. + # timestamp_ms: The timestamp of the input image in milliseconds. + # + # Raises: + # ValueError: If the current input timestamp is smaller than what the object + # detector has already processed. + # """ + # self._send_live_stream_data({ + # _IMAGE_IN_STREAM_NAME: + # packet_creator.create_image(image).at(timestamp_ms) + # }) From 7287e5a0ed860a29abb8f1ad9c88d82021d1c8e1 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 21 Sep 2022 03:27:14 -0700 Subject: [PATCH 004/125] Added the image classifier task graph --- mediapipe/python/BUILD | 1 + 1 file changed, 1 insertion(+) diff --git a/mediapipe/python/BUILD b/mediapipe/python/BUILD index 3a4a90b44..9fe21ab9e 100644 --- a/mediapipe/python/BUILD +++ b/mediapipe/python/BUILD @@ -86,6 +86,7 @@ cc_library( name = "builtin_task_graphs", deps = [ "//mediapipe/tasks/cc/vision/object_detector:object_detector_graph", + "//mediapipe/tasks/cc/vision/image_classification:image_classifier_graph", ], ) From 500ad5a7f0263232bfa864968befce3ced6be010 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 21 Sep 2022 03:43:18 -0700 Subject: [PATCH 005/125] Updated some files --- mediapipe/python/BUILD | 1 - mediapipe/tasks/python/test/vision/image_segmenter_test.py | 5 +++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/mediapipe/python/BUILD b/mediapipe/python/BUILD index 331ee836c..55c0a22e5 100644 --- a/mediapipe/python/BUILD +++ b/mediapipe/python/BUILD @@ -86,7 +86,6 @@ cc_library( name = "builtin_task_graphs", deps = [ "//mediapipe/tasks/cc/vision/object_detector:object_detector_graph", - "//mediapipe/tasks/cc/vision/image_classification:image_classifier_graph", "//mediapipe/tasks/cc/vision/image_segmenter:image_segmenter_graph", ], ) diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index 704b0fc57..6194f7661 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -104,10 +104,11 @@ class ImageSegmenterTest(parameterized.TestCase): segmenter = _ImageSegmenter.create_from_options(options) # Performs image segmentation on the input. - image_result = segmenter.segment(self.test_image) + category_masks = segmenter.segment(self.test_image) # Comparing results. - print(image_result) + print(len(category_masks)) + s # Closes the segmenter explicitly when the segmenter is not used in # a context. From 660a88b7ead9c4aacd806e6fd7751db87cd428c1 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 21 Sep 2022 04:06:12 -0700 Subject: [PATCH 006/125] Code cleanup --- .../test/vision/image_segmenter_test.py | 9 ++-- .../tasks/python/vision/image_segmenter.py | 41 ++----------------- 2 files changed, 7 insertions(+), 43 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index 6194f7661..8a91766df 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -17,7 +17,6 @@ import enum from absl.testing import absltest from absl.testing import parameterized -import numpy as np from mediapipe.python._framework_bindings import image as image_module from mediapipe.tasks.python.components import segmenter_options @@ -30,6 +29,7 @@ _BaseOptions = base_options_module.BaseOptions _Image = image_module.Image _OutputType = segmenter_options.OutputType _Activation = segmenter_options.Activation +_SegmenterOptions = segmenter_options.SegmenterOptions _ImageSegmenter = image_segmenter.ImageSegmenter _ImageSegmenterOptions = image_segmenter.ImageSegmenterOptions _RUNNING_MODE = running_mode_module.VisionTaskRunningMode @@ -99,17 +99,14 @@ class ImageSegmenterTest(parameterized.TestCase): # Should never happen raise ValueError('model_file_type is invalid.') + segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) options = _ImageSegmenterOptions(base_options=base_options, - output_type=_OutputType.CATEGORY_MASK) + segmenter_options=segmenter_options) segmenter = _ImageSegmenter.create_from_options(options) # Performs image segmentation on the input. category_masks = segmenter.segment(self.test_image) - # Comparing results. - print(len(category_masks)) - s - # Closes the segmenter explicitly when the segmenter is not used in # a context. segmenter.close() diff --git a/mediapipe/tasks/python/vision/image_segmenter.py b/mediapipe/tasks/python/vision/image_segmenter.py index ea40d85c1..47f096473 100644 --- a/mediapipe/tasks/python/vision/image_segmenter.py +++ b/mediapipe/tasks/python/vision/image_segmenter.py @@ -57,16 +57,14 @@ class ImageSegmenterOptions: 2) The video mode for detecting objects on the decoded frames of a video. 3) The live stream mode for detecting objects on a live stream of input data, such as from camera. - output_type: Optional output mask type. - activation: Activation function to apply to input tensor. + segmenter_options: Options for the image segmenter task. result_callback: The user-defined result callback for processing live stream data. The result callback should only be specified when the running mode is set to the live stream mode. """ base_options: _BaseOptions running_mode: _RunningMode = _RunningMode.IMAGE - output_type: Optional[segmenter_options.OutputType] = segmenter_options.OutputType.CATEGORY_MASK - activation: Optional[segmenter_options.Activation] = segmenter_options.Activation.NONE + segmenter_options: _SegmenterOptions = _SegmenterOptions() result_callback: Optional[ Callable[[List[image_module.Image], image_module.Image, int], None]] = None @@ -76,15 +74,11 @@ class ImageSegmenterOptions: """Generates an ImageSegmenterOptions protobuf object.""" base_options_proto = self.base_options.to_pb2() base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True - - segmenter_options = _SegmenterOptions( - output_type=self.output_type, - activation=self.activation - ) + segmenter_options_proto = self.segmenter_options.to_pb2() return _ImageSegmenterOptionsProto( base_options=base_options_proto, - segmenter_options=segmenter_options.to_pb2() + segmenter_options=segmenter_options_proto ) @@ -176,30 +170,3 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): segmentation_result = packet_getter.get_proto_list( output_packets[_SEGMENTATION_OUT_STREAM_NAME]) return segmentation_result - - # def segment_async(self, image: image_module.Image, timestamp_ms: int) -> None: - # """Sends live image data (an Image with a unique timestamp) to perform image segmentation. - # - # This method will return immediately after the input image is accepted. The - # results will be available via the `result_callback` provided in the - # `ImageSegmenterOptions`. The `segment_async` method is designed to process - # live stream data such as camera input. To lower the overall latency, image - # segmenter may drop the input images if needed. In other words, it's not - # guaranteed to have output per input image. The `result_callback` provides: - # - A segmentation result object that contains a list of segmentation masks - # as images. - # - The input image that the image segmenter runs on. - # - The input timestamp in milliseconds. - # - # Args: - # image: MediaPipe Image. - # timestamp_ms: The timestamp of the input image in milliseconds. - # - # Raises: - # ValueError: If the current input timestamp is smaller than what the object - # detector has already processed. - # """ - # self._send_live_stream_data({ - # _IMAGE_IN_STREAM_NAME: - # packet_creator.create_image(image).at(timestamp_ms) - # }) From d8f7c5a43b311e166c337c451595348b5e1610d3 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 21 Sep 2022 04:22:33 -0700 Subject: [PATCH 007/125] Moved ClassifierOptions to mediapipe/tasks/python/components to align with the C++ API --- mediapipe/tasks/python/components/BUILD | 28 ++++++ .../python/components/classifier_options.py | 92 +++++++++++++++++++ .../test/vision/image_classification_test.py | 31 +++++-- mediapipe/tasks/python/vision/BUILD | 2 +- .../python/vision/image_classification.py | 19 +--- 5 files changed, 146 insertions(+), 26 deletions(-) create mode 100644 mediapipe/tasks/python/components/BUILD create mode 100644 mediapipe/tasks/python/components/classifier_options.py diff --git a/mediapipe/tasks/python/components/BUILD b/mediapipe/tasks/python/components/BUILD new file mode 100644 index 000000000..4094b7f7f --- /dev/null +++ b/mediapipe/tasks/python/components/BUILD @@ -0,0 +1,28 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Placeholder for internal Python strict library compatibility macro. + +package(default_visibility = ["//mediapipe/tasks:internal"]) + +licenses(["notice"]) + +py_library( + name = "classifier_options", + srcs = ["classifier_options.py"], + deps = [ + "//mediapipe/tasks/cc/components:classifier_options_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) diff --git a/mediapipe/tasks/python/components/classifier_options.py b/mediapipe/tasks/python/components/classifier_options.py new file mode 100644 index 000000000..f6e61e48c --- /dev/null +++ b/mediapipe/tasks/python/components/classifier_options.py @@ -0,0 +1,92 @@ +# Copyright 2022 The TensorFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Classifier options data class.""" + +import dataclasses +from typing import Any, List, Optional + +from mediapipe.tasks.cc.components import classifier_options_pb2 +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_ClassifierOptionsProto = classifier_options_pb2.ClassifierOptions + + +@dataclasses.dataclass +class ClassifierOptions: + """Options for classification processor. + + Attributes: + display_names_locale: The locale to use for display names specified through + the TFLite Model Metadata. + max_results: The maximum number of top-scored classification results to + return. + score_threshold: Overrides the ones provided in the model metadata. Results + below this value are rejected. + category_allowlist: Allowlist of category names. If non-empty, detection + results whose category name is not in this set will be filtered out. + Duplicate or unknown category names are ignored. Mutually exclusive with + `category_denylist`. + category_denylist: Denylist of category names. If non-empty, detection + results whose category name is in this set will be filtered out. Duplicate + or unknown category names are ignored. Mutually exclusive with + `category_allowlist`. + """ + + display_names_locale: Optional[str] = None + max_results: Optional[int] = None + score_threshold: Optional[float] = None + category_allowlist: Optional[List[str]] = None + category_denylist: Optional[List[str]] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ClassifierOptionsProto: + """Generates a ClassifierOptions protobuf object.""" + return _ClassifierOptionsProto( + score_threshold=self.score_threshold, + category_allowlist=self.category_allowlist, + category_denylist=self.category_denylist, + display_names_locale=self.display_names_locale, + max_results=self.max_results) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, + pb2_obj: _ClassifierOptionsProto + ) -> 'ClassifierOptions': + """Creates a `ClassifierOptions` object from the given protobuf object.""" + return ClassifierOptions( + score_threshold=pb2_obj.score_threshold, + category_allowlist=[ + str(name) for name in pb2_obj.class_name_allowlist + ], + category_denylist=[ + str(name) for name in pb2_obj.class_name_denylist + ], + display_names_locale=pb2_obj.display_names_locale, + max_results=pb2_obj.max_results) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, ClassifierOptions): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/test/vision/image_classification_test.py b/mediapipe/tasks/python/test/vision/image_classification_test.py index a96eee6cb..51dcb1adf 100644 --- a/mediapipe/tasks/python/test/vision/image_classification_test.py +++ b/mediapipe/tasks/python/test/vision/image_classification_test.py @@ -19,6 +19,7 @@ from absl.testing import absltest from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module +from mediapipe.tasks.python.components import classifier_options from mediapipe.tasks.python.components.containers import category as category_module from mediapipe.tasks.python.components.containers import classifications as classifications_module from mediapipe.tasks.python.core import base_options as base_options_module @@ -27,6 +28,7 @@ from mediapipe.tasks.python.vision import image_classification from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module _BaseOptions = base_options_module.BaseOptions +_ClassifierOptions = classifier_options.ClassifierOptions _Category = category_module.Category _ClassificationEntry = classifications_module.ClassificationEntry _Classifications = classifications_module.Classifications @@ -136,8 +138,9 @@ class ImageClassifierTest(parameterized.TestCase): # Should never happen raise ValueError('model_file_type is invalid.') + classifier_options = _ClassifierOptions(max_results=max_results) options = _ImageClassifierOptions( - base_options=base_options, max_results=max_results) + base_options=base_options, classifier_options=classifier_options) classifier = _ImageClassifier.create_from_options(options) # Performs image classification on the input. @@ -163,8 +166,9 @@ class ImageClassifierTest(parameterized.TestCase): # Should never happen raise ValueError('model_file_type is invalid.') + classifier_options = _ClassifierOptions(max_results=max_results) options = _ImageClassifierOptions( - base_options=base_options, max_results=max_results) + base_options=base_options, classifier_options=classifier_options) with _ImageClassifier.create_from_options(options) as classifier: # Performs object detection on the input. image_result = classifier.classify(self.test_image) @@ -172,9 +176,10 @@ class ImageClassifierTest(parameterized.TestCase): self.assertEqual(image_result, expected_classification_result) def test_score_threshold_option(self): + classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) options = _ImageClassifierOptions( base_options=_BaseOptions(file_name=self.model_path), - score_threshold=_SCORE_THRESHOLD) + classifier_options=classifier_options) with _ImageClassifier.create_from_options(options) as classifier: # Performs image classification on the input. image_result = classifier.classify(self.test_image) @@ -189,9 +194,10 @@ class ImageClassifierTest(parameterized.TestCase): f'{classification}') def test_max_results_option(self): + classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) options = _ImageClassifierOptions( base_options=_BaseOptions(file_name=self.model_path), - max_results=_MAX_RESULTS) + classifier_options=classifier_options) with _ImageClassifier.create_from_options(options) as classifier: # Performs image classification on the input. image_result = classifier.classify(self.test_image) @@ -201,9 +207,10 @@ class ImageClassifierTest(parameterized.TestCase): len(categories), _MAX_RESULTS, 'Too many results returned.') def test_allow_list_option(self): + classifier_options = _ClassifierOptions(category_allowlist=_ALLOW_LIST) options = _ImageClassifierOptions( base_options=_BaseOptions(file_name=self.model_path), - category_allowlist=_ALLOW_LIST) + classifier_options=classifier_options) with _ImageClassifier.create_from_options(options) as classifier: # Performs image classification on the input. image_result = classifier.classify(self.test_image) @@ -216,9 +223,10 @@ class ImageClassifierTest(parameterized.TestCase): f'Label {label} found but not in label allow list') def test_deny_list_option(self): + classifier_options = _ClassifierOptions(category_denylist=_DENY_LIST) options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - category_denylist=_DENY_LIST) + base_options=_BaseOptions(file_name=self.model_path), + classifier_options=classifier_options) with _ImageClassifier.create_from_options(options) as classifier: # Performs image classification on the input. image_result = classifier.classify(self.test_image) @@ -236,16 +244,19 @@ class ImageClassifierTest(parameterized.TestCase): ValueError, r'`category_allowlist` and `category_denylist` are mutually ' r'exclusive options.'): + classifier_options = _ClassifierOptions(category_allowlist=['foo'], + category_denylist=['bar']) options = _ImageClassifierOptions( base_options=_BaseOptions(file_name=self.model_path), - category_allowlist=['foo'], - category_denylist=['bar']) + classifier_options=classifier_options) with _ImageClassifier.create_from_options(options) as unused_classifier: pass def test_empty_classification_outputs(self): + classifier_options = _ClassifierOptions(score_threshold=1) options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), score_threshold=1) + base_options=_BaseOptions(file_name=self.model_path), + classifier_options=classifier_options) with _ImageClassifier.create_from_options(options) as classifier: # Performs image classification on the input. image_result = classifier.classify(self.test_image) diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 7a27da179..40caf129f 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -46,8 +46,8 @@ py_library( "//mediapipe/python:_framework_bindings", "//mediapipe/python:packet_creator", "//mediapipe/python:packet_getter", - "//mediapipe/tasks/cc/components:classifier_options_py_pb2", "//mediapipe/tasks/cc/vision/image_classification:image_classifier_options_py_pb2", + "//mediapipe/tasks/python/components:classifier_options", "//mediapipe/tasks/python/components/containers:classifications", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/core:optional_dependencies", diff --git a/mediapipe/tasks/python/vision/image_classification.py b/mediapipe/tasks/python/vision/image_classification.py index 95381d78a..94176cdf8 100644 --- a/mediapipe/tasks/python/vision/image_classification.py +++ b/mediapipe/tasks/python/vision/image_classification.py @@ -21,8 +21,8 @@ from mediapipe.python import packet_getter from mediapipe.python._framework_bindings import image as image_module from mediapipe.python._framework_bindings import packet as packet_module from mediapipe.python._framework_bindings import task_runner as task_runner_module -from mediapipe.tasks.cc.components import classifier_options_pb2 from mediapipe.tasks.cc.vision.image_classification import image_classifier_options_pb2 +from mediapipe.tasks.python.components import classifier_options from mediapipe.tasks.python.components.containers import classifications as classifications_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.core import task_info as task_info_module @@ -31,8 +31,8 @@ from mediapipe.tasks.python.vision.core import base_vision_task_api from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module _BaseOptions = base_options_module.BaseOptions -_ClassifierOptionsProto = classifier_options_pb2.ClassifierOptions _ImageClassifierOptionsProto = image_classifier_options_pb2.ImageClassifierOptions +_ClassifierOptions = classifier_options.ClassifierOptions _RunningMode = running_mode_module.VisionTaskRunningMode _TaskInfo = task_info_module.TaskInfo _TaskRunner = task_runner_module.TaskRunner @@ -77,11 +77,7 @@ class ImageClassifierOptions: """ base_options: _BaseOptions running_mode: _RunningMode = _RunningMode.IMAGE - display_names_locale: Optional[str] = None - max_results: Optional[int] = None - score_threshold: Optional[float] = None - category_allowlist: Optional[List[str]] = None - category_denylist: Optional[List[str]] = None + classifier_options: _ClassifierOptions = _ClassifierOptions() result_callback: Optional[ Callable[[classifications_module.ClassificationResult], None]] = None @@ -91,14 +87,7 @@ class ImageClassifierOptions: """Generates an ImageClassifierOptions protobuf object.""" base_options_proto = self.base_options.to_pb2() base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True - - classifier_options_proto = _ClassifierOptionsProto( - display_names_locale=self.display_names_locale, - max_results=self.max_results, - score_threshold=self.score_threshold, - category_allowlist=self.category_allowlist, - category_denylist=self.category_denylist - ) + classifier_options_proto = self.classifier_options.to_pb2() return _ImageClassifierOptionsProto( base_options=base_options_proto, From bb750befd2e9ca066b76981404f09bbd91919a18 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 21 Sep 2022 04:24:11 -0700 Subject: [PATCH 008/125] Updated ImageClassifierOptions docstring --- .../tasks/python/vision/image_classification.py | 15 +-------------- 1 file changed, 1 insertion(+), 14 deletions(-) diff --git a/mediapipe/tasks/python/vision/image_classification.py b/mediapipe/tasks/python/vision/image_classification.py index 94176cdf8..f08da9f2b 100644 --- a/mediapipe/tasks/python/vision/image_classification.py +++ b/mediapipe/tasks/python/vision/image_classification.py @@ -57,20 +57,7 @@ class ImageClassifierOptions: video. 3) The live stream mode for classifying objects on a live stream of input data, such as from camera. - display_names_locale: The locale to use for display names specified through - the TFLite Model Metadata. - max_results: The maximum number of top-scored classification results to - return. - score_threshold: Overrides the ones provided in the model metadata. Results - below this value are rejected. - category_allowlist: Allowlist of category names. If non-empty, detection - results whose category name is not in this set will be filtered out. - Duplicate or unknown category names are ignored. Mutually exclusive with - `category_denylist`. - category_denylist: Denylist of category names. If non-empty, detection - results whose category name is in this set will be filtered out. Duplicate - or unknown category names are ignored. Mutually exclusive with - `category_allowlist`. + classifier_options: Options for the image classification task. result_callback: The user-defined result callback for processing live stream data. The result callback should only be specified when the running mode is set to the live stream mode. From e028b24c42c8df304551ac6c55ff7706f70855dd Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 21 Sep 2022 04:34:19 -0700 Subject: [PATCH 009/125] Updated values for some constants --- mediapipe/tasks/python/vision/image_segmenter.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/mediapipe/tasks/python/vision/image_segmenter.py b/mediapipe/tasks/python/vision/image_segmenter.py index 47f096473..217867d45 100644 --- a/mediapipe/tasks/python/vision/image_segmenter.py +++ b/mediapipe/tasks/python/vision/image_segmenter.py @@ -36,9 +36,8 @@ _RunningMode = running_mode_module.VisionTaskRunningMode _TaskInfo = task_info_module.TaskInfo _TaskRunner = task_runner_module.TaskRunner -_SEGMENTATION_OUT_STREAM_NAME = 'segmented_masks' -_SEGMENTATION_TAG = 'SEGMENTATION' -_GROUPED_SEGMENTATION_TAG = 'GROUPED_SEGMENTATION' +_SEGMENTATION_OUT_STREAM_NAME = 'segmented_mask_out' +_SEGMENTATION_TAG = 'GROUPED_SEGMENTATION' _IMAGE_IN_STREAM_NAME = 'image_in' _IMAGE_OUT_STREAM_NAME = 'image_out' _IMAGE_TAG = 'IMAGE' From d25626ff63fee6352c6a4f7d15159875c62c5541 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Sun, 25 Sep 2022 09:16:13 -0700 Subject: [PATCH 010/125] Added Image Segmenter implementation and tests --- mediapipe/python/BUILD | 3 +- mediapipe/tasks/python/test/vision/BUILD | 1 + .../test/vision/image_segmenter_test.py | 90 ++++++++++++++++++- .../tasks/python/vision/image_segmenter.py | 4 +- 4 files changed, 92 insertions(+), 6 deletions(-) diff --git a/mediapipe/python/BUILD b/mediapipe/python/BUILD index 55c0a22e5..98e7f80c3 100644 --- a/mediapipe/python/BUILD +++ b/mediapipe/python/BUILD @@ -35,7 +35,7 @@ pybind_extension( }), module_name = "_framework_bindings", deps = [ - ":builtin_calculators", + #":builtin_calculators", ":builtin_task_graphs", "//mediapipe/python/pybind:calculator_graph", "//mediapipe/python/pybind:image", @@ -85,6 +85,7 @@ cc_library( cc_library( name = "builtin_task_graphs", deps = [ + "//mediapipe/calculators/core:flow_limiter_calculator", "//mediapipe/tasks/cc/vision/object_detector:object_detector_graph", "//mediapipe/tasks/cc/vision/image_segmenter:image_segmenter_graph", ], diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 403e00a37..bec75923d 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -47,6 +47,7 @@ py_test( ], deps = [ # build rule placeholder: numpy dep, + # build rule placeholder: cv2 dep, "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/test:test_util", "//mediapipe/tasks/python/components:segmenter_options", diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index 8a91766df..c3763577d 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -14,11 +14,14 @@ """Tests for image segmenter.""" import enum +import numpy as np +import cv2 from absl.testing import absltest from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module +from mediapipe.python._framework_bindings import image_frame as image_frame_module from mediapipe.tasks.python.components import segmenter_options from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_util @@ -27,6 +30,7 @@ from mediapipe.tasks.python.vision.core import vision_task_running_mode as runni _BaseOptions = base_options_module.BaseOptions _Image = image_module.Image +_ImageFormat = image_frame_module.ImageFormat _OutputType = segmenter_options.OutputType _Activation = segmenter_options.Activation _SegmenterOptions = segmenter_options.SegmenterOptions @@ -41,6 +45,13 @@ _MASK_MAGNIFICATION_FACTOR = 10 _MATCH_PIXELS_THRESHOLD = 0.01 +def _iou(ground_truth, prediction): + intersection = np.logical_and(ground_truth, prediction) + union = np.logical_or(ground_truth, prediction) + iou = np.sum(intersection) / np.sum(union) + return iou + + class ModelFileType(enum.Enum): FILE_CONTENT = 1 FILE_NAME = 2 @@ -52,6 +63,7 @@ class ImageSegmenterTest(parameterized.TestCase): super().setUp() self.test_image = test_util.read_test_image( test_util.get_test_data_path(_IMAGE_FILE)) + self.test_seg_path = test_util.get_test_data_path(_SEGMENTATION_FILE) self.model_path = test_util.get_test_data_path(_MODEL_FILE) def test_create_from_file_succeeds_with_valid_model_path(self): @@ -85,9 +97,9 @@ class ImageSegmenterTest(parameterized.TestCase): self.assertIsInstance(segmenter, _ImageSegmenter) @parameterized.parameters( - (ModelFileType.FILE_NAME, 4), - (ModelFileType.FILE_CONTENT, 4)) - def succeeds_with_category_mask(self, model_file_type, max_results): + (ModelFileType.FILE_NAME,), + (ModelFileType.FILE_CONTENT,)) + def test_succeeds_with_category_mask(self, model_file_type): # Creates segmenter. if model_file_type is ModelFileType.FILE_NAME: base_options = _BaseOptions(file_name=self.model_path) @@ -106,6 +118,78 @@ class ImageSegmenterTest(parameterized.TestCase): # Performs image segmentation on the input. category_masks = segmenter.segment(self.test_image) + self.assertEqual(len(category_masks), 1) + result_pixels = category_masks[0].numpy_view().flatten() + + # Check if data type of `category_masks` is correct. + self.assertEqual(result_pixels.dtype, np.uint8) + + # Loads ground truth segmentation file. + image_data = cv2.imread(self.test_seg_path, cv2.IMREAD_GRAYSCALE) + gt_segmentation = _Image(_ImageFormat.GRAY8, image_data) + gt_segmentation_array = gt_segmentation.numpy_view() + gt_segmentation_shape = gt_segmentation_array.shape + num_pixels = gt_segmentation_shape[0] * gt_segmentation_shape[1] + ground_truth_pixels = gt_segmentation_array.flatten() + + self.assertEqual( + len(result_pixels), len(ground_truth_pixels), + 'Segmentation mask size does not match the ground truth mask size.') + + inconsistent_pixels = 0 + + for index in range(num_pixels): + inconsistent_pixels += ( + result_pixels[index] * _MASK_MAGNIFICATION_FACTOR != + ground_truth_pixels[index]) + + self.assertLessEqual( + inconsistent_pixels / num_pixels, _MATCH_PIXELS_THRESHOLD, + f'Number of pixels in the candidate mask differing from that of the ' + f'ground truth mask exceeds {_MATCH_PIXELS_THRESHOLD}.') + + # Closes the segmenter explicitly when the segmenter is not used in + # a context. + segmenter.close() + + def test_succeeds_with_confidence_mask(self): + # Creates segmenter. + base_options = _BaseOptions(file_name=self.model_path) + + # Run segmentation on the model in CATEGORY_MASK mode. + segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) + options = _ImageSegmenterOptions(base_options=base_options, + segmenter_options=segmenter_options) + segmenter = _ImageSegmenter.create_from_options(options) + category_masks = segmenter.segment(self.test_image) + category_mask = category_masks[0].numpy_view() + + # Run segmentation on the model in CONFIDENCE_MASK mode. + segmenter_options = _SegmenterOptions( + output_type=_OutputType.CONFIDENCE_MASK, + activation=_Activation.SOFTMAX) + options = _ImageSegmenterOptions(base_options=base_options, + segmenter_options=segmenter_options) + segmenter = _ImageSegmenter.create_from_options(options) + confidence_masks = segmenter.segment(self.test_image) + + # Check if confidence mask shape is correct. + self.assertEqual( + len(confidence_masks), 21, + 'Number of confidence masks must match with number of categories.') + + # Gather the confidence masks in a single array `confidence_mask_array`. + confidence_mask_array = np.array( + [confidence_mask.numpy_view() for confidence_mask in confidence_masks]) + + # Check if data type of `confidence_masks` are correct. + self.assertEqual(confidence_mask_array.dtype, np.float32) + + # Compute the category mask from the created confidence mask. + calculated_category_mask = np.argmax(confidence_mask_array, axis=0) + self.assertListEqual( + calculated_category_mask.tolist(), category_mask.tolist(), + 'Confidence mask does not match with the category mask.') # Closes the segmenter explicitly when the segmenter is not used in # a context. diff --git a/mediapipe/tasks/python/vision/image_segmenter.py b/mediapipe/tasks/python/vision/image_segmenter.py index 217867d45..b643b1cb8 100644 --- a/mediapipe/tasks/python/vision/image_segmenter.py +++ b/mediapipe/tasks/python/vision/image_segmenter.py @@ -128,7 +128,7 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): def packets_callback(output_packets: Mapping[str, packet_module.Packet]): if output_packets[_IMAGE_OUT_STREAM_NAME].is_empty(): return - segmentation_result = packet_getter.get_proto_list( + segmentation_result = packet_getter.get_image_list( output_packets[_SEGMENTATION_OUT_STREAM_NAME]) image = packet_getter.get_image(output_packets[_IMAGE_OUT_STREAM_NAME]) timestamp = output_packets[_IMAGE_OUT_STREAM_NAME].timestamp @@ -166,6 +166,6 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): """ output_packets = self._process_image_data( {_IMAGE_IN_STREAM_NAME: packet_creator.create_image(image)}) - segmentation_result = packet_getter.get_proto_list( + segmentation_result = packet_getter.get_image_list( output_packets[_SEGMENTATION_OUT_STREAM_NAME]) return segmentation_result From 63e0c042535c8924862fd0b8c82c96223ea3e865 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 29 Sep 2022 02:03:07 -0700 Subject: [PATCH 011/125] Updated BUILD and tests --- mediapipe/tasks/python/test/vision/BUILD | 6 ++---- mediapipe/tasks/python/test/vision/image_segmenter_test.py | 7 ------- 2 files changed, 2 insertions(+), 11 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index bec75923d..6baca8850 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -26,7 +26,7 @@ py_test( "//mediapipe/tasks/testdata/vision:test_models", ], deps = [ - # build rule placeholder: numpy dep, + "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/python/components/containers:bounding_box", "//mediapipe/tasks/python/components/containers:category", "//mediapipe/tasks/python/components/containers:detections", @@ -34,7 +34,6 @@ py_test( "//mediapipe/tasks/python/test:test_util", "//mediapipe/tasks/python/vision:object_detector", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", - "@absl_py//absl/testing:parameterized", ], ) @@ -46,8 +45,7 @@ py_test( "//mediapipe/tasks/testdata/vision:test_models", ], deps = [ - # build rule placeholder: numpy dep, - # build rule placeholder: cv2 dep, + "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/test:test_util", "//mediapipe/tasks/python/components:segmenter_options", diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index c3763577d..72be676d7 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -45,13 +45,6 @@ _MASK_MAGNIFICATION_FACTOR = 10 _MATCH_PIXELS_THRESHOLD = 0.01 -def _iou(ground_truth, prediction): - intersection = np.logical_and(ground_truth, prediction) - union = np.logical_or(ground_truth, prediction) - iou = np.sum(intersection) / np.sum(union) - return iou - - class ModelFileType(enum.Enum): FILE_CONTENT = 1 FILE_NAME = 2 From 72319ecbf57cb56502e8e9af912b7caa37e2b2eb Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 29 Sep 2022 02:14:42 -0700 Subject: [PATCH 012/125] Updated BUILD --- mediapipe/tasks/python/test/vision/BUILD | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index a63c36b55..46efc402d 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -26,7 +26,7 @@ py_test( "//mediapipe/tasks/testdata/vision:test_models", ], deps = [ - # build rule placeholder: numpy dep, + "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/python/components/containers:bounding_box", "//mediapipe/tasks/python/components/containers:category", "//mediapipe/tasks/python/components/containers:detections", @@ -34,7 +34,6 @@ py_test( "//mediapipe/tasks/python/test:test_util", "//mediapipe/tasks/python/vision:object_detector", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", - "@absl_py//absl/testing:parameterized", ], ) @@ -46,6 +45,7 @@ py_test( "//mediapipe/tasks/testdata/vision:test_models", ], deps = [ + "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/python/components/containers:category", "//mediapipe/tasks/python/components/containers:classifications", "//mediapipe/tasks/python/core:base_options", From 8ad591822922338aca7cabd25fddd3bacdc98d9d Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 29 Sep 2022 02:18:10 -0700 Subject: [PATCH 013/125] Removed some tests --- .../test/vision/image_classification_test.py | 165 ------------------ 1 file changed, 165 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_classification_test.py b/mediapipe/tasks/python/test/vision/image_classification_test.py index 51dcb1adf..0d7f9e7f0 100644 --- a/mediapipe/tasks/python/test/vision/image_classification_test.py +++ b/mediapipe/tasks/python/test/vision/image_classification_test.py @@ -92,36 +92,6 @@ class ImageClassifierTest(parameterized.TestCase): test_util.get_test_data_path(_IMAGE_FILE)) self.model_path = test_util.get_test_data_path(_MODEL_FILE) - def test_create_from_file_succeeds_with_valid_model_path(self): - # Creates with default option and valid model file successfully. - with _ImageClassifier.create_from_model_path(self.model_path) as classifier: - self.assertIsInstance(classifier, _ImageClassifier) - - def test_create_from_options_succeeds_with_valid_model_path(self): - # Creates with options containing model file successfully. - base_options = _BaseOptions(file_name=self.model_path) - options = _ImageClassifierOptions(base_options=base_options) - with _ImageClassifier.create_from_options(options) as classifier: - self.assertIsInstance(classifier, _ImageClassifier) - - def test_create_from_options_fails_with_invalid_model_path(self): - # Invalid empty model path. - with self.assertRaisesRegex( - ValueError, - r"ExternalFile must specify at least one of 'file_content', " - r"'file_name' or 'file_descriptor_meta'."): - base_options = _BaseOptions(file_name='') - options = _ImageClassifierOptions(base_options=base_options) - _ImageClassifier.create_from_options(options) - - def test_create_from_options_succeeds_with_valid_model_content(self): - # Creates with options containing model content successfully. - with open(self.model_path, 'rb') as f: - base_options = _BaseOptions(file_content=f.read()) - options = _ImageClassifierOptions(base_options=base_options) - classifier = _ImageClassifier.create_from_options(options) - self.assertIsInstance(classifier, _ImageClassifier) - @parameterized.parameters( (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) @@ -151,141 +121,6 @@ class ImageClassifierTest(parameterized.TestCase): # a context. classifier.close() - @parameterized.parameters( - (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), - (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) - def test_classify_in_context(self, model_file_type, max_results, - expected_classification_result): - if model_file_type is ModelFileType.FILE_NAME: - base_options = _BaseOptions(file_name=self.model_path) - elif model_file_type is ModelFileType.FILE_CONTENT: - with open(self.model_path, 'rb') as f: - model_content = f.read() - base_options = _BaseOptions(file_content=model_content) - else: - # Should never happen - raise ValueError('model_file_type is invalid.') - - classifier_options = _ClassifierOptions(max_results=max_results) - options = _ImageClassifierOptions( - base_options=base_options, classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs object detection on the input. - image_result = classifier.classify(self.test_image) - # Comparing results. - self.assertEqual(image_result, expected_classification_result) - - def test_score_threshold_option(self): - classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - classifications = image_result.classifications - - for classification in classifications: - for entry in classification.entries: - score = entry.categories[0].score - self.assertGreaterEqual( - score, _SCORE_THRESHOLD, - f'Classification with score lower than threshold found. ' - f'{classification}') - - def test_max_results_option(self): - classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - categories = image_result.classifications[0].entries[0].categories - - self.assertLessEqual( - len(categories), _MAX_RESULTS, 'Too many results returned.') - - def test_allow_list_option(self): - classifier_options = _ClassifierOptions(category_allowlist=_ALLOW_LIST) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - classifications = image_result.classifications - - for classification in classifications: - for entry in classification.entries: - label = entry.categories[0].category_name - self.assertIn(label, _ALLOW_LIST, - f'Label {label} found but not in label allow list') - - def test_deny_list_option(self): - classifier_options = _ClassifierOptions(category_denylist=_DENY_LIST) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - classifications = image_result.classifications - - for classification in classifications: - for entry in classification.entries: - label = entry.categories[0].category_name - self.assertNotIn(label, _DENY_LIST, - f'Label {label} found but in deny list.') - - def test_combined_allowlist_and_denylist(self): - # Fails with combined allowlist and denylist - with self.assertRaisesRegex( - ValueError, - r'`category_allowlist` and `category_denylist` are mutually ' - r'exclusive options.'): - classifier_options = _ClassifierOptions(category_allowlist=['foo'], - category_denylist=['bar']) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as unused_classifier: - pass - - def test_empty_classification_outputs(self): - classifier_options = _ClassifierOptions(score_threshold=1) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - self.assertEmpty(image_result.classifications[0].entries[0].categories) - - def test_missing_result_callback(self): - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - running_mode=_RUNNING_MODE.LIVE_STREAM) - with self.assertRaisesRegex(ValueError, - r'result callback must be provided'): - with _ImageClassifier.create_from_options(options) as unused_classifier: - pass - - @parameterized.parameters((_RUNNING_MODE.IMAGE), (_RUNNING_MODE.VIDEO)) - def test_illegal_result_callback(self, running_mode): - - def pass_through(unused_result: _ClassificationResult): - pass - - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - running_mode=running_mode, - result_callback=pass_through) - with self.assertRaisesRegex(ValueError, - r'result callback should not be provided'): - with _ImageClassifier.create_from_options(options) as unused_classifier: - pass - if __name__ == '__main__': absltest.main() From b04af0cafa7b8ec0d48122d20c7bd2f7693b12f0 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 29 Sep 2022 02:45:20 -0700 Subject: [PATCH 014/125] Updated implementation and tests --- mediapipe/python/BUILD | 2 +- mediapipe/tasks/python/components/proto/BUILD | 29 +++++++++++++++++++ .../{ => proto}/classifier_options.py | 0 .../test/vision/image_classification_test.py | 4 +-- mediapipe/tasks/python/vision/BUILD | 4 +-- .../python/vision/image_classification.py | 6 ++-- 6 files changed, 37 insertions(+), 8 deletions(-) create mode 100644 mediapipe/tasks/python/components/proto/BUILD rename mediapipe/tasks/python/components/{ => proto}/classifier_options.py (100%) diff --git a/mediapipe/python/BUILD b/mediapipe/python/BUILD index 9fe21ab9e..33667d18e 100644 --- a/mediapipe/python/BUILD +++ b/mediapipe/python/BUILD @@ -86,7 +86,7 @@ cc_library( name = "builtin_task_graphs", deps = [ "//mediapipe/tasks/cc/vision/object_detector:object_detector_graph", - "//mediapipe/tasks/cc/vision/image_classification:image_classifier_graph", + "//mediapipe/tasks/cc/vision/image_classifier:image_classifier_graph", ], ) diff --git a/mediapipe/tasks/python/components/proto/BUILD b/mediapipe/tasks/python/components/proto/BUILD new file mode 100644 index 000000000..7814ec675 --- /dev/null +++ b/mediapipe/tasks/python/components/proto/BUILD @@ -0,0 +1,29 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Placeholder for internal Python strict library compatibility macro. + +package(default_visibility = ["//mediapipe/tasks:internal"]) + +licenses(["notice"]) + +py_library( + name = "classifier_options", + srcs = ["classifier_options.py"], + deps = [ + "//mediapipe/tasks/cc/components/proto:classifier_options_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) + diff --git a/mediapipe/tasks/python/components/classifier_options.py b/mediapipe/tasks/python/components/proto/classifier_options.py similarity index 100% rename from mediapipe/tasks/python/components/classifier_options.py rename to mediapipe/tasks/python/components/proto/classifier_options.py diff --git a/mediapipe/tasks/python/test/vision/image_classification_test.py b/mediapipe/tasks/python/test/vision/image_classification_test.py index 0d7f9e7f0..08d850dab 100644 --- a/mediapipe/tasks/python/test/vision/image_classification_test.py +++ b/mediapipe/tasks/python/test/vision/image_classification_test.py @@ -99,11 +99,11 @@ class ImageClassifierTest(parameterized.TestCase): expected_classification_result): # Creates classifier. if model_file_type is ModelFileType.FILE_NAME: - base_options = _BaseOptions(file_name=self.model_path) + base_options = _BaseOptions(model_asset_path=self.model_path) elif model_file_type is ModelFileType.FILE_CONTENT: with open(self.model_path, 'rb') as f: model_content = f.read() - base_options = _BaseOptions(file_content=model_content) + base_options = _BaseOptions(model_asset_buffer=model_content) else: # Should never happen raise ValueError('model_file_type is invalid.') diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 40caf129f..5e5bfe3ba 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -46,8 +46,8 @@ py_library( "//mediapipe/python:_framework_bindings", "//mediapipe/python:packet_creator", "//mediapipe/python:packet_getter", - "//mediapipe/tasks/cc/vision/image_classification:image_classifier_options_py_pb2", - "//mediapipe/tasks/python/components:classifier_options", + "//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_options_py_pb2", + "//mediapipe/tasks/python/components/proto:classifier_options", "//mediapipe/tasks/python/components/containers:classifications", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/core:optional_dependencies", diff --git a/mediapipe/tasks/python/vision/image_classification.py b/mediapipe/tasks/python/vision/image_classification.py index f08da9f2b..c240ffedf 100644 --- a/mediapipe/tasks/python/vision/image_classification.py +++ b/mediapipe/tasks/python/vision/image_classification.py @@ -21,8 +21,8 @@ from mediapipe.python import packet_getter from mediapipe.python._framework_bindings import image as image_module from mediapipe.python._framework_bindings import packet as packet_module from mediapipe.python._framework_bindings import task_runner as task_runner_module -from mediapipe.tasks.cc.vision.image_classification import image_classifier_options_pb2 -from mediapipe.tasks.python.components import classifier_options +from mediapipe.tasks.cc.vision.image_classifier.proto import image_classifier_options_pb2 +from mediapipe.tasks.python.components.proto import classifier_options from mediapipe.tasks.python.components.containers import classifications as classifications_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.core import task_info as task_info_module @@ -104,7 +104,7 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): file such as invalid file path. RuntimeError: If other types of error occurred. """ - base_options = _BaseOptions(file_name=model_path) + base_options = _BaseOptions(model_asset_path=model_path) options = ImageClassifierOptions( base_options=base_options, running_mode=_RunningMode.IMAGE) return cls.create_from_options(options) From cba2a6035c55842c440cb8be78244794eca38cf4 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 29 Sep 2022 03:15:17 -0700 Subject: [PATCH 015/125] Code cleanup --- .../tasks/python/components/proto/classifier_options.py | 2 +- mediapipe/tasks/python/test/vision/BUILD | 7 ++++--- ...ge_classification_test.py => image_classifier_test.py} | 8 ++++---- mediapipe/tasks/python/vision/BUILD | 4 ++-- .../{image_classification.py => image_classifier.py} | 0 5 files changed, 11 insertions(+), 10 deletions(-) rename mediapipe/tasks/python/test/vision/{image_classification_test.py => image_classifier_test.py} (94%) rename mediapipe/tasks/python/vision/{image_classification.py => image_classifier.py} (100%) diff --git a/mediapipe/tasks/python/components/proto/classifier_options.py b/mediapipe/tasks/python/components/proto/classifier_options.py index f6e61e48c..c73828c13 100644 --- a/mediapipe/tasks/python/components/proto/classifier_options.py +++ b/mediapipe/tasks/python/components/proto/classifier_options.py @@ -16,7 +16,7 @@ import dataclasses from typing import Any, List, Optional -from mediapipe.tasks.cc.components import classifier_options_pb2 +from mediapipe.tasks.cc.components.proto import classifier_options_pb2 from mediapipe.tasks.python.core.optional_dependencies import doc_controls _ClassifierOptionsProto = classifier_options_pb2.ClassifierOptions diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index c96be63f8..6b6b9e3e2 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -38,19 +38,20 @@ py_test( ) py_test( - name = "image_classification_test", - srcs = ["image_classification_test.py"], + name = "image_classifier_test", + srcs = ["image_classifier_test.py"], data = [ "//mediapipe/tasks/testdata/vision:test_images", "//mediapipe/tasks/testdata/vision:test_models", ], deps = [ "//mediapipe/python:_framework_bindings", + "//mediapipe/tasks/python/components/proto:classifier_options", "//mediapipe/tasks/python/components/containers:category", "//mediapipe/tasks/python/components/containers:classifications", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/test:test_util", - "//mediapipe/tasks/python/vision:image_classification", + "//mediapipe/tasks/python/vision:image_classifier", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", ], ) diff --git a/mediapipe/tasks/python/test/vision/image_classification_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py similarity index 94% rename from mediapipe/tasks/python/test/vision/image_classification_test.py rename to mediapipe/tasks/python/test/vision/image_classifier_test.py index 08d850dab..3d7d116df 100644 --- a/mediapipe/tasks/python/test/vision/image_classification_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -19,12 +19,12 @@ from absl.testing import absltest from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module -from mediapipe.tasks.python.components import classifier_options +from mediapipe.tasks.python.components.proto import classifier_options from mediapipe.tasks.python.components.containers import category as category_module from mediapipe.tasks.python.components.containers import classifications as classifications_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_util -from mediapipe.tasks.python.vision import image_classification +from mediapipe.tasks.python.vision import image_classifier from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module _BaseOptions = base_options_module.BaseOptions @@ -34,8 +34,8 @@ _ClassificationEntry = classifications_module.ClassificationEntry _Classifications = classifications_module.Classifications _ClassificationResult = classifications_module.ClassificationResult _Image = image_module.Image -_ImageClassifier = image_classification.ImageClassifier -_ImageClassifierOptions = image_classification.ImageClassifierOptions +_ImageClassifier = image_classifier.ImageClassifier +_ImageClassifierOptions = image_classifier.ImageClassifierOptions _RUNNING_MODE = running_mode_module.VisionTaskRunningMode _MODEL_FILE = 'mobilenet_v2_1.0_224.tflite' diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 5e5bfe3ba..a724f149a 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -38,9 +38,9 @@ py_library( ) py_library( - name = "image_classification", + name = "image_classifier", srcs = [ - "image_classification.py", + "image_classifier.py", ], deps = [ "//mediapipe/python:_framework_bindings", diff --git a/mediapipe/tasks/python/vision/image_classification.py b/mediapipe/tasks/python/vision/image_classifier.py similarity index 100% rename from mediapipe/tasks/python/vision/image_classification.py rename to mediapipe/tasks/python/vision/image_classifier.py From bef2f6ccedaca0ac28f45602a7676fa794090f57 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 29 Sep 2022 03:40:56 -0700 Subject: [PATCH 016/125] Updated implementation and tests --- mediapipe/tasks/python/components/BUILD | 9 ------ mediapipe/tasks/python/components/proto/BUILD | 28 +++++++++++++++++++ .../{ => proto}/segmenter_options.py | 2 +- mediapipe/tasks/python/test/vision/BUILD | 2 +- .../test/vision/image_segmenter_test.py | 14 +++++----- mediapipe/tasks/python/vision/BUILD | 2 +- .../tasks/python/vision/image_segmenter.py | 4 +-- 7 files changed, 40 insertions(+), 21 deletions(-) create mode 100644 mediapipe/tasks/python/components/proto/BUILD rename mediapipe/tasks/python/components/{ => proto}/segmenter_options.py (97%) diff --git a/mediapipe/tasks/python/components/BUILD b/mediapipe/tasks/python/components/BUILD index eb8714a93..00fd4061c 100644 --- a/mediapipe/tasks/python/components/BUILD +++ b/mediapipe/tasks/python/components/BUILD @@ -17,12 +17,3 @@ package(default_visibility = ["//mediapipe/tasks:internal"]) licenses(["notice"]) - -py_library( - name = "segmenter_options", - srcs = ["segmenter_options.py"], - deps = [ - "//mediapipe/tasks/cc/components:segmenter_options_py_pb2", - "//mediapipe/tasks/python/core:optional_dependencies", - ], -) diff --git a/mediapipe/tasks/python/components/proto/BUILD b/mediapipe/tasks/python/components/proto/BUILD new file mode 100644 index 000000000..a58f77e6c --- /dev/null +++ b/mediapipe/tasks/python/components/proto/BUILD @@ -0,0 +1,28 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Placeholder for internal Python strict library compatibility macro. + +package(default_visibility = ["//mediapipe/tasks:internal"]) + +licenses(["notice"]) + +py_library( + name = "segmenter_options", + srcs = ["segmenter_options.py"], + deps = [ + "//mediapipe/tasks/cc/components/proto:segmenter_options_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) diff --git a/mediapipe/tasks/python/components/segmenter_options.py b/mediapipe/tasks/python/components/proto/segmenter_options.py similarity index 97% rename from mediapipe/tasks/python/components/segmenter_options.py rename to mediapipe/tasks/python/components/proto/segmenter_options.py index 5b94a256d..dcf34cc39 100644 --- a/mediapipe/tasks/python/components/segmenter_options.py +++ b/mediapipe/tasks/python/components/proto/segmenter_options.py @@ -17,7 +17,7 @@ import dataclasses import enum from typing import Any, Optional -from mediapipe.tasks.cc.components import segmenter_options_pb2 +from mediapipe.tasks.cc.components.proto import segmenter_options_pb2 from mediapipe.tasks.python.core.optional_dependencies import doc_controls _SegmenterOptionsProto = segmenter_options_pb2.SegmenterOptions diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 6baca8850..ea6608fcb 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -48,7 +48,7 @@ py_test( "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/test:test_util", - "//mediapipe/tasks/python/components:segmenter_options", + "//mediapipe/tasks/python/components/proto:segmenter_options", "//mediapipe/tasks/python/vision:image_segmenter", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", "@absl_py//absl/testing:parameterized", diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index 72be676d7..9ebd46bc4 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -22,7 +22,7 @@ from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module from mediapipe.python._framework_bindings import image_frame as image_frame_module -from mediapipe.tasks.python.components import segmenter_options +from mediapipe.tasks.python.components.proto import segmenter_options from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_util from mediapipe.tasks.python.vision import image_segmenter @@ -66,7 +66,7 @@ class ImageSegmenterTest(parameterized.TestCase): def test_create_from_options_succeeds_with_valid_model_path(self): # Creates with options containing model file successfully. - base_options = _BaseOptions(file_name=self.model_path) + base_options = _BaseOptions(model_asset_path=self.model_path) options = _ImageSegmenterOptions(base_options=base_options) with _ImageSegmenter.create_from_options(options) as segmenter: self.assertIsInstance(segmenter, _ImageSegmenter) @@ -77,14 +77,14 @@ class ImageSegmenterTest(parameterized.TestCase): ValueError, r"ExternalFile must specify at least one of 'file_content', " r"'file_name' or 'file_descriptor_meta'."): - base_options = _BaseOptions(file_name='') + base_options = _BaseOptions(model_asset_path='') options = _ImageSegmenterOptions(base_options=base_options) _ImageSegmenter.create_from_options(options) def test_create_from_options_succeeds_with_valid_model_content(self): # Creates with options containing model content successfully. with open(self.model_path, 'rb') as f: - base_options = _BaseOptions(file_content=f.read()) + base_options = _BaseOptions(model_asset_buffer=f.read()) options = _ImageSegmenterOptions(base_options=base_options) segmenter = _ImageSegmenter.create_from_options(options) self.assertIsInstance(segmenter, _ImageSegmenter) @@ -95,11 +95,11 @@ class ImageSegmenterTest(parameterized.TestCase): def test_succeeds_with_category_mask(self, model_file_type): # Creates segmenter. if model_file_type is ModelFileType.FILE_NAME: - base_options = _BaseOptions(file_name=self.model_path) + base_options = _BaseOptions(model_asset_path=self.model_path) elif model_file_type is ModelFileType.FILE_CONTENT: with open(self.model_path, 'rb') as f: model_content = f.read() - base_options = _BaseOptions(file_content=model_content) + base_options = _BaseOptions(model_asset_buffer=model_content) else: # Should never happen raise ValueError('model_file_type is invalid.') @@ -147,7 +147,7 @@ class ImageSegmenterTest(parameterized.TestCase): def test_succeeds_with_confidence_mask(self): # Creates segmenter. - base_options = _BaseOptions(file_name=self.model_path) + base_options = _BaseOptions(model_asset_path=self.model_path) # Run segmentation on the model in CATEGORY_MASK mode. segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index ce59763d6..3875ea5de 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -47,7 +47,7 @@ py_library( "//mediapipe/python:packet_creator", "//mediapipe/python:packet_getter", "//mediapipe/tasks/cc/vision/image_segmenter/proto:image_segmenter_options_py_pb2", - "//mediapipe/tasks/python/components:segmenter_options", + "//mediapipe/tasks/python/components/proto:segmenter_options", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/core:optional_dependencies", "//mediapipe/tasks/python/core:task_info", diff --git a/mediapipe/tasks/python/vision/image_segmenter.py b/mediapipe/tasks/python/vision/image_segmenter.py index b643b1cb8..060a67793 100644 --- a/mediapipe/tasks/python/vision/image_segmenter.py +++ b/mediapipe/tasks/python/vision/image_segmenter.py @@ -22,7 +22,7 @@ from mediapipe.python._framework_bindings import image as image_module from mediapipe.python._framework_bindings import packet as packet_module from mediapipe.python._framework_bindings import task_runner as task_runner_module from mediapipe.tasks.cc.vision.image_segmenter.proto import image_segmenter_options_pb2 -from mediapipe.tasks.python.components import segmenter_options +from mediapipe.tasks.python.components.proto import segmenter_options from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.core import task_info as task_info_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls @@ -103,7 +103,7 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): file such as invalid file path. RuntimeError: If other types of error occurred. """ - base_options = _BaseOptions(file_name=model_path) + base_options = _BaseOptions(model_asset_path=model_path) options = ImageSegmenterOptions( base_options=base_options, running_mode=_RunningMode.IMAGE) return cls.create_from_options(options) From 68fea17e30a5c316f30617e1bda2e53336b41108 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 29 Sep 2022 13:34:10 -0700 Subject: [PATCH 017/125] Removed unused dependencies in BUILD --- mediapipe/tasks/python/components/BUILD | 9 --------- 1 file changed, 9 deletions(-) diff --git a/mediapipe/tasks/python/components/BUILD b/mediapipe/tasks/python/components/BUILD index 4094b7f7f..00fd4061c 100644 --- a/mediapipe/tasks/python/components/BUILD +++ b/mediapipe/tasks/python/components/BUILD @@ -17,12 +17,3 @@ package(default_visibility = ["//mediapipe/tasks:internal"]) licenses(["notice"]) - -py_library( - name = "classifier_options", - srcs = ["classifier_options.py"], - deps = [ - "//mediapipe/tasks/cc/components:classifier_options_py_pb2", - "//mediapipe/tasks/python/core:optional_dependencies", - ], -) From 85af7ac9bcbf024178d8f389c8251aed2c5da36d Mon Sep 17 00:00:00 2001 From: kinaryml Date: Thu, 29 Sep 2022 13:36:07 -0700 Subject: [PATCH 018/125] Removed unused BUILD --- mediapipe/tasks/python/components/BUILD | 19 ------------------- 1 file changed, 19 deletions(-) delete mode 100644 mediapipe/tasks/python/components/BUILD diff --git a/mediapipe/tasks/python/components/BUILD b/mediapipe/tasks/python/components/BUILD deleted file mode 100644 index 00fd4061c..000000000 --- a/mediapipe/tasks/python/components/BUILD +++ /dev/null @@ -1,19 +0,0 @@ -# Copyright 2022 The MediaPipe Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Placeholder for internal Python strict library compatibility macro. - -package(default_visibility = ["//mediapipe/tasks:internal"]) - -licenses(["notice"]) From f241630b56261ac5009ba6638c7f5b8db9e699e1 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Mon, 3 Oct 2022 15:11:48 -0700 Subject: [PATCH 019/125] Revised implementation to align with recent changes --- .../components/containers/{ => proto}/BUILD | 2 +- .../containers/{ => proto}/__init__.py | 0 .../containers/{ => proto}/bounding_box.py | 0 .../containers/{ => proto}/category.py | 0 .../containers/{ => proto}/classifications.py | 4 ++-- .../containers/{ => proto}/detections.py | 0 .../components/{ => processors}/proto/BUILD | 3 +-- .../proto/classifier_options.py | 2 +- mediapipe/tasks/python/test/vision/BUILD | 8 ++++---- .../test/vision/image_classifier_test.py | 14 ++++++------- mediapipe/tasks/python/vision/BUILD | 6 +++--- .../tasks/python/vision/image_classifier.py | 20 ++++++++++--------- 12 files changed, 30 insertions(+), 29 deletions(-) rename mediapipe/tasks/python/components/containers/{ => proto}/BUILD (95%) rename mediapipe/tasks/python/components/containers/{ => proto}/__init__.py (100%) rename mediapipe/tasks/python/components/containers/{ => proto}/bounding_box.py (100%) rename mediapipe/tasks/python/components/containers/{ => proto}/category.py (100%) rename mediapipe/tasks/python/components/containers/{ => proto}/classifications.py (96%) rename mediapipe/tasks/python/components/containers/{ => proto}/detections.py (100%) rename mediapipe/tasks/python/components/{ => processors}/proto/BUILD (91%) rename mediapipe/tasks/python/components/{ => processors}/proto/classifier_options.py (97%) diff --git a/mediapipe/tasks/python/components/containers/BUILD b/mediapipe/tasks/python/components/containers/proto/BUILD similarity index 95% rename from mediapipe/tasks/python/components/containers/BUILD rename to mediapipe/tasks/python/components/containers/proto/BUILD index 450111161..d46df22da 100644 --- a/mediapipe/tasks/python/components/containers/BUILD +++ b/mediapipe/tasks/python/components/containers/proto/BUILD @@ -53,7 +53,7 @@ py_library( srcs = ["classifications.py"], deps = [ ":category", - "//mediapipe/tasks/cc/components/containers:classifications_py_pb2", + "//mediapipe/tasks/cc/components/containers/proto:classifications_py_pb2", "//mediapipe/tasks/python/core:optional_dependencies", ], ) diff --git a/mediapipe/tasks/python/components/containers/__init__.py b/mediapipe/tasks/python/components/containers/proto/__init__.py similarity index 100% rename from mediapipe/tasks/python/components/containers/__init__.py rename to mediapipe/tasks/python/components/containers/proto/__init__.py diff --git a/mediapipe/tasks/python/components/containers/bounding_box.py b/mediapipe/tasks/python/components/containers/proto/bounding_box.py similarity index 100% rename from mediapipe/tasks/python/components/containers/bounding_box.py rename to mediapipe/tasks/python/components/containers/proto/bounding_box.py diff --git a/mediapipe/tasks/python/components/containers/category.py b/mediapipe/tasks/python/components/containers/proto/category.py similarity index 100% rename from mediapipe/tasks/python/components/containers/category.py rename to mediapipe/tasks/python/components/containers/proto/category.py diff --git a/mediapipe/tasks/python/components/containers/classifications.py b/mediapipe/tasks/python/components/containers/proto/classifications.py similarity index 96% rename from mediapipe/tasks/python/components/containers/classifications.py rename to mediapipe/tasks/python/components/containers/proto/classifications.py index 19c5decde..2c43370b2 100644 --- a/mediapipe/tasks/python/components/containers/classifications.py +++ b/mediapipe/tasks/python/components/containers/proto/classifications.py @@ -16,8 +16,8 @@ import dataclasses from typing import Any, List, Optional -from mediapipe.tasks.cc.components.containers import classifications_pb2 -from mediapipe.tasks.python.components.containers import category as category_module +from mediapipe.tasks.cc.components.containers.proto import classifications_pb2 +from mediapipe.tasks.python.components.containers.proto import category as category_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls _ClassificationEntryProto = classifications_pb2.ClassificationEntry diff --git a/mediapipe/tasks/python/components/containers/detections.py b/mediapipe/tasks/python/components/containers/proto/detections.py similarity index 100% rename from mediapipe/tasks/python/components/containers/detections.py rename to mediapipe/tasks/python/components/containers/proto/detections.py diff --git a/mediapipe/tasks/python/components/proto/BUILD b/mediapipe/tasks/python/components/processors/proto/BUILD similarity index 91% rename from mediapipe/tasks/python/components/proto/BUILD rename to mediapipe/tasks/python/components/processors/proto/BUILD index 7814ec675..814e15d1f 100644 --- a/mediapipe/tasks/python/components/proto/BUILD +++ b/mediapipe/tasks/python/components/processors/proto/BUILD @@ -22,8 +22,7 @@ py_library( name = "classifier_options", srcs = ["classifier_options.py"], deps = [ - "//mediapipe/tasks/cc/components/proto:classifier_options_py_pb2", + "//mediapipe/tasks/cc/components/processors/proto:classifier_options_py_pb2", "//mediapipe/tasks/python/core:optional_dependencies", ], ) - diff --git a/mediapipe/tasks/python/components/proto/classifier_options.py b/mediapipe/tasks/python/components/processors/proto/classifier_options.py similarity index 97% rename from mediapipe/tasks/python/components/proto/classifier_options.py rename to mediapipe/tasks/python/components/processors/proto/classifier_options.py index c73828c13..b4597e57a 100644 --- a/mediapipe/tasks/python/components/proto/classifier_options.py +++ b/mediapipe/tasks/python/components/processors/proto/classifier_options.py @@ -16,7 +16,7 @@ import dataclasses from typing import Any, List, Optional -from mediapipe.tasks.cc.components.proto import classifier_options_pb2 +from mediapipe.tasks.cc.components.processors.proto import classifier_options_pb2 from mediapipe.tasks.python.core.optional_dependencies import doc_controls _ClassifierOptionsProto = classifier_options_pb2.ClassifierOptions diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index df2e72f98..107a78a33 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -46,11 +46,11 @@ py_test( ], deps = [ "//mediapipe/python:_framework_bindings", - "//mediapipe/tasks/python/components/proto:classifier_options", - "//mediapipe/tasks/python/components/containers:category", - "//mediapipe/tasks/python/components/containers:classifications", + "//mediapipe/tasks/python/components/processors/proto:classifier_options", + "//mediapipe/tasks/python/components/containers/proto:category", + "//mediapipe/tasks/python/components/containers/proto:classifications", "//mediapipe/tasks/python/core:base_options", - "//mediapipe/tasks/python/test:test_util", + "//mediapipe/tasks/python/test:test_utils", "//mediapipe/tasks/python/vision:image_classifier", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", ], diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 3d7d116df..c16587cb5 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -19,11 +19,11 @@ from absl.testing import absltest from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module -from mediapipe.tasks.python.components.proto import classifier_options -from mediapipe.tasks.python.components.containers import category as category_module -from mediapipe.tasks.python.components.containers import classifications as classifications_module +from mediapipe.tasks.python.components.processors.proto import classifier_options +from mediapipe.tasks.python.components.containers.proto import category as category_module +from mediapipe.tasks.python.components.containers.proto import classifications as classifications_module from mediapipe.tasks.python.core import base_options as base_options_module -from mediapipe.tasks.python.test import test_util +from mediapipe.tasks.python.test import test_utils from mediapipe.tasks.python.vision import image_classifier from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module @@ -88,9 +88,9 @@ class ImageClassifierTest(parameterized.TestCase): def setUp(self): super().setUp() - self.test_image = test_util.read_test_image( - test_util.get_test_data_path(_IMAGE_FILE)) - self.model_path = test_util.get_test_data_path(_MODEL_FILE) + self.test_image = _Image.create_from_file( + test_utils.get_test_data_path(_IMAGE_FILE)) + self.model_path = test_utils.get_test_data_path(_MODEL_FILE) @parameterized.parameters( (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index a724f149a..69fd8f2a6 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -46,9 +46,9 @@ py_library( "//mediapipe/python:_framework_bindings", "//mediapipe/python:packet_creator", "//mediapipe/python:packet_getter", - "//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_options_py_pb2", - "//mediapipe/tasks/python/components/proto:classifier_options", - "//mediapipe/tasks/python/components/containers:classifications", + "//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_graph_options_py_pb2", + "//mediapipe/tasks/python/components/processors/proto:classifier_options", + "//mediapipe/tasks/python/components/containers/proto:classifications", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/core:optional_dependencies", "//mediapipe/tasks/python/core:task_info", diff --git a/mediapipe/tasks/python/vision/image_classifier.py b/mediapipe/tasks/python/vision/image_classifier.py index c240ffedf..809429c37 100644 --- a/mediapipe/tasks/python/vision/image_classifier.py +++ b/mediapipe/tasks/python/vision/image_classifier.py @@ -21,9 +21,9 @@ from mediapipe.python import packet_getter from mediapipe.python._framework_bindings import image as image_module from mediapipe.python._framework_bindings import packet as packet_module from mediapipe.python._framework_bindings import task_runner as task_runner_module -from mediapipe.tasks.cc.vision.image_classifier.proto import image_classifier_options_pb2 -from mediapipe.tasks.python.components.proto import classifier_options -from mediapipe.tasks.python.components.containers import classifications as classifications_module +from mediapipe.tasks.cc.vision.image_classifier.proto import image_classifier_graph_options_pb2 +from mediapipe.tasks.python.components.processors.proto import classifier_options +from mediapipe.tasks.python.components.containers.proto import classifications as classifications_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.core import task_info as task_info_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls @@ -31,7 +31,7 @@ from mediapipe.tasks.python.vision.core import base_vision_task_api from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module _BaseOptions = base_options_module.BaseOptions -_ImageClassifierOptionsProto = image_classifier_options_pb2.ImageClassifierOptions +_ImageClassifierGraphOptionsProto = image_classifier_graph_options_pb2.ImageClassifierGraphOptions _ClassifierOptions = classifier_options.ClassifierOptions _RunningMode = running_mode_module.VisionTaskRunningMode _TaskInfo = task_info_module.TaskInfo @@ -41,7 +41,7 @@ _CLASSIFICATION_RESULT_OUT_STREAM_NAME = 'classification_result_out' _CLASSIFICATION_RESULT_TAG = 'CLASSIFICATION_RESULT' _IMAGE_IN_STREAM_NAME = 'image_in' _IMAGE_TAG = 'IMAGE' -_TASK_GRAPH_NAME = 'mediapipe.tasks.vision.ImageClassifierGraph' +_TASK_GRAPH_NAME = 'mediapipe.tasks.vision.image_classifier.ImageClassifierGraph' @dataclasses.dataclass @@ -70,13 +70,13 @@ class ImageClassifierOptions: None]] = None @doc_controls.do_not_generate_docs - def to_pb2(self) -> _ImageClassifierOptionsProto: + def to_pb2(self) -> _ImageClassifierGraphOptionsProto: """Generates an ImageClassifierOptions protobuf object.""" base_options_proto = self.base_options.to_pb2() base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True classifier_options_proto = self.classifier_options.to_pb2() - return _ImageClassifierOptionsProto( + return _ImageClassifierGraphOptionsProto( base_options=base_options_proto, classifier_options=classifier_options_proto ) @@ -138,7 +138,9 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): task_info = _TaskInfo( task_graph=_TASK_GRAPH_NAME, - input_streams=[':'.join([_IMAGE_TAG, _IMAGE_IN_STREAM_NAME])], + input_streams=[ + ':'.join([_IMAGE_TAG, _IMAGE_IN_STREAM_NAME]), + ], output_streams=[ ':'.join([_CLASSIFICATION_RESULT_TAG, _CLASSIFICATION_RESULT_OUT_STREAM_NAME]) @@ -153,7 +155,7 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): # TODO: Create an Image class for MediaPipe Tasks. def classify( self, - image: image_module.Image + image: image_module.Image, ) -> classifications_module.ClassificationResult: """Performs image classification on the provided MediaPipe Image. From 64d5c159c6f509b656b8e28ed91375c24db3e35b Mon Sep 17 00:00:00 2001 From: kinaryml Date: Mon, 3 Oct 2022 16:14:35 -0700 Subject: [PATCH 020/125] Fixed an auto formatting issue that caused classification_posprocessing_graph's registration to fail --- .../processors/classification_postprocessing_graph.cc | 4 ++-- .../tasks/python/test/vision/image_classifier_test.py | 8 ++++---- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.cc b/mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.cc index 35adab687..649ff2c11 100644 --- a/mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.cc +++ b/mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.cc @@ -507,8 +507,8 @@ class ClassificationPostprocessingGraph : public mediapipe::Subgraph { } }; -REGISTER_MEDIAPIPE_GRAPH(::mediapipe::tasks::components::processors:: - ClassificationPostprocessingGraph); // NOLINT +REGISTER_MEDIAPIPE_GRAPH( + ::mediapipe::tasks::components::processors::ClassificationPostprocessingGraph); // NOLINT } // namespace processors } // namespace components diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index c16587cb5..0ce70395e 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -48,22 +48,22 @@ _EXPECTED_CLASSIFICATION_RESULT = _ClassificationResult( categories=[ _Category( index=934, - score=0.7952049970626831, + score=0.7939587831497192, display_name='', category_name='cheeseburger'), _Category( index=932, - score=0.02732999622821808, + score=0.02739289402961731, display_name='', category_name='bagel'), _Category( index=925, - score=0.01933487318456173, + score=0.01934075355529785, display_name='', category_name='guacamole'), _Category( index=963, - score=0.006279350258409977, + score=0.006327860057353973, display_name='', category_name='meat loaf') ], From a22a5283d272771323186af02ce061c74a32c501 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 5 Oct 2022 04:43:30 -0700 Subject: [PATCH 021/125] Adjusted namespaces --- .../tasks/python/components/containers/{proto => }/BUILD | 0 .../python/components/containers/{proto => }/__init__.py | 0 .../components/containers/{proto => }/bounding_box.py | 0 .../python/components/containers/{proto => }/category.py | 0 .../components/containers/{proto => }/classifications.py | 2 +- .../python/components/containers/{proto => }/detections.py | 0 .../tasks/python/components/processors/{proto => }/BUILD | 0 .../components/processors/{proto => }/classifier_options.py | 0 mediapipe/tasks/python/test/vision/BUILD | 6 +++--- mediapipe/tasks/python/test/vision/image_classifier_test.py | 6 +++--- mediapipe/tasks/python/vision/BUILD | 4 ++-- mediapipe/tasks/python/vision/image_classifier.py | 4 ++-- 12 files changed, 11 insertions(+), 11 deletions(-) rename mediapipe/tasks/python/components/containers/{proto => }/BUILD (100%) rename mediapipe/tasks/python/components/containers/{proto => }/__init__.py (100%) rename mediapipe/tasks/python/components/containers/{proto => }/bounding_box.py (100%) rename mediapipe/tasks/python/components/containers/{proto => }/category.py (100%) rename mediapipe/tasks/python/components/containers/{proto => }/classifications.py (98%) rename mediapipe/tasks/python/components/containers/{proto => }/detections.py (100%) rename mediapipe/tasks/python/components/processors/{proto => }/BUILD (100%) rename mediapipe/tasks/python/components/processors/{proto => }/classifier_options.py (100%) diff --git a/mediapipe/tasks/python/components/containers/proto/BUILD b/mediapipe/tasks/python/components/containers/BUILD similarity index 100% rename from mediapipe/tasks/python/components/containers/proto/BUILD rename to mediapipe/tasks/python/components/containers/BUILD diff --git a/mediapipe/tasks/python/components/containers/proto/__init__.py b/mediapipe/tasks/python/components/containers/__init__.py similarity index 100% rename from mediapipe/tasks/python/components/containers/proto/__init__.py rename to mediapipe/tasks/python/components/containers/__init__.py diff --git a/mediapipe/tasks/python/components/containers/proto/bounding_box.py b/mediapipe/tasks/python/components/containers/bounding_box.py similarity index 100% rename from mediapipe/tasks/python/components/containers/proto/bounding_box.py rename to mediapipe/tasks/python/components/containers/bounding_box.py diff --git a/mediapipe/tasks/python/components/containers/proto/category.py b/mediapipe/tasks/python/components/containers/category.py similarity index 100% rename from mediapipe/tasks/python/components/containers/proto/category.py rename to mediapipe/tasks/python/components/containers/category.py diff --git a/mediapipe/tasks/python/components/containers/proto/classifications.py b/mediapipe/tasks/python/components/containers/classifications.py similarity index 98% rename from mediapipe/tasks/python/components/containers/proto/classifications.py rename to mediapipe/tasks/python/components/containers/classifications.py index 2c43370b2..c51816e07 100644 --- a/mediapipe/tasks/python/components/containers/proto/classifications.py +++ b/mediapipe/tasks/python/components/containers/classifications.py @@ -17,7 +17,7 @@ import dataclasses from typing import Any, List, Optional from mediapipe.tasks.cc.components.containers.proto import classifications_pb2 -from mediapipe.tasks.python.components.containers.proto import category as category_module +from mediapipe.tasks.python.components.containers import category as category_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls _ClassificationEntryProto = classifications_pb2.ClassificationEntry diff --git a/mediapipe/tasks/python/components/containers/proto/detections.py b/mediapipe/tasks/python/components/containers/detections.py similarity index 100% rename from mediapipe/tasks/python/components/containers/proto/detections.py rename to mediapipe/tasks/python/components/containers/detections.py diff --git a/mediapipe/tasks/python/components/processors/proto/BUILD b/mediapipe/tasks/python/components/processors/BUILD similarity index 100% rename from mediapipe/tasks/python/components/processors/proto/BUILD rename to mediapipe/tasks/python/components/processors/BUILD diff --git a/mediapipe/tasks/python/components/processors/proto/classifier_options.py b/mediapipe/tasks/python/components/processors/classifier_options.py similarity index 100% rename from mediapipe/tasks/python/components/processors/proto/classifier_options.py rename to mediapipe/tasks/python/components/processors/classifier_options.py diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 107a78a33..09bbf1958 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -46,9 +46,9 @@ py_test( ], deps = [ "//mediapipe/python:_framework_bindings", - "//mediapipe/tasks/python/components/processors/proto:classifier_options", - "//mediapipe/tasks/python/components/containers/proto:category", - "//mediapipe/tasks/python/components/containers/proto:classifications", + "//mediapipe/tasks/python/components/processors:classifier_options", + "//mediapipe/tasks/python/components/containers:category", + "//mediapipe/tasks/python/components/containers:classifications", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/test:test_utils", "//mediapipe/tasks/python/vision:image_classifier", diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 0ce70395e..7fbd96ddc 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -19,9 +19,9 @@ from absl.testing import absltest from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module -from mediapipe.tasks.python.components.processors.proto import classifier_options -from mediapipe.tasks.python.components.containers.proto import category as category_module -from mediapipe.tasks.python.components.containers.proto import classifications as classifications_module +from mediapipe.tasks.python.components.processors import classifier_options +from mediapipe.tasks.python.components.containers import category as category_module +from mediapipe.tasks.python.components.containers import classifications as classifications_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_utils from mediapipe.tasks.python.vision import image_classifier diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 69fd8f2a6..7d44e3326 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -47,8 +47,8 @@ py_library( "//mediapipe/python:packet_creator", "//mediapipe/python:packet_getter", "//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_graph_options_py_pb2", - "//mediapipe/tasks/python/components/processors/proto:classifier_options", - "//mediapipe/tasks/python/components/containers/proto:classifications", + "//mediapipe/tasks/python/components/processors:classifier_options", + "//mediapipe/tasks/python/components/containers:classifications", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/core:optional_dependencies", "//mediapipe/tasks/python/core:task_info", diff --git a/mediapipe/tasks/python/vision/image_classifier.py b/mediapipe/tasks/python/vision/image_classifier.py index 809429c37..94dcd4d70 100644 --- a/mediapipe/tasks/python/vision/image_classifier.py +++ b/mediapipe/tasks/python/vision/image_classifier.py @@ -22,8 +22,8 @@ from mediapipe.python._framework_bindings import image as image_module from mediapipe.python._framework_bindings import packet as packet_module from mediapipe.python._framework_bindings import task_runner as task_runner_module from mediapipe.tasks.cc.vision.image_classifier.proto import image_classifier_graph_options_pb2 -from mediapipe.tasks.python.components.processors.proto import classifier_options -from mediapipe.tasks.python.components.containers.proto import classifications as classifications_module +from mediapipe.tasks.python.components.processors import classifier_options +from mediapipe.tasks.python.components.containers import classifications as classifications_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.core import task_info as task_info_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls From e250c903f5b6e8c87b9a4cef175137df95802804 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 5 Oct 2022 05:24:52 -0700 Subject: [PATCH 022/125] Added the ClassifyForVideo API --- .../test/vision/image_classifier_test.py | 13 +++++ .../tasks/python/vision/image_classifier.py | 52 ++++++++++++++++--- 2 files changed, 58 insertions(+), 7 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 7fbd96ddc..5143a28db 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -15,6 +15,7 @@ import enum +import numpy as np from absl.testing import absltest from absl.testing import parameterized @@ -121,6 +122,18 @@ class ImageClassifierTest(parameterized.TestCase): # a context. classifier.close() + def test_classify_for_video(self): + classifier_options = _ClassifierOptions(max_results=4) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO, + classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + for timestamp in range(0, 300, 30): + classification_result = classifier.classify_for_video( + self.test_image, timestamp) + self.assertEqual(classification_result, _EXPECTED_CLASSIFICATION_RESULT) + if __name__ == '__main__': absltest.main() diff --git a/mediapipe/tasks/python/vision/image_classifier.py b/mediapipe/tasks/python/vision/image_classifier.py index 94dcd4d70..b3bafa113 100644 --- a/mediapipe/tasks/python/vision/image_classifier.py +++ b/mediapipe/tasks/python/vision/image_classifier.py @@ -14,7 +14,7 @@ """MediaPipe image classifier task.""" import dataclasses -from typing import Callable, List, Mapping, Optional +from typing import Callable, Mapping, Optional from mediapipe.python import packet_creator from mediapipe.python import packet_getter @@ -40,6 +40,7 @@ _TaskRunner = task_runner_module.TaskRunner _CLASSIFICATION_RESULT_OUT_STREAM_NAME = 'classification_result_out' _CLASSIFICATION_RESULT_TAG = 'CLASSIFICATION_RESULT' _IMAGE_IN_STREAM_NAME = 'image_in' +_IMAGE_OUT_STREAM_NAME = 'image_out' _IMAGE_TAG = 'IMAGE' _TASK_GRAPH_NAME = 'mediapipe.tasks.vision.image_classifier.ImageClassifierGraph' @@ -66,8 +67,8 @@ class ImageClassifierOptions: running_mode: _RunningMode = _RunningMode.IMAGE classifier_options: _ClassifierOptions = _ClassifierOptions() result_callback: Optional[ - Callable[[classifications_module.ClassificationResult], - None]] = None + Callable[[classifications_module.ClassificationResult, image_module.Image, + int], None]] = None @doc_controls.do_not_generate_docs def to_pb2(self) -> _ImageClassifierGraphOptionsProto: @@ -134,7 +135,9 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): classifications_module.Classifications.create_from_pb2(classification) for classification in classification_result_proto.classifications ]) - options.result_callback(classification_result) + image = packet_getter.get_image(output_packets[_IMAGE_OUT_STREAM_NAME]) + timestamp = output_packets[_IMAGE_OUT_STREAM_NAME].timestamp + options.result_callback(classification_result, image, timestamp) task_info = _TaskInfo( task_graph=_TASK_GRAPH_NAME, @@ -143,7 +146,8 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): ], output_streams=[ ':'.join([_CLASSIFICATION_RESULT_TAG, - _CLASSIFICATION_RESULT_OUT_STREAM_NAME]) + _CLASSIFICATION_RESULT_OUT_STREAM_NAME]), + ':'.join([_IMAGE_TAG, _IMAGE_OUT_STREAM_NAME]) ], task_options=options) return cls( @@ -175,6 +179,40 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]) return classifications_module.ClassificationResult([ - classifications_module.Classifications.create_from_pb2(classification) - for classification in classification_result_proto.classifications + classifications_module.Classifications.create_from_pb2(classification) + for classification in classification_result_proto.classifications + ]) + + def classify_for_video( + self, image: image_module.Image, + timestamp_ms: int + ) -> classifications_module.ClassificationResult: + """Performs image classification on the provided video frames. + + Only use this method when the ImageClassifier is created with the video + running mode. It's required to provide the video frame's timestamp (in + milliseconds) along with the video frame. The input timestamps should be + monotonically increasing for adjacent calls of this method. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input video frame in milliseconds. + + Returns: + A classification result object that contains a list of classifications. + + Raises: + ValueError: If any of the input arguments is invalid. + RuntimeError: If image classification failed to run. + """ + output_packets = self._process_video_data({ + _IMAGE_IN_STREAM_NAME: + packet_creator.create_image(image).at(timestamp_ms) + }) + classification_result_proto = packet_getter.get_proto( + output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]) + + return classifications_module.ClassificationResult([ + classifications_module.Classifications.create_from_pb2(classification) + for classification in classification_result_proto.classifications ]) From cb806071ba30ba66cfa1ec26d80b9b5c0b3e2501 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Fri, 7 Oct 2022 22:26:49 -0700 Subject: [PATCH 023/125] Added more tests and updated the APIs to use a new constant --- .../test/vision/image_classifier_test.py | 338 ++++++++++++++++-- .../tasks/python/vision/image_classifier.py | 45 ++- 2 files changed, 355 insertions(+), 28 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 5143a28db..073674c3f 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -14,6 +14,7 @@ """Tests for image classifier.""" import enum +from unittest import mock import numpy as np from absl.testing import absltest @@ -41,33 +42,46 @@ _RUNNING_MODE = running_mode_module.VisionTaskRunningMode _MODEL_FILE = 'mobilenet_v2_1.0_224.tflite' _IMAGE_FILE = 'burger.jpg' +_EXPECTED_CATEGORIES = [ + _Category( + index=934, + score=0.7939587831497192, + display_name='', + category_name='cheeseburger'), + _Category( + index=932, + score=0.02739289402961731, + display_name='', + category_name='bagel'), + _Category( + index=925, + score=0.01934075355529785, + display_name='', + category_name='guacamole'), + _Category( + index=963, + score=0.006327860057353973, + display_name='', + category_name='meat loaf') +] _EXPECTED_CLASSIFICATION_RESULT = _ClassificationResult( classifications=[ _Classifications( entries=[ _ClassificationEntry( - categories=[ - _Category( - index=934, - score=0.7939587831497192, - display_name='', - category_name='cheeseburger'), - _Category( - index=932, - score=0.02739289402961731, - display_name='', - category_name='bagel'), - _Category( - index=925, - score=0.01934075355529785, - display_name='', - category_name='guacamole'), - _Category( - index=963, - score=0.006327860057353973, - display_name='', - category_name='meat loaf') - ], + categories=_EXPECTED_CATEGORIES, + timestamp_ms=0 + ) + ], + head_index=0, + head_name='probability') + ]) +_EMPTY_CLASSIFICATION_RESULT = _ClassificationResult( + classifications=[ + _Classifications( + entries=[ + _ClassificationEntry( + categories=[], timestamp_ms=0 ) ], @@ -93,6 +107,36 @@ class ImageClassifierTest(parameterized.TestCase): test_utils.get_test_data_path(_IMAGE_FILE)) self.model_path = test_utils.get_test_data_path(_MODEL_FILE) + def test_create_from_file_succeeds_with_valid_model_path(self): + # Creates with default option and valid model file successfully. + with _ImageClassifier.create_from_model_path(self.model_path) as classifier: + self.assertIsInstance(classifier, _ImageClassifier) + + def test_create_from_options_succeeds_with_valid_model_path(self): + # Creates with options containing model file successfully. + base_options = _BaseOptions(model_asset_path=self.model_path) + options = _ImageClassifierOptions(base_options=base_options) + with _ImageClassifier.create_from_options(options) as classifier: + self.assertIsInstance(classifier, _ImageClassifier) + + def test_create_from_options_fails_with_invalid_model_path(self): + # Invalid empty model path. + with self.assertRaisesRegex( + ValueError, + r"ExternalFile must specify at least one of 'file_content', " + r"'file_name' or 'file_descriptor_meta'."): + base_options = _BaseOptions(model_asset_path='') + options = _ImageClassifierOptions(base_options=base_options) + _ImageClassifier.create_from_options(options) + + def test_create_from_options_succeeds_with_valid_model_content(self): + # Creates with options containing model content successfully. + with open(self.model_path, 'rb') as f: + base_options = _BaseOptions(model_asset_buffer=f.read()) + options = _ImageClassifierOptions(base_options=base_options) + classifier = _ImageClassifier.create_from_options(options) + self.assertIsInstance(classifier, _ImageClassifier) + @parameterized.parameters( (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) @@ -122,6 +166,183 @@ class ImageClassifierTest(parameterized.TestCase): # a context. classifier.close() + @parameterized.parameters( + (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), + (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) + def test_classify_in_context(self, model_file_type, max_results, + expected_classification_result): + if model_file_type is ModelFileType.FILE_NAME: + base_options = _BaseOptions(model_asset_path=self.model_path) + elif model_file_type is ModelFileType.FILE_CONTENT: + with open(self.model_path, 'rb') as f: + model_content = f.read() + base_options = _BaseOptions(model_asset_buffer=model_content) + else: + # Should never happen + raise ValueError('model_file_type is invalid.') + + classifier_options = _ClassifierOptions(max_results=max_results) + options = _ImageClassifierOptions( + base_options=base_options, classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + # Comparing results. + self.assertEqual(image_result, expected_classification_result) + + def test_score_threshold_option(self): + classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + classifications = image_result.classifications + + for classification in classifications: + for entry in classification.entries: + score = entry.categories[0].score + self.assertGreaterEqual( + score, _SCORE_THRESHOLD, + f'Classification with score lower than threshold found. ' + f'{classification}') + + def test_max_results_option(self): + classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + categories = image_result.classifications[0].entries[0].categories + + self.assertLessEqual( + len(categories), _MAX_RESULTS, 'Too many results returned.') + + def test_allow_list_option(self): + classifier_options = _ClassifierOptions(category_allowlist=_ALLOW_LIST) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + classifications = image_result.classifications + + for classification in classifications: + for entry in classification.entries: + label = entry.categories[0].category_name + self.assertIn(label, _ALLOW_LIST, + f'Label {label} found but not in label allow list') + + def test_deny_list_option(self): + classifier_options = _ClassifierOptions(category_denylist=_DENY_LIST) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + classifications = image_result.classifications + + for classification in classifications: + for entry in classification.entries: + label = entry.categories[0].category_name + self.assertNotIn(label, _DENY_LIST, + f'Label {label} found but in deny list.') + + def test_combined_allowlist_and_denylist(self): + # Fails with combined allowlist and denylist + with self.assertRaisesRegex( + ValueError, + r'`category_allowlist` and `category_denylist` are mutually ' + r'exclusive options.'): + classifier_options = _ClassifierOptions(category_allowlist=['foo'], + category_denylist=['bar']) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as unused_classifier: + pass + + def test_empty_classification_outputs(self): + classifier_options = _ClassifierOptions(score_threshold=1) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + # Performs image classification on the input. + image_result = classifier.classify(self.test_image) + self.assertEmpty(image_result.classifications[0].entries[0].categories) + + def test_missing_result_callback(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM) + with self.assertRaisesRegex(ValueError, + r'result callback must be provided'): + with _ImageClassifier.create_from_options(options) as unused_classifier: + pass + + @parameterized.parameters((_RUNNING_MODE.IMAGE), (_RUNNING_MODE.VIDEO)) + def test_illegal_result_callback(self, running_mode): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=running_mode, + result_callback=mock.MagicMock()) + with self.assertRaisesRegex(ValueError, + r'result callback should not be provided'): + with _ImageClassifier.create_from_options(options) as unused_classifier: + pass + + def test_calling_classify_for_video_in_image_mode(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.IMAGE) + with _ImageClassifier.create_from_options(options) as classifier: + with self.assertRaisesRegex(ValueError, + r'not initialized with the video mode'): + classifier.classify_for_video(self.test_image, 0) + + def test_calling_classify_async_in_image_mode(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.IMAGE) + with _ImageClassifier.create_from_options(options) as classifier: + with self.assertRaisesRegex(ValueError, + r'not initialized with the live stream mode'): + classifier.classify_async(self.test_image, 0) + + def test_calling_classify_in_video_mode(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _ImageClassifier.create_from_options(options) as classifier: + with self.assertRaisesRegex(ValueError, + r'not initialized with the image mode'): + classifier.classify(self.test_image) + + def test_calling_classify_async_in_video_mode(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _ImageClassifier.create_from_options(options) as classifier: + with self.assertRaisesRegex(ValueError, + r'not initialized with the live stream mode'): + classifier.classify_async(self.test_image, 0) + + def test_classify_for_video_with_out_of_order_timestamp(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _ImageClassifier.create_from_options(options) as classifier: + unused_result = classifier.classify_for_video(self.test_image, 1) + with self.assertRaisesRegex( + ValueError, r'Input timestamp must be monotonically increasing'): + classifier.classify_for_video(self.test_image, 0) + def test_classify_for_video(self): classifier_options = _ClassifierOptions(max_results=4) options = _ImageClassifierOptions( @@ -132,7 +353,78 @@ class ImageClassifierTest(parameterized.TestCase): for timestamp in range(0, 300, 30): classification_result = classifier.classify_for_video( self.test_image, timestamp) - self.assertEqual(classification_result, _EXPECTED_CLASSIFICATION_RESULT) + expected_classification_result = _ClassificationResult( + classifications=[ + _Classifications( + entries=[ + _ClassificationEntry( + categories=_EXPECTED_CATEGORIES, timestamp_ms=timestamp) + ], + head_index=0, head_name='probability') + ]) + self.assertEqual(classification_result, expected_classification_result) + + def test_calling_classify_in_live_stream_mode(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=mock.MagicMock()) + with _ImageClassifier.create_from_options(options) as classifier: + with self.assertRaisesRegex(ValueError, + r'not initialized with the image mode'): + classifier.classify(self.test_image) + + def test_calling_classify_for_video_in_live_stream_mode(self): + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=mock.MagicMock()) + with _ImageClassifier.create_from_options(options) as classifier: + with self.assertRaisesRegex(ValueError, + r'not initialized with the video mode'): + classifier.classify_for_video(self.test_image, 0) + + def test_classify_async_calls_with_illegal_timestamp(self): + classifier_options = _ClassifierOptions(max_results=4) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + classifier_options=classifier_options, + result_callback=mock.MagicMock()) + with _ImageClassifier.create_from_options(options) as classifier: + classifier.classify_async(self.test_image, 100) + with self.assertRaisesRegex( + ValueError, r'Input timestamp must be monotonically increasing'): + classifier.classify_async(self.test_image, 0) + + # TODO: Fix the packet is empty issue. + """ + @parameterized.parameters((0, _EXPECTED_CLASSIFICATION_RESULT), + (1, _EMPTY_CLASSIFICATION_RESULT)) + def test_classify_async_calls(self, threshold, expected_result): + observed_timestamp_ms = -1 + + def check_result(result: _ClassificationResult, output_image: _Image, + timestamp_ms: int): + self.assertEqual(result, expected_result) + self.assertTrue( + np.array_equal(output_image.numpy_view(), + self.test_image.numpy_view())) + self.assertLess(observed_timestamp_ms, timestamp_ms) + self.observed_timestamp_ms = timestamp_ms + + classifier_options = _ClassifierOptions( + max_results=4, score_threshold=threshold) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + classifier_options=classifier_options, + result_callback=check_result) + classifier = _ImageClassifier.create_from_options(options) + for timestamp in range(0, 300, 30): + classifier.classify_async(self.test_image, timestamp) + classifier.close() + """ if __name__ == '__main__': diff --git a/mediapipe/tasks/python/vision/image_classifier.py b/mediapipe/tasks/python/vision/image_classifier.py index b3bafa113..36c5561c4 100644 --- a/mediapipe/tasks/python/vision/image_classifier.py +++ b/mediapipe/tasks/python/vision/image_classifier.py @@ -43,6 +43,7 @@ _IMAGE_IN_STREAM_NAME = 'image_in' _IMAGE_OUT_STREAM_NAME = 'image_out' _IMAGE_TAG = 'IMAGE' _TASK_GRAPH_NAME = 'mediapipe.tasks.vision.image_classifier.ImageClassifierGraph' +_MICRO_SECONDS_PER_MILLISECOND = 1000 @dataclasses.dataclass @@ -91,7 +92,7 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): """Creates an `ImageClassifier` object from a TensorFlow Lite model and the default `ImageClassifierOptions`. Note that the created `ImageClassifier` instance is in image mode, for - detecting objects on single image inputs. + classifying objects on single image inputs. Args: model_path: Path to the model. @@ -137,7 +138,8 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): ]) image = packet_getter.get_image(output_packets[_IMAGE_OUT_STREAM_NAME]) timestamp = output_packets[_IMAGE_OUT_STREAM_NAME].timestamp - options.result_callback(classification_result, image, timestamp) + options.result_callback(classification_result, image, + timestamp.value / _MICRO_SECONDS_PER_MILLISECOND) task_info = _TaskInfo( task_graph=_TASK_GRAPH_NAME, @@ -156,7 +158,6 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): _RunningMode.LIVE_STREAM), options.running_mode, packets_callback if options.result_callback else None) - # TODO: Create an Image class for MediaPipe Tasks. def classify( self, image: image_module.Image, @@ -206,8 +207,9 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): RuntimeError: If image classification failed to run. """ output_packets = self._process_video_data({ - _IMAGE_IN_STREAM_NAME: - packet_creator.create_image(image).at(timestamp_ms) + _IMAGE_IN_STREAM_NAME: + packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) }) classification_result_proto = packet_getter.get_proto( output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]) @@ -216,3 +218,36 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): classifications_module.Classifications.create_from_pb2(classification) for classification in classification_result_proto.classifications ]) + + def classify_async(self, image: image_module.Image, timestamp_ms: int) -> None: + """Sends live image data (an Image with a unique timestamp) to perform + image classification. + + Only use this method when the ImageClassifier is created with the live + stream running mode. The input timestamps should be monotonically increasing + for adjacent calls of this method. This method will return immediately after + the input image is accepted. The results will be available via the + `result_callback` provided in the `ImageClassifierOptions`. The + `classify_async` method is designed to process live stream data such as + camera input. To lower the overall latency, image classifier may drop the + input images if needed. In other words, it's not guaranteed to have output + per input image. + + The `result_callback` provides: + - A classification result object that contains a list of classifications. + - The input image that the image classifier runs on. + - The input timestamp in milliseconds. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input image in milliseconds. + + Raises: + ValueError: If the current input timestamp is smaller than what the image + classifier has already processed. + """ + self._send_live_stream_data({ + _IMAGE_IN_STREAM_NAME: + packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) + }) From 44e6f8e1a1edea42bc92c1e9c83d59ddce678fb8 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Mon, 10 Oct 2022 08:15:40 -0700 Subject: [PATCH 024/125] Updated image classifier to use a region of interest parameter --- .../tasks/python/components/containers/BUILD | 9 ++ .../python/components/containers/rect.py | 136 ++++++++++++++++ mediapipe/tasks/python/test/vision/BUILD | 1 + .../test/vision/image_classifier_test.py | 146 ++++++++++++------ mediapipe/tasks/python/vision/BUILD | 1 + .../tasks/python/vision/image_classifier.py | 46 ++++-- 6 files changed, 281 insertions(+), 58 deletions(-) create mode 100644 mediapipe/tasks/python/components/containers/rect.py diff --git a/mediapipe/tasks/python/components/containers/BUILD b/mediapipe/tasks/python/components/containers/BUILD index d46df22da..723210f5f 100644 --- a/mediapipe/tasks/python/components/containers/BUILD +++ b/mediapipe/tasks/python/components/containers/BUILD @@ -27,6 +27,15 @@ py_library( ], ) +py_library( + name = "rect", + srcs = ["rect.py"], + deps = [ + "//mediapipe/framework/formats:rect_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) + py_library( name = "category", srcs = ["category.py"], diff --git a/mediapipe/tasks/python/components/containers/rect.py b/mediapipe/tasks/python/components/containers/rect.py new file mode 100644 index 000000000..e74be1b0e --- /dev/null +++ b/mediapipe/tasks/python/components/containers/rect.py @@ -0,0 +1,136 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Rect data class.""" + +import dataclasses +from typing import Any, Optional + +from mediapipe.framework.formats import rect_pb2 +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_RectProto = rect_pb2.Rect +_NormalizedRectProto = rect_pb2.NormalizedRect + + +@dataclasses.dataclass +class Rect: + """A rectangle with rotation in image coordinates. + + Attributes: + x_center : The X coordinate of the top-left corner, in pixels. + y_center : The Y coordinate of the top-left corner, in pixels. + width: The width of the rectangle, in pixels. + height: The height of the rectangle, in pixels. + rotation: Rotation angle is clockwise in radians. + rect_id: Optional unique id to help associate different rectangles to each + other. + """ + + x_center: int + y_center: int + width: int + height: int + rotation: Optional[float] = 0.0 + rect_id: Optional[int] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _RectProto: + """Generates a Rect protobuf object.""" + return _RectProto( + x_center=self.x_center, + y_center=self.y_center, + width=self.width, + height=self.height, + ) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _RectProto) -> 'Rect': + """Creates a `Rect` object from the given protobuf object.""" + return Rect( + x_center=pb2_obj.x_center, + y_center=pb2_obj.y_center, + width=pb2_obj.width, + height=pb2_obj.height) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, Rect): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class NormalizedRect: + """A rectangle with rotation in normalized coordinates. The values of box + center location and size are within [0, 1]. + + Attributes: + x_center : The X normalized coordinate of the top-left corner. + y_center : The Y normalized coordinate of the top-left corner. + width: The width of the rectangle. + height: The height of the rectangle. + rotation: Rotation angle is clockwise in radians. + rect_id: Optional unique id to help associate different rectangles to each + other. + """ + + x_center: float + y_center: float + width: float + height: float + rotation: Optional[float] = 0.0 + rect_id: Optional[int] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _NormalizedRectProto: + """Generates a NormalizedRect protobuf object.""" + return _NormalizedRectProto( + x_center=self.x_center, + y_center=self.y_center, + width=self.width, + height=self.height, + ) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _NormalizedRectProto) -> 'NormalizedRect': + """Creates a `NormalizedRect` object from the given protobuf object.""" + return NormalizedRect( + x_center=pb2_obj.x_center, + y_center=pb2_obj.y_center, + width=pb2_obj.width, + height=pb2_obj.height) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, NormalizedRect): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 09bbf1958..e4d331784 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -49,6 +49,7 @@ py_test( "//mediapipe/tasks/python/components/processors:classifier_options", "//mediapipe/tasks/python/components/containers:category", "//mediapipe/tasks/python/components/containers:classifications", + "//mediapipe/tasks/python/components/containers:rect", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/test:test_utils", "//mediapipe/tasks/python/vision:image_classifier", diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 073674c3f..b9098b55b 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -24,11 +24,13 @@ from mediapipe.python._framework_bindings import image as image_module from mediapipe.tasks.python.components.processors import classifier_options from mediapipe.tasks.python.components.containers import category as category_module from mediapipe.tasks.python.components.containers import classifications as classifications_module +from mediapipe.tasks.python.components.containers import rect as rect_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_utils from mediapipe.tasks.python.vision import image_classifier from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module +_NormalizedRect = rect_module.NormalizedRect _BaseOptions = base_options_module.BaseOptions _ClassifierOptions = classifier_options.ClassifierOptions _Category = category_module.Category @@ -42,40 +44,6 @@ _RUNNING_MODE = running_mode_module.VisionTaskRunningMode _MODEL_FILE = 'mobilenet_v2_1.0_224.tflite' _IMAGE_FILE = 'burger.jpg' -_EXPECTED_CATEGORIES = [ - _Category( - index=934, - score=0.7939587831497192, - display_name='', - category_name='cheeseburger'), - _Category( - index=932, - score=0.02739289402961731, - display_name='', - category_name='bagel'), - _Category( - index=925, - score=0.01934075355529785, - display_name='', - category_name='guacamole'), - _Category( - index=963, - score=0.006327860057353973, - display_name='', - category_name='meat loaf') -] -_EXPECTED_CLASSIFICATION_RESULT = _ClassificationResult( - classifications=[ - _Classifications( - entries=[ - _ClassificationEntry( - categories=_EXPECTED_CATEGORIES, - timestamp_ms=0 - ) - ], - head_index=0, - head_name='probability') - ]) _EMPTY_CLASSIFICATION_RESULT = _ClassificationResult( classifications=[ _Classifications( @@ -94,6 +62,60 @@ _SCORE_THRESHOLD = 0.5 _MAX_RESULTS = 3 +def _generate_burger_results(timestamp_ms: int) -> _ClassificationResult: + return _ClassificationResult( + classifications=[ + _Classifications( + entries=[ + _ClassificationEntry( + categories=[ + _Category( + index=934, + score=0.7939587831497192, + display_name='', + category_name='cheeseburger'), + _Category( + index=932, + score=0.02739289402961731, + display_name='', + category_name='bagel'), + _Category( + index=925, + score=0.01934075355529785, + display_name='', + category_name='guacamole'), + _Category( + index=963, + score=0.006327860057353973, + display_name='', + category_name='meat loaf') + ], + timestamp_ms=timestamp_ms + ) + ], + head_index=0, + head_name='probability') + ]) + + +def _generate_soccer_ball_results(timestamp_ms: int) -> _ClassificationResult: + return _ClassificationResult( + classifications=[ + _Classifications( + entries=[ + _ClassificationEntry( + categories=[ + _Category(index=806, score=0.9965274930000305, display_name='', + category_name='soccer ball') + ], + timestamp_ms=timestamp_ms + ) + ], + head_index=0, + head_name='probability') + ]) + + class ModelFileType(enum.Enum): FILE_CONTENT = 1 FILE_NAME = 2 @@ -138,8 +160,8 @@ class ImageClassifierTest(parameterized.TestCase): self.assertIsInstance(classifier, _ImageClassifier) @parameterized.parameters( - (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), - (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) + (ModelFileType.FILE_NAME, 4, _generate_burger_results(0)), + (ModelFileType.FILE_CONTENT, 4, _generate_burger_results(0))) def test_classify(self, model_file_type, max_results, expected_classification_result): # Creates classifier. @@ -167,8 +189,8 @@ class ImageClassifierTest(parameterized.TestCase): classifier.close() @parameterized.parameters( - (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), - (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) + (ModelFileType.FILE_NAME, 4, _generate_burger_results(0)), + (ModelFileType.FILE_CONTENT, 4, _generate_burger_results(0))) def test_classify_in_context(self, model_file_type, max_results, expected_classification_result): if model_file_type is ModelFileType.FILE_NAME: @@ -190,6 +212,23 @@ class ImageClassifierTest(parameterized.TestCase): # Comparing results. self.assertEqual(image_result, expected_classification_result) + def test_classify_succeeds_with_region_of_interest(self): + base_options = _BaseOptions(model_asset_path=self.model_path) + classifier_options = _ClassifierOptions(max_results=1) + options = _ImageClassifierOptions( + base_options=base_options, classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + # Load the test image. + test_image = _Image.create_from_file( + test_utils.get_test_data_path('multi_objects.jpg')) + # NormalizedRect around the soccer ball. + roi = _NormalizedRect(x_center=0.532, y_center=0.521, width=0.164, + height=0.427) + # Performs image classification on the input. + image_result = classifier.classify(test_image, roi) + # Comparing results. + self.assertEqual(image_result, _generate_soccer_ball_results(0)) + def test_score_threshold_option(self): classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) options = _ImageClassifierOptions( @@ -353,16 +392,27 @@ class ImageClassifierTest(parameterized.TestCase): for timestamp in range(0, 300, 30): classification_result = classifier.classify_for_video( self.test_image, timestamp) - expected_classification_result = _ClassificationResult( - classifications=[ - _Classifications( - entries=[ - _ClassificationEntry( - categories=_EXPECTED_CATEGORIES, timestamp_ms=timestamp) - ], - head_index=0, head_name='probability') - ]) - self.assertEqual(classification_result, expected_classification_result) + self.assertEqual(classification_result, + _generate_burger_results(timestamp)) + + def test_classify_for_video_succeeds_with_region_of_interest(self): + classifier_options = _ClassifierOptions(max_results=1) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO, + classifier_options=classifier_options) + with _ImageClassifier.create_from_options(options) as classifier: + # Load the test image. + test_image = _Image.create_from_file( + test_utils.get_test_data_path('multi_objects.jpg')) + # NormalizedRect around the soccer ball. + roi = _NormalizedRect(x_center=0.532, y_center=0.521, width=0.164, + height=0.427) + for timestamp in range(0, 300, 30): + classification_result = classifier.classify_for_video( + test_image, timestamp, roi) + self.assertEqual(classification_result, + _generate_soccer_ball_results(timestamp)) def test_calling_classify_in_live_stream_mode(self): options = _ImageClassifierOptions( diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 7d44e3326..273804f0a 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -49,6 +49,7 @@ py_library( "//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_graph_options_py_pb2", "//mediapipe/tasks/python/components/processors:classifier_options", "//mediapipe/tasks/python/components/containers:classifications", + "//mediapipe/tasks/python/components/containers:rect", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/core:optional_dependencies", "//mediapipe/tasks/python/core:task_info", diff --git a/mediapipe/tasks/python/vision/image_classifier.py b/mediapipe/tasks/python/vision/image_classifier.py index 36c5561c4..348e848ab 100644 --- a/mediapipe/tasks/python/vision/image_classifier.py +++ b/mediapipe/tasks/python/vision/image_classifier.py @@ -24,12 +24,14 @@ from mediapipe.python._framework_bindings import task_runner as task_runner_modu from mediapipe.tasks.cc.vision.image_classifier.proto import image_classifier_graph_options_pb2 from mediapipe.tasks.python.components.processors import classifier_options from mediapipe.tasks.python.components.containers import classifications as classifications_module +from mediapipe.tasks.python.components.containers import rect as rect_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.core import task_info as task_info_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls from mediapipe.tasks.python.vision.core import base_vision_task_api from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module +_NormalizedRect = rect_module.NormalizedRect _BaseOptions = base_options_module.BaseOptions _ImageClassifierGraphOptionsProto = image_classifier_graph_options_pb2.ImageClassifierGraphOptions _ClassifierOptions = classifier_options.ClassifierOptions @@ -42,10 +44,17 @@ _CLASSIFICATION_RESULT_TAG = 'CLASSIFICATION_RESULT' _IMAGE_IN_STREAM_NAME = 'image_in' _IMAGE_OUT_STREAM_NAME = 'image_out' _IMAGE_TAG = 'IMAGE' +_NORM_RECT_NAME = 'norm_rect_in' +_NORM_RECT_TAG = 'NORM_RECT' _TASK_GRAPH_NAME = 'mediapipe.tasks.vision.image_classifier.ImageClassifierGraph' _MICRO_SECONDS_PER_MILLISECOND = 1000 +def _build_full_image_norm_rect() -> _NormalizedRect: + # Builds a NormalizedRect covering the entire image. + return _NormalizedRect(x_center=0.5, y_center=0.5, width=1, height=1) + + @dataclasses.dataclass class ImageClassifierOptions: """Options for the image classifier task. @@ -145,6 +154,7 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): task_graph=_TASK_GRAPH_NAME, input_streams=[ ':'.join([_IMAGE_TAG, _IMAGE_IN_STREAM_NAME]), + ':'.join([_NORM_RECT_TAG, _NORM_RECT_NAME]), ], output_streams=[ ':'.join([_CLASSIFICATION_RESULT_TAG, @@ -161,11 +171,13 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): def classify( self, image: image_module.Image, + roi: Optional[_NormalizedRect] = None ) -> classifications_module.ClassificationResult: """Performs image classification on the provided MediaPipe Image. Args: image: MediaPipe Image. + roi: The region of interest. Returns: A classification result object that contains a list of classifications. @@ -174,8 +186,10 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): ValueError: If any of the input arguments is invalid. RuntimeError: If image classification failed to run. """ - output_packets = self._process_image_data( - {_IMAGE_IN_STREAM_NAME: packet_creator.create_image(image)}) + norm_rect = roi if roi is not None else _build_full_image_norm_rect() + output_packets = self._process_image_data({ + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image), + _NORM_RECT_NAME: packet_creator.create_proto(norm_rect.to_pb2())}) classification_result_proto = packet_getter.get_proto( output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]) @@ -186,7 +200,8 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): def classify_for_video( self, image: image_module.Image, - timestamp_ms: int + timestamp_ms: int, + roi: Optional[_NormalizedRect] = None ) -> classifications_module.ClassificationResult: """Performs image classification on the provided video frames. @@ -198,6 +213,7 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): Args: image: MediaPipe Image. timestamp_ms: The timestamp of the input video frame in milliseconds. + roi: The region of interest. Returns: A classification result object that contains a list of classifications. @@ -206,10 +222,12 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): ValueError: If any of the input arguments is invalid. RuntimeError: If image classification failed to run. """ + norm_rect = roi if roi is not None else _build_full_image_norm_rect() output_packets = self._process_video_data({ - _IMAGE_IN_STREAM_NAME: - packet_creator.create_image(image).at( - timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND), + _NORM_RECT_NAME: packet_creator.create_proto(norm_rect.to_pb2()).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) }) classification_result_proto = packet_getter.get_proto( output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]) @@ -219,7 +237,12 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): for classification in classification_result_proto.classifications ]) - def classify_async(self, image: image_module.Image, timestamp_ms: int) -> None: + def classify_async( + self, + image: image_module.Image, + timestamp_ms: int, + roi: Optional[_NormalizedRect] = None + ) -> None: """Sends live image data (an Image with a unique timestamp) to perform image classification. @@ -241,13 +264,16 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): Args: image: MediaPipe Image. timestamp_ms: The timestamp of the input image in milliseconds. + roi: The region of interest. Raises: ValueError: If the current input timestamp is smaller than what the image classifier has already processed. """ + norm_rect = roi if roi is not None else _build_full_image_norm_rect() self._send_live_stream_data({ - _IMAGE_IN_STREAM_NAME: - packet_creator.create_image(image).at( - timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND), + _NORM_RECT_NAME: packet_creator.create_proto(norm_rect.to_pb2()).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) }) From c2672d040f9b79a77610efd6cd9f591f2b047f77 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Mon, 10 Oct 2022 08:19:12 -0700 Subject: [PATCH 025/125] Updated error message for the invalid model path test case --- mediapipe/tasks/python/test/vision/image_classifier_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index b9098b55b..336f1f306 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -146,7 +146,7 @@ class ImageClassifierTest(parameterized.TestCase): with self.assertRaisesRegex( ValueError, r"ExternalFile must specify at least one of 'file_content', " - r"'file_name' or 'file_descriptor_meta'."): + r"'file_name', 'file_pointer_meta' or 'file_descriptor_meta'."): base_options = _BaseOptions(model_asset_path='') options = _ImageClassifierOptions(base_options=base_options) _ImageClassifier.create_from_options(options) From 0a8dbc7576fd5381eefe98bf7e645f9f7b01ad04 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Mon, 10 Oct 2022 13:58:37 -0700 Subject: [PATCH 026/125] Added remaining parameters to initialize the Rect data class --- mediapipe/tasks/python/components/containers/rect.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/mediapipe/tasks/python/components/containers/rect.py b/mediapipe/tasks/python/components/containers/rect.py index e74be1b0e..aadb404db 100644 --- a/mediapipe/tasks/python/components/containers/rect.py +++ b/mediapipe/tasks/python/components/containers/rect.py @@ -109,6 +109,8 @@ class NormalizedRect: y_center=self.y_center, width=self.width, height=self.height, + rotation=self.rotation, + rect_id=self.rect_id ) @classmethod @@ -119,7 +121,10 @@ class NormalizedRect: x_center=pb2_obj.x_center, y_center=pb2_obj.y_center, width=pb2_obj.width, - height=pb2_obj.height) + height=pb2_obj.height, + rotation=pb2_obj.rotation, + rect_id=pb2_obj.rect_id + ) def __eq__(self, other: Any) -> bool: """Checks if this object is equal to the given object. From 8ea0018397fc98289e60d3498c90b98b82bb3e18 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 11 Oct 2022 22:34:56 -0700 Subject: [PATCH 027/125] Added a check to see if the output packet is empty in the API and updated tests --- .../test/vision/image_classifier_test.py | 38 +++++++++---------- .../tasks/python/vision/image_classifier.py | 4 +- 2 files changed, 22 insertions(+), 20 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 336f1f306..5bb479d7a 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -44,24 +44,27 @@ _RUNNING_MODE = running_mode_module.VisionTaskRunningMode _MODEL_FILE = 'mobilenet_v2_1.0_224.tflite' _IMAGE_FILE = 'burger.jpg' -_EMPTY_CLASSIFICATION_RESULT = _ClassificationResult( - classifications=[ - _Classifications( - entries=[ - _ClassificationEntry( - categories=[], - timestamp_ms=0 - ) - ], - head_index=0, - head_name='probability') - ]) _ALLOW_LIST = ['cheeseburger', 'guacamole'] _DENY_LIST = ['cheeseburger'] _SCORE_THRESHOLD = 0.5 _MAX_RESULTS = 3 +def _generate_empty_results(timestamp_ms: int) -> _ClassificationResult: + return _ClassificationResult( + classifications=[ + _Classifications( + entries=[ + _ClassificationEntry( + categories=[], + timestamp_ms=timestamp_ms + ) + ], + head_index=0, + head_name='probability') + ]) + + def _generate_burger_results(timestamp_ms: int) -> _ClassificationResult: return _ClassificationResult( classifications=[ @@ -447,16 +450,14 @@ class ImageClassifierTest(parameterized.TestCase): ValueError, r'Input timestamp must be monotonically increasing'): classifier.classify_async(self.test_image, 0) - # TODO: Fix the packet is empty issue. - """ - @parameterized.parameters((0, _EXPECTED_CLASSIFICATION_RESULT), - (1, _EMPTY_CLASSIFICATION_RESULT)) - def test_classify_async_calls(self, threshold, expected_result): + @parameterized.parameters((0, _generate_burger_results), + (1, _generate_empty_results)) + def test_classify_async_calls(self, threshold, expected_result_fn): observed_timestamp_ms = -1 def check_result(result: _ClassificationResult, output_image: _Image, timestamp_ms: int): - self.assertEqual(result, expected_result) + self.assertEqual(result, expected_result_fn(timestamp_ms)) self.assertTrue( np.array_equal(output_image.numpy_view(), self.test_image.numpy_view())) @@ -474,7 +475,6 @@ class ImageClassifierTest(parameterized.TestCase): for timestamp in range(0, 300, 30): classifier.classify_async(self.test_image, timestamp) classifier.close() - """ if __name__ == '__main__': diff --git a/mediapipe/tasks/python/vision/image_classifier.py b/mediapipe/tasks/python/vision/image_classifier.py index 348e848ab..1d6b69778 100644 --- a/mediapipe/tasks/python/vision/image_classifier.py +++ b/mediapipe/tasks/python/vision/image_classifier.py @@ -138,6 +138,8 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): """ def packets_callback(output_packets: Mapping[str, packet_module.Packet]): + if output_packets[_IMAGE_OUT_STREAM_NAME].is_empty(): + return classification_result_proto = packet_getter.get_proto( output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]) @@ -148,7 +150,7 @@ class ImageClassifier(base_vision_task_api.BaseVisionTaskApi): image = packet_getter.get_image(output_packets[_IMAGE_OUT_STREAM_NAME]) timestamp = output_packets[_IMAGE_OUT_STREAM_NAME].timestamp options.result_callback(classification_result, image, - timestamp.value / _MICRO_SECONDS_PER_MILLISECOND) + timestamp.value // _MICRO_SECONDS_PER_MILLISECOND) task_info = _TaskInfo( task_graph=_TASK_GRAPH_NAME, From 7726205d851cab65bbe1e7508201704c57869ae1 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 11 Oct 2022 22:42:50 -0700 Subject: [PATCH 028/125] Added a test to run classify_async in region of interest mode --- .../test/vision/image_classifier_test.py | 26 +++++++++++++++++++ 1 file changed, 26 insertions(+) diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 5bb479d7a..d2140f1da 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -476,6 +476,32 @@ class ImageClassifierTest(parameterized.TestCase): classifier.classify_async(self.test_image, timestamp) classifier.close() + def test_classify_async_succeeds_with_region_of_interest(self): + observed_timestamp_ms = -1 + + def check_result(result: _ClassificationResult, unused_output_image: _Image, + timestamp_ms: int): + self.assertEqual(result, _generate_soccer_ball_results(timestamp_ms)) + self.assertLess(observed_timestamp_ms, timestamp_ms) + self.observed_timestamp_ms = timestamp_ms + + classifier_options = _ClassifierOptions(max_results=1) + options = _ImageClassifierOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + classifier_options=classifier_options, + result_callback=check_result) + classifier = _ImageClassifier.create_from_options(options) + # Load the test image. + test_image = _Image.create_from_file( + test_utils.get_test_data_path('multi_objects.jpg')) + # NormalizedRect around the soccer ball. + roi = _NormalizedRect(x_center=0.532, y_center=0.521, width=0.164, + height=0.427) + for timestamp in range(0, 300, 30): + classifier.classify_async(test_image, timestamp, roi) + classifier.close() + if __name__ == '__main__': absltest.main() From 6771fe69e9803bdfe8925dcb53b4445c83a72454 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 11 Oct 2022 22:52:18 -0700 Subject: [PATCH 029/125] Included checks for image sizes while running in async and roi mode --- .../python/test/vision/image_classifier_test.py | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index d2140f1da..783718d06 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -477,11 +477,19 @@ class ImageClassifierTest(parameterized.TestCase): classifier.close() def test_classify_async_succeeds_with_region_of_interest(self): + # Load the test image. + test_image = _Image.create_from_file( + test_utils.get_test_data_path('multi_objects.jpg')) + # NormalizedRect around the soccer ball. + roi = _NormalizedRect(x_center=0.532, y_center=0.521, width=0.164, + height=0.427) observed_timestamp_ms = -1 - def check_result(result: _ClassificationResult, unused_output_image: _Image, + def check_result(result: _ClassificationResult, output_image: _Image, timestamp_ms: int): self.assertEqual(result, _generate_soccer_ball_results(timestamp_ms)) + self.assertEqual(output_image.width, test_image.width) + self.assertEqual(output_image.height, test_image.height) self.assertLess(observed_timestamp_ms, timestamp_ms) self.observed_timestamp_ms = timestamp_ms @@ -492,12 +500,6 @@ class ImageClassifierTest(parameterized.TestCase): classifier_options=classifier_options, result_callback=check_result) classifier = _ImageClassifier.create_from_options(options) - # Load the test image. - test_image = _Image.create_from_file( - test_utils.get_test_data_path('multi_objects.jpg')) - # NormalizedRect around the soccer ball. - roi = _NormalizedRect(x_center=0.532, y_center=0.521, width=0.164, - height=0.427) for timestamp in range(0, 300, 30): classifier.classify_async(test_image, timestamp, roi) classifier.close() From 803210a86b460f53fa6eb6c4ef4d67131e70d457 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Fri, 14 Oct 2022 03:00:29 -0700 Subject: [PATCH 030/125] Simplified async test cases to invoke the classifier in context --- .../python/test/vision/image_classifier_test.py | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 783718d06..a90ddd53e 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -471,10 +471,9 @@ class ImageClassifierTest(parameterized.TestCase): running_mode=_RUNNING_MODE.LIVE_STREAM, classifier_options=classifier_options, result_callback=check_result) - classifier = _ImageClassifier.create_from_options(options) - for timestamp in range(0, 300, 30): - classifier.classify_async(self.test_image, timestamp) - classifier.close() + with _ImageClassifier.create_from_options(options) as classifier: + for timestamp in range(0, 300, 30): + classifier.classify_async(self.test_image, timestamp) def test_classify_async_succeeds_with_region_of_interest(self): # Load the test image. @@ -499,10 +498,9 @@ class ImageClassifierTest(parameterized.TestCase): running_mode=_RUNNING_MODE.LIVE_STREAM, classifier_options=classifier_options, result_callback=check_result) - classifier = _ImageClassifier.create_from_options(options) - for timestamp in range(0, 300, 30): - classifier.classify_async(test_image, timestamp, roi) - classifier.close() + with _ImageClassifier.create_from_options(options) as classifier: + for timestamp in range(0, 300, 30): + classifier.classify_async(test_image, timestamp, roi) if __name__ == '__main__': From f84e0bc1c61a0b4de6a296d08bba6934bcf2f18d Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 18 Oct 2022 04:24:12 -0700 Subject: [PATCH 031/125] Revised API implementation and added more tests for segment_for_video and segment_async --- mediapipe/tasks/python/test/vision/BUILD | 2 +- .../test/vision/image_segmenter_test.py | 233 +++++++++++++++--- .../tasks/python/vision/image_segmenter.py | 82 +++++- 3 files changed, 277 insertions(+), 40 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 51a9c514b..63fc56b42 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -47,7 +47,7 @@ py_test( deps = [ "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/python/core:base_options", - "//mediapipe/tasks/python/test:test_util", + "//mediapipe/tasks/python/test:test_utils", "//mediapipe/tasks/python/components/proto:segmenter_options", "//mediapipe/tasks/python/vision:image_segmenter", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index 9ebd46bc4..a97aed10e 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -16,6 +16,8 @@ import enum import numpy as np import cv2 +from typing import List +from unittest import mock from absl.testing import absltest from absl.testing import parameterized @@ -24,7 +26,7 @@ from mediapipe.python._framework_bindings import image as image_module from mediapipe.python._framework_bindings import image_frame as image_frame_module from mediapipe.tasks.python.components.proto import segmenter_options from mediapipe.tasks.python.core import base_options as base_options_module -from mediapipe.tasks.python.test import test_util +from mediapipe.tasks.python.test import test_utils from mediapipe.tasks.python.vision import image_segmenter from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module @@ -42,7 +44,22 @@ _MODEL_FILE = 'deeplabv3.tflite' _IMAGE_FILE = 'segmentation_input_rotation0.jpg' _SEGMENTATION_FILE = 'segmentation_golden_rotation0.png' _MASK_MAGNIFICATION_FACTOR = 10 -_MATCH_PIXELS_THRESHOLD = 0.01 +_MASK_SIMILARITY_THRESHOLD = 0.98 + + +def _similar_to_uint8_mask(actual_mask, expected_mask): + actual_mask_pixels = actual_mask.numpy_view().flatten() + expected_mask_pixels = expected_mask.numpy_view().flatten() + + consistent_pixels = 0 + num_pixels = len(expected_mask_pixels) + + for index in range(num_pixels): + consistent_pixels += ( + actual_mask_pixels[index] * _MASK_MAGNIFICATION_FACTOR == + expected_mask_pixels[index]) + + return consistent_pixels / num_pixels >= _MASK_SIMILARITY_THRESHOLD class ModelFileType(enum.Enum): @@ -54,10 +71,14 @@ class ImageSegmenterTest(parameterized.TestCase): def setUp(self): super().setUp() - self.test_image = test_util.read_test_image( - test_util.get_test_data_path(_IMAGE_FILE)) - self.test_seg_path = test_util.get_test_data_path(_SEGMENTATION_FILE) - self.model_path = test_util.get_test_data_path(_MODEL_FILE) + # Load the test input image. + self.test_image = _Image.create_from_file( + test_utils.get_test_data_path(_IMAGE_FILE)) + # Loads ground truth segmentation file. + gt_segmentation_data = cv2.imread( + test_utils.get_test_data_path(_SEGMENTATION_FILE), cv2.IMREAD_GRAYSCALE) + self.test_seg_image = _Image(_ImageFormat.GRAY8, gt_segmentation_data) + self.model_path = test_utils.get_test_data_path(_MODEL_FILE) def test_create_from_file_succeeds_with_valid_model_path(self): # Creates with default option and valid model file successfully. @@ -76,7 +97,7 @@ class ImageSegmenterTest(parameterized.TestCase): with self.assertRaisesRegex( ValueError, r"ExternalFile must specify at least one of 'file_content', " - r"'file_name' or 'file_descriptor_meta'."): + r"'file_name', 'file_pointer_meta' or 'file_descriptor_meta'."): base_options = _BaseOptions(model_asset_path='') options = _ImageSegmenterOptions(base_options=base_options) _ImageSegmenter.create_from_options(options) @@ -112,34 +133,16 @@ class ImageSegmenterTest(parameterized.TestCase): # Performs image segmentation on the input. category_masks = segmenter.segment(self.test_image) self.assertEqual(len(category_masks), 1) - result_pixels = category_masks[0].numpy_view().flatten() + category_mask = category_masks[0] + result_pixels = category_mask.numpy_view().flatten() - # Check if data type of `category_masks` is correct. + # Check if data type of `category_mask` is correct. self.assertEqual(result_pixels.dtype, np.uint8) - # Loads ground truth segmentation file. - image_data = cv2.imread(self.test_seg_path, cv2.IMREAD_GRAYSCALE) - gt_segmentation = _Image(_ImageFormat.GRAY8, image_data) - gt_segmentation_array = gt_segmentation.numpy_view() - gt_segmentation_shape = gt_segmentation_array.shape - num_pixels = gt_segmentation_shape[0] * gt_segmentation_shape[1] - ground_truth_pixels = gt_segmentation_array.flatten() - - self.assertEqual( - len(result_pixels), len(ground_truth_pixels), - 'Segmentation mask size does not match the ground truth mask size.') - - inconsistent_pixels = 0 - - for index in range(num_pixels): - inconsistent_pixels += ( - result_pixels[index] * _MASK_MAGNIFICATION_FACTOR != - ground_truth_pixels[index]) - - self.assertLessEqual( - inconsistent_pixels / num_pixels, _MATCH_PIXELS_THRESHOLD, + self.assertTrue( + _similar_to_uint8_mask(category_masks[0], self.test_seg_image), f'Number of pixels in the candidate mask differing from that of the ' - f'ground truth mask exceeds {_MATCH_PIXELS_THRESHOLD}.') + f'ground truth mask exceeds {_MASK_SIMILARITY_THRESHOLD}.') # Closes the segmenter explicitly when the segmenter is not used in # a context. @@ -188,6 +191,174 @@ class ImageSegmenterTest(parameterized.TestCase): # a context. segmenter.close() + @parameterized.parameters( + (ModelFileType.FILE_NAME,), + (ModelFileType.FILE_CONTENT,)) + def test_segment_in_context(self, model_file_type): + if model_file_type is ModelFileType.FILE_NAME: + base_options = _BaseOptions(model_asset_path=self.model_path) + elif model_file_type is ModelFileType.FILE_CONTENT: + with open(self.model_path, 'rb') as f: + model_contents = f.read() + base_options = _BaseOptions(model_asset_buffer=model_contents) + else: + # Should never happen + raise ValueError('model_file_type is invalid.') + + segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) + options = _ImageSegmenterOptions(base_options=base_options, + segmenter_options=segmenter_options) + with _ImageSegmenter.create_from_options(options) as segmenter: + # Performs image segmentation on the input. + category_masks = segmenter.segment(self.test_image) + self.assertEqual(len(category_masks), 1) + + self.assertTrue( + _similar_to_uint8_mask(category_masks[0], self.test_seg_image), + f'Number of pixels in the candidate mask differing from that of the ' + f'ground truth mask exceeds {_MASK_SIMILARITY_THRESHOLD}.') + + def test_missing_result_callback(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM) + with self.assertRaisesRegex(ValueError, + r'result callback must be provided'): + with _ImageSegmenter.create_from_options(options) as unused_segmenter: + pass + + @parameterized.parameters((_RUNNING_MODE.IMAGE), (_RUNNING_MODE.VIDEO)) + def test_illegal_result_callback(self, running_mode): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=running_mode, + result_callback=mock.MagicMock()) + with self.assertRaisesRegex(ValueError, + r'result callback should not be provided'): + with _ImageSegmenter.create_from_options(options) as unused_segmenter: + pass + + def test_calling_segment_for_video_in_image_mode(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.IMAGE) + with _ImageSegmenter.create_from_options(options) as segmenter: + with self.assertRaisesRegex(ValueError, + r'not initialized with the video mode'): + segmenter.segment_for_video(self.test_image, 0) + + def test_calling_segment_async_in_image_mode(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.IMAGE) + with _ImageSegmenter.create_from_options(options) as segmenter: + with self.assertRaisesRegex(ValueError, + r'not initialized with the live stream mode'): + segmenter.segment_async(self.test_image, 0) + + def test_calling_segment_in_video_mode(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _ImageSegmenter.create_from_options(options) as segmenter: + with self.assertRaisesRegex(ValueError, + r'not initialized with the image mode'): + segmenter.segment(self.test_image) + + def test_calling_segment_async_in_video_mode(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _ImageSegmenter.create_from_options(options) as segmenter: + with self.assertRaisesRegex(ValueError, + r'not initialized with the live stream mode'): + segmenter.segment_async(self.test_image, 0) + + def test_detect_for_video_with_out_of_order_timestamp(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _ImageSegmenter.create_from_options(options) as segmenter: + unused_result = segmenter.segment_for_video(self.test_image, 1) + with self.assertRaisesRegex( + ValueError, r'Input timestamp must be monotonically increasing'): + segmenter.segment_for_video(self.test_image, 0) + + def test_segment_for_video(self): + segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + segmenter_options=segmenter_options, + running_mode=_RUNNING_MODE.VIDEO) + with _ImageSegmenter.create_from_options(options) as segmenter: + for timestamp in range(0, 300, 30): + category_masks = segmenter.segment_for_video(self.test_image, timestamp) + self.assertEqual(len(category_masks), 1) + self.assertTrue( + _similar_to_uint8_mask(category_masks[0], self.test_seg_image), + f'Number of pixels in the candidate mask differing from that of the ' + f'ground truth mask exceeds {_MASK_SIMILARITY_THRESHOLD}.') + + def test_calling_segment_in_live_stream_mode(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=mock.MagicMock()) + with _ImageSegmenter.create_from_options(options) as segmenter: + with self.assertRaisesRegex(ValueError, + r'not initialized with the image mode'): + segmenter.segment(self.test_image) + + def test_calling_segment_for_video_in_live_stream_mode(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=mock.MagicMock()) + with _ImageSegmenter.create_from_options(options) as segmenter: + with self.assertRaisesRegex(ValueError, + r'not initialized with the video mode'): + segmenter.segment_for_video(self.test_image, 0) + + def test_segment_async_calls_with_illegal_timestamp(self): + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=mock.MagicMock()) + with _ImageSegmenter.create_from_options(options) as segmenter: + segmenter.segment_async(self.test_image, 100) + with self.assertRaisesRegex( + ValueError, r'Input timestamp must be monotonically increasing'): + segmenter.segment_async(self.test_image, 0) + + def test_segment_async_calls(self): + observed_timestamp_ms = -1 + + def check_result(result: List[image_module.Image], + output_image: _Image, + timestamp_ms: int): + # Get the output category mask. + category_mask = result[0] + self.assertEqual(output_image.width, self.test_image.width) + self.assertEqual(output_image.height, self.test_image.height) + self.assertEqual(output_image.width, self.test_seg_image.width) + self.assertEqual(output_image.height, self.test_seg_image.height) + self.assertTrue( + _similar_to_uint8_mask(category_mask, self.test_seg_image), + f'Number of pixels in the candidate mask differing from that of the ' + f'ground truth mask exceeds {_MASK_SIMILARITY_THRESHOLD}.') + self.assertLess(observed_timestamp_ms, timestamp_ms) + self.observed_timestamp_ms = timestamp_ms + + segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) + options = _ImageSegmenterOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + segmenter_options=segmenter_options, + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=check_result) + with _ImageSegmenter.create_from_options(options) as segmenter: + for timestamp in range(0, 300, 30): + segmenter.segment_async(self.test_image, timestamp) + if __name__ == '__main__': absltest.main() diff --git a/mediapipe/tasks/python/vision/image_segmenter.py b/mediapipe/tasks/python/vision/image_segmenter.py index 060a67793..51f802925 100644 --- a/mediapipe/tasks/python/vision/image_segmenter.py +++ b/mediapipe/tasks/python/vision/image_segmenter.py @@ -42,6 +42,7 @@ _IMAGE_IN_STREAM_NAME = 'image_in' _IMAGE_OUT_STREAM_NAME = 'image_out' _IMAGE_TAG = 'IMAGE' _TASK_GRAPH_NAME = 'mediapipe.tasks.vision.ImageSegmenterGraph' +_MICRO_SECONDS_PER_MILLISECOND = 1000 @dataclasses.dataclass @@ -52,9 +53,9 @@ class ImageSegmenterOptions: base_options: Base options for the image segmenter task. running_mode: The running mode of the task. Default to the image mode. Image segmenter task has three running modes: - 1) The image mode for detecting objects on single image inputs. - 2) The video mode for detecting objects on the decoded frames of a video. - 3) The live stream mode for detecting objects on a live stream of input + 1) The image mode for segmenting objects on single image inputs. + 2) The video mode for segmenting objects on the decoded frames of a video. + 3) The live stream mode for segmenting objects on a live stream of input data, such as from camera. segmenter_options: Options for the image segmenter task. result_callback: The user-defined result callback for processing live stream @@ -86,7 +87,8 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): @classmethod def create_from_model_path(cls, model_path: str) -> 'ImageSegmenter': - """Creates an `ImageSegmenter` object from a TensorFlow Lite model and the default `ImageSegmenterOptions`. + """Creates an `ImageSegmenter` object from a TensorFlow Lite model and the + default `ImageSegmenterOptions`. Note that the created `ImageSegmenter` instance is in image mode, for performing image segmentation on single image inputs. @@ -131,8 +133,9 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): segmentation_result = packet_getter.get_image_list( output_packets[_SEGMENTATION_OUT_STREAM_NAME]) image = packet_getter.get_image(output_packets[_IMAGE_OUT_STREAM_NAME]) - timestamp = output_packets[_IMAGE_OUT_STREAM_NAME].timestamp - options.result_callback(segmentation_result, image, timestamp) + timestamp = output_packets[_SEGMENTATION_OUT_STREAM_NAME].timestamp + options.result_callback(segmentation_result, image, + timestamp.value // _MICRO_SECONDS_PER_MILLISECOND) task_info = _TaskInfo( task_graph=_TASK_GRAPH_NAME, @@ -148,7 +151,6 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): _RunningMode.LIVE_STREAM), options.running_mode, packets_callback if options.result_callback else None) - # TODO: Create an Image class for MediaPipe Tasks. def segment(self, image: image_module.Image) -> List[image_module.Image]: """Performs the actual segmentation task on the provided MediaPipe Image. @@ -162,10 +164,74 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): Raises: ValueError: If any of the input arguments is invalid. - RuntimeError: If object detection failed to run. + RuntimeError: If image segmentation failed to run. """ output_packets = self._process_image_data( {_IMAGE_IN_STREAM_NAME: packet_creator.create_image(image)}) segmentation_result = packet_getter.get_image_list( output_packets[_SEGMENTATION_OUT_STREAM_NAME]) return segmentation_result + + def segment_for_video(self, image: image_module.Image, + timestamp_ms: int) -> List[image_module.Image]: + """Performs segmentation on the provided video frames. + + Only use this method when the ImageSegmenter is created with the video + running mode. It's required to provide the video frame's timestamp (in + milliseconds) along with the video frame. The input timestamps should be + monotonically increasing for adjacent calls of this method. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input video frame in milliseconds. + + Returns: + A segmentation result object that contains a list of segmentation masks + as images. + + Raises: + ValueError: If any of the input arguments is invalid. + RuntimeError: If image segmentation failed to run. + """ + output_packets = self._process_video_data({ + _IMAGE_IN_STREAM_NAME: + packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) + }) + segmentation_result = packet_getter.get_image_list( + output_packets[_SEGMENTATION_OUT_STREAM_NAME]) + return segmentation_result + + def segment_async(self, image: image_module.Image, timestamp_ms: int) -> None: + """Sends live image data (an Image with a unique timestamp) to perform + image segmentation. + + Only use this method when the ImageSegmenter is created with the live stream + running mode. The input timestamps should be monotonically increasing for + adjacent calls of this method. This method will return immediately after the + input image is accepted. The results will be available via the + `result_callback` provided in the `ImageSegmenterOptions`. The + `segment_async` method is designed to process live stream data such as + camera input. To lower the overall latency, image segmenter may drop the + input images if needed. In other words, it's not guaranteed to have output + per input image. + + The `result_callback` prvoides: + - A segmentation result object that contains a list of segmentation masks + as images. + - The input image that the image segmenter runs on. + - The input timestamp in milliseconds. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input image in milliseconds. + + Raises: + ValueError: If the current input timestamp is smaller than what the image + segmenter has already processed. + """ + self._send_live_stream_data({ + _IMAGE_IN_STREAM_NAME: + packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) + }) From 4932844410b0d2f7f18d7cd63b5b9f4915c7ea86 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 18 Oct 2022 04:29:28 -0700 Subject: [PATCH 032/125] Reverted changes to BUILD --- mediapipe/python/BUILD | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/mediapipe/python/BUILD b/mediapipe/python/BUILD index a329c44e3..07ad97810 100644 --- a/mediapipe/python/BUILD +++ b/mediapipe/python/BUILD @@ -35,7 +35,7 @@ pybind_extension( }), module_name = "_framework_bindings", deps = [ - #":builtin_calculators", + ":builtin_calculators", ":builtin_task_graphs", "//mediapipe/python/pybind:calculator_graph", "//mediapipe/python/pybind:image", @@ -87,7 +87,6 @@ cc_library( cc_library( name = "builtin_task_graphs", deps = [ - "//mediapipe/calculators/core:flow_limiter_calculator", "//mediapipe/tasks/cc/vision/object_detector:object_detector_graph", "//mediapipe/tasks/cc/vision/image_segmenter:image_segmenter_graph", ], From 69f4daf9bc67c2d2ba03e9737a027cd09bf51b1e Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 18 Oct 2022 04:31:35 -0700 Subject: [PATCH 033/125] Removed unused BUILD --- mediapipe/tasks/python/components/BUILD | 19 ------------------- 1 file changed, 19 deletions(-) delete mode 100644 mediapipe/tasks/python/components/BUILD diff --git a/mediapipe/tasks/python/components/BUILD b/mediapipe/tasks/python/components/BUILD deleted file mode 100644 index 00fd4061c..000000000 --- a/mediapipe/tasks/python/components/BUILD +++ /dev/null @@ -1,19 +0,0 @@ -# Copyright 2022 The MediaPipe Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Placeholder for internal Python strict library compatibility macro. - -package(default_visibility = ["//mediapipe/tasks:internal"]) - -licenses(["notice"]) From f166eb32e88df10ef6c56f63a6acaa5fac4dc0c3 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 18 Oct 2022 04:34:17 -0700 Subject: [PATCH 034/125] Updated names of test case methods --- mediapipe/tasks/python/test/vision/image_segmenter_test.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index a97aed10e..054c3e962 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -113,7 +113,7 @@ class ImageSegmenterTest(parameterized.TestCase): @parameterized.parameters( (ModelFileType.FILE_NAME,), (ModelFileType.FILE_CONTENT,)) - def test_succeeds_with_category_mask(self, model_file_type): + def test_segment_succeeds_with_category_mask(self, model_file_type): # Creates segmenter. if model_file_type is ModelFileType.FILE_NAME: base_options = _BaseOptions(model_asset_path=self.model_path) @@ -148,7 +148,7 @@ class ImageSegmenterTest(parameterized.TestCase): # a context. segmenter.close() - def test_succeeds_with_confidence_mask(self): + def test_segment_succeeds_with_confidence_mask(self): # Creates segmenter. base_options = _BaseOptions(model_asset_path=self.model_path) @@ -192,8 +192,7 @@ class ImageSegmenterTest(parameterized.TestCase): segmenter.close() @parameterized.parameters( - (ModelFileType.FILE_NAME,), - (ModelFileType.FILE_CONTENT,)) + (ModelFileType.FILE_NAME), (ModelFileType.FILE_CONTENT)) def test_segment_in_context(self, model_file_type): if model_file_type is ModelFileType.FILE_NAME: base_options = _BaseOptions(model_asset_path=self.model_path) From 91b60da1dcc3a3df43ebcf00ebfe93c12b9f5337 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 18 Oct 2022 05:35:05 -0700 Subject: [PATCH 035/125] Updated name for a test case --- mediapipe/tasks/python/test/vision/image_segmenter_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index 054c3e962..b53f301b1 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -273,7 +273,7 @@ class ImageSegmenterTest(parameterized.TestCase): r'not initialized with the live stream mode'): segmenter.segment_async(self.test_image, 0) - def test_detect_for_video_with_out_of_order_timestamp(self): + def test_segment_for_video_with_out_of_order_timestamp(self): options = _ImageSegmenterOptions( base_options=_BaseOptions(model_asset_path=self.model_path), running_mode=_RUNNING_MODE.VIDEO) From e71638cf679bf2c5aca1a4355d9cc69ed67633f1 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 20 Oct 2022 10:19:15 -0700 Subject: [PATCH 036/125] Add an export_tflite API to gesture recognizer model maker library. PiperOrigin-RevId: 482527017 --- .../python/core/tasks/custom_model.py | 8 ++--- .../python/core/tasks/custom_model_test.py | 6 ++-- .../python/core/utils/model_util.py | 4 +-- .../python/core/utils/model_util_test.py | 32 ++++++++----------- .../python/core/utils/test_util.py | 29 +++++++++++++++++ 5 files changed, 50 insertions(+), 29 deletions(-) diff --git a/mediapipe/model_maker/python/core/tasks/custom_model.py b/mediapipe/model_maker/python/core/tasks/custom_model.py index 2cea4e0a1..66d1494db 100644 --- a/mediapipe/model_maker/python/core/tasks/custom_model.py +++ b/mediapipe/model_maker/python/core/tasks/custom_model.py @@ -21,8 +21,6 @@ import abc import os from typing import Any, Callable, Optional -# Dependency imports - import tensorflow as tf from mediapipe.model_maker.python.core.data import dataset @@ -77,9 +75,9 @@ class CustomModel(abc.ABC): tflite_filepath = os.path.join(export_dir, tflite_filename) # TODO: Populate metadata to the exported TFLite model. model_util.export_tflite( - self._model, - tflite_filepath, - quantization_config, + model=self._model, + tflite_filepath=tflite_filepath, + quantization_config=quantization_config, preprocess=preprocess) tf.compat.v1.logging.info( 'TensorFlow Lite model exported successfully: %s' % tflite_filepath) diff --git a/mediapipe/model_maker/python/core/tasks/custom_model_test.py b/mediapipe/model_maker/python/core/tasks/custom_model_test.py index e693e1275..ad77d4ecd 100644 --- a/mediapipe/model_maker/python/core/tasks/custom_model_test.py +++ b/mediapipe/model_maker/python/core/tasks/custom_model_test.py @@ -40,8 +40,8 @@ class CustomModelTest(tf.test.TestCase): def setUp(self): super(CustomModelTest, self).setUp() - self.model = MockCustomModel(model_spec=None, shuffle=False) - self.model._model = test_util.build_model(input_shape=[4], num_classes=2) + self._model = MockCustomModel(model_spec=None, shuffle=False) + self._model._model = test_util.build_model(input_shape=[4], num_classes=2) def _check_nonempty_file(self, filepath): self.assertTrue(os.path.isfile(filepath)) @@ -49,7 +49,7 @@ class CustomModelTest(tf.test.TestCase): def test_export_tflite(self): export_path = os.path.join(self.get_temp_dir(), 'export/') - self.model.export_tflite(export_dir=export_path) + self._model.export_tflite(export_dir=export_path) self._check_nonempty_file(os.path.join(export_path, 'model.tflite')) if __name__ == '__main__': diff --git a/mediapipe/model_maker/python/core/utils/model_util.py b/mediapipe/model_maker/python/core/utils/model_util.py index 0899a9b1a..e1228eb6e 100644 --- a/mediapipe/model_maker/python/core/utils/model_util.py +++ b/mediapipe/model_maker/python/core/utils/model_util.py @@ -104,8 +104,8 @@ def export_tflite( quantization_config: Configuration for post-training quantization. supported_ops: A list of supported ops in the converted TFLite file. preprocess: A callable to preprocess the representative dataset for - quantization. The callable takes three arguments in order: feature, - label, and is_training. + quantization. The callable takes three arguments in order: feature, label, + and is_training. """ if tflite_filepath is None: raise ValueError( diff --git a/mediapipe/model_maker/python/core/utils/model_util_test.py b/mediapipe/model_maker/python/core/utils/model_util_test.py index ce31c1877..35b52eb75 100644 --- a/mediapipe/model_maker/python/core/utils/model_util_test.py +++ b/mediapipe/model_maker/python/core/utils/model_util_test.py @@ -100,7 +100,8 @@ class ModelUtilTest(tf.test.TestCase, parameterized.TestCase): model = test_util.build_model(input_shape=[input_dim], num_classes=2) tflite_file = os.path.join(self.get_temp_dir(), 'model.tflite') model_util.export_tflite(model, tflite_file) - self._test_tflite(model, tflite_file, input_dim) + test_util.test_tflite( + keras_model=model, tflite_file=tflite_file, size=[1, input_dim]) @parameterized.named_parameters( dict( @@ -121,27 +122,20 @@ class ModelUtilTest(tf.test.TestCase, parameterized.TestCase): input_dim = 16 num_classes = 2 max_input_value = 5 - model = test_util.build_model([input_dim], num_classes) + model = test_util.build_model( + input_shape=[input_dim], num_classes=num_classes) tflite_file = os.path.join(self.get_temp_dir(), 'model_quantized.tflite') - model_util.export_tflite(model, tflite_file, config) - self._test_tflite( - model, tflite_file, input_dim, max_input_value, atol=1e-00) - self.assertNear(os.path.getsize(tflite_file), model_size, 300) - - def _test_tflite(self, - keras_model: tf.keras.Model, - tflite_model_file: str, - input_dim: int, - max_input_value: int = 1000, - atol: float = 1e-04): - random_input = test_util.create_random_sample( - size=[1, input_dim], high=max_input_value) - random_input = tf.convert_to_tensor(random_input) - + model_util.export_tflite( + model=model, tflite_filepath=tflite_file, quantization_config=config) self.assertTrue( - test_util.is_same_output( - tflite_model_file, keras_model, random_input, atol=atol)) + test_util.test_tflite( + keras_model=model, + tflite_file=tflite_file, + size=[1, input_dim], + high=max_input_value, + atol=1e-00)) + self.assertNear(os.path.getsize(tflite_file), model_size, 300) if __name__ == '__main__': diff --git a/mediapipe/model_maker/python/core/utils/test_util.py b/mediapipe/model_maker/python/core/utils/test_util.py index cac2a0e1f..b402d3793 100644 --- a/mediapipe/model_maker/python/core/utils/test_util.py +++ b/mediapipe/model_maker/python/core/utils/test_util.py @@ -92,3 +92,32 @@ def is_same_output(tflite_file: str, keras_output = keras_model.predict_on_batch(input_tensors) return np.allclose(lite_output, keras_output, atol=atol) + + +def test_tflite(keras_model: tf.keras.Model, + tflite_file: str, + size: Union[int, List[int]], + high: float = 1, + atol: float = 1e-04) -> bool: + """Verifies if the output of TFLite model and TF Keras model are identical. + + Args: + keras_model: Input TensorFlow Keras model. + tflite_file: Input TFLite model file. + size: Size of the input tesnor. + high: Higher boundary of the values in input tensors. + atol: Absolute tolerance of the difference between the outputs of Keras + model and TFLite model. + + Returns: + True if the output of TFLite model and TF Keras model are identical. + Otherwise, False. + """ + random_input = create_random_sample(size=size, high=high) + random_input = tf.convert_to_tensor(random_input) + + return is_same_output( + tflite_file=tflite_file, + keras_model=keras_model, + input_tensors=random_input, + atol=atol) From 4b5df1cb9610e9707184a857b9e5f4e25d73ec0a Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 20 Oct 2022 10:40:56 -0700 Subject: [PATCH 037/125] Add support for rotations in GestureRecognizer C++ API. PiperOrigin-RevId: 482533599 --- .../tasks/cc/vision/gesture_recognizer/BUILD | 3 + .../gesture_recognizer/calculators/BUILD | 2 + .../landmarks_to_matrix_calculator.cc | 32 +++ .../landmarks_to_matrix_calculator_test.cc | 44 +++- .../gesture_recognizer/gesture_recognizer.cc | 67 +++++- .../gesture_recognizer/gesture_recognizer.h | 30 ++- .../gesture_recognizer_graph.cc | 16 +- .../hand_gesture_recognizer_graph.cc | 36 ++- mediapipe/tasks/cc/vision/hand_detector/BUILD | 2 +- .../hand_detector/hand_detector_graph.cc | 37 +-- .../hand_detector/hand_detector_graph_test.cc | 34 ++- .../hand_landmarker/hand_landmarker_graph.cc | 21 +- .../hand_landmarker_graph_test.cc | 55 ++++- .../gesturerecognizer/GestureRecognizer.java | 22 +- mediapipe/tasks/testdata/vision/BUILD | 13 + ..._left_down_hand_rotated_landmarks.prototxt | 84 +++++++ ...ed_left_up_hand_rotated_landmarks.prototxt | 84 +++++++ ...and_detector_result_one_hand_rotated.pbtxt | 33 +++ .../pointing_up_rotated_landmarks.pbtxt | 223 ++++++++++++++++++ .../vision/thumb_up_rotated_landmarks.pbtxt | 223 ++++++++++++++++++ third_party/external_files.bzl | 50 +++- 21 files changed, 1048 insertions(+), 63 deletions(-) create mode 100644 mediapipe/tasks/testdata/vision/expected_left_down_hand_rotated_landmarks.prototxt create mode 100644 mediapipe/tasks/testdata/vision/expected_left_up_hand_rotated_landmarks.prototxt create mode 100644 mediapipe/tasks/testdata/vision/hand_detector_result_one_hand_rotated.pbtxt create mode 100644 mediapipe/tasks/testdata/vision/pointing_up_rotated_landmarks.pbtxt create mode 100644 mediapipe/tasks/testdata/vision/thumb_up_rotated_landmarks.pbtxt diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD b/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD index 985c25cfb..e5b1f0479 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD @@ -56,6 +56,7 @@ cc_library( "//mediapipe/framework/formats:classification_cc_proto", "//mediapipe/framework/formats:landmark_cc_proto", "//mediapipe/framework/formats:matrix", + "//mediapipe/framework/formats:rect_cc_proto", "//mediapipe/framework/formats:tensor", "//mediapipe/tasks/cc:common", "//mediapipe/tasks/cc/components:image_preprocessing", @@ -91,6 +92,7 @@ cc_library( "//mediapipe/framework/formats:classification_cc_proto", "//mediapipe/framework/formats:image", "//mediapipe/framework/formats:landmark_cc_proto", + "//mediapipe/framework/formats:rect_cc_proto", "//mediapipe/tasks/cc:common", "//mediapipe/tasks/cc/components/processors/proto:classifier_options_cc_proto", "//mediapipe/tasks/cc/core:model_task_graph", @@ -123,6 +125,7 @@ cc_library( "//mediapipe/framework/formats:classification_cc_proto", "//mediapipe/framework/formats:image", "//mediapipe/framework/formats:landmark_cc_proto", + "//mediapipe/framework/formats:rect_cc_proto", "//mediapipe/tasks/cc:common", "//mediapipe/tasks/cc/components:image_preprocessing", "//mediapipe/tasks/cc/components/containers:gesture_recognition_result", diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/BUILD b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/BUILD index a6de4f950..08f7f45d0 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/BUILD +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/BUILD @@ -69,6 +69,7 @@ cc_library( "//mediapipe/framework:calculator_framework", "//mediapipe/framework/formats:landmark_cc_proto", "//mediapipe/framework/formats:matrix", + "//mediapipe/framework/formats:rect_cc_proto", "//mediapipe/framework/port:ret_check", "@com_google_absl//absl/status", "@com_google_absl//absl/status:statusor", @@ -86,6 +87,7 @@ cc_test( "//mediapipe/framework:calculator_runner", "//mediapipe/framework/formats:landmark_cc_proto", "//mediapipe/framework/formats:matrix", + "//mediapipe/framework/formats:rect_cc_proto", "//mediapipe/framework/port:gtest_main", "//mediapipe/framework/port:parse_text_proto", "@com_google_absl//absl/strings", diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator.cc index b70689eaf..277bb170a 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator.cc @@ -14,6 +14,7 @@ limitations under the License. ==============================================================================*/ #include +#include #include #include #include @@ -26,6 +27,7 @@ limitations under the License. #include "mediapipe/framework/calculator_framework.h" #include "mediapipe/framework/formats/landmark.pb.h" #include "mediapipe/framework/formats/matrix.h" +#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/port/ret_check.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator.pb.h" @@ -38,6 +40,7 @@ namespace { constexpr char kLandmarksTag[] = "LANDMARKS"; constexpr char kWorldLandmarksTag[] = "WORLD_LANDMARKS"; constexpr char kImageSizeTag[] = "IMAGE_SIZE"; +constexpr char kNormRectTag[] = "NORM_RECT"; constexpr char kLandmarksMatrixTag[] = "LANDMARKS_MATRIX"; constexpr int kFeaturesPerLandmark = 3; @@ -62,6 +65,25 @@ absl::StatusOr NormalizeLandmarkAspectRatio( return normalized_landmarks; } +template +absl::StatusOr RotateLandmarks(const LandmarkListT& landmarks, + float rotation) { + float cos = std::cos(rotation); + // Negate because Y-axis points down and not up. + float sin = std::sin(-rotation); + LandmarkListT rotated_landmarks; + for (int i = 0; i < landmarks.landmark_size(); ++i) { + const auto& old_landmark = landmarks.landmark(i); + float x = old_landmark.x() - 0.5; + float y = old_landmark.y() - 0.5; + auto* new_landmark = rotated_landmarks.add_landmark(); + new_landmark->set_x(x * cos - y * sin + 0.5); + new_landmark->set_y(y * cos + x * sin + 0.5); + new_landmark->set_z(old_landmark.z()); + } + return rotated_landmarks; +} + template absl::StatusOr NormalizeObject(const LandmarkListT& landmarks, int origin_offset) { @@ -134,6 +156,13 @@ absl::Status ProcessLandmarks(LandmarkListT landmarks, CalculatorContext* cc) { NormalizeLandmarkAspectRatio(landmarks, width, height)); } + if (cc->Inputs().HasTag(kNormRectTag)) { + RET_CHECK(!cc->Inputs().Tag(kNormRectTag).IsEmpty()); + const auto rotation = + cc->Inputs().Tag(kNormRectTag).Get().rotation(); + ASSIGN_OR_RETURN(landmarks, RotateLandmarks(landmarks, rotation)); + } + const auto& options = cc->Options(); if (options.object_normalization()) { ASSIGN_OR_RETURN( @@ -163,6 +192,8 @@ absl::Status ProcessLandmarks(LandmarkListT landmarks, CalculatorContext* cc) { // WORLD_LANDMARKS - World 3d landmarks of one object. Use *either* // LANDMARKS or WORLD_LANDMARKS. // IMAGE_SIZE - (width, height) of the image +// NORM_RECT - Optional NormalizedRect object whose 'rotation' field is used +// to rotate the landmarks. // Output: // LANDMARKS_MATRIX - Matrix for the landmarks. // @@ -185,6 +216,7 @@ class LandmarksToMatrixCalculator : public CalculatorBase { cc->Inputs().Tag(kLandmarksTag).Set().Optional(); cc->Inputs().Tag(kWorldLandmarksTag).Set().Optional(); cc->Inputs().Tag(kImageSizeTag).Set>().Optional(); + cc->Inputs().Tag(kNormRectTag).Set().Optional(); cc->Outputs().Tag(kLandmarksMatrixTag).Set(); return absl::OkStatus(); } diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator_test.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator_test.cc index 8a68d8dae..fe6f1162b 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator_test.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator_test.cc @@ -13,6 +13,7 @@ See the License for the specific language governing permissions and limitations under the License. ==============================================================================*/ +#include #include #include #include @@ -23,6 +24,7 @@ limitations under the License. #include "mediapipe/framework/calculator_runner.h" #include "mediapipe/framework/formats/landmark.pb.h" #include "mediapipe/framework/formats/matrix.h" +#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/port/gtest.h" #include "mediapipe/framework/port/parse_text_proto.h" #include "mediapipe/framework/port/status_matchers.h" @@ -35,6 +37,7 @@ constexpr char kLandmarksTag[] = "LANDMARKS"; constexpr char kWorldLandmarksTag[] = "WORLD_LANDMARKS"; constexpr char kImageSizeTag[] = "IMAGE_SIZE"; constexpr char kLandmarksMatrixTag[] = "LANDMARKS_MATRIX"; +constexpr char kNormRectTag[] = "NORM_RECT"; template LandmarkListT BuildPseudoLandmarks(int num_landmarks, int offset = 0) { @@ -54,6 +57,7 @@ struct Landmarks2dToMatrixCalculatorTestCase { int object_normalization_origin_offset = -1; float expected_cell_0_2; float expected_cell_1_5; + float rotation; }; using Landmarks2dToMatrixCalculatorTest = @@ -68,6 +72,7 @@ TEST_P(Landmarks2dToMatrixCalculatorTest, OutputsCorrectResult) { calculator: "LandmarksToMatrixCalculator" input_stream: "LANDMARKS:landmarks" input_stream: "IMAGE_SIZE:image_size" + input_stream: "NORM_RECT:norm_rect" output_stream: "LANDMARKS_MATRIX:landmarks_matrix" options { [mediapipe.LandmarksToMatrixCalculatorOptions.ext] { @@ -91,6 +96,11 @@ TEST_P(Landmarks2dToMatrixCalculatorTest, OutputsCorrectResult) { runner.MutableInputs() ->Tag(kImageSizeTag) .packets.push_back(Adopt(image_size.release()).At(Timestamp(0))); + auto norm_rect = std::make_unique(); + norm_rect->set_rotation(test_case.rotation); + runner.MutableInputs() + ->Tag(kNormRectTag) + .packets.push_back(Adopt(norm_rect.release()).At(Timestamp(0))); MP_ASSERT_OK(runner.Run()) << "Calculator execution failed."; @@ -109,12 +119,20 @@ INSTANTIATE_TEST_CASE_P( .base_offset = 0, .object_normalization_origin_offset = 0, .expected_cell_0_2 = 0.1f, - .expected_cell_1_5 = 0.1875f}, + .expected_cell_1_5 = 0.1875f, + .rotation = 0}, {.test_name = "TestWithOffset21", .base_offset = 21, .object_normalization_origin_offset = 0, .expected_cell_0_2 = 0.1f, - .expected_cell_1_5 = 0.1875f}}), + .expected_cell_1_5 = 0.1875f, + .rotation = 0}, + {.test_name = "TestWithRotation", + .base_offset = 0, + .object_normalization_origin_offset = 0, + .expected_cell_0_2 = 0.075f, + .expected_cell_1_5 = -0.25f, + .rotation = M_PI / 2.0}}), [](const testing::TestParamInfo< Landmarks2dToMatrixCalculatorTest::ParamType>& info) { return info.param.test_name; @@ -126,6 +144,7 @@ struct LandmarksWorld3dToMatrixCalculatorTestCase { int object_normalization_origin_offset = -1; float expected_cell_0_2; float expected_cell_1_5; + float rotation; }; using LandmarksWorld3dToMatrixCalculatorTest = @@ -140,6 +159,7 @@ TEST_P(LandmarksWorld3dToMatrixCalculatorTest, OutputsCorrectResult) { calculator: "LandmarksToMatrixCalculator" input_stream: "WORLD_LANDMARKS:landmarks" input_stream: "IMAGE_SIZE:image_size" + input_stream: "NORM_RECT:norm_rect" output_stream: "LANDMARKS_MATRIX:landmarks_matrix" options { [mediapipe.LandmarksToMatrixCalculatorOptions.ext] { @@ -162,6 +182,11 @@ TEST_P(LandmarksWorld3dToMatrixCalculatorTest, OutputsCorrectResult) { runner.MutableInputs() ->Tag(kImageSizeTag) .packets.push_back(Adopt(image_size.release()).At(Timestamp(0))); + auto norm_rect = std::make_unique(); + norm_rect->set_rotation(test_case.rotation); + runner.MutableInputs() + ->Tag(kNormRectTag) + .packets.push_back(Adopt(norm_rect.release()).At(Timestamp(0))); MP_ASSERT_OK(runner.Run()) << "Calculator execution failed."; @@ -180,17 +205,26 @@ INSTANTIATE_TEST_CASE_P( .base_offset = 0, .object_normalization_origin_offset = 0, .expected_cell_0_2 = 0.1f, - .expected_cell_1_5 = 0.25}, + .expected_cell_1_5 = 0.25, + .rotation = 0}, {.test_name = "TestWithOffset21", .base_offset = 21, .object_normalization_origin_offset = 0, .expected_cell_0_2 = 0.1f, - .expected_cell_1_5 = 0.25}, + .expected_cell_1_5 = 0.25, + .rotation = 0}, {.test_name = "NoObjectNormalization", .base_offset = 0, .object_normalization_origin_offset = -1, .expected_cell_0_2 = 0.021f, - .expected_cell_1_5 = 0.052f}}), + .expected_cell_1_5 = 0.052f, + .rotation = 0}, + {.test_name = "TestWithRotation", + .base_offset = 0, + .object_normalization_origin_offset = 0, + .expected_cell_0_2 = 0.1f, + .expected_cell_1_5 = -0.25f, + .rotation = M_PI / 2.0}}), [](const testing::TestParamInfo< LandmarksWorld3dToMatrixCalculatorTest::ParamType>& info) { return info.param.test_name; diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc index e0d1473c2..333edb6fb 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc @@ -17,6 +17,7 @@ limitations under the License. #include #include +#include #include #include "absl/memory/memory.h" @@ -27,6 +28,7 @@ limitations under the License. #include "mediapipe/framework/formats/classification.pb.h" #include "mediapipe/framework/formats/image.h" #include "mediapipe/framework/formats/landmark.pb.h" +#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/packet.h" #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/components/image_preprocessing.h" @@ -62,6 +64,8 @@ constexpr char kHandGestureSubgraphTypeName[] = constexpr char kImageTag[] = "IMAGE"; constexpr char kImageInStreamName[] = "image_in"; constexpr char kImageOutStreamName[] = "image_out"; +constexpr char kNormRectTag[] = "NORM_RECT"; +constexpr char kNormRectStreamName[] = "norm_rect_in"; constexpr char kHandGesturesTag[] = "HAND_GESTURES"; constexpr char kHandGesturesStreamName[] = "hand_gestures"; constexpr char kHandednessTag[] = "HANDEDNESS"; @@ -72,6 +76,31 @@ constexpr char kHandWorldLandmarksTag[] = "WORLD_LANDMARKS"; constexpr char kHandWorldLandmarksStreamName[] = "world_landmarks"; constexpr int kMicroSecondsPerMilliSecond = 1000; +// Returns a NormalizedRect filling the whole image. If input is present, its +// rotation is set in the returned NormalizedRect and a check is performed to +// make sure no region-of-interest was provided. Otherwise, rotation is set to +// 0. +absl::StatusOr FillNormalizedRect( + std::optional normalized_rect) { + NormalizedRect result; + if (normalized_rect.has_value()) { + result = *normalized_rect; + } + bool has_coordinates = result.has_x_center() || result.has_y_center() || + result.has_width() || result.has_height(); + if (has_coordinates) { + return CreateStatusWithPayload( + absl::StatusCode::kInvalidArgument, + "GestureRecognizer does not support region-of-interest.", + MediaPipeTasksStatus::kInvalidArgumentError); + } + result.set_x_center(0.5); + result.set_y_center(0.5); + result.set_width(1); + result.set_height(1); + return result; +} + // Creates a MediaPipe graph config that contains a subgraph node of // "mediapipe.tasks.vision.GestureRecognizerGraph". If the task is running // in the live stream mode, a "FlowLimiterCalculator" will be added to limit the @@ -83,6 +112,7 @@ CalculatorGraphConfig CreateGraphConfig( auto& subgraph = graph.AddNode(kHandGestureSubgraphTypeName); subgraph.GetOptions().Swap(options.get()); graph.In(kImageTag).SetName(kImageInStreamName); + graph.In(kNormRectTag).SetName(kNormRectStreamName); subgraph.Out(kHandGesturesTag).SetName(kHandGesturesStreamName) >> graph.Out(kHandGesturesTag); subgraph.Out(kHandednessTag).SetName(kHandednessStreamName) >> @@ -93,10 +123,11 @@ CalculatorGraphConfig CreateGraphConfig( graph.Out(kHandWorldLandmarksTag); subgraph.Out(kImageTag).SetName(kImageOutStreamName) >> graph.Out(kImageTag); if (enable_flow_limiting) { - return tasks::core::AddFlowLimiterCalculator(graph, subgraph, {kImageTag}, - kHandGesturesTag); + return tasks::core::AddFlowLimiterCalculator( + graph, subgraph, {kImageTag, kNormRectTag}, kHandGesturesTag); } graph.In(kImageTag) >> subgraph.In(kImageTag); + graph.In(kNormRectTag) >> subgraph.In(kNormRectTag); return graph.GetConfig(); } @@ -216,16 +247,22 @@ absl::StatusOr> GestureRecognizer::Create( } absl::StatusOr GestureRecognizer::Recognize( - mediapipe::Image image) { + mediapipe::Image image, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, "GPU input images are currently not supported.", MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - ASSIGN_OR_RETURN(auto output_packets, - ProcessImageData({{kImageInStreamName, - MakePacket(std::move(image))}})); + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + FillNormalizedRect(image_processing_options)); + ASSIGN_OR_RETURN( + auto output_packets, + ProcessImageData( + {{kImageInStreamName, MakePacket(std::move(image))}, + {kNormRectStreamName, + MakePacket(std::move(norm_rect))}})); if (output_packets[kHandGesturesStreamName].IsEmpty()) { return {{{}, {}, {}, {}}}; } @@ -245,18 +282,24 @@ absl::StatusOr GestureRecognizer::Recognize( } absl::StatusOr GestureRecognizer::RecognizeForVideo( - mediapipe::Image image, int64 timestamp_ms) { + mediapipe::Image image, int64 timestamp_ms, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + FillNormalizedRect(image_processing_options)); ASSIGN_OR_RETURN( auto output_packets, ProcessVideoData( {{kImageInStreamName, MakePacket(std::move(image)) + .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}, + {kNormRectStreamName, + MakePacket(std::move(norm_rect)) .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}})); if (output_packets[kHandGesturesStreamName].IsEmpty()) { return {{{}, {}, {}, {}}}; @@ -276,17 +319,23 @@ absl::StatusOr GestureRecognizer::RecognizeForVideo( }; } -absl::Status GestureRecognizer::RecognizeAsync(mediapipe::Image image, - int64 timestamp_ms) { +absl::Status GestureRecognizer::RecognizeAsync( + mediapipe::Image image, int64 timestamp_ms, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + FillNormalizedRect(image_processing_options)); return SendLiveStreamData( {{kImageInStreamName, MakePacket(std::move(image)) + .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}, + {kNormRectStreamName, + MakePacket(std::move(norm_rect)) .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}}); } diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h index 53b824e25..892b3c16a 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h @@ -17,11 +17,13 @@ limitations under the License. #define MEDIAPIPE_TASKS_CC_VISION_GESTURE_RECOGNIZRER_GESTURE_RECOGNIZER_H_ #include +#include #include "absl/status/statusor.h" #include "mediapipe/framework/formats/classification.pb.h" #include "mediapipe/framework/formats/image.h" #include "mediapipe/framework/formats/landmark.pb.h" +#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/tasks/cc/components/containers/gesture_recognition_result.h" #include "mediapipe/tasks/cc/core/base_options.h" #include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h" @@ -93,6 +95,13 @@ struct GestureRecognizerOptions { // Inputs: // Image // - The image that gesture recognition runs on. +// std::optional +// - If provided, can be used to specify the rotation to apply to the image +// before performing gesture recognition, by setting its 'rotation' field +// in radians (e.g. 'M_PI / 2' for a 90° anti-clockwise rotation). Note +// that specifying a region-of-interest using the 'x_center', 'y_center', +// 'width' and 'height' fields is NOT supported and will result in an +// invalid argument error being returned. // Outputs: // GestureRecognitionResult // - The hand gesture recognition results. @@ -122,12 +131,23 @@ class GestureRecognizer : tasks::vision::core::BaseVisionTaskApi { // // image - mediapipe::Image // Image to perform hand gesture recognition on. + // imageProcessingOptions - std::optional + // If provided, can be used to specify the rotation to apply to the image + // before performing classification, by setting its 'rotation' field in + // radians (e.g. 'M_PI / 2' for a 90° anti-clockwise rotation). Note that + // specifying a region-of-interest using the 'x_center', 'y_center', 'width' + // and 'height' fields is NOT supported and will result in an invalid + // argument error being returned. // // The image can be of any size with format RGB or RGBA. // TODO: Describes how the input image will be preprocessed // after the yuv support is implemented. + // TODO: use an ImageProcessingOptions struct instead of + // NormalizedRect. absl::StatusOr Recognize( - Image image); + Image image, + std::optional image_processing_options = + std::nullopt); // Performs gesture recognition on the provided video frame. // Only use this method when the GestureRecognizer is created with the video @@ -137,7 +157,9 @@ class GestureRecognizer : tasks::vision::core::BaseVisionTaskApi { // provide the video frame's timestamp (in milliseconds). The input timestamps // must be monotonically increasing. absl::StatusOr - RecognizeForVideo(Image image, int64 timestamp_ms); + RecognizeForVideo(Image image, int64 timestamp_ms, + std::optional + image_processing_options = std::nullopt); // Sends live image data to perform gesture recognition, and the results will // be available via the "result_callback" provided in the @@ -157,7 +179,9 @@ class GestureRecognizer : tasks::vision::core::BaseVisionTaskApi { // longer be valid when the callback returns. To access the image data // outside of the callback, callers need to make a copy of the image. // - The input timestamp in milliseconds. - absl::Status RecognizeAsync(Image image, int64 timestamp_ms); + absl::Status RecognizeAsync(Image image, int64 timestamp_ms, + std::optional + image_processing_options = std::nullopt); // Shuts down the GestureRecognizer when all works are done. absl::Status Close() { return runner_->Close(); } diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer_graph.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer_graph.cc index b4f2af4d8..e02eadde8 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer_graph.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer_graph.cc @@ -24,6 +24,7 @@ limitations under the License. #include "mediapipe/framework/formats/classification.pb.h" #include "mediapipe/framework/formats/image.h" #include "mediapipe/framework/formats/landmark.pb.h" +#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/core/model_task_graph.h" #include "mediapipe/tasks/cc/core/utils.h" @@ -53,6 +54,7 @@ using ::mediapipe::tasks::vision::hand_landmarker::proto:: HandLandmarkerGraphOptions; constexpr char kImageTag[] = "IMAGE"; +constexpr char kNormRectTag[] = "NORM_RECT"; constexpr char kLandmarksTag[] = "LANDMARKS"; constexpr char kWorldLandmarksTag[] = "WORLD_LANDMARKS"; constexpr char kHandednessTag[] = "HANDEDNESS"; @@ -76,6 +78,9 @@ struct GestureRecognizerOutputs { // Inputs: // IMAGE - Image // Image to perform hand gesture recognition on. +// NORM_RECT - NormalizedRect +// Describes image rotation and region of image to perform landmarks +// detection on. // // Outputs: // HAND_GESTURES - std::vector @@ -93,13 +98,15 @@ struct GestureRecognizerOutputs { // IMAGE - mediapipe::Image // The image that gesture recognizer runs on and has the pixel data stored // on the target storage (CPU vs GPU). -// +// All returned coordinates are in the unrotated and uncropped input image +// coordinates system. // // Example: // node { // calculator: // "mediapipe.tasks.vision.gesture_recognizer.GestureRecognizerGraph" // input_stream: "IMAGE:image_in" +// input_stream: "NORM_RECT:norm_rect" // output_stream: "HAND_GESTURES:hand_gestures" // output_stream: "LANDMARKS:hand_landmarks" // output_stream: "WORLD_LANDMARKS:world_hand_landmarks" @@ -132,7 +139,8 @@ class GestureRecognizerGraph : public core::ModelTaskGraph { ASSIGN_OR_RETURN(auto hand_gesture_recognition_output, BuildGestureRecognizerGraph( *sc->MutableOptions(), - graph[Input(kImageTag)], graph)); + graph[Input(kImageTag)], + graph[Input(kNormRectTag)], graph)); hand_gesture_recognition_output.gesture >> graph[Output>(kHandGesturesTag)]; hand_gesture_recognition_output.handedness >> @@ -148,7 +156,7 @@ class GestureRecognizerGraph : public core::ModelTaskGraph { private: absl::StatusOr BuildGestureRecognizerGraph( GestureRecognizerGraphOptions& graph_options, Source image_in, - Graph& graph) { + Source norm_rect_in, Graph& graph) { auto& image_property = graph.AddNode("ImagePropertiesCalculator"); image_in >> image_property.In("IMAGE"); auto image_size = image_property.Out("SIZE"); @@ -162,6 +170,7 @@ class GestureRecognizerGraph : public core::ModelTaskGraph { graph_options.mutable_hand_landmarker_graph_options()); image_in >> hand_landmarker_graph.In(kImageTag); + norm_rect_in >> hand_landmarker_graph.In(kNormRectTag); auto hand_landmarks = hand_landmarker_graph[Output>( kLandmarksTag)]; @@ -187,6 +196,7 @@ class GestureRecognizerGraph : public core::ModelTaskGraph { hand_world_landmarks >> hand_gesture_subgraph.In(kWorldLandmarksTag); handedness >> hand_gesture_subgraph.In(kHandednessTag); image_size >> hand_gesture_subgraph.In(kImageSizeTag); + norm_rect_in >> hand_gesture_subgraph.In(kNormRectTag); hand_landmarks_id >> hand_gesture_subgraph.In(kHandTrackingIdsTag); auto hand_gestures = hand_gesture_subgraph[Output>( diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc index 8d7e0bc07..4bbe94974 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc @@ -25,6 +25,7 @@ limitations under the License. #include "mediapipe/framework/formats/classification.pb.h" #include "mediapipe/framework/formats/landmark.pb.h" #include "mediapipe/framework/formats/matrix.h" +#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/formats/tensor.h" #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.h" @@ -57,6 +58,7 @@ constexpr char kHandednessTag[] = "HANDEDNESS"; constexpr char kLandmarksTag[] = "LANDMARKS"; constexpr char kWorldLandmarksTag[] = "WORLD_LANDMARKS"; constexpr char kImageSizeTag[] = "IMAGE_SIZE"; +constexpr char kNormRectTag[] = "NORM_RECT"; constexpr char kHandTrackingIdsTag[] = "HAND_TRACKING_IDS"; constexpr char kHandGesturesTag[] = "HAND_GESTURES"; constexpr char kLandmarksMatrixTag[] = "LANDMARKS_MATRIX"; @@ -92,6 +94,9 @@ Source> ConvertMatrixToTensor(Source matrix, // Detected hand landmarks in world coordinates. // IMAGE_SIZE - std::pair // The size of image from which the landmarks detected from. +// NORM_RECT - NormalizedRect +// NormalizedRect whose 'rotation' field is used to rotate the +// landmarks before processing them. // // Outputs: // HAND_GESTURES - ClassificationList @@ -106,6 +111,7 @@ Source> ConvertMatrixToTensor(Source matrix, // input_stream: "LANDMARKS:landmarks" // input_stream: "WORLD_LANDMARKS:world_landmarks" // input_stream: "IMAGE_SIZE:image_size" +// input_stream: "NORM_RECT:norm_rect" // output_stream: "HAND_GESTURES:hand_gestures" // options { // [mediapipe.tasks.vision.gesture_recognizer.proto.HandGestureRecognizerGraphOptions.ext] @@ -133,7 +139,8 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { graph[Input(kHandednessTag)], graph[Input(kLandmarksTag)], graph[Input(kWorldLandmarksTag)], - graph[Input>(kImageSizeTag)], graph)); + graph[Input>(kImageSizeTag)], + graph[Input(kNormRectTag)], graph)); hand_gestures >> graph[Output(kHandGesturesTag)]; return graph.GetConfig(); } @@ -145,7 +152,8 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { Source handedness, Source hand_landmarks, Source hand_world_landmarks, - Source> image_size, Graph& graph) { + Source> image_size, Source norm_rect, + Graph& graph) { // Converts the ClassificationList to a matrix. auto& handedness_to_matrix = graph.AddNode("HandednessToMatrixCalculator"); handedness >> handedness_to_matrix.In(kHandednessTag); @@ -166,6 +174,7 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { landmarks_options; hand_landmarks >> hand_landmarks_to_matrix.In(kLandmarksTag); image_size >> hand_landmarks_to_matrix.In(kImageSizeTag); + norm_rect >> hand_landmarks_to_matrix.In(kNormRectTag); auto hand_landmarks_matrix = hand_landmarks_to_matrix[Output(kLandmarksMatrixTag)]; @@ -181,6 +190,7 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { hand_world_landmarks >> hand_world_landmarks_to_matrix.In(kWorldLandmarksTag); image_size >> hand_world_landmarks_to_matrix.In(kImageSizeTag); + norm_rect >> hand_world_landmarks_to_matrix.In(kNormRectTag); auto hand_world_landmarks_matrix = hand_world_landmarks_to_matrix[Output(kLandmarksMatrixTag)]; @@ -239,6 +249,9 @@ REGISTER_MEDIAPIPE_GRAPH( // A vector hand landmarks in world coordinates. // IMAGE_SIZE - std::pair // The size of image from which the landmarks detected from. +// NORM_RECT - NormalizedRect +// NormalizedRect whose 'rotation' field is used to rotate the +// landmarks before processing them. // HAND_TRACKING_IDS - std::vector // A vector of the tracking ids of the hands. The tracking id is the vector // index corresponding to the same hand if the graph runs multiple times. @@ -257,6 +270,7 @@ REGISTER_MEDIAPIPE_GRAPH( // input_stream: "LANDMARKS:landmarks" // input_stream: "WORLD_LANDMARKS:world_landmarks" // input_stream: "IMAGE_SIZE:image_size" +// input_stream: "NORM_RECT:norm_rect" // input_stream: "HAND_TRACKING_IDS:hand_tracking_ids" // output_stream: "HAND_GESTURES:hand_gestures" // options { @@ -283,6 +297,7 @@ class MultipleHandGestureRecognizerGraph : public core::ModelTaskGraph { graph[Input>(kLandmarksTag)], graph[Input>(kWorldLandmarksTag)], graph[Input>(kImageSizeTag)], + graph[Input(kNormRectTag)], graph[Input>(kHandTrackingIdsTag)], graph)); multi_hand_gestures >> graph[Output>(kHandGesturesTag)]; @@ -296,18 +311,20 @@ class MultipleHandGestureRecognizerGraph : public core::ModelTaskGraph { Source> multi_handedness, Source> multi_hand_landmarks, Source> multi_hand_world_landmarks, - Source> image_size, + Source> image_size, Source norm_rect, Source> multi_hand_tracking_ids, Graph& graph) { auto& begin_loop_int = graph.AddNode("BeginLoopIntCalculator"); image_size >> begin_loop_int.In(kCloneTag)[0]; - multi_handedness >> begin_loop_int.In(kCloneTag)[1]; - multi_hand_landmarks >> begin_loop_int.In(kCloneTag)[2]; - multi_hand_world_landmarks >> begin_loop_int.In(kCloneTag)[3]; + norm_rect >> begin_loop_int.In(kCloneTag)[1]; + multi_handedness >> begin_loop_int.In(kCloneTag)[2]; + multi_hand_landmarks >> begin_loop_int.In(kCloneTag)[3]; + multi_hand_world_landmarks >> begin_loop_int.In(kCloneTag)[4]; multi_hand_tracking_ids >> begin_loop_int.In(kIterableTag); auto image_size_clone = begin_loop_int.Out(kCloneTag)[0]; - auto multi_handedness_clone = begin_loop_int.Out(kCloneTag)[1]; - auto multi_hand_landmarks_clone = begin_loop_int.Out(kCloneTag)[2]; - auto multi_hand_world_landmarks_clone = begin_loop_int.Out(kCloneTag)[3]; + auto norm_rect_clone = begin_loop_int.Out(kCloneTag)[1]; + auto multi_handedness_clone = begin_loop_int.Out(kCloneTag)[2]; + auto multi_hand_landmarks_clone = begin_loop_int.Out(kCloneTag)[3]; + auto multi_hand_world_landmarks_clone = begin_loop_int.Out(kCloneTag)[4]; auto hand_tracking_id = begin_loop_int.Out(kItemTag); auto batch_end = begin_loop_int.Out(kBatchEndTag); @@ -341,6 +358,7 @@ class MultipleHandGestureRecognizerGraph : public core::ModelTaskGraph { hand_world_landmarks >> hand_gesture_recognizer_graph.In(kWorldLandmarksTag); image_size_clone >> hand_gesture_recognizer_graph.In(kImageSizeTag); + norm_rect_clone >> hand_gesture_recognizer_graph.In(kNormRectTag); auto hand_gestures = hand_gesture_recognizer_graph.Out(kHandGesturesTag); auto& end_loop_classification_lists = diff --git a/mediapipe/tasks/cc/vision/hand_detector/BUILD b/mediapipe/tasks/cc/vision/hand_detector/BUILD index 433a30471..71cef6270 100644 --- a/mediapipe/tasks/cc/vision/hand_detector/BUILD +++ b/mediapipe/tasks/cc/vision/hand_detector/BUILD @@ -32,7 +32,7 @@ cc_library( "//mediapipe/calculators/tflite:ssd_anchors_calculator_cc_proto", "//mediapipe/calculators/util:detection_label_id_to_text_calculator", "//mediapipe/calculators/util:detection_label_id_to_text_calculator_cc_proto", - "//mediapipe/calculators/util:detection_letterbox_removal_calculator", + "//mediapipe/calculators/util:detection_projection_calculator", "//mediapipe/calculators/util:detections_to_rects_calculator", "//mediapipe/calculators/util:detections_to_rects_calculator_cc_proto", "//mediapipe/calculators/util:non_max_suppression_calculator", diff --git a/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph.cc b/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph.cc index 8573d718f..e876d7d09 100644 --- a/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph.cc +++ b/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph.cc @@ -58,6 +58,7 @@ using ::mediapipe::tasks::vision::hand_detector::proto:: HandDetectorGraphOptions; constexpr char kImageTag[] = "IMAGE"; +constexpr char kNormRectTag[] = "NORM_RECT"; constexpr char kPalmDetectionsTag[] = "PALM_DETECTIONS"; constexpr char kHandRectsTag[] = "HAND_RECTS"; constexpr char kPalmRectsTag[] = "PALM_RECTS"; @@ -148,6 +149,9 @@ void ConfigureRectTransformationCalculator( // Inputs: // IMAGE - Image // Image to perform detection on. +// NORM_RECT - NormalizedRect +// Describes image rotation and region of image to perform detection +// on. // // Outputs: // PALM_DETECTIONS - std::vector @@ -159,11 +163,14 @@ void ConfigureRectTransformationCalculator( // IMAGE - Image // The input image that the hand detector runs on and has the pixel data // stored on the target storage (CPU vs GPU). +// All returned coordinates are in the unrotated and uncropped input image +// coordinates system. // // Example: // node { // calculator: "mediapipe.tasks.vision.hand_detector.HandDetectorGraph" // input_stream: "IMAGE:image" +// input_stream: "NORM_RECT:norm_rect" // output_stream: "PALM_DETECTIONS:palm_detections" // output_stream: "HAND_RECTS:hand_rects_from_palm_detections" // output_stream: "PALM_RECTS:palm_rects" @@ -189,11 +196,11 @@ class HandDetectorGraph : public core::ModelTaskGraph { ASSIGN_OR_RETURN(const auto* model_resources, CreateModelResources(sc)); Graph graph; - ASSIGN_OR_RETURN( - auto hand_detection_outs, - BuildHandDetectionSubgraph(sc->Options(), - *model_resources, - graph[Input(kImageTag)], graph)); + ASSIGN_OR_RETURN(auto hand_detection_outs, + BuildHandDetectionSubgraph( + sc->Options(), + *model_resources, graph[Input(kImageTag)], + graph[Input(kNormRectTag)], graph)); hand_detection_outs.palm_detections >> graph[Output>(kPalmDetectionsTag)]; hand_detection_outs.hand_rects >> @@ -216,7 +223,7 @@ class HandDetectorGraph : public core::ModelTaskGraph { absl::StatusOr BuildHandDetectionSubgraph( const HandDetectorGraphOptions& subgraph_options, const core::ModelResources& model_resources, Source image_in, - Graph& graph) { + Source norm_rect_in, Graph& graph) { // Add image preprocessing subgraph. The model expects aspect ratio // unchanged. auto& preprocessing = @@ -233,8 +240,9 @@ class HandDetectorGraph : public core::ModelTaskGraph { &preprocessing .GetOptions())); image_in >> preprocessing.In("IMAGE"); + norm_rect_in >> preprocessing.In("NORM_RECT"); auto preprocessed_tensors = preprocessing.Out("TENSORS"); - auto letterbox_padding = preprocessing.Out("LETTERBOX_PADDING"); + auto matrix = preprocessing.Out("MATRIX"); auto image_size = preprocessing.Out("IMAGE_SIZE"); // Adds SSD palm detection model. @@ -278,17 +286,12 @@ class HandDetectorGraph : public core::ModelTaskGraph { nms_detections >> detection_label_id_to_text.In(""); auto detections_with_text = detection_label_id_to_text.Out(""); - // Adjusts detection locations (already normalized to [0.f, 1.f]) on the - // letterboxed image (after image transformation with the FIT scale mode) to - // the corresponding locations on the same image with the letterbox removed - // (the input image to the graph before image transformation). - auto& detection_letterbox_removal = - graph.AddNode("DetectionLetterboxRemovalCalculator"); - detections_with_text >> detection_letterbox_removal.In("DETECTIONS"); - letterbox_padding >> detection_letterbox_removal.In("LETTERBOX_PADDING"); + // Projects detections back into the input image coordinates system. + auto& detection_projection = graph.AddNode("DetectionProjectionCalculator"); + detections_with_text >> detection_projection.In("DETECTIONS"); + matrix >> detection_projection.In("PROJECTION_MATRIX"); auto palm_detections = - detection_letterbox_removal[Output>( - "DETECTIONS")]; + detection_projection[Output>("DETECTIONS")]; // Converts each palm detection into a rectangle (normalized by image size) // that encloses the palm and is rotated such that the line connecting diff --git a/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph_test.cc b/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph_test.cc index 11cfc3026..cbbc0e193 100644 --- a/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph_test.cc +++ b/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph_test.cc @@ -13,6 +13,7 @@ See the License for the specific language governing permissions and limitations under the License. ==============================================================================*/ +#include #include #include #include @@ -75,13 +76,18 @@ using ::testing::proto::Partially; constexpr char kTestDataDirectory[] = "/mediapipe/tasks/testdata/vision/"; constexpr char kPalmDetectionModel[] = "palm_detection_full.tflite"; constexpr char kTestRightHandsImage[] = "right_hands.jpg"; +constexpr char kTestRightHandsRotatedImage[] = "right_hands_rotated.jpg"; constexpr char kTestModelResourcesTag[] = "test_model_resources"; constexpr char kOneHandResultFile[] = "hand_detector_result_one_hand.pbtxt"; +constexpr char kOneHandRotatedResultFile[] = + "hand_detector_result_one_hand_rotated.pbtxt"; constexpr char kTwoHandsResultFile[] = "hand_detector_result_two_hands.pbtxt"; constexpr char kImageTag[] = "IMAGE"; constexpr char kImageName[] = "image"; +constexpr char kNormRectTag[] = "NORM_RECT"; +constexpr char kNormRectName[] = "norm_rect"; constexpr char kPalmDetectionsTag[] = "PALM_DETECTIONS"; constexpr char kPalmDetectionsName[] = "palm_detections"; constexpr char kHandRectsTag[] = "HAND_RECTS"; @@ -117,6 +123,8 @@ absl::StatusOr> CreateTaskRunner( graph[Input(kImageTag)].SetName(kImageName) >> hand_detection.In(kImageTag); + graph[Input(kNormRectTag)].SetName(kNormRectName) >> + hand_detection.In(kNormRectTag); hand_detection.Out(kPalmDetectionsTag).SetName(kPalmDetectionsName) >> graph[Output>(kPalmDetectionsTag)]; @@ -142,6 +150,9 @@ struct TestParams { std::string hand_detection_model_name; // The filename of test image. std::string test_image_name; + // The rotation to apply to the test image before processing, in radians + // counter-clockwise. + float rotation; // The number of maximum detected hands. int num_hands; // The expected hand detector result. @@ -154,14 +165,22 @@ TEST_P(HandDetectionTest, DetectTwoHands) { MP_ASSERT_OK_AND_ASSIGN( Image image, DecodeImageFromFile(JoinPath("./", kTestDataDirectory, GetParam().test_image_name))); + NormalizedRect input_norm_rect; + input_norm_rect.set_rotation(GetParam().rotation); + input_norm_rect.set_x_center(0.5); + input_norm_rect.set_y_center(0.5); + input_norm_rect.set_width(1.0); + input_norm_rect.set_height(1.0); MP_ASSERT_OK_AND_ASSIGN( auto model_resources, CreateModelResourcesForModel(GetParam().hand_detection_model_name)); MP_ASSERT_OK_AND_ASSIGN( auto task_runner, CreateTaskRunner(*model_resources, kPalmDetectionModel, GetParam().num_hands)); - auto output_packets = - task_runner->Process({{kImageName, MakePacket(std::move(image))}}); + auto output_packets = task_runner->Process( + {{kImageName, MakePacket(std::move(image))}, + {kNormRectName, + MakePacket(std::move(input_norm_rect))}}); MP_ASSERT_OK(output_packets); const std::vector& palm_detections = (*output_packets)[kPalmDetectionsName].Get>(); @@ -188,15 +207,24 @@ INSTANTIATE_TEST_SUITE_P( Values(TestParams{.test_name = "DetectOneHand", .hand_detection_model_name = kPalmDetectionModel, .test_image_name = kTestRightHandsImage, + .rotation = 0, .num_hands = 1, .expected_result = GetExpectedHandDetectorResult(kOneHandResultFile)}, TestParams{.test_name = "DetectTwoHands", .hand_detection_model_name = kPalmDetectionModel, .test_image_name = kTestRightHandsImage, + .rotation = 0, .num_hands = 2, .expected_result = - GetExpectedHandDetectorResult(kTwoHandsResultFile)}), + GetExpectedHandDetectorResult(kTwoHandsResultFile)}, + TestParams{.test_name = "DetectOneHandWithRotation", + .hand_detection_model_name = kPalmDetectionModel, + .test_image_name = kTestRightHandsRotatedImage, + .rotation = M_PI / 2.0f, + .num_hands = 1, + .expected_result = GetExpectedHandDetectorResult( + kOneHandRotatedResultFile)}), [](const TestParamInfo& info) { return info.param.test_name; }); diff --git a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph.cc b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph.cc index 7e199348c..3fbe38c1c 100644 --- a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph.cc +++ b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph.cc @@ -64,6 +64,7 @@ using ::mediapipe::tasks::vision::hand_landmarker::proto:: HandLandmarksDetectorGraphOptions; constexpr char kImageTag[] = "IMAGE"; +constexpr char kNormRectTag[] = "NORM_RECT"; constexpr char kLandmarksTag[] = "LANDMARKS"; constexpr char kWorldLandmarksTag[] = "WORLD_LANDMARKS"; constexpr char kHandRectNextFrameTag[] = "HAND_RECT_NEXT_FRAME"; @@ -122,6 +123,9 @@ absl::Status SetSubTaskBaseOptions(const ModelAssetBundleResources& resources, // Inputs: // IMAGE - Image // Image to perform hand landmarks detection on. +// NORM_RECT - NormalizedRect +// Describes image rotation and region of image to perform landmarks +// detection on. // // Outputs: // LANDMARKS: - std::vector @@ -140,11 +144,14 @@ absl::Status SetSubTaskBaseOptions(const ModelAssetBundleResources& resources, // IMAGE - Image // The input image that the hand landmarker runs on and has the pixel data // stored on the target storage (CPU vs GPU). +// All returned coordinates are in the unrotated and uncropped input image +// coordinates system. // // Example: // node { // calculator: "mediapipe.tasks.vision.hand_landmarker.HandLandmarkerGraph" // input_stream: "IMAGE:image_in" +// input_stream: "NORM_RECT:norm_rect" // output_stream: "LANDMARKS:hand_landmarks" // output_stream: "WORLD_LANDMARKS:world_hand_landmarks" // output_stream: "HAND_RECT_NEXT_FRAME:hand_rect_next_frame" @@ -198,10 +205,11 @@ class HandLandmarkerGraph : public core::ModelTaskGraph { !sc->Service(::mediapipe::tasks::core::kModelResourcesCacheService) .IsAvailable())); } - ASSIGN_OR_RETURN( - auto hand_landmarker_outputs, - BuildHandLandmarkerGraph(sc->Options(), - graph[Input(kImageTag)], graph)); + ASSIGN_OR_RETURN(auto hand_landmarker_outputs, + BuildHandLandmarkerGraph( + sc->Options(), + graph[Input(kImageTag)], + graph[Input(kNormRectTag)], graph)); hand_landmarker_outputs.landmark_lists >> graph[Output>(kLandmarksTag)]; hand_landmarker_outputs.world_landmark_lists >> @@ -240,7 +248,7 @@ class HandLandmarkerGraph : public core::ModelTaskGraph { // graph: the mediapipe graph instance to be updated. absl::StatusOr BuildHandLandmarkerGraph( const HandLandmarkerGraphOptions& tasks_options, Source image_in, - Graph& graph) { + Source norm_rect_in, Graph& graph) { const int max_num_hands = tasks_options.hand_detector_graph_options().num_hands(); @@ -258,12 +266,15 @@ class HandLandmarkerGraph : public core::ModelTaskGraph { auto image_for_hand_detector = DisallowIf(image_in, has_enough_hands, graph); + auto norm_rect_in_for_hand_detector = + DisallowIf(norm_rect_in, has_enough_hands, graph); auto& hand_detector = graph.AddNode("mediapipe.tasks.vision.hand_detector.HandDetectorGraph"); hand_detector.GetOptions().CopyFrom( tasks_options.hand_detector_graph_options()); image_for_hand_detector >> hand_detector.In("IMAGE"); + norm_rect_in_for_hand_detector >> hand_detector.In("NORM_RECT"); auto hand_rects_from_hand_detector = hand_detector.Out("HAND_RECTS"); auto& hand_association = graph.AddNode("HandAssociationCalculator"); diff --git a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph_test.cc b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph_test.cc index 604f37d53..08beb1a1b 100644 --- a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph_test.cc +++ b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph_test.cc @@ -13,10 +13,12 @@ See the License for the specific language governing permissions and limitations under the License. ==============================================================================*/ +#include #include #include #include #include +#include #include "absl/flags/flag.h" #include "absl/status/statusor.h" @@ -67,9 +69,12 @@ using ::testing::proto::Partially; constexpr char kTestDataDirectory[] = "/mediapipe/tasks/testdata/vision/"; constexpr char kHandLandmarkerModelBundle[] = "hand_landmark.task"; constexpr char kLeftHandsImage[] = "left_hands.jpg"; +constexpr char kLeftHandsRotatedImage[] = "left_hands_rotated.jpg"; constexpr char kImageTag[] = "IMAGE"; constexpr char kImageName[] = "image_in"; +constexpr char kNormRectTag[] = "NORM_RECT"; +constexpr char kNormRectName[] = "norm_rect_in"; constexpr char kLandmarksTag[] = "LANDMARKS"; constexpr char kLandmarksName[] = "landmarks"; constexpr char kWorldLandmarksTag[] = "WORLD_LANDMARKS"; @@ -84,6 +89,11 @@ constexpr char kExpectedLeftUpHandLandmarksFilename[] = "expected_left_up_hand_landmarks.prototxt"; constexpr char kExpectedLeftDownHandLandmarksFilename[] = "expected_left_down_hand_landmarks.prototxt"; +// Same but for the rotated image. +constexpr char kExpectedLeftUpHandRotatedLandmarksFilename[] = + "expected_left_up_hand_rotated_landmarks.prototxt"; +constexpr char kExpectedLeftDownHandRotatedLandmarksFilename[] = + "expected_left_down_hand_rotated_landmarks.prototxt"; constexpr float kFullModelFractionDiff = 0.03; // percentage constexpr float kAbsMargin = 0.03; @@ -111,6 +121,8 @@ absl::StatusOr> CreateTaskRunner() { graph[Input(kImageTag)].SetName(kImageName) >> hand_landmarker_graph.In(kImageTag); + graph[Input(kNormRectTag)].SetName(kNormRectName) >> + hand_landmarker_graph.In(kNormRectTag); hand_landmarker_graph.Out(kLandmarksTag).SetName(kLandmarksName) >> graph[Output>(kLandmarksTag)]; hand_landmarker_graph.Out(kWorldLandmarksTag).SetName(kWorldLandmarksName) >> @@ -130,9 +142,16 @@ TEST_F(HandLandmarkerTest, Succeeds) { MP_ASSERT_OK_AND_ASSIGN( Image image, DecodeImageFromFile(JoinPath("./", kTestDataDirectory, kLeftHandsImage))); + NormalizedRect input_norm_rect; + input_norm_rect.set_x_center(0.5); + input_norm_rect.set_y_center(0.5); + input_norm_rect.set_width(1.0); + input_norm_rect.set_height(1.0); MP_ASSERT_OK_AND_ASSIGN(auto task_runner, CreateTaskRunner()); - auto output_packets = - task_runner->Process({{kImageName, MakePacket(std::move(image))}}); + auto output_packets = task_runner->Process( + {{kImageName, MakePacket(std::move(image))}, + {kNormRectName, + MakePacket(std::move(input_norm_rect))}}); const auto& landmarks = (*output_packets)[kLandmarksName] .Get>(); ASSERT_EQ(landmarks.size(), kMaxNumHands); @@ -150,6 +169,38 @@ TEST_F(HandLandmarkerTest, Succeeds) { /*fraction=*/kFullModelFractionDiff)); } +TEST_F(HandLandmarkerTest, SucceedsWithRotation) { + MP_ASSERT_OK_AND_ASSIGN( + Image image, DecodeImageFromFile(JoinPath("./", kTestDataDirectory, + kLeftHandsRotatedImage))); + NormalizedRect input_norm_rect; + input_norm_rect.set_x_center(0.5); + input_norm_rect.set_y_center(0.5); + input_norm_rect.set_width(1.0); + input_norm_rect.set_height(1.0); + input_norm_rect.set_rotation(M_PI / 2.0); + MP_ASSERT_OK_AND_ASSIGN(auto task_runner, CreateTaskRunner()); + auto output_packets = task_runner->Process( + {{kImageName, MakePacket(std::move(image))}, + {kNormRectName, + MakePacket(std::move(input_norm_rect))}}); + const auto& landmarks = (*output_packets)[kLandmarksName] + .Get>(); + ASSERT_EQ(landmarks.size(), kMaxNumHands); + std::vector expected_landmarks = { + GetExpectedLandmarkList(kExpectedLeftUpHandRotatedLandmarksFilename), + GetExpectedLandmarkList(kExpectedLeftDownHandRotatedLandmarksFilename)}; + + EXPECT_THAT(landmarks[0], + Approximately(Partially(EqualsProto(expected_landmarks[0])), + /*margin=*/kAbsMargin, + /*fraction=*/kFullModelFractionDiff)); + EXPECT_THAT(landmarks[1], + Approximately(Partially(EqualsProto(expected_landmarks[1])), + /*margin=*/kAbsMargin, + /*fraction=*/kFullModelFractionDiff)); +} + } // namespace } // namespace hand_landmarker diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java index 128f6eab3..32473b299 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java @@ -15,6 +15,7 @@ package com.google.mediapipe.tasks.vision.gesturerecognizer; import android.content.Context; +import android.graphics.RectF; import android.os.ParcelFileDescriptor; import com.google.auto.value.AutoValue; import com.google.mediapipe.formats.proto.LandmarkProto.LandmarkList; @@ -71,8 +72,10 @@ import java.util.Optional; public final class GestureRecognizer extends BaseVisionTaskApi { private static final String TAG = GestureRecognizer.class.getSimpleName(); private static final String IMAGE_IN_STREAM_NAME = "image_in"; + private static final String NORM_RECT_IN_STREAM_NAME = "norm_rect_in"; private static final List INPUT_STREAMS = - Collections.unmodifiableList(Arrays.asList("IMAGE:" + IMAGE_IN_STREAM_NAME)); + Collections.unmodifiableList( + Arrays.asList("IMAGE:" + IMAGE_IN_STREAM_NAME, "NORM_RECT:" + NORM_RECT_IN_STREAM_NAME)); private static final List OUTPUT_STREAMS = Collections.unmodifiableList( Arrays.asList( @@ -205,7 +208,7 @@ public final class GestureRecognizer extends BaseVisionTaskApi { * @param runningMode a mediapipe vision task {@link RunningMode}. */ private GestureRecognizer(TaskRunner taskRunner, RunningMode runningMode) { - super(taskRunner, runningMode, IMAGE_IN_STREAM_NAME); + super(taskRunner, runningMode, IMAGE_IN_STREAM_NAME, NORM_RECT_IN_STREAM_NAME); } /** @@ -223,7 +226,8 @@ public final class GestureRecognizer extends BaseVisionTaskApi { * @throws MediaPipeException if there is an internal error. */ public GestureRecognitionResult recognize(Image inputImage) { - return (GestureRecognitionResult) processImageData(inputImage); + // TODO: add proper support for rotations. + return (GestureRecognitionResult) processImageData(inputImage, buildFullImageRectF()); } /** @@ -244,7 +248,9 @@ public final class GestureRecognizer extends BaseVisionTaskApi { * @throws MediaPipeException if there is an internal error. */ public GestureRecognitionResult recognizeForVideo(Image inputImage, long inputTimestampMs) { - return (GestureRecognitionResult) processVideoData(inputImage, inputTimestampMs); + // TODO: add proper support for rotations. + return (GestureRecognitionResult) + processVideoData(inputImage, buildFullImageRectF(), inputTimestampMs); } /** @@ -266,7 +272,8 @@ public final class GestureRecognizer extends BaseVisionTaskApi { * @throws MediaPipeException if there is an internal error. */ public void recognizeAsync(Image inputImage, long inputTimestampMs) { - sendLiveStreamData(inputImage, inputTimestampMs); + // TODO: add proper support for rotations. + sendLiveStreamData(inputImage, buildFullImageRectF(), inputTimestampMs); } /** Options for setting up an {@link GestureRecognizer}. */ @@ -464,4 +471,9 @@ public final class GestureRecognizer extends BaseVisionTaskApi { .build(); } } + + /** Creates a RectF covering the full image. */ + private static RectF buildFullImageRectF() { + return new RectF(0, 0, 1, 1); + } } diff --git a/mediapipe/tasks/testdata/vision/BUILD b/mediapipe/tasks/testdata/vision/BUILD index 0532458aa..ffb4760d9 100644 --- a/mediapipe/tasks/testdata/vision/BUILD +++ b/mediapipe/tasks/testdata/vision/BUILD @@ -39,6 +39,7 @@ mediapipe_files(srcs = [ "hand_landmark_full.tflite", "hand_landmark_lite.tflite", "left_hands.jpg", + "left_hands_rotated.jpg", "mobilenet_v1_0.25_192_quantized_1_default_1.tflite", "mobilenet_v1_0.25_224_1_default_1.tflite", "mobilenet_v1_0.25_224_1_metadata_1.tflite", @@ -52,7 +53,9 @@ mediapipe_files(srcs = [ "multi_objects_rotated.jpg", "palm_detection_full.tflite", "pointing_up.jpg", + "pointing_up_rotated.jpg", "right_hands.jpg", + "right_hands_rotated.jpg", "segmentation_golden_rotation0.png", "segmentation_input_rotation0.jpg", "selfie_segm_128_128_3.tflite", @@ -65,7 +68,9 @@ mediapipe_files(srcs = [ exports_files( srcs = [ "expected_left_down_hand_landmarks.prototxt", + "expected_left_down_hand_rotated_landmarks.prototxt", "expected_left_up_hand_landmarks.prototxt", + "expected_left_up_hand_rotated_landmarks.prototxt", "expected_right_down_hand_landmarks.prototxt", "expected_right_up_hand_landmarks.prototxt", ], @@ -85,11 +90,14 @@ filegroup( "hand_landmark_full.tflite", "hand_landmark_lite.tflite", "left_hands.jpg", + "left_hands_rotated.jpg", "mozart_square.jpg", "multi_objects.jpg", "multi_objects_rotated.jpg", "pointing_up.jpg", + "pointing_up_rotated.jpg", "right_hands.jpg", + "right_hands_rotated.jpg", "segmentation_golden_rotation0.png", "segmentation_input_rotation0.jpg", "selfie_segm_128_128_3_expected_mask.jpg", @@ -131,12 +139,17 @@ filegroup( name = "test_protos", srcs = [ "expected_left_down_hand_landmarks.prototxt", + "expected_left_down_hand_rotated_landmarks.prototxt", "expected_left_up_hand_landmarks.prototxt", + "expected_left_up_hand_rotated_landmarks.prototxt", "expected_right_down_hand_landmarks.prototxt", "expected_right_up_hand_landmarks.prototxt", "hand_detector_result_one_hand.pbtxt", + "hand_detector_result_one_hand_rotated.pbtxt", "hand_detector_result_two_hands.pbtxt", "pointing_up_landmarks.pbtxt", + "pointing_up_rotated_landmarks.pbtxt", "thumb_up_landmarks.pbtxt", + "thumb_up_rotated_landmarks.pbtxt", ], ) diff --git a/mediapipe/tasks/testdata/vision/expected_left_down_hand_rotated_landmarks.prototxt b/mediapipe/tasks/testdata/vision/expected_left_down_hand_rotated_landmarks.prototxt new file mode 100644 index 000000000..3cbf8804f --- /dev/null +++ b/mediapipe/tasks/testdata/vision/expected_left_down_hand_rotated_landmarks.prototxt @@ -0,0 +1,84 @@ +landmark { + x: 0.9259716 + y: 0.18969846 +} +landmark { + x: 0.88135517 + y: 0.28856543 +} +landmark { + x: 0.7600651 + y: 0.3578236 +} +landmark { + x: 0.62631166 + y: 0.40490413 +} +landmark { + x: 0.5374573 + y: 0.45170194 +} +landmark { + x: 0.57372385 + y: 0.29924914 +} +landmark { + x: 0.36731184 + y: 0.33081773 +} +landmark { + x: 0.24132833 + y: 0.34759054 +} +landmark { + x: 0.13690609 + y: 0.35727677 +} +landmark { + x: 0.5535803 + y: 0.2398035 +} +landmark { + x: 0.31834763 + y: 0.24999242 +} +landmark { + x: 0.16748133 + y: 0.25625145 +} +landmark { + x: 0.050747424 + y: 0.25991398 +} +landmark { + x: 0.56593156 + y: 0.1867483 +} +landmark { + x: 0.3543046 + y: 0.17923892 +} +landmark { + x: 0.21360746 + y: 0.17454882 +} +landmark { + x: 0.11110917 + y: 0.17232567 +} +landmark { + x: 0.5948908 + y: 0.14024714 +} +landmark { + x: 0.42692152 + y: 0.11949824 +} +landmark { + x: 0.32239118 + y: 0.106370345 +} +landmark { + x: 0.23672739 + y: 0.09432885 +} diff --git a/mediapipe/tasks/testdata/vision/expected_left_up_hand_rotated_landmarks.prototxt b/mediapipe/tasks/testdata/vision/expected_left_up_hand_rotated_landmarks.prototxt new file mode 100644 index 000000000..42eccbcc5 --- /dev/null +++ b/mediapipe/tasks/testdata/vision/expected_left_up_hand_rotated_landmarks.prototxt @@ -0,0 +1,84 @@ +landmark { + x: 0.06676084 + y: 0.8095678 +} +landmark { + x: 0.11359626 + y: 0.71148247 +} +landmark { + x: 0.23572624 + y: 0.6414506 +} +landmark { + x: 0.37323278 + y: 0.5959156 +} +landmark { + x: 0.46243322 + y: 0.55125874 +} +landmark { + x: 0.4205411 + y: 0.69531494 +} +landmark { + x: 0.62798893 + y: 0.66715276 +} +landmark { + x: 0.7568023 + y: 0.65208924 +} +landmark { + x: 0.86370826 + y: 0.6437276 +} +landmark { + x: 0.445136 + y: 0.75394773 +} +landmark { + x: 0.6787485 + y: 0.745853 +} +landmark { + x: 0.8290694 + y: 0.7412988 +} +landmark { + x: 0.94454145 + y: 0.7384017 +} +landmark { + x: 0.43516788 + y: 0.8082166 +} +landmark { + x: 0.6459554 + y: 0.81768996 +} +landmark { + x: 0.7875173 + y: 0.825062 +} +landmark { + x: 0.89249825 + y: 0.82850707 +} +landmark { + x: 0.40665048 + y: 0.8567925 +} +landmark { + x: 0.57228816 + y: 0.8802181 +} +landmark { + x: 0.6762071 + y: 0.8941581 +} +landmark { + x: 0.76453924 + y: 0.90583205 +} diff --git a/mediapipe/tasks/testdata/vision/hand_detector_result_one_hand_rotated.pbtxt b/mediapipe/tasks/testdata/vision/hand_detector_result_one_hand_rotated.pbtxt new file mode 100644 index 000000000..cec4d6166 --- /dev/null +++ b/mediapipe/tasks/testdata/vision/hand_detector_result_one_hand_rotated.pbtxt @@ -0,0 +1,33 @@ +detections { + label: "Palm" + score: 0.97115 + location_data { + format: RELATIVE_BOUNDING_BOX + relative_bounding_box { + xmin: 0.5198178 + ymin: 0.6467485 + width: 0.42467535 + height: 0.22546273 + } + } +} +detections { + label: "Palm" + score: 0.96701413 + location_data { + format: RELATIVE_BOUNDING_BOX + relative_bounding_box { + xmin: 0.024490356 + ymin: 0.12620124 + width: 0.43832153 + height: 0.23269764 + } + } +} +hand_rects { + x_center: 0.5760683 + y_center: 0.6829921 + height: 0.5862031 + width: 1.1048855 + rotation: -0.8250832 +} diff --git a/mediapipe/tasks/testdata/vision/pointing_up_rotated_landmarks.pbtxt b/mediapipe/tasks/testdata/vision/pointing_up_rotated_landmarks.pbtxt new file mode 100644 index 000000000..65bb11bc8 --- /dev/null +++ b/mediapipe/tasks/testdata/vision/pointing_up_rotated_landmarks.pbtxt @@ -0,0 +1,223 @@ +classifications { + classification { + score: 1.0 + label: "Left" + display_name: "Left" + } +} + +landmarks { + landmark { + x: 0.25546086 + y: 0.47584262 + z: 1.835341e-07 + } + landmark { + x: 0.3363011 + y: 0.54135 + z: -0.041144375 + } + landmark { + x: 0.4375146 + y: 0.57881975 + z: -0.06807727 + } + landmark { + x: 0.49603376 + y: 0.5263966 + z: -0.09387612 + } + landmark { + x: 0.5022822 + y: 0.4413827 + z: -0.1189948 + } + landmark { + x: 0.5569452 + y: 0.4724485 + z: -0.05138246 + } + landmark { + x: 0.6687125 + y: 0.47918057 + z: -0.09121969 + } + landmark { + x: 0.73666537 + y: 0.48318353 + z: -0.11703273 + } + landmark { + x: 0.7998315 + y: 0.4741413 + z: -0.1386424 + } + landmark { + x: 0.5244063 + y: 0.39292705 + z: -0.061040796 + } + landmark { + x: 0.57215345 + y: 0.41514704 + z: -0.11967233 + } + landmark { + x: 0.4724468 + y: 0.45553637 + z: -0.13287684 + } + landmark { + x: 0.43794966 + y: 0.45210314 + z: -0.13210714 + } + landmark { + x: 0.47838163 + y: 0.33329 + z: -0.07421263 + } + landmark { + x: 0.51081127 + y: 0.35479474 + z: -0.13596693 + } + landmark { + x: 0.42433846 + y: 0.40486792 + z: -0.121291734 + } + landmark { + x: 0.40280548 + y: 0.39977497 + z: -0.09928809 + } + landmark { + x: 0.42269367 + y: 0.2798249 + z: -0.09064263 + } + landmark { + x: 0.45849988 + y: 0.3069861 + z: -0.12894689 + } + landmark { + x: 0.40754712 + y: 0.35153976 + z: -0.109160855 + } + landmark { + x: 0.38855004 + y: 0.3467068 + z: -0.08820164 + } +} + +world_landmarks { + landmark { + x: -0.08568013 + y: 0.016593203 + z: 0.036527164 + } + landmark { + x: -0.0565372 + y: 0.041761592 + z: 0.019493781 + } + landmark { + x: -0.031365488 + y: 0.05031186 + z: 0.0025481891 + } + landmark { + x: -0.008534161 + y: 0.04286737 + z: -0.024755282 + } + landmark { + x: -0.0047254 + y: 0.015748458 + z: -0.035581928 + } + landmark { + x: 0.013083893 + y: 0.024668094 + z: 0.0035934823 + } + landmark { + x: 0.04149521 + y: 0.024621274 + z: -0.0030611698 + } + landmark { + x: 0.06257473 + y: 0.025388625 + z: -0.010340984 + } + landmark { + x: 0.08009179 + y: 0.023082614 + z: -0.03162942 + } + landmark { + x: 0.006135068 + y: 0.000696786 + z: 0.0048212176 + } + landmark { + x: 0.01678449 + y: 0.0067061195 + z: -0.029920919 + } + landmark { + x: -0.008948593 + y: 0.016808286 + z: -0.03755109 + } + landmark { + x: -0.01789449 + y: 0.0153161455 + z: -0.012059977 + } + landmark { + x: -0.0061980113 + y: -0.017872887 + z: -0.002366997 + } + landmark { + x: -0.004643807 + y: -0.0108282855 + z: -0.034515083 + } + landmark { + x: -0.027603384 + y: 0.003529715 + z: -0.033665676 + } + landmark { + x: -0.035679806 + y: 0.0038255951 + z: -0.008094264 + } + landmark { + x: -0.02957782 + y: -0.031701155 + z: -0.008180461 + } + landmark { + x: -0.020741666 + y: -0.02506058 + z: -0.026839724 + } + landmark { + x: -0.0310834 + y: -0.009496164 + z: -0.032422185 + } + landmark { + x: -0.037420202 + y: -0.012883307 + z: -0.017971724 + } +} diff --git a/mediapipe/tasks/testdata/vision/thumb_up_rotated_landmarks.pbtxt b/mediapipe/tasks/testdata/vision/thumb_up_rotated_landmarks.pbtxt new file mode 100644 index 000000000..3636e2e4d --- /dev/null +++ b/mediapipe/tasks/testdata/vision/thumb_up_rotated_landmarks.pbtxt @@ -0,0 +1,223 @@ +classifications { + classification { + score: 1.0 + label: "Left" + display_name: "Left" + } +} + +landmarks { + landmark { + x: 0.3283601 + y: 0.63773525 + z: -3.2280354e-07 + } + landmark { + x: 0.46280807 + y: 0.6339767 + z: -0.06408348 + } + landmark { + x: 0.5831279 + y: 0.57430106 + z: -0.08583106 + } + landmark { + x: 0.6689471 + y: 0.49959752 + z: -0.09886064 + } + landmark { + x: 0.74378216 + y: 0.47357544 + z: -0.09680563 + } + landmark { + x: 0.5233122 + y: 0.41020474 + z: -0.038088404 + } + landmark { + x: 0.5296913 + y: 0.3372598 + z: -0.08874837 + } + landmark { + x: 0.49039274 + y: 0.43994758 + z: -0.102315836 + } + landmark { + x: 0.4824569 + y: 0.47969607 + z: -0.1030014 + } + landmark { + x: 0.4451338 + y: 0.39520803 + z: -0.02177739 + } + landmark { + x: 0.4410001 + y: 0.34107083 + z: -0.07294245 + } + landmark { + x: 0.4162798 + y: 0.46102384 + z: -0.07746907 + } + landmark { + x: 0.43492994 + y: 0.47154287 + z: -0.07404131 + } + landmark { + x: 0.37671578 + y: 0.39535576 + z: -0.016277775 + } + landmark { + x: 0.36978847 + y: 0.34265152 + z: -0.07346253 + } + landmark { + x: 0.3559884 + y: 0.44905427 + z: -0.057693005 + } + landmark { + x: 0.37711847 + y: 0.46414754 + z: -0.03662908 + } + landmark { + x: 0.3142985 + y: 0.3942253 + z: -0.0152847925 + } + landmark { + x: 0.30000874 + y: 0.35543376 + z: -0.046002634 + } + landmark { + x: 0.30002704 + y: 0.42357764 + z: -0.032671776 + } + landmark { + x: 0.31079838 + y: 0.44218025 + z: -0.016200554 + } +} + +world_landmarks { + landmark { + x: -0.030687196 + y: 0.0678545 + z: 0.051061403 + } + landmark { + x: 0.0047719833 + y: 0.06330968 + z: 0.018945374 + } + landmark { + x: 0.039799504 + y: 0.054109577 + z: 0.007930638 + } + landmark { + x: 0.069374144 + y: 0.035063196 + z: 2.2522348e-05 + } + landmark { + x: 0.087818466 + y: 0.018390425 + z: 0.004055788 + } + landmark { + x: 0.02810654 + y: 0.0043561812 + z: -0.0038672548 + } + landmark { + x: 0.025270049 + y: -0.0039896416 + z: -0.032991238 + } + landmark { + x: 0.020414166 + y: 0.006768506 + z: -0.032724563 + } + landmark { + x: 0.016415983 + y: 0.024563588 + z: -0.0058115427 + } + landmark { + x: 0.0038743173 + y: -0.0044466974 + z: 0.0024876352 + } + landmark { + x: 0.0041790796 + y: -0.0115309935 + z: -0.03532454 + } + landmark { + x: -0.0016900161 + y: 0.015519895 + z: -0.03596156 + } + landmark { + x: 0.004309217 + y: 0.01917039 + z: 0.003907912 + } + landmark { + x: -0.016969737 + y: -0.005584497 + z: 0.0034258277 + } + landmark { + x: -0.016737012 + y: -0.01159037 + z: -0.02876696 + } + landmark { + x: -0.018165365 + y: 0.01376111 + z: -0.026835402 + } + landmark { + x: -0.012430167 + y: 0.02064222 + z: -0.00087265146 + } + landmark { + x: -0.043247573 + y: 0.0011161827 + z: 0.0056269006 + } + landmark { + x: -0.038128495 + y: -0.011477032 + z: -0.016374081 + } + landmark { + x: -0.034920715 + y: 0.005510211 + z: -0.029714659 + } + landmark { + x: -0.03815982 + y: 0.011989757 + z: -0.014853194 + } +} diff --git a/third_party/external_files.bzl b/third_party/external_files.bzl index b85d93318..2c92293ff 100644 --- a/third_party/external_files.bzl +++ b/third_party/external_files.bzl @@ -151,7 +151,7 @@ def external_files(): http_file( name = "com_google_mediapipe_dummy_gesture_recognizer_task", sha256 = "18e54586bda33300d459ca140cd045f6daf43d897224ba215a16db3423eae18e", - urls = ["https://storage.googleapis.com/mediapipe-assets/dummy_gesture_recognizer.task?generation=1665524417056146"], + urls = ["https://storage.googleapis.com/mediapipe-assets/dummy_gesture_recognizer.task?generation=1665707319890725"], ) http_file( @@ -166,12 +166,24 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_down_hand_landmarks.prototxt?generation=1661875720230540"], ) + http_file( + name = "com_google_mediapipe_expected_left_down_hand_rotated_landmarks_prototxt", + sha256 = "a16d6cb8dd07d60f0678ddeb6a7447b73b9b03d4ddde365c8770b472205bb6cf", + urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_down_hand_rotated_landmarks.prototxt?generation=1666037061297507"], + ) + http_file( name = "com_google_mediapipe_expected_left_up_hand_landmarks_prototxt", sha256 = "1353ba617c4f048083618587cd23a8a22115f634521c153d4e1bd1ebd4f49dd7", urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_up_hand_landmarks.prototxt?generation=1661875726008879"], ) + http_file( + name = "com_google_mediapipe_expected_left_up_hand_rotated_landmarks_prototxt", + sha256 = "a9b9789c274d48a7cb9cc10af7bc644eb2512bb934529790d0a5404726daa86a", + urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_up_hand_rotated_landmarks.prototxt?generation=1666037063443676"], + ) + http_file( name = "com_google_mediapipe_expected_right_down_hand_landmarks_prototxt", sha256 = "f281b745175aaa7f458def6cf4c89521fb56302dd61a05642b3b4a4f237ffaa3", @@ -250,6 +262,12 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/hand_detector_result_one_hand.pbtxt?generation=1662745351291628"], ) + http_file( + name = "com_google_mediapipe_hand_detector_result_one_hand_rotated_pbtxt", + sha256 = "ff5ca0654028d78a3380df90054273cae79abe1b7369b164063fd1d5758ec370", + urls = ["https://storage.googleapis.com/mediapipe-assets/hand_detector_result_one_hand_rotated.pbtxt?generation=1666037065601724"], + ) + http_file( name = "com_google_mediapipe_hand_detector_result_two_hands_pbtxt", sha256 = "2589cb08b0ee027dc24649fe597adcfa2156a21d12ea2480f83832714ebdf95f", @@ -352,6 +370,12 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/left_hands.jpg?generation=1661875796949017"], ) + http_file( + name = "com_google_mediapipe_left_hands_rotated_jpg", + sha256 = "8609c6202bca43a99bbf23fa8e687e49fa525e89481152e4c0987f46d60d7931", + urls = ["https://storage.googleapis.com/mediapipe-assets/left_hands_rotated.jpg?generation=1666037068103465"], + ) + http_file( name = "com_google_mediapipe_mobilebert_embedding_with_metadata_tflite", sha256 = "fa47142dcc6f446168bc672f2df9605b6da5d0c0d6264e9be62870282365b95c", @@ -544,6 +568,18 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_landmarks.pbtxt?generation=1665174976408451"], ) + http_file( + name = "com_google_mediapipe_pointing_up_rotated_jpg", + sha256 = "50ff66f50281207072a038e5bb6648c43f4aacbfb8204a4d2591868756aaeff1", + urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_rotated.jpg?generation=1666037072219697"], + ) + + http_file( + name = "com_google_mediapipe_pointing_up_rotated_landmarks_pbtxt", + sha256 = "ccf67e5867094ffb6c465a4dfbf2ef1eb3f9db2465803fc25a0b84c958e050de", + urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_rotated_landmarks.pbtxt?generation=1666037074376515"], + ) + http_file( name = "com_google_mediapipe_pose_detection_tflite", sha256 = "a63c614bef30d35947f13be361820b1e4e3bec9cfeebf4d11216a18373108e85", @@ -580,6 +616,12 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/right_hands.jpg?generation=1661875908672404"], ) + http_file( + name = "com_google_mediapipe_right_hands_rotated_jpg", + sha256 = "b3bdf692f0d54b86c8b67e6d1286dd0078fbe6e9dfcd507b187e3bd8b398c0f9", + urls = ["https://storage.googleapis.com/mediapipe-assets/right_hands_rotated.jpg?generation=1666037076873345"], + ) + http_file( name = "com_google_mediapipe_score_calibration_file_meta_json", sha256 = "6a3c305620371f662419a496f75be5a10caebca7803b1e99d8d5d22ba51cda94", @@ -724,6 +766,12 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/thumb_up_landmarks.pbtxt?generation=1665174979747784"], ) + http_file( + name = "com_google_mediapipe_thumb_up_rotated_landmarks_pbtxt", + sha256 = "5d0a465959cacbd201ac8dd8fc8a66c5997a172b71809b12d27296db6a28a102", + urls = ["https://storage.googleapis.com/mediapipe-assets/thumb_up_rotated_landmarks.pbtxt?generation=1666037079490527"], + ) + http_file( name = "com_google_mediapipe_two_heads_16000_hz_mono_wav", sha256 = "a291a9c22c39bba30138a26915e154a96286ba6ca3b413053123c504a58cce3b", From 9e2a9bb4be88f2b9a5f886209ff254d743c5aeee Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 20 Oct 2022 12:32:07 -0700 Subject: [PATCH 038/125] Internal change PiperOrigin-RevId: 482565462 --- .../tensor/image_to_tensor_converter_gl_buffer.cc | 13 +++++++------ .../tensor/image_to_tensor_converter_gl_texture.cc | 6 +++--- 2 files changed, 10 insertions(+), 9 deletions(-) diff --git a/mediapipe/calculators/tensor/image_to_tensor_converter_gl_buffer.cc b/mediapipe/calculators/tensor/image_to_tensor_converter_gl_buffer.cc index 5671d7b4d..14de410ff 100644 --- a/mediapipe/calculators/tensor/image_to_tensor_converter_gl_buffer.cc +++ b/mediapipe/calculators/tensor/image_to_tensor_converter_gl_buffer.cc @@ -270,10 +270,10 @@ class GlProcessor : public ImageToTensorConverter { Tensor& output_tensor) override { if (input.format() != mediapipe::GpuBufferFormat::kBGRA32 && input.format() != mediapipe::GpuBufferFormat::kRGBAHalf64 && - input.format() != mediapipe::GpuBufferFormat::kRGBAFloat128) { + input.format() != mediapipe::GpuBufferFormat::kRGBAFloat128 && + input.format() != mediapipe::GpuBufferFormat::kRGB24) { return InvalidArgumentError(absl::StrCat( - "Only 4-channel texture input formats are supported, passed format: ", - static_cast(input.format()))); + "Unsupported format: ", static_cast(input.format()))); } const auto& output_shape = output_tensor.shape(); MP_RETURN_IF_ERROR(ValidateTensorShape(output_shape)); @@ -281,12 +281,13 @@ class GlProcessor : public ImageToTensorConverter { MP_RETURN_IF_ERROR(gl_helper_.RunInGlContext( [this, &output_tensor, &input, &roi, &output_shape, range_min, range_max, tensor_buffer_offset]() -> absl::Status { - constexpr int kRgbaNumChannels = 4; + const int input_num_channels = input.channels(); auto source_texture = gl_helper_.CreateSourceTexture(input); tflite::gpu::gl::GlTexture input_texture( - GL_TEXTURE_2D, source_texture.name(), GL_RGBA, + GL_TEXTURE_2D, source_texture.name(), + input_num_channels == 4 ? GL_RGB : GL_RGBA, source_texture.width() * source_texture.height() * - kRgbaNumChannels * sizeof(uint8_t), + input_num_channels * sizeof(uint8_t), /*layer=*/0, /*owned=*/false); diff --git a/mediapipe/calculators/tensor/image_to_tensor_converter_gl_texture.cc b/mediapipe/calculators/tensor/image_to_tensor_converter_gl_texture.cc index 06dfd578e..5efd34041 100644 --- a/mediapipe/calculators/tensor/image_to_tensor_converter_gl_texture.cc +++ b/mediapipe/calculators/tensor/image_to_tensor_converter_gl_texture.cc @@ -174,10 +174,10 @@ class GlProcessor : public ImageToTensorConverter { Tensor& output_tensor) override { if (input.format() != mediapipe::GpuBufferFormat::kBGRA32 && input.format() != mediapipe::GpuBufferFormat::kRGBAHalf64 && - input.format() != mediapipe::GpuBufferFormat::kRGBAFloat128) { + input.format() != mediapipe::GpuBufferFormat::kRGBAFloat128 && + input.format() != mediapipe::GpuBufferFormat::kRGB24) { return InvalidArgumentError(absl::StrCat( - "Only 4-channel texture input formats are supported, passed format: ", - static_cast(input.format()))); + "Unsupported format: ", static_cast(input.format()))); } // TODO: support tensor_buffer_offset > 0 scenario. RET_CHECK_EQ(tensor_buffer_offset, 0) From 086fc442fde87ba7b26fbdc9ee7173f24f6e3578 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 20 Oct 2022 23:12:58 -0700 Subject: [PATCH 039/125] Internal change PiperOrigin-RevId: 482697999 --- .../core/data/classification_dataset.py | 12 ++++-- .../core/data/classification_dataset_test.py | 42 ++++++++++++------- .../python/core/tasks/classifier.py | 10 ++--- .../python/core/tasks/classifier_test.py | 4 +- .../python/vision/image_classifier/dataset.py | 6 +-- .../vision/image_classifier/dataset_test.py | 18 ++++---- .../image_classifier/image_classifier.py | 10 ++--- 7 files changed, 60 insertions(+), 42 deletions(-) diff --git a/mediapipe/model_maker/python/core/data/classification_dataset.py b/mediapipe/model_maker/python/core/data/classification_dataset.py index 9075e46eb..af761d9ea 100644 --- a/mediapipe/model_maker/python/core/data/classification_dataset.py +++ b/mediapipe/model_maker/python/core/data/classification_dataset.py @@ -23,13 +23,17 @@ from mediapipe.model_maker.python.core.data import dataset as ds class ClassificationDataset(ds.Dataset): """DataLoader for classification models.""" - def __init__(self, dataset: tf.data.Dataset, size: int, index_to_label: Any): + def __init__(self, dataset: tf.data.Dataset, size: int, index_by_label: Any): super().__init__(dataset, size) - self.index_to_label = index_to_label + self._index_by_label = index_by_label @property def num_classes(self: ds._DatasetT) -> int: - return len(self.index_to_label) + return len(self._index_by_label) + + @property + def index_by_label(self: ds._DatasetT) -> Any: + return self._index_by_label def split(self: ds._DatasetT, fraction: float) -> Tuple[ds._DatasetT, ds._DatasetT]: @@ -44,4 +48,4 @@ class ClassificationDataset(ds.Dataset): Returns: The splitted two sub datasets. """ - return self._split(fraction, self.index_to_label) + return self._split(fraction, self._index_by_label) diff --git a/mediapipe/model_maker/python/core/data/classification_dataset_test.py b/mediapipe/model_maker/python/core/data/classification_dataset_test.py index f8688ab14..0fd8575f4 100644 --- a/mediapipe/model_maker/python/core/data/classification_dataset_test.py +++ b/mediapipe/model_maker/python/core/data/classification_dataset_test.py @@ -12,45 +12,59 @@ # See the License for the specific language governing permissions and # limitations under the License. +from typing import Any, Tuple, TypeVar + # Dependency imports import tensorflow as tf from mediapipe.model_maker.python.core.data import classification_dataset +_DatasetT = TypeVar( + '_DatasetT', bound='ClassificationDatasetTest.MagicClassificationDataset') -class ClassificationDataLoaderTest(tf.test.TestCase): + +class ClassificationDatasetTest(tf.test.TestCase): def test_split(self): - class MagicClassificationDataLoader( + class MagicClassificationDataset( classification_dataset.ClassificationDataset): + """A mock classification dataset class for testing purpose. - def __init__(self, dataset, size, index_to_label, value): - super(MagicClassificationDataLoader, - self).__init__(dataset, size, index_to_label) + Attributes: + value: A value variable stored by the mock dataset class for testing. + """ + + def __init__(self, dataset: tf.data.Dataset, size: int, + index_by_label: Any, value: Any): + super().__init__( + dataset=dataset, size=size, index_by_label=index_by_label) self.value = value - def split(self, fraction): - return self._split(fraction, self.index_to_label, self.value) + def split(self, fraction: float) -> Tuple[_DatasetT, _DatasetT]: + return self._split(fraction, self.index_by_label, self.value) # Some dummy inputs. magic_value = 42 num_classes = 2 - index_to_label = (False, True) + index_by_label = (False, True) # Create data loader from sample data. ds = tf.data.Dataset.from_tensor_slices([[0, 1], [1, 1], [0, 0], [1, 0]]) - data = MagicClassificationDataLoader(ds, len(ds), index_to_label, - magic_value) + data = MagicClassificationDataset( + dataset=ds, + size=len(ds), + index_by_label=index_by_label, + value=magic_value) # Train/Test data split. fraction = .25 - train_data, test_data = data.split(fraction) + train_data, test_data = data.split(fraction=fraction) # `split` should return instances of child DataLoader. - self.assertIsInstance(train_data, MagicClassificationDataLoader) - self.assertIsInstance(test_data, MagicClassificationDataLoader) + self.assertIsInstance(train_data, MagicClassificationDataset) + self.assertIsInstance(test_data, MagicClassificationDataset) # Make sure number of entries are right. self.assertEqual(len(train_data.gen_tf_dataset()), len(train_data)) @@ -59,7 +73,7 @@ class ClassificationDataLoaderTest(tf.test.TestCase): # Make sure attributes propagated correctly. self.assertEqual(train_data.num_classes, num_classes) - self.assertEqual(test_data.index_to_label, index_to_label) + self.assertEqual(test_data.index_by_label, index_by_label) self.assertEqual(train_data.value, magic_value) self.assertEqual(test_data.value, magic_value) diff --git a/mediapipe/model_maker/python/core/tasks/classifier.py b/mediapipe/model_maker/python/core/tasks/classifier.py index 6b366f6dc..c327b7ea9 100644 --- a/mediapipe/model_maker/python/core/tasks/classifier.py +++ b/mediapipe/model_maker/python/core/tasks/classifier.py @@ -29,22 +29,22 @@ from mediapipe.model_maker.python.core.tasks import custom_model class Classifier(custom_model.CustomModel): """An abstract base class that represents a TensorFlow classifier.""" - def __init__(self, model_spec: Any, index_to_label: List[str], shuffle: bool, + def __init__(self, model_spec: Any, index_by_label: List[str], shuffle: bool, full_train: bool): """Initilizes a classifier with its specifications. Args: model_spec: Specification for the model. - index_to_label: A list that map from index to label class name. + index_by_label: A list that map from index to label class name. shuffle: Whether the dataset should be shuffled. full_train: If true, train the model end-to-end including the backbone and the classification layers on top. Otherwise, only train the top classification layers. """ super(Classifier, self).__init__(model_spec, shuffle) - self._index_to_label = index_to_label + self._index_by_label = index_by_label self._full_train = full_train - self._num_classes = len(index_to_label) + self._num_classes = len(index_by_label) def evaluate(self, data: dataset.Dataset, batch_size: int = 32) -> Any: """Evaluates the classifier with the provided evaluation dataset. @@ -74,4 +74,4 @@ class Classifier(custom_model.CustomModel): label_filepath = os.path.join(export_dir, label_filename) tf.compat.v1.logging.info('Saving labels in %s', label_filepath) with tf.io.gfile.GFile(label_filepath, 'w') as f: - f.write('\n'.join(self._index_to_label)) + f.write('\n'.join(self._index_by_label)) diff --git a/mediapipe/model_maker/python/core/tasks/classifier_test.py b/mediapipe/model_maker/python/core/tasks/classifier_test.py index fbf231d8b..1484e8e86 100644 --- a/mediapipe/model_maker/python/core/tasks/classifier_test.py +++ b/mediapipe/model_maker/python/core/tasks/classifier_test.py @@ -36,10 +36,10 @@ class ClassifierTest(tf.test.TestCase): def setUp(self): super(ClassifierTest, self).setUp() - index_to_label = ['cat', 'dog'] + index_by_label = ['cat', 'dog'] self.model = MockClassifier( model_spec=None, - index_to_label=index_to_label, + index_by_label=index_by_label, shuffle=False, full_train=False) self.model.model = test_util.build_model(input_shape=[4], num_classes=2) diff --git a/mediapipe/model_maker/python/vision/image_classifier/dataset.py b/mediapipe/model_maker/python/vision/image_classifier/dataset.py index 4d808500c..53c0518ae 100644 --- a/mediapipe/model_maker/python/vision/image_classifier/dataset.py +++ b/mediapipe/model_maker/python/vision/image_classifier/dataset.py @@ -84,10 +84,10 @@ class Dataset(classification_dataset.ClassificationDataset): name for name in os.listdir(data_root) if os.path.isdir(os.path.join(data_root, name))) all_label_size = len(label_names) - label_to_index = dict( + index_by_label = dict( (name, index) for index, name in enumerate(label_names)) all_image_labels = [ - label_to_index[os.path.basename(os.path.dirname(path))] + index_by_label[os.path.basename(os.path.dirname(path))] for path in all_image_paths ] @@ -106,7 +106,7 @@ class Dataset(classification_dataset.ClassificationDataset): 'Load image with size: %d, num_label: %d, labels: %s.', all_image_size, all_label_size, ', '.join(label_names)) return Dataset( - dataset=image_label_ds, size=all_image_size, index_to_label=label_names) + dataset=image_label_ds, size=all_image_size, index_by_label=label_names) @classmethod def load_tf_dataset( diff --git a/mediapipe/model_maker/python/vision/image_classifier/dataset_test.py b/mediapipe/model_maker/python/vision/image_classifier/dataset_test.py index 3a5d198b4..6a0b696f9 100644 --- a/mediapipe/model_maker/python/vision/image_classifier/dataset_test.py +++ b/mediapipe/model_maker/python/vision/image_classifier/dataset_test.py @@ -49,27 +49,27 @@ class DatasetTest(tf.test.TestCase): def test_split(self): ds = tf.data.Dataset.from_tensor_slices([[0, 1], [1, 1], [0, 0], [1, 0]]) - data = dataset.Dataset(ds, 4, ['pos', 'neg']) - train_data, test_data = data.split(0.5) + data = dataset.Dataset(dataset=ds, size=4, index_by_label=['pos', 'neg']) + train_data, test_data = data.split(fraction=0.5) self.assertLen(train_data, 2) for i, elem in enumerate(train_data._dataset): self.assertTrue((elem.numpy() == np.array([i, 1])).all()) self.assertEqual(train_data.num_classes, 2) - self.assertEqual(train_data.index_to_label, ['pos', 'neg']) + self.assertEqual(train_data.index_by_label, ['pos', 'neg']) self.assertLen(test_data, 2) for i, elem in enumerate(test_data._dataset): self.assertTrue((elem.numpy() == np.array([i, 0])).all()) self.assertEqual(test_data.num_classes, 2) - self.assertEqual(test_data.index_to_label, ['pos', 'neg']) + self.assertEqual(test_data.index_by_label, ['pos', 'neg']) def test_from_folder(self): - data = dataset.Dataset.from_folder(self.image_path) + data = dataset.Dataset.from_folder(dirname=self.image_path) self.assertLen(data, 2) self.assertEqual(data.num_classes, 2) - self.assertEqual(data.index_to_label, ['daisy', 'tulips']) + self.assertEqual(data.index_by_label, ['daisy', 'tulips']) for image, label in data.gen_tf_dataset(): self.assertTrue(label.numpy() == 1 or label.numpy() == 0) if label.numpy() == 0: @@ -88,19 +88,19 @@ class DatasetTest(tf.test.TestCase): self.assertIsInstance(train_data.gen_tf_dataset(), tf.data.Dataset) self.assertLen(train_data, 1034) self.assertEqual(train_data.num_classes, 3) - self.assertEqual(train_data.index_to_label, + self.assertEqual(train_data.index_by_label, ['angular_leaf_spot', 'bean_rust', 'healthy']) self.assertIsInstance(validation_data.gen_tf_dataset(), tf.data.Dataset) self.assertLen(validation_data, 133) self.assertEqual(validation_data.num_classes, 3) - self.assertEqual(validation_data.index_to_label, + self.assertEqual(validation_data.index_by_label, ['angular_leaf_spot', 'bean_rust', 'healthy']) self.assertIsInstance(test_data.gen_tf_dataset(), tf.data.Dataset) self.assertLen(test_data, 128) self.assertEqual(test_data.num_classes, 3) - self.assertEqual(test_data.index_to_label, + self.assertEqual(test_data.index_by_label, ['angular_leaf_spot', 'bean_rust', 'healthy']) diff --git a/mediapipe/model_maker/python/vision/image_classifier/image_classifier.py b/mediapipe/model_maker/python/vision/image_classifier/image_classifier.py index 7a99f9ae0..9161b12e4 100644 --- a/mediapipe/model_maker/python/vision/image_classifier/image_classifier.py +++ b/mediapipe/model_maker/python/vision/image_classifier/image_classifier.py @@ -31,18 +31,18 @@ from mediapipe.model_maker.python.vision.image_classifier import train_image_cla class ImageClassifier(classifier.Classifier): """ImageClassifier for building image classification model.""" - def __init__(self, model_spec: ms.ModelSpec, index_to_label: List[Any], + def __init__(self, model_spec: ms.ModelSpec, index_by_label: List[Any], hparams: hp.HParams): """Initializes ImageClassifier class. Args: model_spec: Specification for the model. - index_to_label: A list that maps from index to label class name. + index_by_label: A list that maps from index to label class name. hparams: The hyperparameters for training image classifier. """ - super(ImageClassifier, self).__init__( + super().__init__( model_spec=model_spec, - index_to_label=index_to_label, + index_by_label=index_by_label, shuffle=hparams.shuffle, full_train=hparams.do_fine_tuning) self._hparams = hparams @@ -81,7 +81,7 @@ class ImageClassifier(classifier.Classifier): spec = ms.SupportedModels.get(model_spec) image_classifier = cls( model_spec=spec, - index_to_label=train_data.index_to_label, + index_by_label=train_data.index_by_label, hparams=hparams) image_classifier._create_model() From 348c4e665216b4425d7c350cc34cb8561f12e064 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 20 Oct 2022 23:43:28 -0700 Subject: [PATCH 040/125] Add a test to test saving and loading the gesture recognizer model. Also update the loss function init method to resolve a bug when loading model. PiperOrigin-RevId: 482702020 --- mediapipe/model_maker/python/core/utils/loss_functions.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mediapipe/model_maker/python/core/utils/loss_functions.py b/mediapipe/model_maker/python/core/utils/loss_functions.py index 17c738a14..5b0aa32bf 100644 --- a/mediapipe/model_maker/python/core/utils/loss_functions.py +++ b/mediapipe/model_maker/python/core/utils/loss_functions.py @@ -56,7 +56,7 @@ class FocalLoss(tf.keras.losses.Loss): class_weight: A weight to apply to the loss, one for each class. The weight is applied for each input where the ground truth label matches. """ - super(tf.keras.losses.Loss, self).__init__() + super().__init__() # Used for clipping min/max values of probability values in y_pred to avoid # NaNs and Infs in computation. self._epsilon = 1e-7 From 55ba23ce9a04bb574a53bd8b6921f90dffef6a68 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 20 Oct 2022 23:57:21 -0700 Subject: [PATCH 041/125] Cleans up unused function from image_classifier's Dataset. PiperOrigin-RevId: 482703775 --- .../python/vision/image_classifier/dataset.py | 31 +------------------ 1 file changed, 1 insertion(+), 30 deletions(-) diff --git a/mediapipe/model_maker/python/vision/image_classifier/dataset.py b/mediapipe/model_maker/python/vision/image_classifier/dataset.py index 53c0518ae..4ae8dcfdd 100644 --- a/mediapipe/model_maker/python/vision/image_classifier/dataset.py +++ b/mediapipe/model_maker/python/vision/image_classifier/dataset.py @@ -16,7 +16,7 @@ import os import random -from typing import List, Optional, Tuple +from typing import List, Optional import tensorflow as tf import tensorflow_datasets as tfds @@ -107,32 +107,3 @@ class Dataset(classification_dataset.ClassificationDataset): all_label_size, ', '.join(label_names)) return Dataset( dataset=image_label_ds, size=all_image_size, index_by_label=label_names) - - @classmethod - def load_tf_dataset( - cls, name: str - ) -> Tuple[Optional[classification_dataset.ClassificationDataset], - Optional[classification_dataset.ClassificationDataset], - Optional[classification_dataset.ClassificationDataset]]: - """Loads data from tensorflow_datasets. - - Args: - name: the registered name of the tfds.core.DatasetBuilder. Refer to the - documentation of tfds.load for more details. - - Returns: - A tuple of Datasets for the train/validation/test. - - Raises: - ValueError: if the input tf dataset does not have train/validation/test - labels. - """ - data, info = tfds.load(name, with_info=True) - if 'label' not in info.features: - raise ValueError('info.features need to contain \'label\' key.') - label_names = info.features['label'].names - - train_data = _create_data('train', data, info, label_names) - validation_data = _create_data('validation', data, info, label_names) - test_data = _create_data('test', data, info, label_names) - return train_data, validation_data, test_data From ed938a9214b3db30085cd5eafcd1a7c14184485f Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Fri, 21 Oct 2022 11:27:53 -0700 Subject: [PATCH 042/125] Replace the usage of InvalidProtocolBufferException with IOException. PiperOrigin-RevId: 482844446 --- .../mediapipe/tasks/text/textclassifier/TextClassifier.java | 3 +-- .../tasks/vision/imageclassifier/ImageClassifier.java | 3 +-- 2 files changed, 2 insertions(+), 4 deletions(-) diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassifier.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassifier.java index 0ebffe7cf..76117d2e4 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassifier.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassifier.java @@ -31,7 +31,6 @@ import com.google.mediapipe.tasks.core.TaskOptions; import com.google.mediapipe.tasks.core.TaskRunner; import com.google.mediapipe.tasks.core.proto.BaseOptionsProto; import com.google.mediapipe.tasks.text.textclassifier.proto.TextClassifierGraphOptionsProto; -import com.google.protobuf.InvalidProtocolBufferException; import java.io.File; import java.io.IOException; import java.util.Arrays; @@ -154,7 +153,7 @@ public final class TextClassifier implements AutoCloseable { packets.get(CLASSIFICATION_RESULT_OUT_STREAM_INDEX), ClassificationsProto.ClassificationResult.getDefaultInstance()), packets.get(CLASSIFICATION_RESULT_OUT_STREAM_INDEX).getTimestamp()); - } catch (InvalidProtocolBufferException e) { + } catch (IOException e) { throw new MediaPipeException( MediaPipeException.StatusCode.INTERNAL.ordinal(), e.getMessage()); } diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java index 68cae151f..e8e263b71 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java @@ -39,7 +39,6 @@ import com.google.mediapipe.tasks.core.proto.BaseOptionsProto; import com.google.mediapipe.tasks.vision.core.BaseVisionTaskApi; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.imageclassifier.proto.ImageClassifierGraphOptionsProto; -import com.google.protobuf.InvalidProtocolBufferException; import java.io.File; import java.io.IOException; import java.nio.ByteBuffer; @@ -176,7 +175,7 @@ public final class ImageClassifier extends BaseVisionTaskApi { packets.get(CLASSIFICATION_RESULT_OUT_STREAM_INDEX), ClassificationsProto.ClassificationResult.getDefaultInstance()), packets.get(CLASSIFICATION_RESULT_OUT_STREAM_INDEX).getTimestamp()); - } catch (InvalidProtocolBufferException e) { + } catch (IOException e) { throw new MediaPipeException( MediaPipeException.StatusCode.INTERNAL.ordinal(), e.getMessage()); } From fe77c5489fe8a08e4411ec65f3668a48cbabd6a9 Mon Sep 17 00:00:00 2001 From: Sebastian Schmidt Date: Fri, 21 Oct 2022 12:05:47 -0700 Subject: [PATCH 043/125] Fix comments in GestureRecognizer PiperOrigin-RevId: 482854253 --- .../cc/vision/gesture_recognizer/gesture_recognizer.h | 6 +++--- .../tasks/vision/gesturerecognizer/GestureRecognizer.java | 8 ++++---- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h index 892b3c16a..750a99797 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h @@ -59,7 +59,7 @@ struct GestureRecognizerOptions { int num_hands = 1; // The minimum confidence score for the hand detection to be considered - // successfully. + // successful. float min_hand_detection_confidence = 0.5; // The minimum confidence score of hand presence score in the hand landmark @@ -67,11 +67,11 @@ struct GestureRecognizerOptions { float min_hand_presence_confidence = 0.5; // The minimum confidence score for the hand tracking to be considered - // successfully. + // successful. float min_tracking_confidence = 0.5; // The minimum confidence score for the gestures to be considered - // successfully. If < 0, the gesture confidence thresholds in the model + // successful. If < 0, the gesture confidence thresholds in the model // metadata are used. // TODO Note this option is subject to change, after scoring // merging calculator is implemented. diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java index 32473b299..660645d9c 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java @@ -310,18 +310,18 @@ public final class GestureRecognizer extends BaseVisionTaskApi { /** Sets the maximum number of hands can be detected by the GestureRecognizer. */ public abstract Builder setNumHands(Integer value); - /** Sets minimum confidence score for the hand detection to be considered successfully */ + /** Sets minimum confidence score for the hand detection to be considered successful */ public abstract Builder setMinHandDetectionConfidence(Float value); /** Sets minimum confidence score of hand presence score in the hand landmark detection. */ public abstract Builder setMinHandPresenceConfidence(Float value); - /** Sets the minimum confidence score for the hand tracking to be considered successfully. */ + /** Sets the minimum confidence score for the hand tracking to be considered successful. */ public abstract Builder setMinTrackingConfidence(Float value); /** - * Sets the minimum confidence score for the gestures to be considered successfully. If < 0, - * the gesture confidence threshold=0.5 for the model is used. + * Sets the minimum confidence score for the gestures to be considered successful. If < 0, the + * gesture confidence threshold=0.5 for the model is used. * *

TODO Note this option is subject to change, after scoring merging * calculator is implemented. From 55a536e55e81eab186f8c325e9fa42477b2c2f63 Mon Sep 17 00:00:00 2001 From: Sebastian Schmidt Date: Fri, 21 Oct 2022 12:07:52 -0700 Subject: [PATCH 044/125] Typo fix in Landmark PiperOrigin-RevId: 482854764 --- .../mediapipe/tasks/components/containers/Landmark.java | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers/Landmark.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers/Landmark.java index 3f96d7779..e45866190 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers/Landmark.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers/Landmark.java @@ -30,13 +30,13 @@ public abstract class Landmark { return new AutoValue_Landmark(x, y, z, normalized); } - // The x coordniates of the landmark. + // The x coordinates of the landmark. public abstract float x(); - // The y coordniates of the landmark. + // The y coordinates of the landmark. public abstract float y(); - // The z coordniates of the landmark. + // The z coordinates of the landmark. public abstract float z(); // Whether this landmark is normalized with respect to the image size. From e453c3b20666889ccdc15b4fb2f01c4a0f0d010d Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Fri, 21 Oct 2022 12:14:49 -0700 Subject: [PATCH 045/125] Migrates `image_preprocessing` from `core` to `vision`. PiperOrigin-RevId: 482856336 --- mediapipe/model_maker/python/core/utils/BUILD | 14 -------- .../model_maker/python/vision/core/BUILD | 33 +++++++++++++++++++ .../python/vision/core/__init__.py | 13 ++++++++ .../core}/image_preprocessing.py | 4 --- .../core}/image_preprocessing_test.py | 7 +--- .../python/vision/image_classifier/BUILD | 2 +- .../image_classifier/image_classifier.py | 2 +- 7 files changed, 49 insertions(+), 26 deletions(-) create mode 100644 mediapipe/model_maker/python/vision/core/BUILD create mode 100644 mediapipe/model_maker/python/vision/core/__init__.py rename mediapipe/model_maker/python/{core/utils => vision/core}/image_preprocessing.py (98%) rename mediapipe/model_maker/python/{core/utils => vision/core}/image_preprocessing_test.py (94%) diff --git a/mediapipe/model_maker/python/core/utils/BUILD b/mediapipe/model_maker/python/core/utils/BUILD index e4b18b395..2538ec8fa 100644 --- a/mediapipe/model_maker/python/core/utils/BUILD +++ b/mediapipe/model_maker/python/core/utils/BUILD @@ -31,20 +31,6 @@ py_library( ], ) -py_library( - name = "image_preprocessing", - srcs = ["image_preprocessing.py"], - srcs_version = "PY3", -) - -py_test( - name = "image_preprocessing_test", - srcs = ["image_preprocessing_test.py"], - python_version = "PY3", - srcs_version = "PY3", - deps = [":image_preprocessing"], -) - py_library( name = "model_util", srcs = ["model_util.py"], diff --git a/mediapipe/model_maker/python/vision/core/BUILD b/mediapipe/model_maker/python/vision/core/BUILD new file mode 100644 index 000000000..2658841ae --- /dev/null +++ b/mediapipe/model_maker/python/vision/core/BUILD @@ -0,0 +1,33 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict test compatibility macro. + +licenses(["notice"]) + +package( + default_visibility = ["//mediapipe:__subpackages__"], +) + +py_library( + name = "image_preprocessing", + srcs = ["image_preprocessing.py"], +) + +py_test( + name = "image_preprocessing_test", + srcs = ["image_preprocessing_test.py"], + deps = [":image_preprocessing"], +) diff --git a/mediapipe/model_maker/python/vision/core/__init__.py b/mediapipe/model_maker/python/vision/core/__init__.py new file mode 100644 index 000000000..7ca2f9216 --- /dev/null +++ b/mediapipe/model_maker/python/vision/core/__init__.py @@ -0,0 +1,13 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/mediapipe/model_maker/python/core/utils/image_preprocessing.py b/mediapipe/model_maker/python/vision/core/image_preprocessing.py similarity index 98% rename from mediapipe/model_maker/python/core/utils/image_preprocessing.py rename to mediapipe/model_maker/python/vision/core/image_preprocessing.py index 62b34fb27..104ccd9ca 100644 --- a/mediapipe/model_maker/python/core/utils/image_preprocessing.py +++ b/mediapipe/model_maker/python/vision/core/image_preprocessing.py @@ -13,11 +13,7 @@ # limitations under the License. # ============================================================================== """ImageNet preprocessing.""" -from __future__ import absolute_import -from __future__ import division -from __future__ import print_function -# Dependency imports import tensorflow as tf IMAGE_SIZE = 224 diff --git a/mediapipe/model_maker/python/core/utils/image_preprocessing_test.py b/mediapipe/model_maker/python/vision/core/image_preprocessing_test.py similarity index 94% rename from mediapipe/model_maker/python/core/utils/image_preprocessing_test.py rename to mediapipe/model_maker/python/vision/core/image_preprocessing_test.py index bc4b44569..0594b4376 100644 --- a/mediapipe/model_maker/python/core/utils/image_preprocessing_test.py +++ b/mediapipe/model_maker/python/vision/core/image_preprocessing_test.py @@ -12,15 +12,10 @@ # See the License for the specific language governing permissions and # limitations under the License. -from __future__ import absolute_import -from __future__ import division -from __future__ import print_function - -# Dependency imports import numpy as np import tensorflow as tf -from mediapipe.model_maker.python.core.utils import image_preprocessing +from mediapipe.model_maker.python.vision.core import image_preprocessing def _get_preprocessed_image(preprocessor, is_training=False): diff --git a/mediapipe/model_maker/python/vision/image_classifier/BUILD b/mediapipe/model_maker/python/vision/image_classifier/BUILD index a9386d56e..5b4ec2bd1 100644 --- a/mediapipe/model_maker/python/vision/image_classifier/BUILD +++ b/mediapipe/model_maker/python/vision/image_classifier/BUILD @@ -78,9 +78,9 @@ py_library( ":train_image_classifier_lib", "//mediapipe/model_maker/python/core/data:classification_dataset", "//mediapipe/model_maker/python/core/tasks:classifier", - "//mediapipe/model_maker/python/core/utils:image_preprocessing", "//mediapipe/model_maker/python/core/utils:model_util", "//mediapipe/model_maker/python/core/utils:quantization", + "//mediapipe/model_maker/python/vision/core:image_preprocessing", ], ) diff --git a/mediapipe/model_maker/python/vision/image_classifier/image_classifier.py b/mediapipe/model_maker/python/vision/image_classifier/image_classifier.py index 9161b12e4..dd8929a71 100644 --- a/mediapipe/model_maker/python/vision/image_classifier/image_classifier.py +++ b/mediapipe/model_maker/python/vision/image_classifier/image_classifier.py @@ -20,9 +20,9 @@ import tensorflow_hub as hub from mediapipe.model_maker.python.core.data import classification_dataset as classification_ds from mediapipe.model_maker.python.core.tasks import classifier -from mediapipe.model_maker.python.core.utils import image_preprocessing from mediapipe.model_maker.python.core.utils import model_util from mediapipe.model_maker.python.core.utils import quantization +from mediapipe.model_maker.python.vision.core import image_preprocessing from mediapipe.model_maker.python.vision.image_classifier import hyperparameters as hp from mediapipe.model_maker.python.vision.image_classifier import model_spec as ms from mediapipe.model_maker.python.vision.image_classifier import train_image_classifier_lib From e1a9615e1a1a4f5abfa54ac2262e4b97c2c86d17 Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Fri, 21 Oct 2022 12:46:44 -0700 Subject: [PATCH 046/125] Add "alwayslink = 1" to "universal_sentence_encoder_preprocessor_calculator". PiperOrigin-RevId: 482864252 --- mediapipe/calculators/tensor/BUILD | 1 + 1 file changed, 1 insertion(+) diff --git a/mediapipe/calculators/tensor/BUILD b/mediapipe/calculators/tensor/BUILD index 654b71351..ae8a0cbf0 100644 --- a/mediapipe/calculators/tensor/BUILD +++ b/mediapipe/calculators/tensor/BUILD @@ -304,6 +304,7 @@ cc_library( "@com_google_absl//absl/status", "@com_google_absl//absl/strings", ], + alwayslink = 1, ) mediapipe_proto_library( From 5231a0ad9f7588512119547e271e06a7a54ef7c9 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Fri, 21 Oct 2022 13:34:30 -0700 Subject: [PATCH 047/125] Removed SegmenterOptions dataclasses to enumerate options within ImageSegmenterOptions instead --- mediapipe/tasks/python/components/proto/BUILD | 6 +-- .../components/proto/segmenter_options.py | 50 ------------------- .../test/vision/image_segmenter_test.py | 22 +++----- mediapipe/tasks/python/vision/BUILD | 1 + .../tasks/python/vision/image_segmenter.py | 44 ++++++++++------ 5 files changed, 38 insertions(+), 85 deletions(-) diff --git a/mediapipe/tasks/python/components/proto/BUILD b/mediapipe/tasks/python/components/proto/BUILD index a58f77e6c..ef37d9270 100644 --- a/mediapipe/tasks/python/components/proto/BUILD +++ b/mediapipe/tasks/python/components/proto/BUILD @@ -20,9 +20,5 @@ licenses(["notice"]) py_library( name = "segmenter_options", - srcs = ["segmenter_options.py"], - deps = [ - "//mediapipe/tasks/cc/components/proto:segmenter_options_py_pb2", - "//mediapipe/tasks/python/core:optional_dependencies", - ], + srcs = ["segmenter_options.py"] ) diff --git a/mediapipe/tasks/python/components/proto/segmenter_options.py b/mediapipe/tasks/python/components/proto/segmenter_options.py index dcf34cc39..5f8e22777 100644 --- a/mediapipe/tasks/python/components/proto/segmenter_options.py +++ b/mediapipe/tasks/python/components/proto/segmenter_options.py @@ -13,14 +13,7 @@ # limitations under the License. """Segmenter options data class.""" -import dataclasses import enum -from typing import Any, Optional - -from mediapipe.tasks.cc.components.proto import segmenter_options_pb2 -from mediapipe.tasks.python.core.optional_dependencies import doc_controls - -_SegmenterOptionsProto = segmenter_options_pb2.SegmenterOptions class OutputType(enum.Enum): @@ -33,46 +26,3 @@ class Activation(enum.Enum): NONE = 0 SIGMOID = 1 SOFTMAX = 2 - - -@dataclasses.dataclass -class SegmenterOptions: - """Options for segmentation processor. - Attributes: - output_type: The output mask type allows specifying the type of - post-processing to perform on the raw model results. - activation: Activation function to apply to input tensor. - """ - - output_type: Optional[OutputType] = OutputType.CATEGORY_MASK - activation: Optional[Activation] = Activation.NONE - - @doc_controls.do_not_generate_docs - def to_pb2(self) -> _SegmenterOptionsProto: - """Generates a protobuf object to pass to the C++ layer.""" - return _SegmenterOptionsProto( - output_type=self.output_type.value, - activation=self.activation.value - ) - - @classmethod - @doc_controls.do_not_generate_docs - def create_from_pb2( - cls, pb2_obj: _SegmenterOptionsProto) -> "SegmenterOptions": - """Creates a `SegmenterOptions` object from the given protobuf object.""" - return SegmenterOptions( - output_type=OutputType(pb2_obj.output_type), - activation=Activation(pb2_obj.output_type) - ) - - def __eq__(self, other: Any) -> bool: - """Checks if this object is equal to the given object. - Args: - other: The object to be compared with. - Returns: - True if the objects are equal. - """ - if not isinstance(other, SegmenterOptions): - return False - - return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index b53f301b1..2395eae57 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -35,7 +35,6 @@ _Image = image_module.Image _ImageFormat = image_frame_module.ImageFormat _OutputType = segmenter_options.OutputType _Activation = segmenter_options.Activation -_SegmenterOptions = segmenter_options.SegmenterOptions _ImageSegmenter = image_segmenter.ImageSegmenter _ImageSegmenterOptions = image_segmenter.ImageSegmenterOptions _RUNNING_MODE = running_mode_module.VisionTaskRunningMode @@ -125,9 +124,8 @@ class ImageSegmenterTest(parameterized.TestCase): # Should never happen raise ValueError('model_file_type is invalid.') - segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) options = _ImageSegmenterOptions(base_options=base_options, - segmenter_options=segmenter_options) + output_type=_OutputType.CATEGORY_MASK) segmenter = _ImageSegmenter.create_from_options(options) # Performs image segmentation on the input. @@ -153,19 +151,16 @@ class ImageSegmenterTest(parameterized.TestCase): base_options = _BaseOptions(model_asset_path=self.model_path) # Run segmentation on the model in CATEGORY_MASK mode. - segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) options = _ImageSegmenterOptions(base_options=base_options, - segmenter_options=segmenter_options) + output_type=_OutputType.CATEGORY_MASK) segmenter = _ImageSegmenter.create_from_options(options) category_masks = segmenter.segment(self.test_image) category_mask = category_masks[0].numpy_view() # Run segmentation on the model in CONFIDENCE_MASK mode. - segmenter_options = _SegmenterOptions( - output_type=_OutputType.CONFIDENCE_MASK, - activation=_Activation.SOFTMAX) options = _ImageSegmenterOptions(base_options=base_options, - segmenter_options=segmenter_options) + output_type=_OutputType.CONFIDENCE_MASK, + activation=_Activation.SOFTMAX) segmenter = _ImageSegmenter.create_from_options(options) confidence_masks = segmenter.segment(self.test_image) @@ -204,9 +199,8 @@ class ImageSegmenterTest(parameterized.TestCase): # Should never happen raise ValueError('model_file_type is invalid.') - segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) options = _ImageSegmenterOptions(base_options=base_options, - segmenter_options=segmenter_options) + output_type=_OutputType.CATEGORY_MASK) with _ImageSegmenter.create_from_options(options) as segmenter: # Performs image segmentation on the input. category_masks = segmenter.segment(self.test_image) @@ -284,10 +278,9 @@ class ImageSegmenterTest(parameterized.TestCase): segmenter.segment_for_video(self.test_image, 0) def test_segment_for_video(self): - segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) options = _ImageSegmenterOptions( base_options=_BaseOptions(model_asset_path=self.model_path), - segmenter_options=segmenter_options, + output_type=_OutputType.CATEGORY_MASK, running_mode=_RUNNING_MODE.VIDEO) with _ImageSegmenter.create_from_options(options) as segmenter: for timestamp in range(0, 300, 30): @@ -348,10 +341,9 @@ class ImageSegmenterTest(parameterized.TestCase): self.assertLess(observed_timestamp_ms, timestamp_ms) self.observed_timestamp_ms = timestamp_ms - segmenter_options = _SegmenterOptions(output_type=_OutputType.CATEGORY_MASK) options = _ImageSegmenterOptions( base_options=_BaseOptions(model_asset_path=self.model_path), - segmenter_options=segmenter_options, + output_type=_OutputType.CATEGORY_MASK, running_mode=_RUNNING_MODE.LIVE_STREAM, result_callback=check_result) with _ImageSegmenter.create_from_options(options) as segmenter: diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 3875ea5de..863312e4c 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -46,6 +46,7 @@ py_library( "//mediapipe/python:_framework_bindings", "//mediapipe/python:packet_creator", "//mediapipe/python:packet_getter", + "//mediapipe/tasks/cc/components/proto:segmenter_options_py_pb2", "//mediapipe/tasks/cc/vision/image_segmenter/proto:image_segmenter_options_py_pb2", "//mediapipe/tasks/python/components/proto:segmenter_options", "//mediapipe/tasks/python/core:base_options", diff --git a/mediapipe/tasks/python/vision/image_segmenter.py b/mediapipe/tasks/python/vision/image_segmenter.py index 51f802925..e7278eb96 100644 --- a/mediapipe/tasks/python/vision/image_segmenter.py +++ b/mediapipe/tasks/python/vision/image_segmenter.py @@ -19,22 +19,25 @@ from typing import Callable, List, Mapping, Optional from mediapipe.python import packet_creator from mediapipe.python import packet_getter from mediapipe.python._framework_bindings import image as image_module -from mediapipe.python._framework_bindings import packet as packet_module -from mediapipe.python._framework_bindings import task_runner as task_runner_module +from mediapipe.python._framework_bindings import packet +from mediapipe.python._framework_bindings import task_runner +from mediapipe.tasks.cc.components.proto import segmenter_options_pb2 from mediapipe.tasks.cc.vision.image_segmenter.proto import image_segmenter_options_pb2 from mediapipe.tasks.python.components.proto import segmenter_options from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.core import task_info as task_info_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls from mediapipe.tasks.python.vision.core import base_vision_task_api -from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module +from mediapipe.tasks.python.vision.core import vision_task_running_mode _BaseOptions = base_options_module.BaseOptions +_SegmenterOptionsProto = segmenter_options_pb2.SegmenterOptions _ImageSegmenterOptionsProto = image_segmenter_options_pb2.ImageSegmenterOptions -_SegmenterOptions = segmenter_options.SegmenterOptions -_RunningMode = running_mode_module.VisionTaskRunningMode +_OutputType = segmenter_options.OutputType +_Activation = segmenter_options.Activation +_RunningMode = vision_task_running_mode.VisionTaskRunningMode _TaskInfo = task_info_module.TaskInfo -_TaskRunner = task_runner_module.TaskRunner +_TaskRunner = task_runner.TaskRunner _SEGMENTATION_OUT_STREAM_NAME = 'segmented_mask_out' _SEGMENTATION_TAG = 'GROUPED_SEGMENTATION' @@ -57,14 +60,17 @@ class ImageSegmenterOptions: 2) The video mode for segmenting objects on the decoded frames of a video. 3) The live stream mode for segmenting objects on a live stream of input data, such as from camera. - segmenter_options: Options for the image segmenter task. + output_type: The output mask type allows specifying the type of + post-processing to perform on the raw model results. + activation: Activation function to apply to input tensor. result_callback: The user-defined result callback for processing live stream data. The result callback should only be specified when the running mode is set to the live stream mode. """ base_options: _BaseOptions running_mode: _RunningMode = _RunningMode.IMAGE - segmenter_options: _SegmenterOptions = _SegmenterOptions() + output_type: Optional[_OutputType] = _OutputType.CATEGORY_MASK + activation: Optional[_Activation] = _Activation.NONE result_callback: Optional[ Callable[[List[image_module.Image], image_module.Image, int], None]] = None @@ -74,8 +80,10 @@ class ImageSegmenterOptions: """Generates an ImageSegmenterOptions protobuf object.""" base_options_proto = self.base_options.to_pb2() base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True - segmenter_options_proto = self.segmenter_options.to_pb2() - + segmenter_options_proto = _SegmenterOptionsProto( + output_type=self.output_type.value, + activation=self.activation.value + ) return _ImageSegmenterOptionsProto( base_options=base_options_proto, segmenter_options=segmenter_options_proto @@ -127,7 +135,7 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): RuntimeError: If other types of error occurred. """ - def packets_callback(output_packets: Mapping[str, packet_module.Packet]): + def packets_callback(output_packets: Mapping[str, packet.Packet]): if output_packets[_IMAGE_OUT_STREAM_NAME].is_empty(): return segmentation_result = packet_getter.get_image_list( @@ -159,8 +167,11 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): image: MediaPipe Image. Returns: - A segmentation result object that contains a list of segmentation masks - as images. + If the output_type is CATEGORY_MASK, the returned vector of images is + per-category segmented image mask. + If the output_type is CONFIDENCE_MASK, the returned vector of images + contains only one confidence image mask. A segmentation result object that + contains a list of segmentation masks as images. Raises: ValueError: If any of the input arguments is invalid. @@ -186,8 +197,11 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi): timestamp_ms: The timestamp of the input video frame in milliseconds. Returns: - A segmentation result object that contains a list of segmentation masks - as images. + If the output_type is CATEGORY_MASK, the returned vector of images is + per-category segmented image mask. + If the output_type is CONFIDENCE_MASK, the returned vector of images + contains only one confidence image mask. A segmentation result object that + contains a list of segmentation masks as images. Raises: ValueError: If any of the input arguments is invalid. From 36d69971a7b645273374410a589f4afdb186272d Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Fri, 21 Oct 2022 13:33:22 -0700 Subject: [PATCH 048/125] Internal change PiperOrigin-RevId: 482875698 --- mediapipe/calculators/tensor/BUILD | 21 +++++++++++++++++++++ 1 file changed, 21 insertions(+) diff --git a/mediapipe/calculators/tensor/BUILD b/mediapipe/calculators/tensor/BUILD index ae8a0cbf0..e953342da 100644 --- a/mediapipe/calculators/tensor/BUILD +++ b/mediapipe/calculators/tensor/BUILD @@ -307,6 +307,27 @@ cc_library( alwayslink = 1, ) +cc_test( + name = "universal_sentence_encoder_preprocessor_calculator_test", + srcs = ["universal_sentence_encoder_preprocessor_calculator_test.cc"], + data = ["//mediapipe/tasks/testdata/text:universal_sentence_encoder_qa"], + deps = [ + ":universal_sentence_encoder_preprocessor_calculator", + "//mediapipe/framework:calculator_framework", + "//mediapipe/framework:packet", + "//mediapipe/framework/formats:tensor", + "//mediapipe/framework/port:gtest_main", + "//mediapipe/framework/port:parse_text_proto", + "//mediapipe/framework/port:status", + "//mediapipe/framework/tool:options_map", + "//mediapipe/tasks/cc/core:utils", + "//mediapipe/tasks/cc/metadata:metadata_extractor", + "@com_google_absl//absl/status", + "@com_google_absl//absl/status:statusor", + "@com_google_absl//absl/strings", + ], +) + mediapipe_proto_library( name = "inference_calculator_proto", srcs = ["inference_calculator.proto"], From 024a6866a7ba41bb0e8e33106c2195f0ced88e6e Mon Sep 17 00:00:00 2001 From: kinaryml Date: Fri, 21 Oct 2022 13:39:59 -0700 Subject: [PATCH 049/125] Removed some unneeded aliases --- .../tasks/python/test/vision/image_segmenter_test.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index 2395eae57..9b4e2c4b4 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -23,21 +23,21 @@ from absl.testing import absltest from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module -from mediapipe.python._framework_bindings import image_frame as image_frame_module +from mediapipe.python._framework_bindings import image_frame from mediapipe.tasks.python.components.proto import segmenter_options from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_utils from mediapipe.tasks.python.vision import image_segmenter -from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module +from mediapipe.tasks.python.vision.core import vision_task_running_mode _BaseOptions = base_options_module.BaseOptions _Image = image_module.Image -_ImageFormat = image_frame_module.ImageFormat +_ImageFormat = image_frame.ImageFormat _OutputType = segmenter_options.OutputType _Activation = segmenter_options.Activation _ImageSegmenter = image_segmenter.ImageSegmenter _ImageSegmenterOptions = image_segmenter.ImageSegmenterOptions -_RUNNING_MODE = running_mode_module.VisionTaskRunningMode +_RUNNING_MODE = vision_task_running_mode.VisionTaskRunningMode _MODEL_FILE = 'deeplabv3.tflite' _IMAGE_FILE = 'segmentation_input_rotation0.jpg' From d0437b7f9152a723a48835916872ea7b051ac96d Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Fri, 21 Oct 2022 15:25:38 -0700 Subject: [PATCH 050/125] Add tensor_index and tensor_name fields to ClassificationList PiperOrigin-RevId: 482901854 --- .../tensors_to_classification_calculator.cc | 7 +++++ ...tensors_to_classification_calculator.proto | 5 ++++ ...nsors_to_classification_calculator_test.cc | 30 +++++++++++++++++++ .../framework/formats/classification.proto | 4 +++ 4 files changed, 46 insertions(+) diff --git a/mediapipe/calculators/tensor/tensors_to_classification_calculator.cc b/mediapipe/calculators/tensor/tensors_to_classification_calculator.cc index 5bfc00ed7..76d2869e8 100644 --- a/mediapipe/calculators/tensor/tensors_to_classification_calculator.cc +++ b/mediapipe/calculators/tensor/tensors_to_classification_calculator.cc @@ -163,6 +163,7 @@ absl::Status TensorsToClassificationCalculator::Open(CalculatorContext* cc) { } absl::Status TensorsToClassificationCalculator::Process(CalculatorContext* cc) { + const auto& options = cc->Options(); const auto& input_tensors = *kInTensors(cc); RET_CHECK_EQ(input_tensors.size(), 1); RET_CHECK(input_tensors[0].element_type() == Tensor::ElementType::kFloat32); @@ -181,6 +182,12 @@ absl::Status TensorsToClassificationCalculator::Process(CalculatorContext* cc) { auto raw_scores = view.buffer(); auto classification_list = absl::make_unique(); + if (options.has_tensor_index()) { + classification_list->set_tensor_index(options.tensor_index()); + } + if (options.has_tensor_name()) { + classification_list->set_tensor_name(options.tensor_name()); + } if (is_binary_classification_) { Classification* class_first = classification_list->add_classification(); Classification* class_second = classification_list->add_classification(); diff --git a/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto b/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto index 32bc4b63a..f0f7727ba 100644 --- a/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto +++ b/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto @@ -72,4 +72,9 @@ message TensorsToClassificationCalculatorOptions { // that are not in the `allow_classes` field will be completely ignored. // `ignore_classes` and `allow_classes` are mutually exclusive. repeated int32 allow_classes = 8 [packed = true]; + + // The optional index of the tensor these classifications originate from. + optional int32 tensor_index = 10; + // The optional name of the tensor these classifications originate from. + optional string tensor_name = 11; } diff --git a/mediapipe/calculators/tensor/tensors_to_classification_calculator_test.cc b/mediapipe/calculators/tensor/tensors_to_classification_calculator_test.cc index 9634635f0..b20f2768c 100644 --- a/mediapipe/calculators/tensor/tensors_to_classification_calculator_test.cc +++ b/mediapipe/calculators/tensor/tensors_to_classification_calculator_test.cc @@ -240,6 +240,36 @@ TEST_F(TensorsToClassificationCalculatorTest, } } +TEST_F(TensorsToClassificationCalculatorTest, + CorrectOutputWithTensorNameAndIndex) { + mediapipe::CalculatorRunner runner(ParseTextProtoOrDie(R"pb( + calculator: "TensorsToClassificationCalculator" + input_stream: "TENSORS:tensors" + output_stream: "CLASSIFICATIONS:classifications" + options { + [mediapipe.TensorsToClassificationCalculatorOptions.ext] { + tensor_index: 1 + tensor_name: "foo" + } + } + )pb")); + + BuildGraph(&runner, {0, 0.5, 1}); + MP_ASSERT_OK(runner.Run()); + + const auto& output_packets_ = runner.Outputs().Tag("CLASSIFICATIONS").packets; + + EXPECT_EQ(1, output_packets_.size()); + + const auto& classification_list = + output_packets_[0].Get(); + EXPECT_EQ(3, classification_list.classification_size()); + + // Verify that the tensor_index and tensor_name fields are correctly set. + EXPECT_EQ(classification_list.tensor_index(), 1); + EXPECT_EQ(classification_list.tensor_name(), "foo"); +} + TEST_F(TensorsToClassificationCalculatorTest, ClassNameAllowlistWithLabelItems) { mediapipe::CalculatorRunner runner(ParseTextProtoOrDie(R"pb( diff --git a/mediapipe/framework/formats/classification.proto b/mediapipe/framework/formats/classification.proto index 7efd9074d..c3eea07ff 100644 --- a/mediapipe/framework/formats/classification.proto +++ b/mediapipe/framework/formats/classification.proto @@ -37,6 +37,10 @@ message Classification { // Group of Classification protos. message ClassificationList { repeated Classification classification = 1; + // Optional index of the tensor that produced these classifications. + optional int32 tensor_index = 2; + // Optional name of the tensor that produced these classifications. + optional string tensor_name = 3; } // Group of ClassificationList protos. From 4a6c23a76a70369ba5a1a65789fcfc2d6497cc82 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Fri, 21 Oct 2022 15:47:13 -0700 Subject: [PATCH 051/125] Internal change PiperOrigin-RevId: 482906478 --- mediapipe/tasks/cc/vision/core/BUILD | 11 ++ .../cc/vision/core/base_vision_task_api.h | 59 ++++++++++ .../cc/vision/core/image_processing_options.h | 52 +++++++++ .../tasks/cc/vision/gesture_recognizer/BUILD | 1 + .../gesture_recognizer/gesture_recognizer.cc | 47 +++----- .../gesture_recognizer/gesture_recognizer.h | 36 +++--- .../tasks/cc/vision/image_classifier/BUILD | 1 + .../image_classifier/image_classifier.cc | 37 ++---- .../image_classifier/image_classifier.h | 31 ++--- .../image_classifier/image_classifier_test.cc | 109 +++++++++++++----- .../tasks/cc/vision/object_detector/BUILD | 1 + .../vision/object_detector/object_detector.cc | 47 +++----- .../vision/object_detector/object_detector.h | 29 +++-- .../object_detector/object_detector_test.cc | 22 ++-- 14 files changed, 302 insertions(+), 181 deletions(-) create mode 100644 mediapipe/tasks/cc/vision/core/image_processing_options.h diff --git a/mediapipe/tasks/cc/vision/core/BUILD b/mediapipe/tasks/cc/vision/core/BUILD index 12d789901..e8e197a1d 100644 --- a/mediapipe/tasks/cc/vision/core/BUILD +++ b/mediapipe/tasks/cc/vision/core/BUILD @@ -21,12 +21,23 @@ cc_library( hdrs = ["running_mode.h"], ) +cc_library( + name = "image_processing_options", + hdrs = ["image_processing_options.h"], + deps = [ + "//mediapipe/tasks/cc/components/containers:rect", + ], +) + cc_library( name = "base_vision_task_api", hdrs = ["base_vision_task_api.h"], deps = [ + ":image_processing_options", ":running_mode", "//mediapipe/calculators/core:flow_limiter_calculator", + "//mediapipe/framework/formats:rect_cc_proto", + "//mediapipe/tasks/cc/components/containers:rect", "//mediapipe/tasks/cc/core:base_task_api", "//mediapipe/tasks/cc/core:task_runner", "@com_google_absl//absl/status", diff --git a/mediapipe/tasks/cc/vision/core/base_vision_task_api.h b/mediapipe/tasks/cc/vision/core/base_vision_task_api.h index 4586cbbdd..c3c0a0261 100644 --- a/mediapipe/tasks/cc/vision/core/base_vision_task_api.h +++ b/mediapipe/tasks/cc/vision/core/base_vision_task_api.h @@ -16,15 +16,20 @@ limitations under the License. #ifndef MEDIAPIPE_TASKS_CC_VISION_CORE_BASE_VISION_TASK_API_H_ #define MEDIAPIPE_TASKS_CC_VISION_CORE_BASE_VISION_TASK_API_H_ +#include #include +#include #include #include #include "absl/status/status.h" #include "absl/status/statusor.h" #include "absl/strings/str_cat.h" +#include "mediapipe/framework/formats/rect.pb.h" +#include "mediapipe/tasks/cc/components/containers/rect.h" #include "mediapipe/tasks/cc/core/base_task_api.h" #include "mediapipe/tasks/cc/core/task_runner.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" namespace mediapipe { @@ -87,6 +92,60 @@ class BaseVisionTaskApi : public tasks::core::BaseTaskApi { return runner_->Send(std::move(inputs)); } + // Convert from ImageProcessingOptions to NormalizedRect, performing sanity + // checks on-the-fly. If the input ImageProcessingOptions is not present, + // returns a default NormalizedRect covering the whole image with rotation set + // to 0. If 'roi_allowed' is false, an error will be returned if the input + // ImageProcessingOptions has its 'region_or_interest' field set. + static absl::StatusOr ConvertToNormalizedRect( + std::optional options, bool roi_allowed = true) { + mediapipe::NormalizedRect normalized_rect; + normalized_rect.set_rotation(0); + normalized_rect.set_x_center(0.5); + normalized_rect.set_y_center(0.5); + normalized_rect.set_width(1.0); + normalized_rect.set_height(1.0); + if (!options.has_value()) { + return normalized_rect; + } + + if (options->rotation_degrees % 90 != 0) { + return CreateStatusWithPayload( + absl::StatusCode::kInvalidArgument, + "Expected rotation to be a multiple of 90°.", + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError); + } + // Convert to radians counter-clockwise. + normalized_rect.set_rotation(-options->rotation_degrees * M_PI / 180.0); + + if (options->region_of_interest.has_value()) { + if (!roi_allowed) { + return CreateStatusWithPayload( + absl::StatusCode::kInvalidArgument, + "This task doesn't support region-of-interest.", + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError); + } + auto& roi = *options->region_of_interest; + if (roi.left >= roi.right || roi.top >= roi.bottom) { + return CreateStatusWithPayload( + absl::StatusCode::kInvalidArgument, + "Expected Rect with left < right and top < bottom.", + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError); + } + if (roi.left < 0 || roi.top < 0 || roi.right > 1 || roi.bottom > 1) { + return CreateStatusWithPayload( + absl::StatusCode::kInvalidArgument, + "Expected Rect values to be in [0,1].", + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError); + } + normalized_rect.set_x_center((roi.left + roi.right) / 2.0); + normalized_rect.set_y_center((roi.top + roi.bottom) / 2.0); + normalized_rect.set_width(roi.right - roi.left); + normalized_rect.set_height(roi.bottom - roi.top); + } + return normalized_rect; + } + private: RunningMode running_mode_; }; diff --git a/mediapipe/tasks/cc/vision/core/image_processing_options.h b/mediapipe/tasks/cc/vision/core/image_processing_options.h new file mode 100644 index 000000000..7e764c1fe --- /dev/null +++ b/mediapipe/tasks/cc/vision/core/image_processing_options.h @@ -0,0 +1,52 @@ +/* Copyright 2022 The MediaPipe Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +#ifndef MEDIAPIPE_TASKS_CC_VISION_CORE_IMAGE_PROCESSING_OPTIONS_H_ +#define MEDIAPIPE_TASKS_CC_VISION_CORE_IMAGE_PROCESSING_OPTIONS_H_ + +#include + +#include "mediapipe/tasks/cc/components/containers/rect.h" + +namespace mediapipe { +namespace tasks { +namespace vision { +namespace core { + +// Options for image processing. +// +// If both region-or-interest and rotation are specified, the crop around the +// region-of-interest is extracted first, the the specified rotation is applied +// to the crop. +struct ImageProcessingOptions { + // The optional region-of-interest to crop from the image. If not specified, + // the full image is used. + // + // Coordinates must be in [0,1] with 'left' < 'right' and 'top' < bottom. + std::optional region_of_interest = std::nullopt; + + // The rotation to apply to the image (or cropped region-of-interest), in + // degrees clockwise. + // + // The rotation must be a multiple (positive or negative) of 90°. + int rotation_degrees = 0; +}; + +} // namespace core +} // namespace vision +} // namespace tasks +} // namespace mediapipe + +#endif // MEDIAPIPE_TASKS_CC_VISION_CORE_IMAGE_PROCESSING_OPTIONS_H_ diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD b/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD index e5b1f0479..a766c6b3f 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD @@ -137,6 +137,7 @@ cc_library( "//mediapipe/tasks/cc/core:utils", "//mediapipe/tasks/cc/core/proto:inference_subgraph_cc_proto", "//mediapipe/tasks/cc/vision/core:base_vision_task_api", + "//mediapipe/tasks/cc/vision/core:image_processing_options", "//mediapipe/tasks/cc/vision/core:running_mode", "//mediapipe/tasks/cc/vision/core:vision_task_api_factory", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_cc_proto", diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc index 333edb6fb..000a2e141 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc @@ -39,6 +39,7 @@ limitations under the License. #include "mediapipe/tasks/cc/core/task_runner.h" #include "mediapipe/tasks/cc/core/utils.h" #include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/vision_task_api_factory.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_recognizer_graph_options.pb.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.pb.h" @@ -76,31 +77,6 @@ constexpr char kHandWorldLandmarksTag[] = "WORLD_LANDMARKS"; constexpr char kHandWorldLandmarksStreamName[] = "world_landmarks"; constexpr int kMicroSecondsPerMilliSecond = 1000; -// Returns a NormalizedRect filling the whole image. If input is present, its -// rotation is set in the returned NormalizedRect and a check is performed to -// make sure no region-of-interest was provided. Otherwise, rotation is set to -// 0. -absl::StatusOr FillNormalizedRect( - std::optional normalized_rect) { - NormalizedRect result; - if (normalized_rect.has_value()) { - result = *normalized_rect; - } - bool has_coordinates = result.has_x_center() || result.has_y_center() || - result.has_width() || result.has_height(); - if (has_coordinates) { - return CreateStatusWithPayload( - absl::StatusCode::kInvalidArgument, - "GestureRecognizer does not support region-of-interest.", - MediaPipeTasksStatus::kInvalidArgumentError); - } - result.set_x_center(0.5); - result.set_y_center(0.5); - result.set_width(1); - result.set_height(1); - return result; -} - // Creates a MediaPipe graph config that contains a subgraph node of // "mediapipe.tasks.vision.GestureRecognizerGraph". If the task is running // in the live stream mode, a "FlowLimiterCalculator" will be added to limit the @@ -248,15 +224,16 @@ absl::StatusOr> GestureRecognizer::Create( absl::StatusOr GestureRecognizer::Recognize( mediapipe::Image image, - std::optional image_processing_options) { + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, "GPU input images are currently not supported.", MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - ASSIGN_OR_RETURN(NormalizedRect norm_rect, - FillNormalizedRect(image_processing_options)); + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); ASSIGN_OR_RETURN( auto output_packets, ProcessImageData( @@ -283,15 +260,16 @@ absl::StatusOr GestureRecognizer::Recognize( absl::StatusOr GestureRecognizer::RecognizeForVideo( mediapipe::Image image, int64 timestamp_ms, - std::optional image_processing_options) { + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - ASSIGN_OR_RETURN(NormalizedRect norm_rect, - FillNormalizedRect(image_processing_options)); + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); ASSIGN_OR_RETURN( auto output_packets, ProcessVideoData( @@ -321,15 +299,16 @@ absl::StatusOr GestureRecognizer::RecognizeForVideo( absl::Status GestureRecognizer::RecognizeAsync( mediapipe::Image image, int64 timestamp_ms, - std::optional image_processing_options) { + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - ASSIGN_OR_RETURN(NormalizedRect norm_rect, - FillNormalizedRect(image_processing_options)); + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); return SendLiveStreamData( {{kImageInStreamName, MakePacket(std::move(image)) diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h index 750a99797..29c8bea7b 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h @@ -23,10 +23,10 @@ limitations under the License. #include "mediapipe/framework/formats/classification.pb.h" #include "mediapipe/framework/formats/image.h" #include "mediapipe/framework/formats/landmark.pb.h" -#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/tasks/cc/components/containers/gesture_recognition_result.h" #include "mediapipe/tasks/cc/core/base_options.h" #include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" namespace mediapipe { @@ -129,36 +129,36 @@ class GestureRecognizer : tasks::vision::core::BaseVisionTaskApi { // Only use this method when the GestureRecognizer is created with the image // running mode. // - // image - mediapipe::Image - // Image to perform hand gesture recognition on. - // imageProcessingOptions - std::optional - // If provided, can be used to specify the rotation to apply to the image - // before performing classification, by setting its 'rotation' field in - // radians (e.g. 'M_PI / 2' for a 90° anti-clockwise rotation). Note that - // specifying a region-of-interest using the 'x_center', 'y_center', 'width' - // and 'height' fields is NOT supported and will result in an invalid - // argument error being returned. + // The optional 'image_processing_options' parameter can be used to specify + // the rotation to apply to the image before performing recognition, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported + // and will result in an invalid argument error being returned. // // The image can be of any size with format RGB or RGBA. // TODO: Describes how the input image will be preprocessed // after the yuv support is implemented. - // TODO: use an ImageProcessingOptions struct instead of - // NormalizedRect. absl::StatusOr Recognize( Image image, - std::optional image_processing_options = + std::optional image_processing_options = std::nullopt); // Performs gesture recognition on the provided video frame. // Only use this method when the GestureRecognizer is created with the video // running mode. // + // The optional 'image_processing_options' parameter can be used to specify + // the rotation to apply to the image before performing recognition, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported + // and will result in an invalid argument error being returned. + // // The image can be of any size with format RGB or RGBA. It's required to // provide the video frame's timestamp (in milliseconds). The input timestamps // must be monotonically increasing. absl::StatusOr RecognizeForVideo(Image image, int64 timestamp_ms, - std::optional + std::optional image_processing_options = std::nullopt); // Sends live image data to perform gesture recognition, and the results will @@ -171,6 +171,12 @@ class GestureRecognizer : tasks::vision::core::BaseVisionTaskApi { // sent to the gesture recognizer. The input timestamps must be monotonically // increasing. // + // The optional 'image_processing_options' parameter can be used to specify + // the rotation to apply to the image before performing recognition, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported + // and will result in an invalid argument error being returned. + // // The "result_callback" provides // - A vector of GestureRecognitionResult, each is the recognized results // for a input frame. @@ -180,7 +186,7 @@ class GestureRecognizer : tasks::vision::core::BaseVisionTaskApi { // outside of the callback, callers need to make a copy of the image. // - The input timestamp in milliseconds. absl::Status RecognizeAsync(Image image, int64 timestamp_ms, - std::optional + std::optional image_processing_options = std::nullopt); // Shuts down the GestureRecognizer when all works are done. diff --git a/mediapipe/tasks/cc/vision/image_classifier/BUILD b/mediapipe/tasks/cc/vision/image_classifier/BUILD index dfa77cb96..3d655cd50 100644 --- a/mediapipe/tasks/cc/vision/image_classifier/BUILD +++ b/mediapipe/tasks/cc/vision/image_classifier/BUILD @@ -59,6 +59,7 @@ cc_library( "//mediapipe/tasks/cc/core/proto:base_options_cc_proto", "//mediapipe/tasks/cc/core/proto:inference_subgraph_cc_proto", "//mediapipe/tasks/cc/vision/core:base_vision_task_api", + "//mediapipe/tasks/cc/vision/core:image_processing_options", "//mediapipe/tasks/cc/vision/core:running_mode", "//mediapipe/tasks/cc/vision/core:vision_task_api_factory", "//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_graph_options_cc_proto", diff --git a/mediapipe/tasks/cc/vision/image_classifier/image_classifier.cc b/mediapipe/tasks/cc/vision/image_classifier/image_classifier.cc index f3dcdd07d..8a32758f4 100644 --- a/mediapipe/tasks/cc/vision/image_classifier/image_classifier.cc +++ b/mediapipe/tasks/cc/vision/image_classifier/image_classifier.cc @@ -34,6 +34,7 @@ limitations under the License. #include "mediapipe/tasks/cc/core/proto/inference_subgraph.pb.h" #include "mediapipe/tasks/cc/core/task_runner.h" #include "mediapipe/tasks/cc/core/utils.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" #include "mediapipe/tasks/cc/vision/core/vision_task_api_factory.h" #include "mediapipe/tasks/cc/vision/image_classifier/proto/image_classifier_graph_options.pb.h" @@ -59,26 +60,6 @@ constexpr int kMicroSecondsPerMilliSecond = 1000; using ::mediapipe::tasks::components::containers::proto::ClassificationResult; using ::mediapipe::tasks::core::PacketMap; -// Returns a NormalizedRect covering the full image if input is not present. -// Otherwise, makes sure the x_center, y_center, width and height are set in -// case only a rotation was provided in the input. -NormalizedRect FillNormalizedRect( - std::optional normalized_rect) { - NormalizedRect result; - if (normalized_rect.has_value()) { - result = *normalized_rect; - } - bool has_coordinates = result.has_x_center() || result.has_y_center() || - result.has_width() || result.has_height(); - if (!has_coordinates) { - result.set_x_center(0.5); - result.set_y_center(0.5); - result.set_width(1); - result.set_height(1); - } - return result; -} - // Creates a MediaPipe graph config that contains a subgraph node of // type "ImageClassifierGraph". If the task is running in the live stream mode, // a "FlowLimiterCalculator" will be added to limit the number of frames in @@ -164,14 +145,16 @@ absl::StatusOr> ImageClassifier::Create( } absl::StatusOr ImageClassifier::Classify( - Image image, std::optional image_processing_options) { + Image image, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, "GPU input images are currently not supported.", MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - NormalizedRect norm_rect = FillNormalizedRect(image_processing_options); + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options)); ASSIGN_OR_RETURN( auto output_packets, ProcessImageData( @@ -183,14 +166,15 @@ absl::StatusOr ImageClassifier::Classify( absl::StatusOr ImageClassifier::ClassifyForVideo( Image image, int64 timestamp_ms, - std::optional image_processing_options) { + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, "GPU input images are currently not supported.", MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - NormalizedRect norm_rect = FillNormalizedRect(image_processing_options); + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options)); ASSIGN_OR_RETURN( auto output_packets, ProcessVideoData( @@ -206,14 +190,15 @@ absl::StatusOr ImageClassifier::ClassifyForVideo( absl::Status ImageClassifier::ClassifyAsync( Image image, int64 timestamp_ms, - std::optional image_processing_options) { + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, "GPU input images are currently not supported.", MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - NormalizedRect norm_rect = FillNormalizedRect(image_processing_options); + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options)); return SendLiveStreamData( {{kImageInStreamName, MakePacket(std::move(image)) diff --git a/mediapipe/tasks/cc/vision/image_classifier/image_classifier.h b/mediapipe/tasks/cc/vision/image_classifier/image_classifier.h index 5dff06cc7..de69b7994 100644 --- a/mediapipe/tasks/cc/vision/image_classifier/image_classifier.h +++ b/mediapipe/tasks/cc/vision/image_classifier/image_classifier.h @@ -22,11 +22,11 @@ limitations under the License. #include "absl/status/statusor.h" #include "mediapipe/framework/formats/image.h" -#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/tasks/cc/components/containers/proto/classifications.pb.h" #include "mediapipe/tasks/cc/components/processors/classifier_options.h" #include "mediapipe/tasks/cc/core/base_options.h" #include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" namespace mediapipe { @@ -109,12 +109,10 @@ class ImageClassifier : tasks::vision::core::BaseVisionTaskApi { // // The optional 'image_processing_options' parameter can be used to specify: // - the rotation to apply to the image before performing classification, by - // setting its 'rotation' field in radians (e.g. 'M_PI / 2' for a 90° - // anti-clockwise rotation). + // setting its 'rotation_degrees' field. // and/or // - the region-of-interest on which to perform classification, by setting its - // 'x_center', 'y_center', 'width' and 'height' fields. If none of these is - // set, they will automatically be set to cover the full image. + // 'region_of_interest' field. If not specified, the full image is used. // If both are specified, the crop around the region-of-interest is extracted // first, then the specified rotation is applied to the crop. // @@ -126,19 +124,17 @@ class ImageClassifier : tasks::vision::core::BaseVisionTaskApi { // YUVToImageCalculator is integrated. absl::StatusOr Classify( mediapipe::Image image, - std::optional image_processing_options = + std::optional image_processing_options = std::nullopt); // Performs image classification on the provided video frame. // // The optional 'image_processing_options' parameter can be used to specify: // - the rotation to apply to the image before performing classification, by - // setting its 'rotation' field in radians (e.g. 'M_PI / 2' for a 90° - // anti-clockwise rotation). + // setting its 'rotation_degrees' field. // and/or // - the region-of-interest on which to perform classification, by setting its - // 'x_center', 'y_center', 'width' and 'height' fields. If none of these is - // set, they will automatically be set to cover the full image. + // 'region_of_interest' field. If not specified, the full image is used. // If both are specified, the crop around the region-of-interest is extracted // first, then the specified rotation is applied to the crop. // @@ -150,7 +146,7 @@ class ImageClassifier : tasks::vision::core::BaseVisionTaskApi { // must be monotonically increasing. absl::StatusOr ClassifyForVideo(mediapipe::Image image, int64 timestamp_ms, - std::optional + std::optional image_processing_options = std::nullopt); // Sends live image data to image classification, and the results will be @@ -158,12 +154,10 @@ class ImageClassifier : tasks::vision::core::BaseVisionTaskApi { // // The optional 'image_processing_options' parameter can be used to specify: // - the rotation to apply to the image before performing classification, by - // setting its 'rotation' field in radians (e.g. 'M_PI / 2' for a 90° - // anti-clockwise rotation). + // setting its 'rotation_degrees' field. // and/or // - the region-of-interest on which to perform classification, by setting its - // 'x_center', 'y_center', 'width' and 'height' fields. If none of these is - // set, they will automatically be set to cover the full image. + // 'region_of_interest' field. If not specified, the full image is used. // If both are specified, the crop around the region-of-interest is extracted // first, then the specified rotation is applied to the crop. // @@ -175,7 +169,7 @@ class ImageClassifier : tasks::vision::core::BaseVisionTaskApi { // sent to the object detector. The input timestamps must be monotonically // increasing. // - // The "result_callback" prvoides + // The "result_callback" provides: // - The classification results as a ClassificationResult object. // - The const reference to the corresponding input image that the image // classifier runs on. Note that the const reference to the image will no @@ -183,12 +177,9 @@ class ImageClassifier : tasks::vision::core::BaseVisionTaskApi { // outside of the callback, callers need to make a copy of the image. // - The input timestamp in milliseconds. absl::Status ClassifyAsync(mediapipe::Image image, int64 timestamp_ms, - std::optional + std::optional image_processing_options = std::nullopt); - // TODO: add Classify() variants taking a region of interest as - // additional argument. - // Shuts down the ImageClassifier when all works are done. absl::Status Close() { return runner_->Close(); } }; diff --git a/mediapipe/tasks/cc/vision/image_classifier/image_classifier_test.cc b/mediapipe/tasks/cc/vision/image_classifier/image_classifier_test.cc index 55830e520..0c45122c0 100644 --- a/mediapipe/tasks/cc/vision/image_classifier/image_classifier_test.cc +++ b/mediapipe/tasks/cc/vision/image_classifier/image_classifier_test.cc @@ -27,7 +27,6 @@ limitations under the License. #include "absl/strings/str_format.h" #include "mediapipe/framework/deps/file_path.h" #include "mediapipe/framework/formats/image.h" -#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/port/gmock.h" #include "mediapipe/framework/port/gtest.h" #include "mediapipe/framework/port/parse_text_proto.h" @@ -35,6 +34,8 @@ limitations under the License. #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/components/containers/proto/category.pb.h" #include "mediapipe/tasks/cc/components/containers/proto/classifications.pb.h" +#include "mediapipe/tasks/cc/components/containers/rect.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" #include "mediapipe/tasks/cc/vision/utils/image_utils.h" #include "tensorflow/lite/core/api/op_resolver.h" @@ -49,9 +50,11 @@ namespace image_classifier { namespace { using ::mediapipe::file::JoinPath; +using ::mediapipe::tasks::components::containers::Rect; using ::mediapipe::tasks::components::containers::proto::ClassificationEntry; using ::mediapipe::tasks::components::containers::proto::ClassificationResult; using ::mediapipe::tasks::components::containers::proto::Classifications; +using ::mediapipe::tasks::vision::core::ImageProcessingOptions; using ::testing::HasSubstr; using ::testing::Optional; @@ -547,12 +550,9 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterest) { options->classifier_options.max_results = 1; MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr image_classifier, ImageClassifier::Create(std::move(options))); - // Crop around the soccer ball. - NormalizedRect image_processing_options; - image_processing_options.set_x_center(0.532); - image_processing_options.set_y_center(0.521); - image_processing_options.set_width(0.164); - image_processing_options.set_height(0.427); + // Region-of-interest around the soccer ball. + Rect roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345}; + ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0}; MP_ASSERT_OK_AND_ASSIGN(auto results, image_classifier->Classify( image, image_processing_options)); @@ -572,8 +572,8 @@ TEST_F(ImageModeTest, SucceedsWithRotation) { ImageClassifier::Create(std::move(options))); // Specify a 90° anti-clockwise rotation. - NormalizedRect image_processing_options; - image_processing_options.set_rotation(M_PI / 2.0); + ImageProcessingOptions image_processing_options; + image_processing_options.rotation_degrees = -90; MP_ASSERT_OK_AND_ASSIGN(auto results, image_classifier->Classify( image, image_processing_options)); @@ -616,13 +616,10 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterestAndRotation) { options->classifier_options.max_results = 1; MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr image_classifier, ImageClassifier::Create(std::move(options))); - // Crop around the chair, with 90° anti-clockwise rotation. - NormalizedRect image_processing_options; - image_processing_options.set_x_center(0.2821); - image_processing_options.set_y_center(0.2406); - image_processing_options.set_width(0.5642); - image_processing_options.set_height(0.1286); - image_processing_options.set_rotation(M_PI / 2.0); + // Region-of-interest around the chair, with 90° anti-clockwise rotation. + Rect roi{/*left=*/0.006, /*top=*/0.1763, /*right=*/0.5702, /*bottom=*/0.3049}; + ImageProcessingOptions image_processing_options{roi, + /*rotation_degrees=*/-90}; MP_ASSERT_OK_AND_ASSIGN(auto results, image_classifier->Classify( image, image_processing_options)); @@ -633,7 +630,7 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterestAndRotation) { entries { categories { index: 560 - score: 0.6800408 + score: 0.6522213 category_name: "folding chair" } timestamp_ms: 0 @@ -643,6 +640,69 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterestAndRotation) { })pb")); } +// Testing all these once with ImageClassifier. +TEST_F(ImageModeTest, FailsWithInvalidImageProcessingOptions) { + MP_ASSERT_OK_AND_ASSIGN(Image image, + DecodeImageFromFile(JoinPath("./", kTestDataDirectory, + "multi_objects.jpg"))); + auto options = std::make_unique(); + options->base_options.model_asset_path = + JoinPath("./", kTestDataDirectory, kMobileNetFloatWithMetadata); + MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr image_classifier, + ImageClassifier::Create(std::move(options))); + + // Invalid: left > right. + Rect roi{/*left=*/0.9, /*top=*/0, /*right=*/0.1, /*bottom=*/1}; + ImageProcessingOptions image_processing_options{roi, + /*rotation_degrees=*/0}; + auto results = image_classifier->Classify(image, image_processing_options); + EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument); + EXPECT_THAT(results.status().message(), + HasSubstr("Expected Rect with left < right and top < bottom")); + EXPECT_THAT( + results.status().GetPayload(kMediaPipeTasksPayload), + Optional(absl::Cord(absl::StrCat( + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError)))); + + // Invalid: top > bottom. + roi = {/*left=*/0, /*top=*/0.9, /*right=*/1, /*bottom=*/0.1}; + image_processing_options = {roi, + /*rotation_degrees=*/0}; + results = image_classifier->Classify(image, image_processing_options); + EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument); + EXPECT_THAT(results.status().message(), + HasSubstr("Expected Rect with left < right and top < bottom")); + EXPECT_THAT( + results.status().GetPayload(kMediaPipeTasksPayload), + Optional(absl::Cord(absl::StrCat( + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError)))); + + // Invalid: coordinates out of [0,1] range. + roi = {/*left=*/-0.1, /*top=*/0, /*right=*/1, /*bottom=*/1}; + image_processing_options = {roi, + /*rotation_degrees=*/0}; + results = image_classifier->Classify(image, image_processing_options); + EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument); + EXPECT_THAT(results.status().message(), + HasSubstr("Expected Rect values to be in [0,1]")); + EXPECT_THAT( + results.status().GetPayload(kMediaPipeTasksPayload), + Optional(absl::Cord(absl::StrCat( + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError)))); + + // Invalid: rotation not a multiple of 90°. + image_processing_options = {/*region_of_interest=*/std::nullopt, + /*rotation_degrees=*/1}; + results = image_classifier->Classify(image, image_processing_options); + EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument); + EXPECT_THAT(results.status().message(), + HasSubstr("Expected rotation to be a multiple of 90°")); + EXPECT_THAT( + results.status().GetPayload(kMediaPipeTasksPayload), + Optional(absl::Cord(absl::StrCat( + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError)))); +} + class VideoModeTest : public tflite_shims::testing::Test {}; TEST_F(VideoModeTest, FailsWithCallingWrongMethod) { @@ -732,11 +792,9 @@ TEST_F(VideoModeTest, SucceedsWithRegionOfInterest) { MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr image_classifier, ImageClassifier::Create(std::move(options))); // Crop around the soccer ball. - NormalizedRect image_processing_options; - image_processing_options.set_x_center(0.532); - image_processing_options.set_y_center(0.521); - image_processing_options.set_width(0.164); - image_processing_options.set_height(0.427); + // Region-of-interest around the soccer ball. + Rect roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345}; + ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0}; for (int i = 0; i < iterations; ++i) { MP_ASSERT_OK_AND_ASSIGN( @@ -877,11 +935,8 @@ TEST_F(LiveStreamModeTest, SucceedsWithRegionOfInterest) { MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr image_classifier, ImageClassifier::Create(std::move(options))); // Crop around the soccer ball. - NormalizedRect image_processing_options; - image_processing_options.set_x_center(0.532); - image_processing_options.set_y_center(0.521); - image_processing_options.set_width(0.164); - image_processing_options.set_height(0.427); + Rect roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345}; + ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0}; for (int i = 0; i < iterations; ++i) { MP_ASSERT_OK( diff --git a/mediapipe/tasks/cc/vision/object_detector/BUILD b/mediapipe/tasks/cc/vision/object_detector/BUILD index 186909509..8220d8b7f 100644 --- a/mediapipe/tasks/cc/vision/object_detector/BUILD +++ b/mediapipe/tasks/cc/vision/object_detector/BUILD @@ -75,6 +75,7 @@ cc_library( "//mediapipe/tasks/cc/core/proto:base_options_cc_proto", "//mediapipe/tasks/cc/core/proto:inference_subgraph_cc_proto", "//mediapipe/tasks/cc/vision/core:base_vision_task_api", + "//mediapipe/tasks/cc/vision/core:image_processing_options", "//mediapipe/tasks/cc/vision/core:running_mode", "//mediapipe/tasks/cc/vision/core:vision_task_api_factory", "//mediapipe/tasks/cc/vision/object_detector/proto:object_detector_options_cc_proto", diff --git a/mediapipe/tasks/cc/vision/object_detector/object_detector.cc b/mediapipe/tasks/cc/vision/object_detector/object_detector.cc index 9149a3cbe..dd19237ff 100644 --- a/mediapipe/tasks/cc/vision/object_detector/object_detector.cc +++ b/mediapipe/tasks/cc/vision/object_detector/object_detector.cc @@ -34,6 +34,7 @@ limitations under the License. #include "mediapipe/tasks/cc/core/proto/base_options.pb.h" #include "mediapipe/tasks/cc/core/proto/inference_subgraph.pb.h" #include "mediapipe/tasks/cc/core/utils.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" #include "mediapipe/tasks/cc/vision/core/vision_task_api_factory.h" #include "mediapipe/tasks/cc/vision/object_detector/proto/object_detector_options.pb.h" @@ -58,31 +59,6 @@ constexpr int kMicroSecondsPerMilliSecond = 1000; using ObjectDetectorOptionsProto = object_detector::proto::ObjectDetectorOptions; -// Returns a NormalizedRect filling the whole image. If input is present, its -// rotation is set in the returned NormalizedRect and a check is performed to -// make sure no region-of-interest was provided. Otherwise, rotation is set to -// 0. -absl::StatusOr FillNormalizedRect( - std::optional normalized_rect) { - NormalizedRect result; - if (normalized_rect.has_value()) { - result = *normalized_rect; - } - bool has_coordinates = result.has_x_center() || result.has_y_center() || - result.has_width() || result.has_height(); - if (has_coordinates) { - return CreateStatusWithPayload( - absl::StatusCode::kInvalidArgument, - "ObjectDetector does not support region-of-interest.", - MediaPipeTasksStatus::kInvalidArgumentError); - } - result.set_x_center(0.5); - result.set_y_center(0.5); - result.set_width(1); - result.set_height(1); - return result; -} - // Creates a MediaPipe graph config that contains a subgraph node of // "mediapipe.tasks.vision.ObjectDetectorGraph". If the task is running in the // live stream mode, a "FlowLimiterCalculator" will be added to limit the @@ -170,15 +146,16 @@ absl::StatusOr> ObjectDetector::Create( absl::StatusOr> ObjectDetector::Detect( mediapipe::Image image, - std::optional image_processing_options) { + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - ASSIGN_OR_RETURN(NormalizedRect norm_rect, - FillNormalizedRect(image_processing_options)); + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); ASSIGN_OR_RETURN( auto output_packets, ProcessImageData( @@ -189,15 +166,16 @@ absl::StatusOr> ObjectDetector::Detect( absl::StatusOr> ObjectDetector::DetectForVideo( mediapipe::Image image, int64 timestamp_ms, - std::optional image_processing_options) { + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - ASSIGN_OR_RETURN(NormalizedRect norm_rect, - FillNormalizedRect(image_processing_options)); + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); ASSIGN_OR_RETURN( auto output_packets, ProcessVideoData( @@ -212,15 +190,16 @@ absl::StatusOr> ObjectDetector::DetectForVideo( absl::Status ObjectDetector::DetectAsync( Image image, int64 timestamp_ms, - std::optional image_processing_options) { + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - ASSIGN_OR_RETURN(NormalizedRect norm_rect, - FillNormalizedRect(image_processing_options)); + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); return SendLiveStreamData( {{kImageInStreamName, MakePacket(std::move(image)) diff --git a/mediapipe/tasks/cc/vision/object_detector/object_detector.h b/mediapipe/tasks/cc/vision/object_detector/object_detector.h index 2e5ed7b8d..44ce68ed9 100644 --- a/mediapipe/tasks/cc/vision/object_detector/object_detector.h +++ b/mediapipe/tasks/cc/vision/object_detector/object_detector.h @@ -27,9 +27,9 @@ limitations under the License. #include "absl/status/statusor.h" #include "mediapipe/framework/formats/detection.pb.h" #include "mediapipe/framework/formats/image.h" -#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/tasks/cc/core/base_options.h" #include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" namespace mediapipe { @@ -154,10 +154,9 @@ class ObjectDetector : tasks::vision::core::BaseVisionTaskApi { // after the yuv support is implemented. // // The optional 'image_processing_options' parameter can be used to specify - // the rotation to apply to the image before performing classification, by - // setting its 'rotation' field in radians (e.g. 'M_PI / 2' for a 90° - // anti-clockwise rotation). Note that specifying a region-of-interest using - // the 'x_center', 'y_center', 'width' and 'height' fields is NOT supported + // the rotation to apply to the image before performing detection, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported // and will result in an invalid argument error being returned. // // For CPU images, the returned bounding boxes are expressed in the @@ -168,7 +167,7 @@ class ObjectDetector : tasks::vision::core::BaseVisionTaskApi { // images after enabling the gpu support in MediaPipe Tasks. absl::StatusOr> Detect( mediapipe::Image image, - std::optional image_processing_options = + std::optional image_processing_options = std::nullopt); // Performs object detection on the provided video frame. @@ -180,10 +179,9 @@ class ObjectDetector : tasks::vision::core::BaseVisionTaskApi { // must be monotonically increasing. // // The optional 'image_processing_options' parameter can be used to specify - // the rotation to apply to the image before performing classification, by - // setting its 'rotation' field in radians (e.g. 'M_PI / 2' for a 90° - // anti-clockwise rotation). Note that specifying a region-of-interest using - // the 'x_center', 'y_center', 'width' and 'height' fields is NOT supported + // the rotation to apply to the image before performing detection, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported // and will result in an invalid argument error being returned. // // For CPU images, the returned bounding boxes are expressed in the @@ -192,7 +190,7 @@ class ObjectDetector : tasks::vision::core::BaseVisionTaskApi { // underlying image data. absl::StatusOr> DetectForVideo( mediapipe::Image image, int64 timestamp_ms, - std::optional image_processing_options = + std::optional image_processing_options = std::nullopt); // Sends live image data to perform object detection, and the results will be @@ -206,10 +204,9 @@ class ObjectDetector : tasks::vision::core::BaseVisionTaskApi { // increasing. // // The optional 'image_processing_options' parameter can be used to specify - // the rotation to apply to the image before performing classification, by - // setting its 'rotation' field in radians (e.g. 'M_PI / 2' for a 90° - // anti-clockwise rotation). Note that specifying a region-of-interest using - // the 'x_center', 'y_center', 'width' and 'height' fields is NOT supported + // the rotation to apply to the image before performing detection, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported // and will result in an invalid argument error being returned. // // The "result_callback" provides @@ -223,7 +220,7 @@ class ObjectDetector : tasks::vision::core::BaseVisionTaskApi { // outside of the callback, callers need to make a copy of the image. // - The input timestamp in milliseconds. absl::Status DetectAsync(mediapipe::Image image, int64 timestamp_ms, - std::optional + std::optional image_processing_options = std::nullopt); // Shuts down the ObjectDetector when all works are done. diff --git a/mediapipe/tasks/cc/vision/object_detector/object_detector_test.cc b/mediapipe/tasks/cc/vision/object_detector/object_detector_test.cc index 8db3fa767..1747685dd 100644 --- a/mediapipe/tasks/cc/vision/object_detector/object_detector_test.cc +++ b/mediapipe/tasks/cc/vision/object_detector/object_detector_test.cc @@ -31,11 +31,12 @@ limitations under the License. #include "mediapipe/framework/deps/file_path.h" #include "mediapipe/framework/formats/image.h" #include "mediapipe/framework/formats/location_data.pb.h" -#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/port/gmock.h" #include "mediapipe/framework/port/gtest.h" #include "mediapipe/framework/port/parse_text_proto.h" #include "mediapipe/framework/port/status_matchers.h" +#include "mediapipe/tasks/cc/components/containers/rect.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" #include "mediapipe/tasks/cc/vision/utils/image_utils.h" #include "tensorflow/lite/c/common.h" @@ -64,6 +65,8 @@ namespace vision { namespace { using ::mediapipe::file::JoinPath; +using ::mediapipe::tasks::components::containers::Rect; +using ::mediapipe::tasks::vision::core::ImageProcessingOptions; using ::testing::HasSubstr; using ::testing::Optional; @@ -532,8 +535,8 @@ TEST_F(ImageModeTest, SucceedsWithRotation) { JoinPath("./", kTestDataDirectory, kMobileSsdWithMetadata); MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr object_detector, ObjectDetector::Create(std::move(options))); - NormalizedRect image_processing_options; - image_processing_options.set_rotation(M_PI / 2.0); + ImageProcessingOptions image_processing_options; + image_processing_options.rotation_degrees = -90; MP_ASSERT_OK_AND_ASSIGN( auto results, object_detector->Detect(image, image_processing_options)); MP_ASSERT_OK(object_detector->Close()); @@ -557,16 +560,17 @@ TEST_F(ImageModeTest, FailsWithRegionOfInterest) { JoinPath("./", kTestDataDirectory, kMobileSsdWithMetadata); MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr object_detector, ObjectDetector::Create(std::move(options))); - NormalizedRect image_processing_options; - image_processing_options.set_x_center(0.5); - image_processing_options.set_y_center(0.5); - image_processing_options.set_width(1.0); - image_processing_options.set_height(1.0); + Rect roi{/*left=*/0.1, /*top=*/0, /*right=*/0.9, /*bottom=*/1}; + ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0}; auto results = object_detector->Detect(image, image_processing_options); EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument); EXPECT_THAT(results.status().message(), - HasSubstr("ObjectDetector does not support region-of-interest")); + HasSubstr("This task doesn't support region-of-interest")); + EXPECT_THAT( + results.status().GetPayload(kMediaPipeTasksPayload), + Optional(absl::Cord(absl::StrCat( + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError)))); } class VideoModeTest : public tflite_shims::testing::Test {}; From ea1d85d811f81cc10496bbef0a7f57703cc8e7b2 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Fri, 21 Oct 2022 16:41:07 -0700 Subject: [PATCH 052/125] Update model_task_graph to support multiple local model resources. PiperOrigin-RevId: 482917453 --- mediapipe/tasks/cc/core/model_task_graph.cc | 24 +++++++++++++-------- mediapipe/tasks/cc/core/model_task_graph.h | 23 ++++++++++++++------ 2 files changed, 32 insertions(+), 15 deletions(-) diff --git a/mediapipe/tasks/cc/core/model_task_graph.cc b/mediapipe/tasks/cc/core/model_task_graph.cc index 47334b673..66434483b 100644 --- a/mediapipe/tasks/cc/core/model_task_graph.cc +++ b/mediapipe/tasks/cc/core/model_task_graph.cc @@ -156,21 +156,24 @@ absl::StatusOr ModelTaskGraph::GetConfig( } absl::StatusOr ModelTaskGraph::CreateModelResources( - SubgraphContext* sc, std::unique_ptr external_file) { + SubgraphContext* sc, std::unique_ptr external_file, + const std::string tag_suffix) { auto model_resources_cache_service = sc->Service(kModelResourcesCacheService); if (!model_resources_cache_service.IsAvailable()) { - ASSIGN_OR_RETURN(local_model_resources_, + ASSIGN_OR_RETURN(auto local_model_resource, ModelResources::Create("", std::move(external_file))); LOG(WARNING) << "A local ModelResources object is created. Please consider using " "ModelResourcesCacheService to cache the created ModelResources " "object in the CalculatorGraph."; - return local_model_resources_.get(); + local_model_resources_.push_back(std::move(local_model_resource)); + return local_model_resources_.back().get(); } ASSIGN_OR_RETURN( auto op_resolver_packet, model_resources_cache_service.GetObject().GetGraphOpResolverPacket()); - const std::string tag = CreateModelResourcesTag(sc->OriginalNode()); + const std::string tag = + absl::StrCat(CreateModelResourcesTag(sc->OriginalNode()), tag_suffix); ASSIGN_OR_RETURN(auto model_resources, ModelResources::Create(tag, std::move(external_file), op_resolver_packet)); @@ -182,7 +185,8 @@ absl::StatusOr ModelTaskGraph::CreateModelResources( absl::StatusOr ModelTaskGraph::CreateModelAssetBundleResources( - SubgraphContext* sc, std::unique_ptr external_file) { + SubgraphContext* sc, std::unique_ptr external_file, + const std::string tag_suffix) { auto model_resources_cache_service = sc->Service(kModelResourcesCacheService); bool has_file_pointer_meta = external_file->has_file_pointer_meta(); // if external file is set by file pointer, no need to add the model asset @@ -190,7 +194,7 @@ ModelTaskGraph::CreateModelAssetBundleResources( // not owned by this model asset bundle resources. if (!model_resources_cache_service.IsAvailable() || has_file_pointer_meta) { ASSIGN_OR_RETURN( - local_model_asset_bundle_resources_, + auto local_model_asset_bundle_resource, ModelAssetBundleResources::Create("", std::move(external_file))); if (!has_file_pointer_meta) { LOG(WARNING) @@ -198,10 +202,12 @@ ModelTaskGraph::CreateModelAssetBundleResources( "ModelResourcesCacheService to cache the created ModelResources " "object in the CalculatorGraph."; } - return local_model_asset_bundle_resources_.get(); + local_model_asset_bundle_resources_.push_back( + std::move(local_model_asset_bundle_resource)); + return local_model_asset_bundle_resources_.back().get(); } - const std::string tag = - CreateModelAssetBundleResourcesTag(sc->OriginalNode()); + const std::string tag = absl::StrCat( + CreateModelAssetBundleResourcesTag(sc->OriginalNode()), tag_suffix); ASSIGN_OR_RETURN( auto model_bundle_resources, ModelAssetBundleResources::Create(tag, std::move(external_file))); diff --git a/mediapipe/tasks/cc/core/model_task_graph.h b/mediapipe/tasks/cc/core/model_task_graph.h index 5ee70e8f3..50dcc903b 100644 --- a/mediapipe/tasks/cc/core/model_task_graph.h +++ b/mediapipe/tasks/cc/core/model_task_graph.h @@ -19,6 +19,7 @@ limitations under the License. #include #include #include +#include #include "absl/status/statusor.h" #include "absl/strings/str_format.h" @@ -75,9 +76,14 @@ class ModelTaskGraph : public Subgraph { // construction stage. Note that the external file contents will be moved // into the model resources object on creation. The returned model resources // pointer will provide graph authors with the access to the metadata - // extractor and the tflite model. + // extractor and the tflite model. When the model resources graph service is + // available, a tag is generated internally asscoiated with the created model + // resource. If more than one model resources are created in a graph, the + // model resources graph service add the tag_suffix to support multiple + // resources. absl::StatusOr CreateModelResources( - SubgraphContext* sc, std::unique_ptr external_file); + SubgraphContext* sc, std::unique_ptr external_file, + const std::string tag_suffix = ""); // If the model resources graph service is available, creates a model asset // bundle resources object from the subgraph context, and caches the created @@ -103,10 +109,15 @@ class ModelTaskGraph : public Subgraph { // that can only be used in the graph construction stage. Note that the // external file contents will be moved into the model asset bundle resources // object on creation. The returned model asset bundle resources pointer will - // provide graph authors with the access to extracted model files. + // provide graph authors with the access to extracted model files. When the + // model resources graph service is available, a tag is generated internally + // asscoiated with the created model asset bundle resource. If more than one + // model asset bundle resources are created in a graph, the model resources + // graph service add the tag_suffix to support multiple resources. absl::StatusOr CreateModelAssetBundleResources( - SubgraphContext* sc, std::unique_ptr external_file); + SubgraphContext* sc, std::unique_ptr external_file, + const std::string tag_suffix = ""); // Inserts a mediapipe task inference subgraph into the provided // GraphBuilder. The returned node provides the following interfaces to the @@ -124,9 +135,9 @@ class ModelTaskGraph : public Subgraph { api2::builder::Graph& graph) const; private: - std::unique_ptr local_model_resources_; + std::vector> local_model_resources_; - std::unique_ptr + std::vector> local_model_asset_bundle_resources_; }; From 7196db275efae1738bc31f18fb2ed366f1b41b1d Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Fri, 21 Oct 2022 17:26:48 -0700 Subject: [PATCH 053/125] Internal change PiperOrigin-RevId: 482925717 --- mediapipe/calculators/tensor/BUILD | 20 +++ mediapipe/tasks/cc/text/text_classifier/BUILD | 23 ++++ .../text_classifier/text_classifier_test.cc | 124 ------------------ mediapipe/tasks/cc/text/tokenizers/BUILD | 4 - mediapipe/tasks/testdata/text/BUILD | 7 +- 5 files changed, 47 insertions(+), 131 deletions(-) diff --git a/mediapipe/calculators/tensor/BUILD b/mediapipe/calculators/tensor/BUILD index e953342da..99b5b3e91 100644 --- a/mediapipe/calculators/tensor/BUILD +++ b/mediapipe/calculators/tensor/BUILD @@ -253,6 +253,26 @@ cc_library( alwayslink = 1, ) +cc_test( + name = "regex_preprocessor_calculator_test", + srcs = ["regex_preprocessor_calculator_test.cc"], + data = ["//mediapipe/tasks/testdata/text:text_classifier_models"], + linkopts = ["-ldl"], + deps = [ + ":regex_preprocessor_calculator", + "//mediapipe/framework:calculator_framework", + "//mediapipe/framework/formats:tensor", + "//mediapipe/framework/port:gtest_main", + "//mediapipe/framework/port:parse_text_proto", + "//mediapipe/framework/tool:sink", + "//mediapipe/tasks/cc/core:utils", + "//mediapipe/tasks/cc/metadata:metadata_extractor", + "@com_google_absl//absl/status", + "@com_google_absl//absl/status:statusor", + "@com_google_absl//absl/strings", + ], +) + cc_library( name = "text_to_tensor_calculator", srcs = ["text_to_tensor_calculator.cc"], diff --git a/mediapipe/tasks/cc/text/text_classifier/BUILD b/mediapipe/tasks/cc/text/text_classifier/BUILD index a85538631..336b1bb45 100644 --- a/mediapipe/tasks/cc/text/text_classifier/BUILD +++ b/mediapipe/tasks/cc/text/text_classifier/BUILD @@ -63,6 +63,29 @@ cc_library( ], ) +cc_test( + name = "text_classifier_test", + srcs = ["text_classifier_test.cc"], + data = [ + "//mediapipe/tasks/testdata/text:bert_text_classifier_models", + "//mediapipe/tasks/testdata/text:text_classifier_models", + ], + deps = [ + ":text_classifier", + ":text_classifier_test_utils", + "//mediapipe/framework/deps:file_path", + "//mediapipe/framework/port:gtest_main", + "//mediapipe/tasks/cc:common", + "//mediapipe/tasks/cc/components/containers/proto:classifications_cc_proto", + "@com_google_absl//absl/flags:flag", + "@com_google_absl//absl/status", + "@com_google_absl//absl/status:statusor", + "@com_google_absl//absl/strings", + "@com_google_absl//absl/strings:cord", + "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util", + ], +) + cc_library( name = "text_classifier_test_utils", srcs = ["text_classifier_test_utils.cc"], diff --git a/mediapipe/tasks/cc/text/text_classifier/text_classifier_test.cc b/mediapipe/tasks/cc/text/text_classifier/text_classifier_test.cc index 5b33f6606..62837be8c 100644 --- a/mediapipe/tasks/cc/text/text_classifier/text_classifier_test.cc +++ b/mediapipe/tasks/cc/text/text_classifier/text_classifier_test.cc @@ -49,9 +49,6 @@ using ::mediapipe::tasks::kMediaPipeTasksPayload; using ::mediapipe::tasks::components::containers::proto::ClassificationResult; using ::testing::HasSubstr; using ::testing::Optional; -using ::testing::proto::Approximately; -using ::testing::proto::IgnoringRepeatedFieldOrdering; -using ::testing::proto::Partially; constexpr float kEpsilon = 0.001; constexpr int kMaxSeqLen = 128; @@ -110,127 +107,6 @@ TEST_F(TextClassifierTest, CreateSucceedsWithRegexModel) { MP_ASSERT_OK(TextClassifier::Create(std::move(options))); } -TEST_F(TextClassifierTest, TextClassifierWithBert) { - auto options = std::make_unique(); - options->base_options.model_asset_path = GetFullPath(kTestBertModelPath); - MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr classifier, - TextClassifier::Create(std::move(options))); - MP_ASSERT_OK_AND_ASSIGN( - ClassificationResult negative_result, - classifier->Classify("unflinchingly bleak and desperate")); - ASSERT_THAT(negative_result, - Partially(IgnoringRepeatedFieldOrdering(Approximately( - EqualsProto(R"pb( - classifications { - entries { - categories { category_name: "negative" score: 0.956 } - categories { category_name: "positive" score: 0.044 } - } - } - )pb"), - kEpsilon)))); - - MP_ASSERT_OK_AND_ASSIGN( - ClassificationResult positive_result, - classifier->Classify("it's a charming and often affecting journey")); - ASSERT_THAT(positive_result, - Partially(IgnoringRepeatedFieldOrdering(Approximately( - EqualsProto(R"pb( - classifications { - entries { - categories { category_name: "negative" score: 0.0 } - categories { category_name: "positive" score: 1.0 } - } - } - )pb"), - kEpsilon)))); - MP_ASSERT_OK(classifier->Close()); -} - -TEST_F(TextClassifierTest, TextClassifierWithIntInputs) { - auto options = std::make_unique(); - options->base_options.model_asset_path = GetFullPath(kTestRegexModelPath); - MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr classifier, - TextClassifier::Create(std::move(options))); - MP_ASSERT_OK_AND_ASSIGN(ClassificationResult negative_result, - classifier->Classify("What a waste of my time.")); - ASSERT_THAT(negative_result, - Partially(IgnoringRepeatedFieldOrdering(Approximately( - EqualsProto(R"pb( - classifications { - entries { - categories { category_name: "Negative" score: 0.813 } - categories { category_name: "Positive" score: 0.187 } - } - } - )pb"), - kEpsilon)))); - - MP_ASSERT_OK_AND_ASSIGN( - ClassificationResult positive_result, - classifier->Classify("This is the best movie I’ve seen in recent years. " - "Strongly recommend it!")); - ASSERT_THAT(positive_result, - Partially(IgnoringRepeatedFieldOrdering(Approximately( - EqualsProto(R"pb( - classifications { - entries { - categories { category_name: "Negative" score: 0.487 } - categories { category_name: "Positive" score: 0.513 } - } - } - )pb"), - kEpsilon)))); - MP_ASSERT_OK(classifier->Close()); -} - -TEST_F(TextClassifierTest, TextClassifierWithStringToBool) { - auto options = std::make_unique(); - options->base_options.model_asset_path = GetFullPath(kStringToBoolModelPath); - options->base_options.op_resolver = CreateCustomResolver(); - MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr classifier, - TextClassifier::Create(std::move(options))); - MP_ASSERT_OK_AND_ASSIGN(ClassificationResult result, - classifier->Classify("hello")); - ASSERT_THAT(result, Partially(IgnoringRepeatedFieldOrdering(EqualsProto(R"pb( - classifications { - entries { - categories { index: 1 score: 1 } - categories { index: 0 score: 1 } - categories { index: 2 score: 0 } - } - } - )pb")))); -} - -TEST_F(TextClassifierTest, BertLongPositive) { - std::stringstream ss_for_positive_review; - ss_for_positive_review - << "it's a charming and often affecting journey and this is a long"; - for (int i = 0; i < kMaxSeqLen; ++i) { - ss_for_positive_review << " long"; - } - ss_for_positive_review << " movie review"; - auto options = std::make_unique(); - options->base_options.model_asset_path = GetFullPath(kTestBertModelPath); - MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr classifier, - TextClassifier::Create(std::move(options))); - MP_ASSERT_OK_AND_ASSIGN(ClassificationResult result, - classifier->Classify(ss_for_positive_review.str())); - ASSERT_THAT(result, - Partially(IgnoringRepeatedFieldOrdering(Approximately( - EqualsProto(R"pb( - classifications { - entries { - categories { category_name: "negative" score: 0.014 } - categories { category_name: "positive" score: 0.986 } - } - } - )pb"), - kEpsilon)))); - MP_ASSERT_OK(classifier->Close()); -} - } // namespace } // namespace text_classifier } // namespace text diff --git a/mediapipe/tasks/cc/text/tokenizers/BUILD b/mediapipe/tasks/cc/text/tokenizers/BUILD index 048c7021d..e76d943c5 100644 --- a/mediapipe/tasks/cc/text/tokenizers/BUILD +++ b/mediapipe/tasks/cc/text/tokenizers/BUILD @@ -73,8 +73,6 @@ cc_library( ], ) -# TODO: This test fails in OSS - cc_library( name = "tokenizer_utils", srcs = ["tokenizer_utils.cc"], @@ -97,8 +95,6 @@ cc_library( ], ) -# TODO: This test fails in OSS - cc_library( name = "regex_tokenizer", srcs = [ diff --git a/mediapipe/tasks/testdata/text/BUILD b/mediapipe/tasks/testdata/text/BUILD index 6cce5ae41..14999a03e 100644 --- a/mediapipe/tasks/testdata/text/BUILD +++ b/mediapipe/tasks/testdata/text/BUILD @@ -76,9 +76,10 @@ filegroup( filegroup( name = "text_classifier_models", - srcs = glob([ - "test_model_text_classifier*.tflite", - ]), + srcs = [ + "test_model_text_classifier_bool_output.tflite", + "test_model_text_classifier_with_regex_tokenizer.tflite", + ], ) filegroup( From abed54ea30f9d14bbdf2fb2da1544f685d2346e4 Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Fri, 21 Oct 2022 18:15:22 -0700 Subject: [PATCH 054/125] Rename the mediapipe java image container from Image to MPImage. PiperOrigin-RevId: 482933122 --- .../framework/AndroidPacketCreator.java | 20 ++-- .../framework/image/BitmapExtractor.java | 14 +-- .../framework/image/BitmapImageBuilder.java | 12 +-- .../framework/image/BitmapImageContainer.java | 20 ++-- .../framework/image/ByteBufferExtractor.java | 97 ++++++++++--------- .../image/ByteBufferImageBuilder.java | 16 +-- .../image/ByteBufferImageContainer.java | 22 ++--- .../image/{Image.java => MPImage.java} | 58 +++++------ ...mageConsumer.java => MPImageConsumer.java} | 8 +- ...geContainer.java => MPImageContainer.java} | 4 +- ...mageProducer.java => MPImageProducer.java} | 8 +- ...Properties.java => MPImageProperties.java} | 36 +++---- .../framework/image/MediaImageBuilder.java | 15 +-- .../framework/image/MediaImageContainer.java | 31 +++--- .../framework/image/MediaImageExtractor.java | 19 ++-- .../examples/objectdetector/MainActivity.java | 7 +- .../ObjectDetectionResultImageView.java | 8 +- .../tasks/vision/core/BaseVisionTaskApi.java | 26 ++--- .../gesturerecognizer/GestureRecognizer.java | 26 ++--- .../imageclassifier/ImageClassifier.java | 36 +++---- .../vision/objectdetector/ObjectDetector.java | 25 ++--- .../GestureRecognizerTest.java | 10 +- .../imageclassifier/ImageClassifierTest.java | 12 +-- .../objectdetector/ObjectDetectorTest.java | 10 +- 24 files changed, 273 insertions(+), 267 deletions(-) rename mediapipe/java/com/google/mediapipe/framework/image/{Image.java => MPImage.java} (76%) rename mediapipe/java/com/google/mediapipe/framework/image/{ImageConsumer.java => MPImageConsumer.java} (87%) rename mediapipe/java/com/google/mediapipe/framework/image/{ImageContainer.java => MPImageContainer.java} (93%) rename mediapipe/java/com/google/mediapipe/framework/image/{ImageProducer.java => MPImageProducer.java} (75%) rename mediapipe/java/com/google/mediapipe/framework/image/{ImageProperties.java => MPImageProperties.java} (63%) diff --git a/mediapipe/java/com/google/mediapipe/framework/AndroidPacketCreator.java b/mediapipe/java/com/google/mediapipe/framework/AndroidPacketCreator.java index 4af9dae78..e3a878f91 100644 --- a/mediapipe/java/com/google/mediapipe/framework/AndroidPacketCreator.java +++ b/mediapipe/java/com/google/mediapipe/framework/AndroidPacketCreator.java @@ -17,8 +17,8 @@ package com.google.mediapipe.framework; import android.graphics.Bitmap; import com.google.mediapipe.framework.image.BitmapExtractor; import com.google.mediapipe.framework.image.ByteBufferExtractor; -import com.google.mediapipe.framework.image.Image; -import com.google.mediapipe.framework.image.ImageProperties; +import com.google.mediapipe.framework.image.MPImage; +import com.google.mediapipe.framework.image.MPImageProperties; import java.nio.ByteBuffer; // TODO: use Preconditions in this file. @@ -60,24 +60,24 @@ public class AndroidPacketCreator extends PacketCreator { } /** - * Creates an Image packet from an {@link Image}. + * Creates a MediaPipe Image packet from a {@link MPImage}. * *

The ImageContainerType must be IMAGE_CONTAINER_BYTEBUFFER or IMAGE_CONTAINER_BITMAP. */ - public Packet createImage(Image image) { + public Packet createImage(MPImage image) { // TODO: Choose the best storage from multiple containers. - ImageProperties properties = image.getContainedImageProperties().get(0); - if (properties.getStorageType() == Image.STORAGE_TYPE_BYTEBUFFER) { + MPImageProperties properties = image.getContainedImageProperties().get(0); + if (properties.getStorageType() == MPImage.STORAGE_TYPE_BYTEBUFFER) { ByteBuffer buffer = ByteBufferExtractor.extract(image); int numChannels = 0; switch (properties.getImageFormat()) { - case Image.IMAGE_FORMAT_RGBA: + case MPImage.IMAGE_FORMAT_RGBA: numChannels = 4; break; - case Image.IMAGE_FORMAT_RGB: + case MPImage.IMAGE_FORMAT_RGB: numChannels = 3; break; - case Image.IMAGE_FORMAT_ALPHA: + case MPImage.IMAGE_FORMAT_ALPHA: numChannels = 1; break; default: // fall out @@ -90,7 +90,7 @@ public class AndroidPacketCreator extends PacketCreator { int height = image.getHeight(); return createImage(buffer, width, height, numChannels); } - if (properties.getImageFormat() == Image.STORAGE_TYPE_BITMAP) { + if (properties.getImageFormat() == MPImage.STORAGE_TYPE_BITMAP) { Bitmap bitmap = BitmapExtractor.extract(image); if (bitmap.getConfig() != Bitmap.Config.ARGB_8888) { throw new UnsupportedOperationException("bitmap must use ARGB_8888 config."); diff --git a/mediapipe/java/com/google/mediapipe/framework/image/BitmapExtractor.java b/mediapipe/java/com/google/mediapipe/framework/image/BitmapExtractor.java index 4c6cebd4d..d6f50bf30 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/BitmapExtractor.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/BitmapExtractor.java @@ -18,29 +18,29 @@ package com.google.mediapipe.framework.image; import android.graphics.Bitmap; /** - * Utility for extracting {@link android.graphics.Bitmap} from {@link Image}. + * Utility for extracting {@link android.graphics.Bitmap} from {@link MPImage}. * - *

Currently it only supports {@link Image} with {@link Image#STORAGE_TYPE_BITMAP}, otherwise + *

Currently it only supports {@link MPImage} with {@link MPImage#STORAGE_TYPE_BITMAP}, otherwise * {@link IllegalArgumentException} will be thrown. */ public final class BitmapExtractor { /** - * Extracts a {@link android.graphics.Bitmap} from an {@link Image}. + * Extracts a {@link android.graphics.Bitmap} from a {@link MPImage}. * * @param image the image to extract {@link android.graphics.Bitmap} from. - * @return the {@link android.graphics.Bitmap} stored in {@link Image} + * @return the {@link android.graphics.Bitmap} stored in {@link MPImage} * @throws IllegalArgumentException when the extraction requires unsupported format or data type * conversions. */ - public static Bitmap extract(Image image) { - ImageContainer imageContainer = image.getContainer(Image.STORAGE_TYPE_BITMAP); + public static Bitmap extract(MPImage image) { + MPImageContainer imageContainer = image.getContainer(MPImage.STORAGE_TYPE_BITMAP); if (imageContainer != null) { return ((BitmapImageContainer) imageContainer).getBitmap(); } else { // TODO: Support ByteBuffer -> Bitmap conversion. throw new IllegalArgumentException( - "Extracting Bitmap from an Image created by objects other than Bitmap is not" + "Extracting Bitmap from a MPImage created by objects other than Bitmap is not" + " supported"); } } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/BitmapImageBuilder.java b/mediapipe/java/com/google/mediapipe/framework/image/BitmapImageBuilder.java index ea2ca6b1f..988cdf542 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/BitmapImageBuilder.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/BitmapImageBuilder.java @@ -22,7 +22,7 @@ import android.provider.MediaStore; import java.io.IOException; /** - * Builds {@link Image} from {@link android.graphics.Bitmap}. + * Builds {@link MPImage} from {@link android.graphics.Bitmap}. * *

You can pass in either mutable or immutable {@link android.graphics.Bitmap}. However once * {@link android.graphics.Bitmap} is passed in, to keep data integrity you shouldn't modify content @@ -49,7 +49,7 @@ public class BitmapImageBuilder { } /** - * Creates the builder to build {@link Image} from a file. + * Creates the builder to build {@link MPImage} from a file. * * @param context the application context. * @param uri the path to the resource file. @@ -58,15 +58,15 @@ public class BitmapImageBuilder { this(MediaStore.Images.Media.getBitmap(context.getContentResolver(), uri)); } - /** Sets value for {@link Image#getTimestamp()}. */ + /** Sets value for {@link MPImage#getTimestamp()}. */ BitmapImageBuilder setTimestamp(long timestamp) { this.timestamp = timestamp; return this; } - /** Builds an {@link Image} instance. */ - public Image build() { - return new Image( + /** Builds a {@link MPImage} instance. */ + public MPImage build() { + return new MPImage( new BitmapImageContainer(bitmap), timestamp, bitmap.getWidth(), bitmap.getHeight()); } } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/BitmapImageContainer.java b/mediapipe/java/com/google/mediapipe/framework/image/BitmapImageContainer.java index 0457e1e9b..6fbcac214 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/BitmapImageContainer.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/BitmapImageContainer.java @@ -16,19 +16,19 @@ limitations under the License. package com.google.mediapipe.framework.image; import android.graphics.Bitmap; -import com.google.mediapipe.framework.image.Image.ImageFormat; +import com.google.mediapipe.framework.image.MPImage.MPImageFormat; -class BitmapImageContainer implements ImageContainer { +class BitmapImageContainer implements MPImageContainer { private final Bitmap bitmap; - private final ImageProperties properties; + private final MPImageProperties properties; public BitmapImageContainer(Bitmap bitmap) { this.bitmap = bitmap; this.properties = - ImageProperties.builder() + MPImageProperties.builder() .setImageFormat(convertFormatCode(bitmap.getConfig())) - .setStorageType(Image.STORAGE_TYPE_BITMAP) + .setStorageType(MPImage.STORAGE_TYPE_BITMAP) .build(); } @@ -37,7 +37,7 @@ class BitmapImageContainer implements ImageContainer { } @Override - public ImageProperties getImageProperties() { + public MPImageProperties getImageProperties() { return properties; } @@ -46,15 +46,15 @@ class BitmapImageContainer implements ImageContainer { bitmap.recycle(); } - @ImageFormat + @MPImageFormat static int convertFormatCode(Bitmap.Config config) { switch (config) { case ALPHA_8: - return Image.IMAGE_FORMAT_ALPHA; + return MPImage.IMAGE_FORMAT_ALPHA; case ARGB_8888: - return Image.IMAGE_FORMAT_RGBA; + return MPImage.IMAGE_FORMAT_RGBA; default: - return Image.IMAGE_FORMAT_UNKNOWN; + return MPImage.IMAGE_FORMAT_UNKNOWN; } } } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferExtractor.java b/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferExtractor.java index a0e8c3dff..748a10667 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferExtractor.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferExtractor.java @@ -21,45 +21,45 @@ import android.graphics.Bitmap.Config; import android.os.Build.VERSION; import android.os.Build.VERSION_CODES; import com.google.auto.value.AutoValue; -import com.google.mediapipe.framework.image.Image.ImageFormat; +import com.google.mediapipe.framework.image.MPImage.MPImageFormat; import java.nio.ByteBuffer; import java.nio.ByteOrder; import java.util.Locale; /** - * Utility for extracting {@link ByteBuffer} from {@link Image}. + * Utility for extracting {@link ByteBuffer} from {@link MPImage}. * - *

Currently it only supports {@link Image} with {@link Image#STORAGE_TYPE_BYTEBUFFER}, otherwise - * {@link IllegalArgumentException} will be thrown. + *

Currently it only supports {@link MPImage} with {@link MPImage#STORAGE_TYPE_BYTEBUFFER}, + * otherwise {@link IllegalArgumentException} will be thrown. */ public class ByteBufferExtractor { /** - * Extracts a {@link ByteBuffer} from an {@link Image}. + * Extracts a {@link ByteBuffer} from a {@link MPImage}. * *

The returned {@link ByteBuffer} is a read-only view, with the first available {@link - * ImageProperties} whose storage type is {@code Image.STORAGE_TYPE_BYTEBUFFER}. + * MPImageProperties} whose storage type is {@code MPImage.STORAGE_TYPE_BYTEBUFFER}. * - * @see Image#getContainedImageProperties() + * @see MPImage#getContainedImageProperties() * @return A read-only {@link ByteBuffer}. * @throws IllegalArgumentException when the image doesn't contain a {@link ByteBuffer} storage. */ @SuppressLint("SwitchIntDef") - public static ByteBuffer extract(Image image) { - ImageContainer container = image.getContainer(); + public static ByteBuffer extract(MPImage image) { + MPImageContainer container = image.getContainer(); switch (container.getImageProperties().getStorageType()) { - case Image.STORAGE_TYPE_BYTEBUFFER: + case MPImage.STORAGE_TYPE_BYTEBUFFER: ByteBufferImageContainer byteBufferImageContainer = (ByteBufferImageContainer) container; return byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer(); default: throw new IllegalArgumentException( - "Extract ByteBuffer from an Image created by objects other than Bytebuffer is not" + "Extract ByteBuffer from a MPImage created by objects other than Bytebuffer is not" + " supported"); } } /** - * Extracts a readonly {@link ByteBuffer} in given {@code targetFormat} from an {@link Image}. + * Extracts a readonly {@link ByteBuffer} in given {@code targetFormat} from a {@link MPImage}. * *

Format conversion spec: * @@ -70,26 +70,26 @@ public class ByteBufferExtractor { * * @param image the image to extract buffer from. * @param targetFormat the image format of the result bytebuffer. - * @return the readonly {@link ByteBuffer} stored in {@link Image} + * @return the readonly {@link ByteBuffer} stored in {@link MPImage} * @throws IllegalArgumentException when the extraction requires unsupported format or data type * conversions. */ - static ByteBuffer extract(Image image, @ImageFormat int targetFormat) { - ImageContainer container; - ImageProperties byteBufferProperties = - ImageProperties.builder() - .setStorageType(Image.STORAGE_TYPE_BYTEBUFFER) + static ByteBuffer extract(MPImage image, @MPImageFormat int targetFormat) { + MPImageContainer container; + MPImageProperties byteBufferProperties = + MPImageProperties.builder() + .setStorageType(MPImage.STORAGE_TYPE_BYTEBUFFER) .setImageFormat(targetFormat) .build(); if ((container = image.getContainer(byteBufferProperties)) != null) { ByteBufferImageContainer byteBufferImageContainer = (ByteBufferImageContainer) container; return byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer(); - } else if ((container = image.getContainer(Image.STORAGE_TYPE_BYTEBUFFER)) != null) { + } else if ((container = image.getContainer(MPImage.STORAGE_TYPE_BYTEBUFFER)) != null) { ByteBufferImageContainer byteBufferImageContainer = (ByteBufferImageContainer) container; - @ImageFormat int sourceFormat = byteBufferImageContainer.getImageFormat(); + @MPImageFormat int sourceFormat = byteBufferImageContainer.getImageFormat(); return convertByteBuffer(byteBufferImageContainer.getByteBuffer(), sourceFormat, targetFormat) .asReadOnlyBuffer(); - } else if ((container = image.getContainer(Image.STORAGE_TYPE_BITMAP)) != null) { + } else if ((container = image.getContainer(MPImage.STORAGE_TYPE_BITMAP)) != null) { BitmapImageContainer bitmapImageContainer = (BitmapImageContainer) container; ByteBuffer byteBuffer = extractByteBufferFromBitmap(bitmapImageContainer.getBitmap(), targetFormat) @@ -98,85 +98,89 @@ public class ByteBufferExtractor { return byteBuffer; } else { throw new IllegalArgumentException( - "Extracting ByteBuffer from an Image created by objects other than Bitmap or" + "Extracting ByteBuffer from a MPImage created by objects other than Bitmap or" + " Bytebuffer is not supported"); } } - /** A wrapper for a {@link ByteBuffer} and its {@link ImageFormat}. */ + /** A wrapper for a {@link ByteBuffer} and its {@link MPImageFormat}. */ @AutoValue abstract static class Result { - /** Gets the {@link ByteBuffer} in the result of {@link ByteBufferExtractor#extract(Image)}. */ + /** + * Gets the {@link ByteBuffer} in the result of {@link ByteBufferExtractor#extract(MPImage)}. + */ public abstract ByteBuffer buffer(); - /** Gets the {@link ImageFormat} in the result of {@link ByteBufferExtractor#extract(Image)}. */ - @ImageFormat + /** + * Gets the {@link MPImageFormat} in the result of {@link ByteBufferExtractor#extract(MPImage)}. + */ + @MPImageFormat public abstract int format(); - static Result create(ByteBuffer buffer, @ImageFormat int imageFormat) { + static Result create(ByteBuffer buffer, @MPImageFormat int imageFormat) { return new AutoValue_ByteBufferExtractor_Result(buffer, imageFormat); } } /** - * Extracts a {@link ByteBuffer} in any available {@code imageFormat} from an {@link Image}. + * Extracts a {@link ByteBuffer} in any available {@code imageFormat} from a {@link MPImage}. * *

It will make the best effort to return an already existed {@link ByteBuffer} to avoid copy. * - * @return the readonly {@link ByteBuffer} stored in {@link Image} + * @return the readonly {@link ByteBuffer} stored in {@link MPImage} * @throws IllegalArgumentException when {@code image} doesn't contain {@link ByteBuffer} with * given {@code imageFormat} */ - static Result extractInRecommendedFormat(Image image) { - ImageContainer container; - if ((container = image.getContainer(Image.STORAGE_TYPE_BITMAP)) != null) { + static Result extractInRecommendedFormat(MPImage image) { + MPImageContainer container; + if ((container = image.getContainer(MPImage.STORAGE_TYPE_BITMAP)) != null) { Bitmap bitmap = ((BitmapImageContainer) container).getBitmap(); - @ImageFormat int format = adviseImageFormat(bitmap); + @MPImageFormat int format = adviseImageFormat(bitmap); Result result = Result.create(extractByteBufferFromBitmap(bitmap, format).asReadOnlyBuffer(), format); boolean unused = image.addContainer(new ByteBufferImageContainer(result.buffer(), result.format())); return result; - } else if ((container = image.getContainer(Image.STORAGE_TYPE_BYTEBUFFER)) != null) { + } else if ((container = image.getContainer(MPImage.STORAGE_TYPE_BYTEBUFFER)) != null) { ByteBufferImageContainer byteBufferImageContainer = (ByteBufferImageContainer) container; return Result.create( byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer(), byteBufferImageContainer.getImageFormat()); } else { throw new IllegalArgumentException( - "Extract ByteBuffer from an Image created by objects other than Bitmap or Bytebuffer" + "Extract ByteBuffer from a MPImage created by objects other than Bitmap or Bytebuffer" + " is not supported"); } } - @ImageFormat + @MPImageFormat private static int adviseImageFormat(Bitmap bitmap) { if (bitmap.getConfig() == Config.ARGB_8888) { - return Image.IMAGE_FORMAT_RGBA; + return MPImage.IMAGE_FORMAT_RGBA; } else { throw new IllegalArgumentException( String.format( - "Extracting ByteBuffer from an Image created by a Bitmap in config %s is not" + "Extracting ByteBuffer from a MPImage created by a Bitmap in config %s is not" + " supported", bitmap.getConfig())); } } private static ByteBuffer extractByteBufferFromBitmap( - Bitmap bitmap, @ImageFormat int imageFormat) { + Bitmap bitmap, @MPImageFormat int imageFormat) { if (VERSION.SDK_INT >= VERSION_CODES.JELLY_BEAN_MR1 && bitmap.isPremultiplied()) { throw new IllegalArgumentException( - "Extracting ByteBuffer from an Image created by a premultiplied Bitmap is not" + "Extracting ByteBuffer from a MPImage created by a premultiplied Bitmap is not" + " supported"); } if (bitmap.getConfig() == Config.ARGB_8888) { - if (imageFormat == Image.IMAGE_FORMAT_RGBA) { + if (imageFormat == MPImage.IMAGE_FORMAT_RGBA) { ByteBuffer buffer = ByteBuffer.allocateDirect(bitmap.getByteCount()); bitmap.copyPixelsToBuffer(buffer); buffer.rewind(); return buffer; - } else if (imageFormat == Image.IMAGE_FORMAT_RGB) { + } else if (imageFormat == MPImage.IMAGE_FORMAT_RGB) { // TODO: Try Use RGBA buffer to create RGB buffer which might be faster. int w = bitmap.getWidth(); int h = bitmap.getHeight(); @@ -196,14 +200,14 @@ public class ByteBufferExtractor { } throw new IllegalArgumentException( String.format( - "Extracting ByteBuffer from an Image created by Bitmap and convert from %s to format" + "Extracting ByteBuffer from a MPImage created by Bitmap and convert from %s to format" + " %d is not supported", bitmap.getConfig(), imageFormat)); } private static ByteBuffer convertByteBuffer( - ByteBuffer source, @ImageFormat int sourceFormat, @ImageFormat int targetFormat) { - if (sourceFormat == Image.IMAGE_FORMAT_RGB && targetFormat == Image.IMAGE_FORMAT_RGBA) { + ByteBuffer source, @MPImageFormat int sourceFormat, @MPImageFormat int targetFormat) { + if (sourceFormat == MPImage.IMAGE_FORMAT_RGB && targetFormat == MPImage.IMAGE_FORMAT_RGBA) { ByteBuffer target = ByteBuffer.allocateDirect(source.capacity() / 3 * 4); // Extend the buffer when the target is longer than the source. Use two cursors and sweep the // array reversely to convert in-place. @@ -221,7 +225,8 @@ public class ByteBufferExtractor { target.put(array, 0, target.capacity()); target.rewind(); return target; - } else if (sourceFormat == Image.IMAGE_FORMAT_RGBA && targetFormat == Image.IMAGE_FORMAT_RGB) { + } else if (sourceFormat == MPImage.IMAGE_FORMAT_RGBA + && targetFormat == MPImage.IMAGE_FORMAT_RGB) { ByteBuffer target = ByteBuffer.allocateDirect(source.capacity() / 4 * 3); // Shrink the buffer when the target is shorter than the source. Use two cursors and sweep the // array to convert in-place. diff --git a/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferImageBuilder.java b/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferImageBuilder.java index 07871da38..a650e4c33 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferImageBuilder.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferImageBuilder.java @@ -15,11 +15,11 @@ limitations under the License. package com.google.mediapipe.framework.image; -import com.google.mediapipe.framework.image.Image.ImageFormat; +import com.google.mediapipe.framework.image.MPImage.MPImageFormat; import java.nio.ByteBuffer; /** - * Builds a {@link Image} from a {@link ByteBuffer}. + * Builds a {@link MPImage} from a {@link ByteBuffer}. * *

You can pass in either mutable or immutable {@link ByteBuffer}. However once {@link * ByteBuffer} is passed in, to keep data integrity you shouldn't modify content in it. @@ -32,7 +32,7 @@ public class ByteBufferImageBuilder { private final ByteBuffer buffer; private final int width; private final int height; - @ImageFormat private final int imageFormat; + @MPImageFormat private final int imageFormat; // Optional fields. private long timestamp; @@ -49,7 +49,7 @@ public class ByteBufferImageBuilder { * @param imageFormat how the data encode the image. */ public ByteBufferImageBuilder( - ByteBuffer byteBuffer, int width, int height, @ImageFormat int imageFormat) { + ByteBuffer byteBuffer, int width, int height, @MPImageFormat int imageFormat) { this.buffer = byteBuffer; this.width = width; this.height = height; @@ -58,14 +58,14 @@ public class ByteBufferImageBuilder { this.timestamp = 0; } - /** Sets value for {@link Image#getTimestamp()}. */ + /** Sets value for {@link MPImage#getTimestamp()}. */ ByteBufferImageBuilder setTimestamp(long timestamp) { this.timestamp = timestamp; return this; } - /** Builds an {@link Image} instance. */ - public Image build() { - return new Image(new ByteBufferImageContainer(buffer, imageFormat), timestamp, width, height); + /** Builds a {@link MPImage} instance. */ + public MPImage build() { + return new MPImage(new ByteBufferImageContainer(buffer, imageFormat), timestamp, width, height); } } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferImageContainer.java b/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferImageContainer.java index 1c24c1dfd..82dbe32ca 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferImageContainer.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/ByteBufferImageContainer.java @@ -15,21 +15,19 @@ limitations under the License. package com.google.mediapipe.framework.image; -import com.google.mediapipe.framework.image.Image.ImageFormat; +import com.google.mediapipe.framework.image.MPImage.MPImageFormat; import java.nio.ByteBuffer; -class ByteBufferImageContainer implements ImageContainer { +class ByteBufferImageContainer implements MPImageContainer { private final ByteBuffer buffer; - private final ImageProperties properties; + private final MPImageProperties properties; - public ByteBufferImageContainer( - ByteBuffer buffer, - @ImageFormat int imageFormat) { + public ByteBufferImageContainer(ByteBuffer buffer, @MPImageFormat int imageFormat) { this.buffer = buffer; this.properties = - ImageProperties.builder() - .setStorageType(Image.STORAGE_TYPE_BYTEBUFFER) + MPImageProperties.builder() + .setStorageType(MPImage.STORAGE_TYPE_BYTEBUFFER) .setImageFormat(imageFormat) .build(); } @@ -39,14 +37,12 @@ class ByteBufferImageContainer implements ImageContainer { } @Override - public ImageProperties getImageProperties() { + public MPImageProperties getImageProperties() { return properties; } - /** - * Returns the image format. - */ - @ImageFormat + /** Returns the image format. */ + @MPImageFormat public int getImageFormat() { return properties.getImageFormat(); } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/Image.java b/mediapipe/java/com/google/mediapipe/framework/image/MPImage.java similarity index 76% rename from mediapipe/java/com/google/mediapipe/framework/image/Image.java rename to mediapipe/java/com/google/mediapipe/framework/image/MPImage.java index 49e63bcc0..e17cc4d30 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/Image.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/MPImage.java @@ -29,10 +29,10 @@ import java.util.Map.Entry; /** * The wrapper class for image objects. * - *

{@link Image} is designed to be an immutable image container, which could be shared + *

{@link MPImage} is designed to be an immutable image container, which could be shared * cross-platforms. * - *

To construct an {@link Image}, use the provided builders: + *

To construct a {@link MPImage}, use the provided builders: * *

    *
  • {@link ByteBufferImageBuilder} @@ -40,7 +40,7 @@ import java.util.Map.Entry; *
  • {@link MediaImageBuilder} *
* - *

{@link Image} uses reference counting to maintain internal storage. When it is created the + *

{@link MPImage} uses reference counting to maintain internal storage. When it is created the * reference count is 1. Developer can call {@link #close()} to reduce reference count to release * internal storage earlier, otherwise Java garbage collection will release the storage eventually. * @@ -53,7 +53,7 @@ import java.util.Map.Entry; *

  • {@link MediaImageExtractor} * */ -public class Image implements Closeable { +public class MPImage implements Closeable { /** Specifies the image format of an image. */ @IntDef({ @@ -69,7 +69,7 @@ public class Image implements Closeable { IMAGE_FORMAT_JPEG, }) @Retention(RetentionPolicy.SOURCE) - public @interface ImageFormat {} + public @interface MPImageFormat {} public static final int IMAGE_FORMAT_UNKNOWN = 0; public static final int IMAGE_FORMAT_RGBA = 1; @@ -98,14 +98,14 @@ public class Image implements Closeable { public static final int STORAGE_TYPE_IMAGE_PROXY = 4; /** - * Returns a list of supported image properties for this {@link Image}. + * Returns a list of supported image properties for this {@link MPImage}. * - *

    Currently {@link Image} only support single storage type so the size of return list will + *

    Currently {@link MPImage} only support single storage type so the size of return list will * always be 1. * - * @see ImageProperties + * @see MPImageProperties */ - public List getContainedImageProperties() { + public List getContainedImageProperties() { return Collections.singletonList(getContainer().getImageProperties()); } @@ -124,7 +124,7 @@ public class Image implements Closeable { return height; } - /** Acquires a reference on this {@link Image}. This will increase the reference count by 1. */ + /** Acquires a reference on this {@link MPImage}. This will increase the reference count by 1. */ private synchronized void acquire() { referenceCount += 1; } @@ -132,7 +132,7 @@ public class Image implements Closeable { /** * Removes a reference that was previously acquired or init. * - *

    When {@link Image} is created, it has 1 reference count. + *

    When {@link MPImage} is created, it has 1 reference count. * *

    When the reference count becomes 0, it will release the resource under the hood. */ @@ -141,24 +141,24 @@ public class Image implements Closeable { public synchronized void close() { referenceCount -= 1; if (referenceCount == 0) { - for (ImageContainer imageContainer : containerMap.values()) { + for (MPImageContainer imageContainer : containerMap.values()) { imageContainer.close(); } } } - /** Advanced API access for {@link Image}. */ + /** Advanced API access for {@link MPImage}. */ static final class Internal { /** - * Acquires a reference on this {@link Image}. This will increase the reference count by 1. + * Acquires a reference on this {@link MPImage}. This will increase the reference count by 1. * *

    This method is more useful for image consumer to acquire a reference so image resource * will not be closed accidentally. As image creator, normal developer doesn't need to call this * method. * - *

    The reference count is 1 when {@link Image} is created. Developer can call {@link - * #close()} to indicate it doesn't need this {@link Image} anymore. + *

    The reference count is 1 when {@link MPImage} is created. Developer can call {@link + * #close()} to indicate it doesn't need this {@link MPImage} anymore. * * @see #close() */ @@ -166,10 +166,10 @@ public class Image implements Closeable { image.acquire(); } - private final Image image; + private final MPImage image; - // Only Image creates the internal helper. - private Internal(Image image) { + // Only MPImage creates the internal helper. + private Internal(MPImage image) { this.image = image; } } @@ -179,15 +179,15 @@ public class Image implements Closeable { return new Internal(this); } - private final Map containerMap; + private final Map containerMap; private final long timestamp; private final int width; private final int height; private int referenceCount; - /** Constructs an {@link Image} with a built container. */ - Image(ImageContainer container, long timestamp, int width, int height) { + /** Constructs a {@link MPImage} with a built container. */ + MPImage(MPImageContainer container, long timestamp, int width, int height) { this.containerMap = new HashMap<>(); containerMap.put(container.getImageProperties(), container); this.timestamp = timestamp; @@ -201,10 +201,10 @@ public class Image implements Closeable { * * @return the current container. */ - ImageContainer getContainer() { + MPImageContainer getContainer() { // According to the design, in the future we will support multiple containers in one image. // Currently just return the original container. - // TODO: Cache multiple containers in Image. + // TODO: Cache multiple containers in MPImage. return containerMap.values().iterator().next(); } @@ -214,8 +214,8 @@ public class Image implements Closeable { *

    If there are multiple containers with required {@code storageType}, returns the first one. */ @Nullable - ImageContainer getContainer(@StorageType int storageType) { - for (Entry entry : containerMap.entrySet()) { + MPImageContainer getContainer(@StorageType int storageType) { + for (Entry entry : containerMap.entrySet()) { if (entry.getKey().getStorageType() == storageType) { return entry.getValue(); } @@ -225,13 +225,13 @@ public class Image implements Closeable { /** Gets container from required {@code imageProperties}. Returns {@code null} if non existed. */ @Nullable - ImageContainer getContainer(ImageProperties imageProperties) { + MPImageContainer getContainer(MPImageProperties imageProperties) { return containerMap.get(imageProperties); } /** Adds a new container if it doesn't exist. Returns {@code true} if it succeeds. */ - boolean addContainer(ImageContainer container) { - ImageProperties imageProperties = container.getImageProperties(); + boolean addContainer(MPImageContainer container) { + MPImageProperties imageProperties = container.getImageProperties(); if (containerMap.containsKey(imageProperties)) { return false; } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/ImageConsumer.java b/mediapipe/java/com/google/mediapipe/framework/image/MPImageConsumer.java similarity index 87% rename from mediapipe/java/com/google/mediapipe/framework/image/ImageConsumer.java rename to mediapipe/java/com/google/mediapipe/framework/image/MPImageConsumer.java index 18eed68c6..f9f343e93 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/ImageConsumer.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/MPImageConsumer.java @@ -14,14 +14,14 @@ limitations under the License. ==============================================================================*/ package com.google.mediapipe.framework.image; -/** Lightweight abstraction for an object that can receive {@link Image} */ -public interface ImageConsumer { +/** Lightweight abstraction for an object that can receive {@link MPImage} */ +public interface MPImageConsumer { /** - * Called when an {@link Image} is available. + * Called when a {@link MPImage} is available. * *

    The argument is only guaranteed to be available until this method returns. if you need to * extend its life time, acquire it, then release it when done. */ - void onNewImage(Image image); + void onNewMPImage(MPImage image); } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/ImageContainer.java b/mediapipe/java/com/google/mediapipe/framework/image/MPImageContainer.java similarity index 93% rename from mediapipe/java/com/google/mediapipe/framework/image/ImageContainer.java rename to mediapipe/java/com/google/mediapipe/framework/image/MPImageContainer.java index 727ec0893..674073b5b 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/ImageContainer.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/MPImageContainer.java @@ -16,9 +16,9 @@ limitations under the License. package com.google.mediapipe.framework.image; /** Manages internal image data storage. The interface is package-private. */ -interface ImageContainer { +interface MPImageContainer { /** Returns the properties of the contained image. */ - ImageProperties getImageProperties(); + MPImageProperties getImageProperties(); /** Close the image container and releases the image resource inside. */ void close(); diff --git a/mediapipe/java/com/google/mediapipe/framework/image/ImageProducer.java b/mediapipe/java/com/google/mediapipe/framework/image/MPImageProducer.java similarity index 75% rename from mediapipe/java/com/google/mediapipe/framework/image/ImageProducer.java rename to mediapipe/java/com/google/mediapipe/framework/image/MPImageProducer.java index 4f3641d6f..9783935d4 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/ImageProducer.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/MPImageProducer.java @@ -14,9 +14,9 @@ limitations under the License. ==============================================================================*/ package com.google.mediapipe.framework.image; -/** Lightweight abstraction for an object that produce {@link Image} */ -public interface ImageProducer { +/** Lightweight abstraction for an object that produce {@link MPImage} */ +public interface MPImageProducer { - /** Sets the consumer that receives the {@link Image}. */ - void setImageConsumer(ImageConsumer imageConsumer); + /** Sets the consumer that receives the {@link MPImage}. */ + void setMPImageConsumer(MPImageConsumer imageConsumer); } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/ImageProperties.java b/mediapipe/java/com/google/mediapipe/framework/image/MPImageProperties.java similarity index 63% rename from mediapipe/java/com/google/mediapipe/framework/image/ImageProperties.java rename to mediapipe/java/com/google/mediapipe/framework/image/MPImageProperties.java index e33b33e7f..6005ce77b 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/ImageProperties.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/MPImageProperties.java @@ -17,25 +17,25 @@ package com.google.mediapipe.framework.image; import com.google.auto.value.AutoValue; import com.google.auto.value.extension.memoized.Memoized; -import com.google.mediapipe.framework.image.Image.ImageFormat; -import com.google.mediapipe.framework.image.Image.StorageType; +import com.google.mediapipe.framework.image.MPImage.MPImageFormat; +import com.google.mediapipe.framework.image.MPImage.StorageType; /** Groups a set of properties to describe how an image is stored. */ @AutoValue -public abstract class ImageProperties { +public abstract class MPImageProperties { /** * Gets the pixel format of the image. * - * @see Image.ImageFormat + * @see MPImage.MPImageFormat */ - @ImageFormat + @MPImageFormat public abstract int getImageFormat(); /** * Gets the storage type of the image. * - * @see Image.StorageType + * @see MPImage.StorageType */ @StorageType public abstract int getStorageType(); @@ -45,36 +45,36 @@ public abstract class ImageProperties { public abstract int hashCode(); /** - * Creates a builder of {@link ImageProperties}. + * Creates a builder of {@link MPImageProperties}. * - * @see ImageProperties.Builder + * @see MPImageProperties.Builder */ static Builder builder() { - return new AutoValue_ImageProperties.Builder(); + return new AutoValue_MPImageProperties.Builder(); } - /** Builds a {@link ImageProperties}. */ + /** Builds a {@link MPImageProperties}. */ @AutoValue.Builder abstract static class Builder { /** - * Sets the {@link Image.ImageFormat}. + * Sets the {@link MPImage.MPImageFormat}. * - * @see ImageProperties#getImageFormat + * @see MPImageProperties#getImageFormat */ - abstract Builder setImageFormat(@ImageFormat int value); + abstract Builder setImageFormat(@MPImageFormat int value); /** - * Sets the {@link Image.StorageType}. + * Sets the {@link MPImage.StorageType}. * - * @see ImageProperties#getStorageType + * @see MPImageProperties#getStorageType */ abstract Builder setStorageType(@StorageType int value); - /** Builds the {@link ImageProperties}. */ - abstract ImageProperties build(); + /** Builds the {@link MPImageProperties}. */ + abstract MPImageProperties build(); } // Hide the constructor. - ImageProperties() {} + MPImageProperties() {} } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/MediaImageBuilder.java b/mediapipe/java/com/google/mediapipe/framework/image/MediaImageBuilder.java index e351a87fd..9e719715d 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/MediaImageBuilder.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/MediaImageBuilder.java @@ -15,11 +15,12 @@ limitations under the License. package com.google.mediapipe.framework.image; +import android.media.Image; import android.os.Build.VERSION_CODES; import androidx.annotation.RequiresApi; /** - * Builds {@link Image} from {@link android.media.Image}. + * Builds {@link MPImage} from {@link android.media.Image}. * *

    Once {@link android.media.Image} is passed in, to keep data integrity you shouldn't modify * content in it. @@ -30,7 +31,7 @@ import androidx.annotation.RequiresApi; public class MediaImageBuilder { // Mandatory fields. - private final android.media.Image mediaImage; + private final Image mediaImage; // Optional fields. private long timestamp; @@ -40,20 +41,20 @@ public class MediaImageBuilder { * * @param mediaImage image data object. */ - public MediaImageBuilder(android.media.Image mediaImage) { + public MediaImageBuilder(Image mediaImage) { this.mediaImage = mediaImage; this.timestamp = 0; } - /** Sets value for {@link Image#getTimestamp()}. */ + /** Sets value for {@link MPImage#getTimestamp()}. */ MediaImageBuilder setTimestamp(long timestamp) { this.timestamp = timestamp; return this; } - /** Builds an {@link Image} instance. */ - public Image build() { - return new Image( + /** Builds a {@link MPImage} instance. */ + public MPImage build() { + return new MPImage( new MediaImageContainer(mediaImage), timestamp, mediaImage.getWidth(), diff --git a/mediapipe/java/com/google/mediapipe/framework/image/MediaImageContainer.java b/mediapipe/java/com/google/mediapipe/framework/image/MediaImageContainer.java index 144b64def..864c76df2 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/MediaImageContainer.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/MediaImageContainer.java @@ -15,33 +15,34 @@ limitations under the License. package com.google.mediapipe.framework.image; +import android.media.Image; import android.os.Build; import android.os.Build.VERSION; import android.os.Build.VERSION_CODES; import androidx.annotation.RequiresApi; -import com.google.mediapipe.framework.image.Image.ImageFormat; +import com.google.mediapipe.framework.image.MPImage.MPImageFormat; @RequiresApi(VERSION_CODES.KITKAT) -class MediaImageContainer implements ImageContainer { +class MediaImageContainer implements MPImageContainer { - private final android.media.Image mediaImage; - private final ImageProperties properties; + private final Image mediaImage; + private final MPImageProperties properties; - public MediaImageContainer(android.media.Image mediaImage) { + public MediaImageContainer(Image mediaImage) { this.mediaImage = mediaImage; this.properties = - ImageProperties.builder() - .setStorageType(Image.STORAGE_TYPE_MEDIA_IMAGE) + MPImageProperties.builder() + .setStorageType(MPImage.STORAGE_TYPE_MEDIA_IMAGE) .setImageFormat(convertFormatCode(mediaImage.getFormat())) .build(); } - public android.media.Image getImage() { + public Image getImage() { return mediaImage; } @Override - public ImageProperties getImageProperties() { + public MPImageProperties getImageProperties() { return properties; } @@ -50,24 +51,24 @@ class MediaImageContainer implements ImageContainer { mediaImage.close(); } - @ImageFormat + @MPImageFormat static int convertFormatCode(int graphicsFormat) { // We only cover the format mentioned in // https://developer.android.com/reference/android/media/Image#getFormat() if (VERSION.SDK_INT >= Build.VERSION_CODES.M) { if (graphicsFormat == android.graphics.ImageFormat.FLEX_RGBA_8888) { - return Image.IMAGE_FORMAT_RGBA; + return MPImage.IMAGE_FORMAT_RGBA; } else if (graphicsFormat == android.graphics.ImageFormat.FLEX_RGB_888) { - return Image.IMAGE_FORMAT_RGB; + return MPImage.IMAGE_FORMAT_RGB; } } switch (graphicsFormat) { case android.graphics.ImageFormat.JPEG: - return Image.IMAGE_FORMAT_JPEG; + return MPImage.IMAGE_FORMAT_JPEG; case android.graphics.ImageFormat.YUV_420_888: - return Image.IMAGE_FORMAT_YUV_420_888; + return MPImage.IMAGE_FORMAT_YUV_420_888; default: - return Image.IMAGE_FORMAT_UNKNOWN; + return MPImage.IMAGE_FORMAT_UNKNOWN; } } } diff --git a/mediapipe/java/com/google/mediapipe/framework/image/MediaImageExtractor.java b/mediapipe/java/com/google/mediapipe/framework/image/MediaImageExtractor.java index 718cb471f..76bb5a5ec 100644 --- a/mediapipe/java/com/google/mediapipe/framework/image/MediaImageExtractor.java +++ b/mediapipe/java/com/google/mediapipe/framework/image/MediaImageExtractor.java @@ -15,13 +15,14 @@ limitations under the License. package com.google.mediapipe.framework.image; +import android.media.Image; import android.os.Build.VERSION_CODES; import androidx.annotation.RequiresApi; /** - * Utility for extracting {@link android.media.Image} from {@link Image}. + * Utility for extracting {@link android.media.Image} from {@link MPImage}. * - *

    Currently it only supports {@link Image} with {@link Image#STORAGE_TYPE_MEDIA_IMAGE}, + *

    Currently it only supports {@link MPImage} with {@link MPImage#STORAGE_TYPE_MEDIA_IMAGE}, * otherwise {@link IllegalArgumentException} will be thrown. */ @RequiresApi(VERSION_CODES.KITKAT) @@ -30,20 +31,20 @@ public class MediaImageExtractor { private MediaImageExtractor() {} /** - * Extracts a {@link android.media.Image} from an {@link Image}. Currently it only works for - * {@link Image} that built from {@link MediaImageBuilder}. + * Extracts a {@link android.media.Image} from a {@link MPImage}. Currently it only works for + * {@link MPImage} that built from {@link MediaImageBuilder}. * * @param image the image to extract {@link android.media.Image} from. - * @return {@link android.media.Image} that stored in {@link Image}. + * @return {@link android.media.Image} that stored in {@link MPImage}. * @throws IllegalArgumentException if the extraction failed. */ - public static android.media.Image extract(Image image) { - ImageContainer container; - if ((container = image.getContainer(Image.STORAGE_TYPE_MEDIA_IMAGE)) != null) { + public static Image extract(MPImage image) { + MPImageContainer container; + if ((container = image.getContainer(MPImage.STORAGE_TYPE_MEDIA_IMAGE)) != null) { return ((MediaImageContainer) container).getImage(); } throw new IllegalArgumentException( - "Extract Media Image from an Image created by objects other than Media Image" + "Extract Media Image from a MPImage created by objects other than Media Image" + " is not supported"); } } diff --git a/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/MainActivity.java b/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/MainActivity.java index 7f7ec1389..11c8c1837 100644 --- a/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/MainActivity.java +++ b/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/MainActivity.java @@ -30,7 +30,7 @@ import androidx.activity.result.contract.ActivityResultContracts; import androidx.exifinterface.media.ExifInterface; // ContentResolver dependency import com.google.mediapipe.framework.image.BitmapImageBuilder; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.core.BaseOptions; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.objectdetector.ObjectDetectionResult; @@ -98,7 +98,7 @@ public class MainActivity extends AppCompatActivity { Log.e(TAG, "Bitmap rotation error:" + e); } if (bitmap != null) { - Image image = new BitmapImageBuilder(bitmap).build(); + MPImage image = new BitmapImageBuilder(bitmap).build(); ObjectDetectionResult detectionResult = objectDetector.detect(image); imageView.setData(image, detectionResult); runOnUiThread(() -> imageView.update()); @@ -144,7 +144,8 @@ public class MainActivity extends AppCompatActivity { MediaMetadataRetriever.METADATA_KEY_VIDEO_FRAME_COUNT)); long frameIntervalMs = duration / numFrames; for (int i = 0; i < numFrames; ++i) { - Image image = new BitmapImageBuilder(metaRetriever.getFrameAtIndex(i)).build(); + MPImage image = + new BitmapImageBuilder(metaRetriever.getFrameAtIndex(i)).build(); ObjectDetectionResult detectionResult = objectDetector.detectForVideo(image, frameIntervalMs * i); // Currently only annotates the detection result on the first video frame and diff --git a/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/ObjectDetectionResultImageView.java b/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/ObjectDetectionResultImageView.java index 94a4a90dc..283e48857 100644 --- a/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/ObjectDetectionResultImageView.java +++ b/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/ObjectDetectionResultImageView.java @@ -22,7 +22,7 @@ import android.graphics.Matrix; import android.graphics.Paint; import androidx.appcompat.widget.AppCompatImageView; import com.google.mediapipe.framework.image.BitmapExtractor; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.components.containers.Detection; import com.google.mediapipe.tasks.vision.objectdetector.ObjectDetectionResult; @@ -40,12 +40,12 @@ public class ObjectDetectionResultImageView extends AppCompatImageView { } /** - * Sets an {@link Image} and an {@link ObjectDetectionResult} to render. + * Sets a {@link MPImage} and an {@link ObjectDetectionResult} to render. * - * @param image an {@link Image} object for annotation. + * @param image a {@link MPImage} object for annotation. * @param result an {@link ObjectDetectionResult} object that contains the detection result. */ - public void setData(Image image, ObjectDetectionResult result) { + public void setData(MPImage image, ObjectDetectionResult result) { if (image == null || result == null) { return; } diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/BaseVisionTaskApi.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/BaseVisionTaskApi.java index 7ab8e75a1..49dab408c 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/BaseVisionTaskApi.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/BaseVisionTaskApi.java @@ -19,7 +19,7 @@ import com.google.mediapipe.formats.proto.RectProto.NormalizedRect; import com.google.mediapipe.framework.MediaPipeException; import com.google.mediapipe.framework.Packet; import com.google.mediapipe.framework.ProtoUtil; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.core.TaskResult; import com.google.mediapipe.tasks.core.TaskRunner; import java.util.HashMap; @@ -77,11 +77,11 @@ public class BaseVisionTaskApi implements AutoCloseable { * A synchronous method to process single image inputs. The call blocks the current thread until a * failure status or a successful result is returned. * - * @param image a MediaPipe {@link Image} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. * @throws MediaPipeException if the task is not in the image mode or requires a normalized rect * input. */ - protected TaskResult processImageData(Image image) { + protected TaskResult processImageData(MPImage image) { if (runningMode != RunningMode.IMAGE) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), @@ -102,13 +102,13 @@ public class BaseVisionTaskApi implements AutoCloseable { * A synchronous method to process single image inputs. The call blocks the current thread until a * failure status or a successful result is returned. * - * @param image a MediaPipe {@link Image} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. * @param roi a {@link RectF} defining the region-of-interest to process in the image. Coordinates * are expected to be specified as normalized values in [0,1]. * @throws MediaPipeException if the task is not in the image mode or doesn't require a normalized * rect. */ - protected TaskResult processImageData(Image image, RectF roi) { + protected TaskResult processImageData(MPImage image, RectF roi) { if (runningMode != RunningMode.IMAGE) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), @@ -132,12 +132,12 @@ public class BaseVisionTaskApi implements AutoCloseable { * A synchronous method to process continuous video frames. The call blocks the current thread * until a failure status or a successful result is returned. * - * @param image a MediaPipe {@link Image} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. * @param timestampMs the corresponding timestamp of the input image in milliseconds. * @throws MediaPipeException if the task is not in the video mode or requires a normalized rect * input. */ - protected TaskResult processVideoData(Image image, long timestampMs) { + protected TaskResult processVideoData(MPImage image, long timestampMs) { if (runningMode != RunningMode.VIDEO) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), @@ -158,14 +158,14 @@ public class BaseVisionTaskApi implements AutoCloseable { * A synchronous method to process continuous video frames. The call blocks the current thread * until a failure status or a successful result is returned. * - * @param image a MediaPipe {@link Image} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. * @param roi a {@link RectF} defining the region-of-interest to process in the image. Coordinates * are expected to be specified as normalized values in [0,1]. * @param timestampMs the corresponding timestamp of the input image in milliseconds. * @throws MediaPipeException if the task is not in the video mode or doesn't require a normalized * rect. */ - protected TaskResult processVideoData(Image image, RectF roi, long timestampMs) { + protected TaskResult processVideoData(MPImage image, RectF roi, long timestampMs) { if (runningMode != RunningMode.VIDEO) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), @@ -189,12 +189,12 @@ public class BaseVisionTaskApi implements AutoCloseable { * An asynchronous method to send live stream data to the {@link TaskRunner}. The results will be * available in the user-defined result listener. * - * @param image a MediaPipe {@link Image} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. * @param timestampMs the corresponding timestamp of the input image in milliseconds. * @throws MediaPipeException if the task is not in the video mode or requires a normalized rect * input. */ - protected void sendLiveStreamData(Image image, long timestampMs) { + protected void sendLiveStreamData(MPImage image, long timestampMs) { if (runningMode != RunningMode.LIVE_STREAM) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), @@ -215,14 +215,14 @@ public class BaseVisionTaskApi implements AutoCloseable { * An asynchronous method to send live stream data to the {@link TaskRunner}. The results will be * available in the user-defined result listener. * - * @param image a MediaPipe {@link Image} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. * @param roi a {@link RectF} defining the region-of-interest to process in the image. Coordinates * are expected to be specified as normalized values in [0,1]. * @param timestampMs the corresponding timestamp of the input image in milliseconds. * @throws MediaPipeException if the task is not in the video mode or doesn't require a normalized * rect. */ - protected void sendLiveStreamData(Image image, RectF roi, long timestampMs) { + protected void sendLiveStreamData(MPImage image, RectF roi, long timestampMs) { if (runningMode != RunningMode.LIVE_STREAM) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java index 660645d9c..560508903 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java @@ -26,7 +26,7 @@ import com.google.mediapipe.framework.AndroidPacketGetter; import com.google.mediapipe.framework.Packet; import com.google.mediapipe.framework.PacketGetter; import com.google.mediapipe.framework.image.BitmapImageBuilder; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.components.processors.proto.ClassifierOptionsProto; import com.google.mediapipe.tasks.core.BaseOptions; import com.google.mediapipe.tasks.core.ErrorListener; @@ -59,7 +59,7 @@ import java.util.Optional; * Model Maker. See . * *

      - *
    • Input image {@link Image} + *
    • Input image {@link MPImage} *
        *
      • The image that gesture recognition runs on. *
      @@ -151,9 +151,9 @@ public final class GestureRecognizer extends BaseVisionTaskApi { public static GestureRecognizer createFromOptions( Context context, GestureRecognizerOptions recognizerOptions) { // TODO: Consolidate OutputHandler and TaskRunner. - OutputHandler handler = new OutputHandler<>(); + OutputHandler handler = new OutputHandler<>(); handler.setOutputPacketConverter( - new OutputHandler.OutputPacketConverter() { + new OutputHandler.OutputPacketConverter() { @Override public GestureRecognitionResult convertToTaskResult(List packets) { // If there is no hands detected in the image, just returns empty lists. @@ -178,7 +178,7 @@ public final class GestureRecognizer extends BaseVisionTaskApi { } @Override - public Image convertToTaskInput(List packets) { + public MPImage convertToTaskInput(List packets) { return new BitmapImageBuilder( AndroidPacketGetter.getBitmapFromRgb(packets.get(IMAGE_OUT_STREAM_INDEX))) .build(); @@ -222,10 +222,10 @@ public final class GestureRecognizer extends BaseVisionTaskApi { *
    • {@link Bitmap.Config.ARGB_8888} *
    * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @throws MediaPipeException if there is an internal error. */ - public GestureRecognitionResult recognize(Image inputImage) { + public GestureRecognitionResult recognize(MPImage inputImage) { // TODO: add proper support for rotations. return (GestureRecognitionResult) processImageData(inputImage, buildFullImageRectF()); } @@ -243,11 +243,11 @@ public final class GestureRecognizer extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param inputTimestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public GestureRecognitionResult recognizeForVideo(Image inputImage, long inputTimestampMs) { + public GestureRecognitionResult recognizeForVideo(MPImage inputImage, long inputTimestampMs) { // TODO: add proper support for rotations. return (GestureRecognitionResult) processVideoData(inputImage, buildFullImageRectF(), inputTimestampMs); @@ -267,11 +267,11 @@ public final class GestureRecognizer extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param inputTimestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public void recognizeAsync(Image inputImage, long inputTimestampMs) { + public void recognizeAsync(MPImage inputImage, long inputTimestampMs) { // TODO: add proper support for rotations. sendLiveStreamData(inputImage, buildFullImageRectF(), inputTimestampMs); } @@ -333,7 +333,7 @@ public final class GestureRecognizer extends BaseVisionTaskApi { * recognizer is in the live stream mode. */ public abstract Builder setResultListener( - ResultListener value); + ResultListener value); /** Sets an optional error listener. */ public abstract Builder setErrorListener(ErrorListener value); @@ -386,7 +386,7 @@ public final class GestureRecognizer extends BaseVisionTaskApi { // TODO update gesture confidence options after score merging calculator is ready. abstract Optional minGestureConfidence(); - abstract Optional> resultListener(); + abstract Optional> resultListener(); abstract Optional errorListener(); diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java index e8e263b71..e7d9e4ea1 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java @@ -25,7 +25,7 @@ import com.google.mediapipe.framework.Packet; import com.google.mediapipe.framework.PacketGetter; import com.google.mediapipe.framework.ProtoUtil; import com.google.mediapipe.framework.image.BitmapImageBuilder; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.components.container.proto.ClassificationsProto; import com.google.mediapipe.tasks.components.processors.ClassifierOptions; import com.google.mediapipe.tasks.core.BaseOptions; @@ -164,9 +164,9 @@ public final class ImageClassifier extends BaseVisionTaskApi { * @throws MediaPipeException if there is an error during {@link ImageClassifier} creation. */ public static ImageClassifier createFromOptions(Context context, ImageClassifierOptions options) { - OutputHandler handler = new OutputHandler<>(); + OutputHandler handler = new OutputHandler<>(); handler.setOutputPacketConverter( - new OutputHandler.OutputPacketConverter() { + new OutputHandler.OutputPacketConverter() { @Override public ImageClassificationResult convertToTaskResult(List packets) { try { @@ -182,7 +182,7 @@ public final class ImageClassifier extends BaseVisionTaskApi { } @Override - public Image convertToTaskInput(List packets) { + public MPImage convertToTaskInput(List packets) { return new BitmapImageBuilder( AndroidPacketGetter.getBitmapFromRgb(packets.get(IMAGE_OUT_STREAM_INDEX))) .build(); @@ -225,10 +225,10 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @throws MediaPipeException if there is an internal error. */ - public ImageClassificationResult classify(Image inputImage) { + public ImageClassificationResult classify(MPImage inputImage) { return (ImageClassificationResult) processImageData(inputImage, buildFullImageRectF()); } @@ -242,12 +242,12 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param roi a {@link RectF} specifying the region of interest on which to perform * classification. Coordinates are expected to be specified as normalized values in [0,1]. * @throws MediaPipeException if there is an internal error. */ - public ImageClassificationResult classify(Image inputImage, RectF roi) { + public ImageClassificationResult classify(MPImage inputImage, RectF roi) { return (ImageClassificationResult) processImageData(inputImage, roi); } @@ -264,11 +264,11 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param inputTimestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public ImageClassificationResult classifyForVideo(Image inputImage, long inputTimestampMs) { + public ImageClassificationResult classifyForVideo(MPImage inputImage, long inputTimestampMs) { return (ImageClassificationResult) processVideoData(inputImage, buildFullImageRectF(), inputTimestampMs); } @@ -286,14 +286,14 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param roi a {@link RectF} specifying the region of interest on which to perform * classification. Coordinates are expected to be specified as normalized values in [0,1]. * @param inputTimestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ public ImageClassificationResult classifyForVideo( - Image inputImage, RectF roi, long inputTimestampMs) { + MPImage inputImage, RectF roi, long inputTimestampMs) { return (ImageClassificationResult) processVideoData(inputImage, roi, inputTimestampMs); } @@ -311,11 +311,11 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param inputTimestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public void classifyAsync(Image inputImage, long inputTimestampMs) { + public void classifyAsync(MPImage inputImage, long inputTimestampMs) { sendLiveStreamData(inputImage, buildFullImageRectF(), inputTimestampMs); } @@ -334,13 +334,13 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param roi a {@link RectF} specifying the region of interest on which to perform * classification. Coordinates are expected to be specified as normalized values in [0,1]. * @param inputTimestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public void classifyAsync(Image inputImage, RectF roi, long inputTimestampMs) { + public void classifyAsync(MPImage inputImage, RectF roi, long inputTimestampMs) { sendLiveStreamData(inputImage, roi, inputTimestampMs); } @@ -379,7 +379,7 @@ public final class ImageClassifier extends BaseVisionTaskApi { * the image classifier is in the live stream mode. */ public abstract Builder setResultListener( - ResultListener resultListener); + ResultListener resultListener); /** Sets an optional {@link ErrorListener}. */ public abstract Builder setErrorListener(ErrorListener errorListener); @@ -416,7 +416,7 @@ public final class ImageClassifier extends BaseVisionTaskApi { abstract Optional classifierOptions(); - abstract Optional> resultListener(); + abstract Optional> resultListener(); abstract Optional errorListener(); diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetector.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetector.java index bfce62791..0f2e7b540 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetector.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetector.java @@ -22,7 +22,7 @@ import com.google.mediapipe.framework.AndroidPacketGetter; import com.google.mediapipe.framework.Packet; import com.google.mediapipe.framework.PacketGetter; import com.google.mediapipe.framework.image.BitmapImageBuilder; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.core.BaseOptions; import com.google.mediapipe.tasks.core.ErrorListener; import com.google.mediapipe.tasks.core.OutputHandler; @@ -162,9 +162,9 @@ public final class ObjectDetector extends BaseVisionTaskApi { public static ObjectDetector createFromOptions( Context context, ObjectDetectorOptions detectorOptions) { // TODO: Consolidate OutputHandler and TaskRunner. - OutputHandler handler = new OutputHandler<>(); + OutputHandler handler = new OutputHandler<>(); handler.setOutputPacketConverter( - new OutputHandler.OutputPacketConverter() { + new OutputHandler.OutputPacketConverter() { @Override public ObjectDetectionResult convertToTaskResult(List packets) { return ObjectDetectionResult.create( @@ -174,7 +174,7 @@ public final class ObjectDetector extends BaseVisionTaskApi { } @Override - public Image convertToTaskInput(List packets) { + public MPImage convertToTaskInput(List packets) { return new BitmapImageBuilder( AndroidPacketGetter.getBitmapFromRgb(packets.get(IMAGE_OUT_STREAM_INDEX))) .build(); @@ -217,10 +217,10 @@ public final class ObjectDetector extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @throws MediaPipeException if there is an internal error. */ - public ObjectDetectionResult detect(Image inputImage) { + public ObjectDetectionResult detect(MPImage inputImage) { return (ObjectDetectionResult) processImageData(inputImage); } @@ -237,11 +237,11 @@ public final class ObjectDetector extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param inputTimestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public ObjectDetectionResult detectForVideo(Image inputImage, long inputTimestampMs) { + public ObjectDetectionResult detectForVideo(MPImage inputImage, long inputTimestampMs) { return (ObjectDetectionResult) processVideoData(inputImage, inputTimestampMs); } @@ -259,11 +259,11 @@ public final class ObjectDetector extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link Image} object for processing. + * @param inputImage a MediaPipe {@link MPImage} object for processing. * @param inputTimestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public void detectAsync(Image inputImage, long inputTimestampMs) { + public void detectAsync(MPImage inputImage, long inputTimestampMs) { sendLiveStreamData(inputImage, inputTimestampMs); } @@ -333,7 +333,8 @@ public final class ObjectDetector extends BaseVisionTaskApi { * Sets the {@link ResultListener} to receive the detection results asynchronously when the * object detector is in the live stream mode. */ - public abstract Builder setResultListener(ResultListener value); + public abstract Builder setResultListener( + ResultListener value); /** Sets an optional {@link ErrorListener}}. */ public abstract Builder setErrorListener(ErrorListener value); @@ -378,7 +379,7 @@ public final class ObjectDetector extends BaseVisionTaskApi { abstract List categoryDenylist(); - abstract Optional> resultListener(); + abstract Optional> resultListener(); abstract Optional errorListener(); diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java index efec02b2a..8beea96ac 100644 --- a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java @@ -25,7 +25,7 @@ import com.google.common.truth.Correspondence; import com.google.mediapipe.formats.proto.ClassificationProto; import com.google.mediapipe.framework.MediaPipeException; import com.google.mediapipe.framework.image.BitmapImageBuilder; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.components.containers.Category; import com.google.mediapipe.tasks.components.containers.Landmark; import com.google.mediapipe.tasks.components.containers.proto.LandmarksDetectionResultProto.LandmarksDetectionResult; @@ -357,7 +357,7 @@ public class GestureRecognizerTest { @Test public void recognize_failsWithOutOfOrderInputTimestamps() throws Exception { - Image image = getImageFromAsset(THUMB_UP_IMAGE); + MPImage image = getImageFromAsset(THUMB_UP_IMAGE); GestureRecognitionResult expectedResult = getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); GestureRecognizerOptions options = @@ -391,7 +391,7 @@ public class GestureRecognizerTest { @Test public void recognize_successWithLiveSteamMode() throws Exception { - Image image = getImageFromAsset(THUMB_UP_IMAGE); + MPImage image = getImageFromAsset(THUMB_UP_IMAGE); GestureRecognitionResult expectedResult = getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); GestureRecognizerOptions options = @@ -420,7 +420,7 @@ public class GestureRecognizerTest { } } - private static Image getImageFromAsset(String filePath) throws Exception { + private static MPImage getImageFromAsset(String filePath) throws Exception { AssetManager assetManager = ApplicationProvider.getApplicationContext().getAssets(); InputStream istr = assetManager.open(filePath); return new BitmapImageBuilder(BitmapFactory.decodeStream(istr)).build(); @@ -487,7 +487,7 @@ public class GestureRecognizerTest { assertThat(expectedGesture.categoryName()).isEqualTo(expectedGesture.categoryName()); } - private static void assertImageSizeIsExpected(Image inputImage) { + private static void assertImageSizeIsExpected(MPImage inputImage) { assertThat(inputImage).isNotNull(); assertThat(inputImage.getWidth()).isEqualTo(IMAGE_WIDTH); assertThat(inputImage.getHeight()).isEqualTo(IMAGE_HEIGHT); diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifierTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifierTest.java index e02e8ebe7..966e4ff4a 100644 --- a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifierTest.java +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifierTest.java @@ -24,7 +24,7 @@ import androidx.test.core.app.ApplicationProvider; import androidx.test.ext.junit.runners.AndroidJUnit4; import com.google.mediapipe.framework.MediaPipeException; import com.google.mediapipe.framework.image.BitmapImageBuilder; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.components.containers.Category; import com.google.mediapipe.tasks.components.processors.ClassifierOptions; import com.google.mediapipe.tasks.core.BaseOptions; @@ -342,7 +342,7 @@ public class ImageClassifierTest { @Test public void classify_succeedsWithVideoMode() throws Exception { - Image image = getImageFromAsset(BURGER_IMAGE); + MPImage image = getImageFromAsset(BURGER_IMAGE); ImageClassifierOptions options = ImageClassifierOptions.builder() .setBaseOptions(BaseOptions.builder().setModelAssetPath(FLOAT_MODEL_FILE).build()) @@ -361,7 +361,7 @@ public class ImageClassifierTest { @Test public void classify_failsWithOutOfOrderInputTimestamps() throws Exception { - Image image = getImageFromAsset(BURGER_IMAGE); + MPImage image = getImageFromAsset(BURGER_IMAGE); ImageClassifierOptions options = ImageClassifierOptions.builder() .setBaseOptions(BaseOptions.builder().setModelAssetPath(FLOAT_MODEL_FILE).build()) @@ -388,7 +388,7 @@ public class ImageClassifierTest { @Test public void classify_succeedsWithLiveStreamMode() throws Exception { - Image image = getImageFromAsset(BURGER_IMAGE); + MPImage image = getImageFromAsset(BURGER_IMAGE); ImageClassifierOptions options = ImageClassifierOptions.builder() .setBaseOptions(BaseOptions.builder().setModelAssetPath(FLOAT_MODEL_FILE).build()) @@ -411,7 +411,7 @@ public class ImageClassifierTest { } } - private static Image getImageFromAsset(String filePath) throws Exception { + private static MPImage getImageFromAsset(String filePath) throws Exception { AssetManager assetManager = ApplicationProvider.getApplicationContext().getAssets(); InputStream istr = assetManager.open(filePath); return new BitmapImageBuilder(BitmapFactory.decodeStream(istr)).build(); @@ -437,7 +437,7 @@ public class ImageClassifierTest { } } - private static void assertImageSizeIsExpected(Image inputImage) { + private static void assertImageSizeIsExpected(MPImage inputImage) { assertThat(inputImage).isNotNull(); assertThat(inputImage.getWidth()).isEqualTo(480); assertThat(inputImage.getHeight()).isEqualTo(325); diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetectorTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetectorTest.java index cdec57d76..91ffa9273 100644 --- a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetectorTest.java +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetectorTest.java @@ -24,7 +24,7 @@ import androidx.test.core.app.ApplicationProvider; import androidx.test.ext.junit.runners.AndroidJUnit4; import com.google.mediapipe.framework.MediaPipeException; import com.google.mediapipe.framework.image.BitmapImageBuilder; -import com.google.mediapipe.framework.image.Image; +import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.components.containers.Category; import com.google.mediapipe.tasks.components.containers.Detection; import com.google.mediapipe.tasks.core.BaseOptions; @@ -370,7 +370,7 @@ public class ObjectDetectorTest { @Test public void detect_failsWithOutOfOrderInputTimestamps() throws Exception { - Image image = getImageFromAsset(CAT_AND_DOG_IMAGE); + MPImage image = getImageFromAsset(CAT_AND_DOG_IMAGE); ObjectDetectorOptions options = ObjectDetectorOptions.builder() .setBaseOptions(BaseOptions.builder().setModelAssetPath(MODEL_FILE).build()) @@ -395,7 +395,7 @@ public class ObjectDetectorTest { @Test public void detect_successWithLiveSteamMode() throws Exception { - Image image = getImageFromAsset(CAT_AND_DOG_IMAGE); + MPImage image = getImageFromAsset(CAT_AND_DOG_IMAGE); ObjectDetectorOptions options = ObjectDetectorOptions.builder() .setBaseOptions(BaseOptions.builder().setModelAssetPath(MODEL_FILE).build()) @@ -416,7 +416,7 @@ public class ObjectDetectorTest { } } - private static Image getImageFromAsset(String filePath) throws Exception { + private static MPImage getImageFromAsset(String filePath) throws Exception { AssetManager assetManager = ApplicationProvider.getApplicationContext().getAssets(); InputStream istr = assetManager.open(filePath); return new BitmapImageBuilder(BitmapFactory.decodeStream(istr)).build(); @@ -448,7 +448,7 @@ public class ObjectDetectorTest { assertThat(boundingBox1.bottom).isWithin(PIXEL_DIFF_TOLERANCE).of(boundingBox2.bottom); } - private static void assertImageSizeIsExpected(Image inputImage) { + private static void assertImageSizeIsExpected(MPImage inputImage) { assertThat(inputImage).isNotNull(); assertThat(inputImage.getWidth()).isEqualTo(IMAGE_WIDTH); assertThat(inputImage.getHeight()).isEqualTo(IMAGE_HEIGHT); From 404323f631048700412cb680f983e0ab646b55ee Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Fri, 21 Oct 2022 18:31:47 -0700 Subject: [PATCH 055/125] Add Mediapipe Tasks Gesture Recognizer benchmarks PiperOrigin-RevId: 482935780 --- mediapipe/tasks/testdata/vision/BUILD | 1 + 1 file changed, 1 insertion(+) diff --git a/mediapipe/tasks/testdata/vision/BUILD b/mediapipe/tasks/testdata/vision/BUILD index ffb4760d9..f899be8ef 100644 --- a/mediapipe/tasks/testdata/vision/BUILD +++ b/mediapipe/tasks/testdata/vision/BUILD @@ -67,6 +67,7 @@ mediapipe_files(srcs = [ exports_files( srcs = [ + "cg_classifier_screen3d_landmark_features_nn_2022_08_04_base_simple_model.tflite", "expected_left_down_hand_landmarks.prototxt", "expected_left_down_hand_rotated_landmarks.prototxt", "expected_left_up_hand_landmarks.prototxt", From d8006a2f87a3dc1bac49244683f68ad09ed841f6 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Fri, 21 Oct 2022 21:52:40 -0700 Subject: [PATCH 056/125] Use model bundle for gesture recognizer. PiperOrigin-RevId: 482960305 --- .../tasks/cc/vision/gesture_recognizer/BUILD | 11 ++ .../gesture_recognizer/gesture_recognizer.cc | 46 ++---- .../gesture_recognizer/gesture_recognizer.h | 6 - .../gesture_recognizer_graph.cc | 71 +++++++++ .../hand_gesture_recognizer_graph.cc | 150 +++++++++++++++--- .../cc/vision/gesture_recognizer/proto/BUILD | 1 - ...and_gesture_recognizer_graph_options.proto | 7 +- .../hand_landmarker/hand_landmarker_graph.cc | 20 ++- .../hand_landmarker_graph_test.cc | 2 +- .../com/google/mediapipe/tasks/vision/BUILD | 1 + .../gesturerecognizer/GestureRecognizer.java | 53 ++----- .../GestureRecognizerTest.java | 141 +++++----------- mediapipe/tasks/testdata/vision/BUILD | 5 +- ...and_landmark.task => hand_landmarker.task} | Bin 7819037 -> 7819037 bytes third_party/external_files.bzl | 24 +-- 15 files changed, 309 insertions(+), 229 deletions(-) rename mediapipe/tasks/testdata/vision/{hand_landmark.task => hand_landmarker.task} (99%) diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD b/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD index a766c6b3f..6296017d4 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD @@ -62,13 +62,19 @@ cc_library( "//mediapipe/tasks/cc/components:image_preprocessing", "//mediapipe/tasks/cc/components/processors:classification_postprocessing_graph", "//mediapipe/tasks/cc/components/processors/proto:classification_postprocessing_graph_options_cc_proto", + "//mediapipe/tasks/cc/core:model_asset_bundle_resources", "//mediapipe/tasks/cc/core:model_resources", + "//mediapipe/tasks/cc/core:model_resources_cache", "//mediapipe/tasks/cc/core:model_task_graph", "//mediapipe/tasks/cc/core:utils", + "//mediapipe/tasks/cc/core/proto:external_file_cc_proto", "//mediapipe/tasks/cc/core/proto:inference_subgraph_cc_proto", + "//mediapipe/tasks/cc/metadata/utils:zip_utils", "//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:handedness_to_matrix_calculator", "//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:landmarks_to_matrix_calculator", "//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:landmarks_to_matrix_calculator_cc_proto", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_classifier_graph_options_cc_proto", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_embedder_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/hand_landmarker:hand_landmarks_detector_graph", "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_cc_proto", @@ -93,10 +99,14 @@ cc_library( "//mediapipe/framework/formats:image", "//mediapipe/framework/formats:landmark_cc_proto", "//mediapipe/framework/formats:rect_cc_proto", + "//mediapipe/framework/port:status", "//mediapipe/tasks/cc:common", "//mediapipe/tasks/cc/components/processors/proto:classifier_options_cc_proto", + "//mediapipe/tasks/cc/core:model_asset_bundle_resources", + "//mediapipe/tasks/cc/core:model_resources_cache", "//mediapipe/tasks/cc/core:model_task_graph", "//mediapipe/tasks/cc/core:utils", + "//mediapipe/tasks/cc/metadata/utils:zip_utils", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/hand_detector:hand_detector_graph", @@ -140,6 +150,7 @@ cc_library( "//mediapipe/tasks/cc/vision/core:image_processing_options", "//mediapipe/tasks/cc/vision/core:running_mode", "//mediapipe/tasks/cc/vision/core:vision_task_api_factory", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_classifier_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_cc_proto", diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc index 000a2e141..d4ab16ac8 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc @@ -41,6 +41,7 @@ limitations under the License. #include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h" #include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/vision_task_api_factory.h" +#include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_classifier_graph_options.pb.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_recognizer_graph_options.pb.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.pb.h" #include "mediapipe/tasks/cc/vision/hand_detector/proto/hand_detector_graph_options.pb.h" @@ -112,57 +113,38 @@ CalculatorGraphConfig CreateGraphConfig( std::unique_ptr ConvertGestureRecognizerGraphOptionsProto(GestureRecognizerOptions* options) { auto options_proto = std::make_unique(); + auto base_options_proto = std::make_unique( + tasks::core::ConvertBaseOptionsToProto(&(options->base_options))); + options_proto->mutable_base_options()->Swap(base_options_proto.get()); + options_proto->mutable_base_options()->set_use_stream_mode( + options->running_mode != core::RunningMode::IMAGE); - bool use_stream_mode = options->running_mode != core::RunningMode::IMAGE; - - // TODO remove these workarounds for base options of subgraphs. // Configure hand detector options. - auto base_options_proto_for_hand_detector = - std::make_unique( - tasks::core::ConvertBaseOptionsToProto( - &(options->base_options_for_hand_detector))); - base_options_proto_for_hand_detector->set_use_stream_mode(use_stream_mode); auto* hand_detector_graph_options = options_proto->mutable_hand_landmarker_graph_options() ->mutable_hand_detector_graph_options(); - hand_detector_graph_options->mutable_base_options()->Swap( - base_options_proto_for_hand_detector.get()); hand_detector_graph_options->set_num_hands(options->num_hands); hand_detector_graph_options->set_min_detection_confidence( options->min_hand_detection_confidence); // Configure hand landmark detector options. - auto base_options_proto_for_hand_landmarker = - std::make_unique( - tasks::core::ConvertBaseOptionsToProto( - &(options->base_options_for_hand_landmarker))); - base_options_proto_for_hand_landmarker->set_use_stream_mode(use_stream_mode); - auto* hand_landmarks_detector_graph_options = - options_proto->mutable_hand_landmarker_graph_options() - ->mutable_hand_landmarks_detector_graph_options(); - hand_landmarks_detector_graph_options->mutable_base_options()->Swap( - base_options_proto_for_hand_landmarker.get()); - hand_landmarks_detector_graph_options->set_min_detection_confidence( - options->min_hand_presence_confidence); - auto* hand_landmarker_graph_options = options_proto->mutable_hand_landmarker_graph_options(); hand_landmarker_graph_options->set_min_tracking_confidence( options->min_tracking_confidence); + auto* hand_landmarks_detector_graph_options = + hand_landmarker_graph_options + ->mutable_hand_landmarks_detector_graph_options(); + hand_landmarks_detector_graph_options->set_min_detection_confidence( + options->min_hand_presence_confidence); // Configure hand gesture recognizer options. - auto base_options_proto_for_gesture_recognizer = - std::make_unique( - tasks::core::ConvertBaseOptionsToProto( - &(options->base_options_for_gesture_recognizer))); - base_options_proto_for_gesture_recognizer->set_use_stream_mode( - use_stream_mode); auto* hand_gesture_recognizer_graph_options = options_proto->mutable_hand_gesture_recognizer_graph_options(); - hand_gesture_recognizer_graph_options->mutable_base_options()->Swap( - base_options_proto_for_gesture_recognizer.get()); if (options->min_gesture_confidence >= 0) { - hand_gesture_recognizer_graph_options->mutable_classifier_options() + hand_gesture_recognizer_graph_options + ->mutable_canned_gesture_classifier_graph_options() + ->mutable_classifier_options() ->set_score_threshold(options->min_gesture_confidence); } return options_proto; diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h index 29c8bea7b..3e281b26e 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.h @@ -39,12 +39,6 @@ struct GestureRecognizerOptions { // model file with metadata, accelerator options, op resolver, etc. tasks::core::BaseOptions base_options; - // TODO: remove these. Temporary solutions before bundle asset is - // ready. - tasks::core::BaseOptions base_options_for_hand_landmarker; - tasks::core::BaseOptions base_options_for_hand_detector; - tasks::core::BaseOptions base_options_for_gesture_recognizer; - // The running mode of the task. Default to the image mode. // GestureRecognizer has three running modes: // 1) The image mode for recognizing hand gestures on single image inputs. diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer_graph.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer_graph.cc index e02eadde8..7ab4847dd 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer_graph.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer_graph.cc @@ -25,9 +25,13 @@ limitations under the License. #include "mediapipe/framework/formats/image.h" #include "mediapipe/framework/formats/landmark.pb.h" #include "mediapipe/framework/formats/rect.pb.h" +#include "mediapipe/framework/port/status_macros.h" #include "mediapipe/tasks/cc/common.h" +#include "mediapipe/tasks/cc/core/model_asset_bundle_resources.h" +#include "mediapipe/tasks/cc/core/model_resources_cache.h" #include "mediapipe/tasks/cc/core/model_task_graph.h" #include "mediapipe/tasks/cc/core/utils.h" +#include "mediapipe/tasks/cc/metadata/utils/zip_utils.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_recognizer_graph_options.pb.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.pb.h" #include "mediapipe/tasks/cc/vision/hand_detector/proto/hand_detector_graph_options.pb.h" @@ -46,6 +50,8 @@ using ::mediapipe::api2::Input; using ::mediapipe::api2::Output; using ::mediapipe::api2::builder::Graph; using ::mediapipe::api2::builder::Source; +using ::mediapipe::tasks::core::ModelAssetBundleResources; +using ::mediapipe::tasks::metadata::SetExternalFile; using ::mediapipe::tasks::vision::gesture_recognizer::proto:: GestureRecognizerGraphOptions; using ::mediapipe::tasks::vision::gesture_recognizer::proto:: @@ -61,6 +67,9 @@ constexpr char kHandednessTag[] = "HANDEDNESS"; constexpr char kImageSizeTag[] = "IMAGE_SIZE"; constexpr char kHandGesturesTag[] = "HAND_GESTURES"; constexpr char kHandTrackingIdsTag[] = "HAND_TRACKING_IDS"; +constexpr char kHandLandmarkerBundleAssetName[] = "hand_landmarker.task"; +constexpr char kHandGestureRecognizerBundleAssetName[] = + "hand_gesture_recognizer.task"; struct GestureRecognizerOutputs { Source> gesture; @@ -70,6 +79,53 @@ struct GestureRecognizerOutputs { Source image; }; +// Sets the base options in the sub tasks. +absl::Status SetSubTaskBaseOptions(const ModelAssetBundleResources& resources, + GestureRecognizerGraphOptions* options, + bool is_copy) { + ASSIGN_OR_RETURN(const auto hand_landmarker_file, + resources.GetModelFile(kHandLandmarkerBundleAssetName)); + auto* hand_landmarker_graph_options = + options->mutable_hand_landmarker_graph_options(); + SetExternalFile(hand_landmarker_file, + hand_landmarker_graph_options->mutable_base_options() + ->mutable_model_asset(), + is_copy); + hand_landmarker_graph_options->mutable_base_options() + ->mutable_acceleration() + ->CopyFrom(options->base_options().acceleration()); + hand_landmarker_graph_options->mutable_base_options()->set_use_stream_mode( + options->base_options().use_stream_mode()); + + ASSIGN_OR_RETURN( + const auto hand_gesture_recognizer_file, + resources.GetModelFile(kHandGestureRecognizerBundleAssetName)); + auto* hand_gesture_recognizer_graph_options = + options->mutable_hand_gesture_recognizer_graph_options(); + SetExternalFile(hand_gesture_recognizer_file, + hand_gesture_recognizer_graph_options->mutable_base_options() + ->mutable_model_asset(), + is_copy); + hand_gesture_recognizer_graph_options->mutable_base_options() + ->mutable_acceleration() + ->CopyFrom(options->base_options().acceleration()); + if (!hand_gesture_recognizer_graph_options->base_options() + .acceleration() + .has_xnnpack() && + !hand_gesture_recognizer_graph_options->base_options() + .acceleration() + .has_tflite()) { + hand_gesture_recognizer_graph_options->mutable_base_options() + ->mutable_acceleration() + ->mutable_xnnpack(); + LOG(WARNING) << "Hand Gesture Recognizer contains CPU only ops. Sets " + << "HandGestureRecognizerGraph acceleartion to Xnnpack."; + } + hand_gesture_recognizer_graph_options->mutable_base_options() + ->set_use_stream_mode(options->base_options().use_stream_mode()); + return absl::OkStatus(); +} + } // namespace // A "mediapipe.tasks.vision.gesture_recognizer.GestureRecognizerGraph" performs @@ -136,6 +192,21 @@ class GestureRecognizerGraph : public core::ModelTaskGraph { absl::StatusOr GetConfig( SubgraphContext* sc) override { Graph graph; + if (sc->Options() + .base_options() + .has_model_asset()) { + ASSIGN_OR_RETURN( + const auto* model_asset_bundle_resources, + CreateModelAssetBundleResources(sc)); + // When the model resources cache service is available, filling in + // the file pointer meta in the subtasks' base options. Otherwise, + // providing the file contents instead. + MP_RETURN_IF_ERROR(SetSubTaskBaseOptions( + *model_asset_bundle_resources, + sc->MutableOptions(), + !sc->Service(::mediapipe::tasks::core::kModelResourcesCacheService) + .IsAvailable())); + } ASSIGN_OR_RETURN(auto hand_gesture_recognition_output, BuildGestureRecognizerGraph( *sc->MutableOptions(), diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc index 4bbe94974..7b7746956 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc @@ -30,11 +30,17 @@ limitations under the License. #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.h" #include "mediapipe/tasks/cc/components/processors/proto/classification_postprocessing_graph_options.pb.h" +#include "mediapipe/tasks/cc/core/model_asset_bundle_resources.h" #include "mediapipe/tasks/cc/core/model_resources.h" +#include "mediapipe/tasks/cc/core/model_resources_cache.h" #include "mediapipe/tasks/cc/core/model_task_graph.h" +#include "mediapipe/tasks/cc/core/proto/external_file.pb.h" #include "mediapipe/tasks/cc/core/proto/inference_subgraph.pb.h" #include "mediapipe/tasks/cc/core/utils.h" +#include "mediapipe/tasks/cc/metadata/utils/zip_utils.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator.pb.h" +#include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_classifier_graph_options.pb.h" +#include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_embedder_graph_options.pb.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.pb.h" #include "mediapipe/tasks/metadata/metadata_schema_generated.h" @@ -51,6 +57,8 @@ using ::mediapipe::api2::builder::Graph; using ::mediapipe::api2::builder::Source; using ::mediapipe::tasks::components::processors:: ConfigureTensorsToClassificationCalculator; +using ::mediapipe::tasks::core::ModelAssetBundleResources; +using ::mediapipe::tasks::metadata::SetExternalFile; using ::mediapipe::tasks::vision::gesture_recognizer::proto:: HandGestureRecognizerGraphOptions; @@ -70,6 +78,14 @@ constexpr char kVectorTag[] = "VECTOR"; constexpr char kIndexTag[] = "INDEX"; constexpr char kIterableTag[] = "ITERABLE"; constexpr char kBatchEndTag[] = "BATCH_END"; +constexpr char kGestureEmbedderTFLiteName[] = "gesture_embedder.tflite"; +constexpr char kCannedGestureClassifierTFLiteName[] = + "canned_gesture_classifier.tflite"; + +struct SubTaskModelResources { + const core::ModelResources* gesture_embedder_model_resource; + const core::ModelResources* canned_gesture_classifier_model_resource; +}; Source> ConvertMatrixToTensor(Source matrix, Graph& graph) { @@ -78,6 +94,41 @@ Source> ConvertMatrixToTensor(Source matrix, return node[Output>{"TENSORS"}]; } +// Sets the base options in the sub tasks. +absl::Status SetSubTaskBaseOptions(const ModelAssetBundleResources& resources, + HandGestureRecognizerGraphOptions* options, + bool is_copy) { + ASSIGN_OR_RETURN(const auto gesture_embedder_file, + resources.GetModelFile(kGestureEmbedderTFLiteName)); + auto* gesture_embedder_graph_options = + options->mutable_gesture_embedder_graph_options(); + SetExternalFile(gesture_embedder_file, + gesture_embedder_graph_options->mutable_base_options() + ->mutable_model_asset(), + is_copy); + gesture_embedder_graph_options->mutable_base_options() + ->mutable_acceleration() + ->CopyFrom(options->base_options().acceleration()); + gesture_embedder_graph_options->mutable_base_options()->set_use_stream_mode( + options->base_options().use_stream_mode()); + + ASSIGN_OR_RETURN(const auto canned_gesture_classifier_file, + resources.GetModelFile(kCannedGestureClassifierTFLiteName)); + auto* canned_gesture_classifier_graph_options = + options->mutable_canned_gesture_classifier_graph_options(); + SetExternalFile( + canned_gesture_classifier_file, + canned_gesture_classifier_graph_options->mutable_base_options() + ->mutable_model_asset(), + is_copy); + canned_gesture_classifier_graph_options->mutable_base_options() + ->mutable_acceleration() + ->CopyFrom(options->base_options().acceleration()); + canned_gesture_classifier_graph_options->mutable_base_options() + ->set_use_stream_mode(options->base_options().use_stream_mode()); + return absl::OkStatus(); +} + } // namespace // A @@ -128,27 +179,70 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { public: absl::StatusOr GetConfig( SubgraphContext* sc) override { - ASSIGN_OR_RETURN( - const auto* model_resources, - CreateModelResources(sc)); + if (sc->Options() + .base_options() + .has_model_asset()) { + ASSIGN_OR_RETURN( + const auto* model_asset_bundle_resources, + CreateModelAssetBundleResources( + sc)); + // When the model resources cache service is available, filling in + // the file pointer meta in the subtasks' base options. Otherwise, + // providing the file contents instead. + MP_RETURN_IF_ERROR(SetSubTaskBaseOptions( + *model_asset_bundle_resources, + sc->MutableOptions(), + !sc->Service(::mediapipe::tasks::core::kModelResourcesCacheService) + .IsAvailable())); + } + ASSIGN_OR_RETURN(const auto sub_task_model_resources, + CreateSubTaskModelResources(sc)); Graph graph; - ASSIGN_OR_RETURN( - auto hand_gestures, - BuildGestureRecognizerGraph( - sc->Options(), *model_resources, - graph[Input(kHandednessTag)], - graph[Input(kLandmarksTag)], - graph[Input(kWorldLandmarksTag)], - graph[Input>(kImageSizeTag)], - graph[Input(kNormRectTag)], graph)); + ASSIGN_OR_RETURN(auto hand_gestures, + BuildGestureRecognizerGraph( + sc->Options(), + sub_task_model_resources, + graph[Input(kHandednessTag)], + graph[Input(kLandmarksTag)], + graph[Input(kWorldLandmarksTag)], + graph[Input>(kImageSizeTag)], + graph[Input(kNormRectTag)], graph)); hand_gestures >> graph[Output(kHandGesturesTag)]; return graph.GetConfig(); } private: + absl::StatusOr CreateSubTaskModelResources( + SubgraphContext* sc) { + auto* options = sc->MutableOptions(); + SubTaskModelResources sub_task_model_resources; + auto& gesture_embedder_model_asset = + *options->mutable_gesture_embedder_graph_options() + ->mutable_base_options() + ->mutable_model_asset(); + ASSIGN_OR_RETURN( + sub_task_model_resources.gesture_embedder_model_resource, + CreateModelResources(sc, + std::make_unique( + std::move(gesture_embedder_model_asset)), + "_gesture_embedder")); + auto& canned_gesture_classifier_model_asset = + *options->mutable_canned_gesture_classifier_graph_options() + ->mutable_base_options() + ->mutable_model_asset(); + ASSIGN_OR_RETURN( + sub_task_model_resources.canned_gesture_classifier_model_resource, + CreateModelResources( + sc, + std::make_unique( + std::move(canned_gesture_classifier_model_asset)), + "_canned_gesture_classifier")); + return sub_task_model_resources; + } + absl::StatusOr> BuildGestureRecognizerGraph( const HandGestureRecognizerGraphOptions& graph_options, - const core::ModelResources& model_resources, + const SubTaskModelResources& sub_task_model_resources, Source handedness, Source hand_landmarks, Source hand_world_landmarks, @@ -209,17 +303,33 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { auto concatenated_tensors = concatenate_tensor_vector.Out(""); // Inference for static hand gesture recognition. - // TODO add embedding step. - auto& inference = AddInference( - model_resources, graph_options.base_options().acceleration(), graph); - concatenated_tensors >> inference.In(kTensorsTag); - auto inference_output_tensors = inference.Out(kTensorsTag); + auto& gesture_embedder_inference = + AddInference(*sub_task_model_resources.gesture_embedder_model_resource, + graph_options.gesture_embedder_graph_options() + .base_options() + .acceleration(), + graph); + concatenated_tensors >> gesture_embedder_inference.In(kTensorsTag); + auto embedding_tensors = gesture_embedder_inference.Out(kTensorsTag); + + auto& canned_gesture_classifier_inference = AddInference( + *sub_task_model_resources.canned_gesture_classifier_model_resource, + graph_options.canned_gesture_classifier_graph_options() + .base_options() + .acceleration(), + graph); + embedding_tensors >> canned_gesture_classifier_inference.In(kTensorsTag); + auto inference_output_tensors = + canned_gesture_classifier_inference.Out(kTensorsTag); auto& tensors_to_classification = graph.AddNode("TensorsToClassificationCalculator"); MP_RETURN_IF_ERROR(ConfigureTensorsToClassificationCalculator( - graph_options.classifier_options(), - *model_resources.GetMetadataExtractor(), 0, + graph_options.canned_gesture_classifier_graph_options() + .classifier_options(), + *sub_task_model_resources.canned_gesture_classifier_model_resource + ->GetMetadataExtractor(), + 0, &tensors_to_classification.GetOptions< mediapipe::TensorsToClassificationCalculatorOptions>())); inference_output_tensors >> tensors_to_classification.In(kTensorsTag); diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/proto/BUILD b/mediapipe/tasks/cc/vision/gesture_recognizer/proto/BUILD index 3b73bf2b0..0db47da7a 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/proto/BUILD +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/proto/BUILD @@ -49,7 +49,6 @@ mediapipe_proto_library( ":gesture_embedder_graph_options_proto", "//mediapipe/framework:calculator_options_proto", "//mediapipe/framework:calculator_proto", - "//mediapipe/tasks/cc/components/processors/proto:classifier_options_proto", "//mediapipe/tasks/cc/core/proto:base_options_proto", ], ) diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.proto b/mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.proto index a3281702a..7df2fed37 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.proto +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.proto @@ -18,7 +18,6 @@ syntax = "proto2"; package mediapipe.tasks.vision.gesture_recognizer.proto; import "mediapipe/framework/calculator.proto"; -import "mediapipe/tasks/cc/components/processors/proto/classifier_options.proto"; import "mediapipe/tasks/cc/core/proto/base_options.proto"; import "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_classifier_graph_options.proto"; import "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_embedder_graph_options.proto"; @@ -37,15 +36,11 @@ message HandGestureRecognizerGraphOptions { // Options for GestureEmbedder. optional GestureEmbedderGraphOptions gesture_embedder_graph_options = 2; - // Options for GestureClassifier of default gestures. + // Options for GestureClassifier of canned gestures. optional GestureClassifierGraphOptions canned_gesture_classifier_graph_options = 3; // Options for GestureClassifier of custom gestures. optional GestureClassifierGraphOptions custom_gesture_classifier_graph_options = 4; - - // TODO: remove these. Temporary solutions before bundle asset is - // ready. - optional components.processors.proto.ClassifierOptions classifier_options = 5; } diff --git a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph.cc b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph.cc index 3fbe38c1c..e610a412e 100644 --- a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph.cc +++ b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph.cc @@ -92,18 +92,30 @@ absl::Status SetSubTaskBaseOptions(const ModelAssetBundleResources& resources, bool is_copy) { ASSIGN_OR_RETURN(const auto hand_detector_file, resources.GetModelFile(kHandDetectorTFLiteName)); + auto* hand_detector_graph_options = + options->mutable_hand_detector_graph_options(); SetExternalFile(hand_detector_file, - options->mutable_hand_detector_graph_options() - ->mutable_base_options() + hand_detector_graph_options->mutable_base_options() ->mutable_model_asset(), is_copy); + hand_detector_graph_options->mutable_base_options() + ->mutable_acceleration() + ->CopyFrom(options->base_options().acceleration()); + hand_detector_graph_options->mutable_base_options()->set_use_stream_mode( + options->base_options().use_stream_mode()); ASSIGN_OR_RETURN(const auto hand_landmarks_detector_file, resources.GetModelFile(kHandLandmarksDetectorTFLiteName)); + auto* hand_landmarks_detector_graph_options = + options->mutable_hand_landmarks_detector_graph_options(); SetExternalFile(hand_landmarks_detector_file, - options->mutable_hand_landmarks_detector_graph_options() - ->mutable_base_options() + hand_landmarks_detector_graph_options->mutable_base_options() ->mutable_model_asset(), is_copy); + hand_landmarks_detector_graph_options->mutable_base_options() + ->mutable_acceleration() + ->CopyFrom(options->base_options().acceleration()); + hand_landmarks_detector_graph_options->mutable_base_options() + ->set_use_stream_mode(options->base_options().use_stream_mode()); return absl::OkStatus(); } diff --git a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph_test.cc b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph_test.cc index 08beb1a1b..f275486f5 100644 --- a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph_test.cc +++ b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_graph_test.cc @@ -67,7 +67,7 @@ using ::testing::proto::Approximately; using ::testing::proto::Partially; constexpr char kTestDataDirectory[] = "/mediapipe/tasks/testdata/vision/"; -constexpr char kHandLandmarkerModelBundle[] = "hand_landmark.task"; +constexpr char kHandLandmarkerModelBundle[] = "hand_landmarker.task"; constexpr char kLeftHandsImage[] = "left_hands.jpg"; constexpr char kLeftHandsRotatedImage[] = "left_hands_rotated.jpg"; diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD index dcf3b3542..2bdcc2522 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD @@ -128,6 +128,7 @@ android_library( "//mediapipe/java/com/google/mediapipe/framework/image", "//mediapipe/tasks/cc/components/processors/proto:classifier_options_java_proto_lite", "//mediapipe/tasks/cc/core/proto:base_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_classifier_graph_options_java_proto_lite", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_java_proto_lite", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_java_proto_lite", "//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_java_proto_lite", diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java index 560508903..55cf275e9 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java @@ -38,6 +38,7 @@ import com.google.mediapipe.tasks.core.TaskRunner; import com.google.mediapipe.tasks.core.proto.BaseOptionsProto; import com.google.mediapipe.tasks.vision.core.BaseVisionTaskApi; import com.google.mediapipe.tasks.vision.core.RunningMode; +import com.google.mediapipe.tasks.vision.gesturerecognizer.proto.GestureClassifierGraphOptionsProto; import com.google.mediapipe.tasks.vision.gesturerecognizer.proto.GestureRecognizerGraphOptionsProto; import com.google.mediapipe.tasks.vision.gesturerecognizer.proto.HandGestureRecognizerGraphOptionsProto; import com.google.mediapipe.tasks.vision.handdetector.proto.HandDetectorGraphOptionsProto; @@ -300,13 +301,6 @@ public final class GestureRecognizer extends BaseVisionTaskApi { */ public abstract Builder setRunningMode(RunningMode value); - // TODO: remove these. Temporary solutions before bundle asset is ready. - public abstract Builder setBaseOptionsHandDetector(BaseOptions value); - - public abstract Builder setBaseOptionsHandLandmarker(BaseOptions value); - - public abstract Builder setBaseOptionsGestureRecognizer(BaseOptions value); - /** Sets the maximum number of hands can be detected by the GestureRecognizer. */ public abstract Builder setNumHands(Integer value); @@ -366,13 +360,6 @@ public final class GestureRecognizer extends BaseVisionTaskApi { abstract BaseOptions baseOptions(); - // TODO: remove these. Temporary solutions before bundle asset is ready. - abstract BaseOptions baseOptionsHandDetector(); - - abstract BaseOptions baseOptionsHandLandmarker(); - - abstract BaseOptions baseOptionsGestureRecognizer(); - abstract RunningMode runningMode(); abstract Optional numHands(); @@ -405,22 +392,18 @@ public final class GestureRecognizer extends BaseVisionTaskApi { */ @Override public CalculatorOptions convertToCalculatorOptionsProto() { - BaseOptionsProto.BaseOptions.Builder baseOptionsBuilder = - BaseOptionsProto.BaseOptions.newBuilder() - .setUseStreamMode(runningMode() != RunningMode.IMAGE) - .mergeFrom(convertBaseOptionsToProto(baseOptions())); GestureRecognizerGraphOptionsProto.GestureRecognizerGraphOptions.Builder taskOptionsBuilder = GestureRecognizerGraphOptionsProto.GestureRecognizerGraphOptions.newBuilder() - .setBaseOptions(baseOptionsBuilder); + .setBaseOptions( + BaseOptionsProto.BaseOptions.newBuilder() + .setUseStreamMode(runningMode() != RunningMode.IMAGE) + .mergeFrom(convertBaseOptionsToProto(baseOptions())) + .build()); // Setup HandDetectorGraphOptions. HandDetectorGraphOptionsProto.HandDetectorGraphOptions.Builder handDetectorGraphOptionsBuilder = - HandDetectorGraphOptionsProto.HandDetectorGraphOptions.newBuilder() - .setBaseOptions( - BaseOptionsProto.BaseOptions.newBuilder() - .setUseStreamMode(runningMode() != RunningMode.IMAGE) - .mergeFrom(convertBaseOptionsToProto(baseOptionsHandDetector()))); + HandDetectorGraphOptionsProto.HandDetectorGraphOptions.newBuilder(); numHands().ifPresent(handDetectorGraphOptionsBuilder::setNumHands); minHandDetectionConfidence() .ifPresent(handDetectorGraphOptionsBuilder::setMinDetectionConfidence); @@ -428,19 +411,12 @@ public final class GestureRecognizer extends BaseVisionTaskApi { // Setup HandLandmarkerGraphOptions. HandLandmarksDetectorGraphOptionsProto.HandLandmarksDetectorGraphOptions.Builder handLandmarksDetectorGraphOptionsBuilder = - HandLandmarksDetectorGraphOptionsProto.HandLandmarksDetectorGraphOptions.newBuilder() - .setBaseOptions( - BaseOptionsProto.BaseOptions.newBuilder() - .setUseStreamMode(runningMode() != RunningMode.IMAGE) - .mergeFrom(convertBaseOptionsToProto(baseOptionsHandLandmarker()))); + HandLandmarksDetectorGraphOptionsProto.HandLandmarksDetectorGraphOptions.newBuilder(); minHandPresenceConfidence() .ifPresent(handLandmarksDetectorGraphOptionsBuilder::setMinDetectionConfidence); HandLandmarkerGraphOptionsProto.HandLandmarkerGraphOptions.Builder handLandmarkerGraphOptionsBuilder = - HandLandmarkerGraphOptionsProto.HandLandmarkerGraphOptions.newBuilder() - .setBaseOptions( - BaseOptionsProto.BaseOptions.newBuilder() - .setUseStreamMode(runningMode() != RunningMode.IMAGE)); + HandLandmarkerGraphOptionsProto.HandLandmarkerGraphOptions.newBuilder(); minTrackingConfidence() .ifPresent(handLandmarkerGraphOptionsBuilder::setMinTrackingConfidence); handLandmarkerGraphOptionsBuilder @@ -450,16 +426,13 @@ public final class GestureRecognizer extends BaseVisionTaskApi { // Setup HandGestureRecognizerGraphOptions. HandGestureRecognizerGraphOptionsProto.HandGestureRecognizerGraphOptions.Builder handGestureRecognizerGraphOptionsBuilder = - HandGestureRecognizerGraphOptionsProto.HandGestureRecognizerGraphOptions.newBuilder() - .setBaseOptions( - BaseOptionsProto.BaseOptions.newBuilder() - .setUseStreamMode(runningMode() != RunningMode.IMAGE) - .mergeFrom(convertBaseOptionsToProto(baseOptionsGestureRecognizer()))); + HandGestureRecognizerGraphOptionsProto.HandGestureRecognizerGraphOptions.newBuilder(); ClassifierOptionsProto.ClassifierOptions.Builder classifierOptionsBuilder = ClassifierOptionsProto.ClassifierOptions.newBuilder(); minGestureConfidence().ifPresent(classifierOptionsBuilder::setScoreThreshold); - handGestureRecognizerGraphOptionsBuilder.setClassifierOptions( - classifierOptionsBuilder.build()); + handGestureRecognizerGraphOptionsBuilder.setCannedGestureClassifierGraphOptions( + GestureClassifierGraphOptionsProto.GestureClassifierGraphOptions.newBuilder() + .setClassifierOptions(classifierOptionsBuilder.build())); taskOptionsBuilder .setHandLandmarkerGraphOptions(handLandmarkerGraphOptionsBuilder.build()) diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java index 8beea96ac..31e59a259 100644 --- a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java @@ -43,10 +43,7 @@ import org.junit.runners.Suite.SuiteClasses; @RunWith(Suite.class) @SuiteClasses({GestureRecognizerTest.General.class, GestureRecognizerTest.RunningModeTest.class}) public class GestureRecognizerTest { - private static final String HAND_DETECTOR_MODEL_FILE = "palm_detection_full.tflite"; - private static final String HAND_LANDMARKER_MODEL_FILE = "hand_landmark_full.tflite"; - private static final String GESTURE_RECOGNIZER_MODEL_FILE = - "cg_classifier_screen3d_landmark_features_nn_2022_08_04_base_simple_model.tflite"; + private static final String GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE = "gesture_recognizer.task"; private static final String TWO_HANDS_IMAGE = "right_hands.jpg"; private static final String THUMB_UP_IMAGE = "thumb_up.jpg"; private static final String NO_HANDS_IMAGE = "cats_and_dogs.jpg"; @@ -66,13 +63,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .build(); GestureRecognizer gestureRecognizer = GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); @@ -88,13 +81,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .build(); GestureRecognizer gestureRecognizer = GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); @@ -111,16 +100,12 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) // TODO update the confidence to be in range [0,1] after embedding model // and scoring calculator is integrated. - .setMinGestureConfidence(3.0f) + .setMinGestureConfidence(2.0f) .build(); GestureRecognizer gestureRecognizer = GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); @@ -139,13 +124,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .setNumHands(2) .build(); GestureRecognizer gestureRecognizer = @@ -168,19 +149,7 @@ public class GestureRecognizerTest { GestureRecognizerOptions.builder() .setBaseOptions( BaseOptions.builder() - .setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE) - .build()) - .setBaseOptionsHandDetector( - BaseOptions.builder() - .setModelAssetPath(HAND_DETECTOR_MODEL_FILE) - .build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder() - .setModelAssetPath(HAND_LANDMARKER_MODEL_FILE) - .build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder() - .setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE) + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) .build()) .setRunningMode(mode) .setResultListener((gestureRecognitionResult, inputImage) -> {}) @@ -201,15 +170,7 @@ public class GestureRecognizerTest { GestureRecognizerOptions.builder() .setBaseOptions( BaseOptions.builder() - .setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE) - .build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder() - .setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE) + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) .build()) .setRunningMode(RunningMode.LIVE_STREAM) .build()); @@ -223,13 +184,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .setRunningMode(RunningMode.IMAGE) .build(); @@ -252,13 +209,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .setRunningMode(RunningMode.VIDEO) .build(); @@ -281,13 +234,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .setRunningMode(RunningMode.LIVE_STREAM) .setResultListener((gestureRecognitionResult, inputImage) -> {}) .build(); @@ -311,13 +260,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .setRunningMode(RunningMode.IMAGE) .build(); @@ -335,13 +280,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .setRunningMode(RunningMode.VIDEO) .build(); GestureRecognizer gestureRecognizer = @@ -363,13 +304,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .setRunningMode(RunningMode.LIVE_STREAM) .setResultListener( (actualResult, inputImage) -> { @@ -397,13 +334,9 @@ public class GestureRecognizerTest { GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) - .setBaseOptionsHandDetector( - BaseOptions.builder().setModelAssetPath(HAND_DETECTOR_MODEL_FILE).build()) - .setBaseOptionsHandLandmarker( - BaseOptions.builder().setModelAssetPath(HAND_LANDMARKER_MODEL_FILE).build()) - .setBaseOptionsGestureRecognizer( - BaseOptions.builder().setModelAssetPath(GESTURE_RECOGNIZER_MODEL_FILE).build()) + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) .setRunningMode(RunningMode.LIVE_STREAM) .setResultListener( (actualResult, inputImage) -> { diff --git a/mediapipe/tasks/testdata/vision/BUILD b/mediapipe/tasks/testdata/vision/BUILD index f899be8ef..ebb8f05a6 100644 --- a/mediapipe/tasks/testdata/vision/BUILD +++ b/mediapipe/tasks/testdata/vision/BUILD @@ -35,7 +35,6 @@ mediapipe_files(srcs = [ "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite", "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_with_dummy_score_calibration.tflite", "deeplabv3.tflite", - "hand_landmark.task", "hand_landmark_full.tflite", "hand_landmark_lite.tflite", "left_hands.jpg", @@ -67,13 +66,13 @@ mediapipe_files(srcs = [ exports_files( srcs = [ - "cg_classifier_screen3d_landmark_features_nn_2022_08_04_base_simple_model.tflite", "expected_left_down_hand_landmarks.prototxt", "expected_left_down_hand_rotated_landmarks.prototxt", "expected_left_up_hand_landmarks.prototxt", "expected_left_up_hand_rotated_landmarks.prototxt", "expected_right_down_hand_landmarks.prototxt", "expected_right_up_hand_landmarks.prototxt", + "gesture_recognizer.task", ], ) @@ -119,9 +118,9 @@ filegroup( "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite", "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_with_dummy_score_calibration.tflite", "deeplabv3.tflite", - "hand_landmark.task", "hand_landmark_full.tflite", "hand_landmark_lite.tflite", + "hand_landmarker.task", "mobilenet_v1_0.25_192_quantized_1_default_1.tflite", "mobilenet_v1_0.25_224_1_default_1.tflite", "mobilenet_v1_0.25_224_1_metadata_1.tflite", diff --git a/mediapipe/tasks/testdata/vision/hand_landmark.task b/mediapipe/tasks/testdata/vision/hand_landmarker.task similarity index 99% rename from mediapipe/tasks/testdata/vision/hand_landmark.task rename to mediapipe/tasks/testdata/vision/hand_landmarker.task index b6eedf3248f860d736929631c3be3d6b0f9d4cdc..1ae9f7f6b33c52e16493b566cc76d014655c4d25 100644 GIT binary patch delta 491 zcmW;I*)ALa7{zgns?t-%sHL#3D#Wm(x)(8{r%S-Do8m2VYT&#gkM$a-PDw2G|~tMpo-rdWW3f5Nd4%2199 zRH6#6@EULM7S(u%8q}f=^=LpNn$V0Ew4x2|c#jTr;sd(SjgRO-FZvKhKL#*}Pxy=> z3}XZljA9Jqi1&};3nnpzY0Tg&zF`(~n8yMZv4mx;U=?dv#|AdBg>CHMJAPmnd)UVT e4snE^IL5Dk;n?r)^Y~ZK{zgu^?!!&wB>ErZ3Beiw delta 491 zcmW;I>oODo7{+l~FPJ|qGrA5h7az5k~5;@z?K0L!6m}zFaiZ$JXd+1*L z*E{o@c|N=|?=x@w@Bcs?nj8zH6{RF6w{iSJ)&ncm3Rr1Yx|Lx)v@)$ME8EJkaxK>K ztbFT{_1G$~3auim*ebC~tupJ0Rc=*SPpwL;%Br@WS~E_G@=R3XhAF5@EYxSgAR1!ExOQ+9=t;@`p}O7gb>Cc-eU+K5Wz4;Fp7`(gfV Date: Sat, 22 Oct 2022 03:34:26 -0700 Subject: [PATCH 057/125] Moved OutputType and Activation to image_segmenter --- mediapipe/tasks/python/components/proto/BUILD | 24 ---------------- .../components/proto/segmenter_options.py | 28 ------------------- mediapipe/tasks/python/test/vision/BUILD | 1 - .../test/vision/image_segmenter_test.py | 5 ++-- mediapipe/tasks/python/vision/BUILD | 1 - .../tasks/python/vision/image_segmenter.py | 20 +++++++++---- 6 files changed, 17 insertions(+), 62 deletions(-) delete mode 100644 mediapipe/tasks/python/components/proto/BUILD delete mode 100644 mediapipe/tasks/python/components/proto/segmenter_options.py diff --git a/mediapipe/tasks/python/components/proto/BUILD b/mediapipe/tasks/python/components/proto/BUILD deleted file mode 100644 index ef37d9270..000000000 --- a/mediapipe/tasks/python/components/proto/BUILD +++ /dev/null @@ -1,24 +0,0 @@ -# Copyright 2022 The MediaPipe Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Placeholder for internal Python strict library compatibility macro. - -package(default_visibility = ["//mediapipe/tasks:internal"]) - -licenses(["notice"]) - -py_library( - name = "segmenter_options", - srcs = ["segmenter_options.py"] -) diff --git a/mediapipe/tasks/python/components/proto/segmenter_options.py b/mediapipe/tasks/python/components/proto/segmenter_options.py deleted file mode 100644 index 5f8e22777..000000000 --- a/mediapipe/tasks/python/components/proto/segmenter_options.py +++ /dev/null @@ -1,28 +0,0 @@ -# Copyright 2022 The TensorFlow Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -"""Segmenter options data class.""" - -import enum - - -class OutputType(enum.Enum): - UNSPECIFIED = 0 - CATEGORY_MASK = 1 - CONFIDENCE_MASK = 2 - - -class Activation(enum.Enum): - NONE = 0 - SIGMOID = 1 - SOFTMAX = 2 diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 63fc56b42..321b33a61 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -48,7 +48,6 @@ py_test( "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/test:test_utils", - "//mediapipe/tasks/python/components/proto:segmenter_options", "//mediapipe/tasks/python/vision:image_segmenter", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", "@absl_py//absl/testing:parameterized", diff --git a/mediapipe/tasks/python/test/vision/image_segmenter_test.py b/mediapipe/tasks/python/test/vision/image_segmenter_test.py index 9b4e2c4b4..3fa01e62f 100644 --- a/mediapipe/tasks/python/test/vision/image_segmenter_test.py +++ b/mediapipe/tasks/python/test/vision/image_segmenter_test.py @@ -24,7 +24,6 @@ from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module from mediapipe.python._framework_bindings import image_frame -from mediapipe.tasks.python.components.proto import segmenter_options from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_utils from mediapipe.tasks.python.vision import image_segmenter @@ -33,8 +32,8 @@ from mediapipe.tasks.python.vision.core import vision_task_running_mode _BaseOptions = base_options_module.BaseOptions _Image = image_module.Image _ImageFormat = image_frame.ImageFormat -_OutputType = segmenter_options.OutputType -_Activation = segmenter_options.Activation +_OutputType = image_segmenter.OutputType +_Activation = image_segmenter.Activation _ImageSegmenter = image_segmenter.ImageSegmenter _ImageSegmenterOptions = image_segmenter.ImageSegmenterOptions _RUNNING_MODE = vision_task_running_mode.VisionTaskRunningMode diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 863312e4c..da9072f18 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -48,7 +48,6 @@ py_library( "//mediapipe/python:packet_getter", "//mediapipe/tasks/cc/components/proto:segmenter_options_py_pb2", "//mediapipe/tasks/cc/vision/image_segmenter/proto:image_segmenter_options_py_pb2", - "//mediapipe/tasks/python/components/proto:segmenter_options", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/core:optional_dependencies", "//mediapipe/tasks/python/core:task_info", diff --git a/mediapipe/tasks/python/vision/image_segmenter.py b/mediapipe/tasks/python/vision/image_segmenter.py index e7278eb96..aea5a8554 100644 --- a/mediapipe/tasks/python/vision/image_segmenter.py +++ b/mediapipe/tasks/python/vision/image_segmenter.py @@ -15,6 +15,7 @@ import dataclasses from typing import Callable, List, Mapping, Optional +import enum from mediapipe.python import packet_creator from mediapipe.python import packet_getter @@ -23,7 +24,6 @@ from mediapipe.python._framework_bindings import packet from mediapipe.python._framework_bindings import task_runner from mediapipe.tasks.cc.components.proto import segmenter_options_pb2 from mediapipe.tasks.cc.vision.image_segmenter.proto import image_segmenter_options_pb2 -from mediapipe.tasks.python.components.proto import segmenter_options from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.core import task_info as task_info_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls @@ -33,8 +33,6 @@ from mediapipe.tasks.python.vision.core import vision_task_running_mode _BaseOptions = base_options_module.BaseOptions _SegmenterOptionsProto = segmenter_options_pb2.SegmenterOptions _ImageSegmenterOptionsProto = image_segmenter_options_pb2.ImageSegmenterOptions -_OutputType = segmenter_options.OutputType -_Activation = segmenter_options.Activation _RunningMode = vision_task_running_mode.VisionTaskRunningMode _TaskInfo = task_info_module.TaskInfo _TaskRunner = task_runner.TaskRunner @@ -48,6 +46,18 @@ _TASK_GRAPH_NAME = 'mediapipe.tasks.vision.ImageSegmenterGraph' _MICRO_SECONDS_PER_MILLISECOND = 1000 +class OutputType(enum.Enum): + UNSPECIFIED = 0 + CATEGORY_MASK = 1 + CONFIDENCE_MASK = 2 + + +class Activation(enum.Enum): + NONE = 0 + SIGMOID = 1 + SOFTMAX = 2 + + @dataclasses.dataclass class ImageSegmenterOptions: """Options for the image segmenter task. @@ -69,8 +79,8 @@ class ImageSegmenterOptions: """ base_options: _BaseOptions running_mode: _RunningMode = _RunningMode.IMAGE - output_type: Optional[_OutputType] = _OutputType.CATEGORY_MASK - activation: Optional[_Activation] = _Activation.NONE + output_type: Optional[OutputType] = OutputType.CATEGORY_MASK + activation: Optional[Activation] = Activation.NONE result_callback: Optional[ Callable[[List[image_module.Image], image_module.Image, int], None]] = None From ab0193bbb7babf518125b3d03db10f67ad0e6e79 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Sat, 22 Oct 2022 15:54:34 -0700 Subject: [PATCH 058/125] Internal change PiperOrigin-RevId: 483078695 --- .../calculators/tensor/inference_calculator_gl.cc | 9 +++++++-- .../tensor/inference_calculator_gl_advanced.cc | 15 ++++++++++----- mediapipe/framework/calculator_profile.proto | 5 +++++ mediapipe/framework/profiler/trace_buffer.h | 5 +++++ 4 files changed, 27 insertions(+), 7 deletions(-) diff --git a/mediapipe/calculators/tensor/inference_calculator_gl.cc b/mediapipe/calculators/tensor/inference_calculator_gl.cc index 1f3768ee0..bd8eb3eed 100644 --- a/mediapipe/calculators/tensor/inference_calculator_gl.cc +++ b/mediapipe/calculators/tensor/inference_calculator_gl.cc @@ -26,6 +26,8 @@ #include "mediapipe/gpu/gl_calculator_helper.h" #include "tensorflow/lite/delegates/gpu/gl_delegate.h" +#define PERFETTO_TRACK_EVENT_NAMESPACE mediapipe + namespace mediapipe { namespace api2 { @@ -191,7 +193,7 @@ absl::Status InferenceCalculatorGlImpl::GpuInferenceRunner::Process( CalculatorContext* cc, const std::vector& input_tensors, std::vector& output_tensors) { return gpu_helper_.RunInGlContext( - [this, &input_tensors, &output_tensors]() -> absl::Status { + [this, cc, &input_tensors, &output_tensors]() -> absl::Status { // Explicitly copy input. for (int i = 0; i < input_tensors.size(); ++i) { glBindBuffer(GL_COPY_READ_BUFFER, @@ -203,7 +205,10 @@ absl::Status InferenceCalculatorGlImpl::GpuInferenceRunner::Process( } // Run inference. - RET_CHECK_EQ(interpreter_->Invoke(), kTfLiteOk); + { + MEDIAPIPE_PROFILING(GPU_TASK_INVOKE, cc); + RET_CHECK_EQ(interpreter_->Invoke(), kTfLiteOk); + } output_tensors.reserve(output_size_); for (int i = 0; i < output_size_; ++i) { diff --git a/mediapipe/calculators/tensor/inference_calculator_gl_advanced.cc b/mediapipe/calculators/tensor/inference_calculator_gl_advanced.cc index 7e11ee072..52359f7f5 100644 --- a/mediapipe/calculators/tensor/inference_calculator_gl_advanced.cc +++ b/mediapipe/calculators/tensor/inference_calculator_gl_advanced.cc @@ -32,6 +32,8 @@ #include "mediapipe/util/android/file/base/helpers.h" #endif // MEDIAPIPE_ANDROID +#define PERFETTO_TRACK_EVENT_NAMESPACE mediapipe + namespace mediapipe { namespace api2 { @@ -83,7 +85,7 @@ class InferenceCalculatorGlAdvancedImpl const mediapipe::InferenceCalculatorOptions::Delegate& delegate); absl::StatusOr> Process( - const std::vector& input_tensors); + CalculatorContext* cc, const std::vector& input_tensors); absl::Status Close(); @@ -121,11 +123,11 @@ absl::Status InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::Init( absl::StatusOr> InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::Process( - const std::vector& input_tensors) { + CalculatorContext* cc, const std::vector& input_tensors) { std::vector output_tensors; MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext( - [this, &input_tensors, &output_tensors]() -> absl::Status { + [this, cc, &input_tensors, &output_tensors]() -> absl::Status { for (int i = 0; i < input_tensors.size(); ++i) { MP_RETURN_IF_ERROR(tflite_gpu_runner_->BindSSBOToInputTensor( input_tensors[i].GetOpenGlBufferReadView().name(), i)); @@ -138,7 +140,10 @@ InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::Process( output_tensors.back().GetOpenGlBufferWriteView().name(), i)); } // Run inference. - return tflite_gpu_runner_->Invoke(); + { + MEDIAPIPE_PROFILING(GPU_TASK_INVOKE, cc); + return tflite_gpu_runner_->Invoke(); + } })); return output_tensors; @@ -354,7 +359,7 @@ absl::Status InferenceCalculatorGlAdvancedImpl::Process(CalculatorContext* cc) { auto output_tensors = absl::make_unique>(); ASSIGN_OR_RETURN(*output_tensors, - gpu_inference_runner_->Process(input_tensors)); + gpu_inference_runner_->Process(cc, input_tensors)); kOutTensors(cc).Send(std::move(output_tensors)); return absl::OkStatus(); diff --git a/mediapipe/framework/calculator_profile.proto b/mediapipe/framework/calculator_profile.proto index 06ec678a9..1512da6af 100644 --- a/mediapipe/framework/calculator_profile.proto +++ b/mediapipe/framework/calculator_profile.proto @@ -133,7 +133,12 @@ message GraphTrace { TPU_TASK = 13; GPU_CALIBRATION = 14; PACKET_QUEUED = 15; + GPU_TASK_INVOKE = 16; + TPU_TASK_INVOKE = 17; } + // //depot/mediapipe/framework/mediapipe_profiling.h:profiler_census_tags, + // //depot/mediapipe/framework/profiler/trace_buffer.h:event_type_list, + // ) // The timing for one packet set being processed at one caclulator node. message CalculatorTrace { diff --git a/mediapipe/framework/profiler/trace_buffer.h b/mediapipe/framework/profiler/trace_buffer.h index 069f09610..60352c705 100644 --- a/mediapipe/framework/profiler/trace_buffer.h +++ b/mediapipe/framework/profiler/trace_buffer.h @@ -109,6 +109,11 @@ struct TraceEvent { static constexpr EventType TPU_TASK = GraphTrace::TPU_TASK; static constexpr EventType GPU_CALIBRATION = GraphTrace::GPU_CALIBRATION; static constexpr EventType PACKET_QUEUED = GraphTrace::PACKET_QUEUED; + static constexpr EventType GPU_TASK_INVOKE = GraphTrace::GPU_TASK_INVOKE; + static constexpr EventType TPU_TASK_INVOKE = GraphTrace::TPU_TASK_INVOKE; + // //depot/mediapipe/framework/mediapipe_profiling.h:profiler_census_tags, + // //depot/mediapipe/framework/calculator_profile.proto:event_type, + // ) }; // Packet trace log buffer. From ec2a34d2a43639d8a9a2169f3377452a8a37b40f Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Sun, 23 Oct 2022 16:42:49 -0700 Subject: [PATCH 059/125] Replace pytype_struct_contrib_test by py_strict_test. Also remove unnecessary BUILD attributes. PiperOrigin-RevId: 483237371 --- mediapipe/model_maker/python/core/BUILD | 2 +- mediapipe/model_maker/python/core/data/BUILD | 9 +-------- mediapipe/model_maker/python/core/tasks/BUILD | 7 +------ mediapipe/model_maker/python/core/utils/BUILD | 9 +-------- mediapipe/model_maker/python/vision/core/BUILD | 2 +- .../model_maker/python/vision/image_classifier/BUILD | 2 +- mediapipe/tasks/python/components/containers/BUILD | 2 +- mediapipe/tasks/python/core/BUILD | 2 +- mediapipe/tasks/python/metadata/metadata_writers/BUILD | 2 +- mediapipe/tasks/python/test/BUILD | 2 +- mediapipe/tasks/python/vision/BUILD | 2 +- mediapipe/tasks/python/vision/core/BUILD | 2 +- 12 files changed, 12 insertions(+), 31 deletions(-) diff --git a/mediapipe/model_maker/python/core/BUILD b/mediapipe/model_maker/python/core/BUILD index 9f205bb11..636a1a720 100644 --- a/mediapipe/model_maker/python/core/BUILD +++ b/mediapipe/model_maker/python/core/BUILD @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict library and test compatibility macro. package( default_visibility = ["//mediapipe:__subpackages__"], diff --git a/mediapipe/model_maker/python/core/data/BUILD b/mediapipe/model_maker/python/core/data/BUILD index c4c659d56..70a62e8f7 100644 --- a/mediapipe/model_maker/python/core/data/BUILD +++ b/mediapipe/model_maker/python/core/data/BUILD @@ -13,6 +13,7 @@ # limitations under the License. # Placeholder for internal Python strict library and test compatibility macro. +# Placeholder for internal Python strict test compatibility macro. licenses(["notice"]) @@ -23,15 +24,12 @@ package( py_library( name = "data_util", srcs = ["data_util.py"], - srcs_version = "PY3", ) py_test( name = "data_util_test", srcs = ["data_util_test.py"], data = ["//mediapipe/model_maker/python/core/data/testdata"], - python_version = "PY3", - srcs_version = "PY3", deps = [":data_util"], ) @@ -44,8 +42,6 @@ py_library( py_test( name = "dataset_test", srcs = ["dataset_test.py"], - python_version = "PY3", - srcs_version = "PY3", deps = [ ":dataset", "//mediapipe/model_maker/python/core/utils:test_util", @@ -55,14 +51,11 @@ py_test( py_library( name = "classification_dataset", srcs = ["classification_dataset.py"], - srcs_version = "PY3", deps = [":dataset"], ) py_test( name = "classification_dataset_test", srcs = ["classification_dataset_test.py"], - python_version = "PY3", - srcs_version = "PY3", deps = [":classification_dataset"], ) diff --git a/mediapipe/model_maker/python/core/tasks/BUILD b/mediapipe/model_maker/python/core/tasks/BUILD index b3588f0be..124de621a 100644 --- a/mediapipe/model_maker/python/core/tasks/BUILD +++ b/mediapipe/model_maker/python/core/tasks/BUILD @@ -13,6 +13,7 @@ # limitations under the License. # Placeholder for internal Python strict library and test compatibility macro. +# Placeholder for internal Python strict test compatibility macro. package( default_visibility = ["//mediapipe:__subpackages__"], @@ -23,7 +24,6 @@ licenses(["notice"]) py_library( name = "custom_model", srcs = ["custom_model.py"], - srcs_version = "PY3", deps = [ "//mediapipe/model_maker/python/core/data:dataset", "//mediapipe/model_maker/python/core/utils:model_util", @@ -34,8 +34,6 @@ py_library( py_test( name = "custom_model_test", srcs = ["custom_model_test.py"], - python_version = "PY3", - srcs_version = "PY3", deps = [ ":custom_model", "//mediapipe/model_maker/python/core/utils:test_util", @@ -45,7 +43,6 @@ py_test( py_library( name = "classifier", srcs = ["classifier.py"], - srcs_version = "PY3", deps = [ ":custom_model", "//mediapipe/model_maker/python/core/data:dataset", @@ -55,8 +52,6 @@ py_library( py_test( name = "classifier_test", srcs = ["classifier_test.py"], - python_version = "PY3", - srcs_version = "PY3", deps = [ ":classifier", "//mediapipe/model_maker/python/core/utils:test_util", diff --git a/mediapipe/model_maker/python/core/utils/BUILD b/mediapipe/model_maker/python/core/utils/BUILD index 2538ec8fa..a2ec52044 100644 --- a/mediapipe/model_maker/python/core/utils/BUILD +++ b/mediapipe/model_maker/python/core/utils/BUILD @@ -13,6 +13,7 @@ # limitations under the License. # Placeholder for internal Python strict library and test compatibility macro. +# Placeholder for internal Python strict test compatibility macro. licenses(["notice"]) @@ -24,7 +25,6 @@ py_library( name = "test_util", testonly = 1, srcs = ["test_util.py"], - srcs_version = "PY3", deps = [ ":model_util", "//mediapipe/model_maker/python/core/data:dataset", @@ -34,7 +34,6 @@ py_library( py_library( name = "model_util", srcs = ["model_util.py"], - srcs_version = "PY3", deps = [ ":quantization", "//mediapipe/model_maker/python/core/data:dataset", @@ -44,8 +43,6 @@ py_library( py_test( name = "model_util_test", srcs = ["model_util_test.py"], - python_version = "PY3", - srcs_version = "PY3", deps = [ ":model_util", ":quantization", @@ -62,8 +59,6 @@ py_library( py_test( name = "loss_functions_test", srcs = ["loss_functions_test.py"], - python_version = "PY3", - srcs_version = "PY3", deps = [":loss_functions"], ) @@ -77,8 +72,6 @@ py_library( py_test( name = "quantization_test", srcs = ["quantization_test.py"], - python_version = "PY3", - srcs_version = "PY3", deps = [ ":quantization", ":test_util", diff --git a/mediapipe/model_maker/python/vision/core/BUILD b/mediapipe/model_maker/python/vision/core/BUILD index 2658841ae..0b15a0276 100644 --- a/mediapipe/model_maker/python/vision/core/BUILD +++ b/mediapipe/model_maker/python/vision/core/BUILD @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict library and test compatibility macro. # Placeholder for internal Python strict test compatibility macro. licenses(["notice"]) diff --git a/mediapipe/model_maker/python/vision/image_classifier/BUILD b/mediapipe/model_maker/python/vision/image_classifier/BUILD index 5b4ec2bd1..a2268059f 100644 --- a/mediapipe/model_maker/python/vision/image_classifier/BUILD +++ b/mediapipe/model_maker/python/vision/image_classifier/BUILD @@ -12,8 +12,8 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Placeholder for internal Python library rule. # Placeholder for internal Python strict library and test compatibility macro. +# Placeholder for internal Python library rule. licenses(["notice"]) diff --git a/mediapipe/tasks/python/components/containers/BUILD b/mediapipe/tasks/python/components/containers/BUILD index 8dd9fcd60..fd25401f7 100644 --- a/mediapipe/tasks/python/components/containers/BUILD +++ b/mediapipe/tasks/python/components/containers/BUILD @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict library and test compatibility macro. package(default_visibility = ["//mediapipe/tasks:internal"]) diff --git a/mediapipe/tasks/python/core/BUILD b/mediapipe/tasks/python/core/BUILD index d5cdeecda..76e2f4f4a 100644 --- a/mediapipe/tasks/python/core/BUILD +++ b/mediapipe/tasks/python/core/BUILD @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict library and test compatibility macro. package(default_visibility = ["//mediapipe/tasks:internal"]) diff --git a/mediapipe/tasks/python/metadata/metadata_writers/BUILD b/mediapipe/tasks/python/metadata/metadata_writers/BUILD index 3e44218ac..2a0c29dec 100644 --- a/mediapipe/tasks/python/metadata/metadata_writers/BUILD +++ b/mediapipe/tasks/python/metadata/metadata_writers/BUILD @@ -1,4 +1,4 @@ -# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict library and test compatibility macro. package( default_visibility = [ diff --git a/mediapipe/tasks/python/test/BUILD b/mediapipe/tasks/python/test/BUILD index 8e5b91cf9..92c5f4038 100644 --- a/mediapipe/tasks/python/test/BUILD +++ b/mediapipe/tasks/python/test/BUILD @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict library and test compatibility macro. package(default_visibility = ["//mediapipe/tasks:internal"]) diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 7ff818610..e7be51c8d 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict library and test compatibility macro. package(default_visibility = ["//mediapipe/tasks:internal"]) diff --git a/mediapipe/tasks/python/vision/core/BUILD b/mediapipe/tasks/python/vision/core/BUILD index c7422969a..df1b06f4c 100644 --- a/mediapipe/tasks/python/vision/core/BUILD +++ b/mediapipe/tasks/python/vision/core/BUILD @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Placeholder for internal Python strict library compatibility macro. +# Placeholder for internal Python strict library and test compatibility macro. package(default_visibility = ["//mediapipe/tasks:internal"]) From ab17be92947d539410c2dc1b111321de9562de04 Mon Sep 17 00:00:00 2001 From: Yuqi Li Date: Sun, 23 Oct 2022 23:03:44 -0700 Subject: [PATCH 060/125] Metadata Writer: Add Metadata Writer for image classifier. PiperOrigin-RevId: 483282627 --- .../python/metadata/metadata_writers/BUILD | 6 + .../metadata_writers/image_classifier.py | 71 ++ .../metadata_writers/metadata_writer.py | 130 ++- .../test/metadata/metadata_writers/BUILD | 21 +- .../metadata_writers/image_classifier_test.py | 76 ++ .../metadata_writers/metadata_writer_test.py | 56 +- mediapipe/tasks/testdata/metadata/BUILD | 10 + mediapipe/tasks/testdata/metadata/labels.txt | 1001 +++++++++++++++++ .../metadata/mobilenet_v2_1.0_224.json | 82 ++ .../metadata/mobilenet_v2_1.0_224_quant.json | 82 ++ third_party/external_files.bzl | 30 + 11 files changed, 1537 insertions(+), 28 deletions(-) create mode 100644 mediapipe/tasks/python/metadata/metadata_writers/image_classifier.py create mode 100644 mediapipe/tasks/python/test/metadata/metadata_writers/image_classifier_test.py create mode 100644 mediapipe/tasks/testdata/metadata/labels.txt create mode 100644 mediapipe/tasks/testdata/metadata/mobilenet_v2_1.0_224.json create mode 100644 mediapipe/tasks/testdata/metadata/mobilenet_v2_1.0_224_quant.json diff --git a/mediapipe/tasks/python/metadata/metadata_writers/BUILD b/mediapipe/tasks/python/metadata/metadata_writers/BUILD index 2a0c29dec..d2b55d47d 100644 --- a/mediapipe/tasks/python/metadata/metadata_writers/BUILD +++ b/mediapipe/tasks/python/metadata/metadata_writers/BUILD @@ -37,3 +37,9 @@ py_library( srcs = ["writer_utils.py"], deps = ["//mediapipe/tasks/metadata:schema_py"], ) + +py_library( + name = "image_classifier", + srcs = ["image_classifier.py"], + deps = [":metadata_writer"], +) diff --git a/mediapipe/tasks/python/metadata/metadata_writers/image_classifier.py b/mediapipe/tasks/python/metadata/metadata_writers/image_classifier.py new file mode 100644 index 000000000..c516a342d --- /dev/null +++ b/mediapipe/tasks/python/metadata/metadata_writers/image_classifier.py @@ -0,0 +1,71 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== +"""Writes metadata and label file to the image classifier models.""" + +from typing import List, Optional + +from mediapipe.tasks.python.metadata.metadata_writers import metadata_writer + +_MODEL_NAME = "ImageClassifier" +_MODEL_DESCRIPTION = ("Identify the most prominent object in the image from a " + "known set of categories.") + + +class MetadataWriter(metadata_writer.MetadataWriterBase): + """MetadataWriter to write the metadata for image classifier.""" + + @classmethod + def create( + cls, + model_buffer: bytearray, + input_norm_mean: List[float], + input_norm_std: List[float], + labels: metadata_writer.Labels, + score_calibration: Optional[metadata_writer.ScoreCalibration] = None + ) -> "MetadataWriter": + """Creates MetadataWriter to write the metadata for image classifier. + + The parameters required in this method are mandatory when using MediaPipe + Tasks. + + Note that only the output TFLite is used for deployment. The output JSON + content is used to interpret the metadata content. + + Args: + model_buffer: A valid flatbuffer loaded from the TFLite model file. + input_norm_mean: the mean value used in the input tensor normalization + [1]. + input_norm_std: the std value used in the input tensor normalizarion [1]. + labels: an instance of Labels helper class used in the output + classification tensor [2]. + score_calibration: A container of the score calibration operation [3] in + the classification tensor. Optional if the model does not use score + calibration. + + [1]: + https://github.com/google/mediapipe/blob/f8af41b1eb49ff4bdad756ff19d1d36f486be614/mediapipe/tasks/metadata/metadata_schema.fbs#L389 + [2]: + https://github.com/google/mediapipe/blob/f8af41b1eb49ff4bdad756ff19d1d36f486be614/mediapipe/tasks/metadata/metadata_schema.fbs#L99 + [3]: + https://github.com/google/mediapipe/blob/f8af41b1eb49ff4bdad756ff19d1d36f486be614/mediapipe/tasks/metadata/metadata_schema.fbs#L456 + + Returns: + An MetadataWrite object. + """ + writer = metadata_writer.MetadataWriter(model_buffer) + writer.add_genernal_info(_MODEL_NAME, _MODEL_DESCRIPTION) + writer.add_image_input(input_norm_mean, input_norm_std) + writer.add_classification_output(labels, score_calibration) + return cls(writer) diff --git a/mediapipe/tasks/python/metadata/metadata_writers/metadata_writer.py b/mediapipe/tasks/python/metadata/metadata_writers/metadata_writer.py index e69efd015..5a2eaba07 100644 --- a/mediapipe/tasks/python/metadata/metadata_writers/metadata_writer.py +++ b/mediapipe/tasks/python/metadata/metadata_writers/metadata_writer.py @@ -15,19 +15,22 @@ """Generic metadata writer.""" import collections +import csv import dataclasses import os import tempfile from typing import List, Optional, Tuple import flatbuffers -from mediapipe.tasks.metadata import metadata_schema_py_generated as _metadata_fb -from mediapipe.tasks.python.metadata import metadata as _metadata +from mediapipe.tasks.metadata import metadata_schema_py_generated as metadata_fb +from mediapipe.tasks.python.metadata import metadata from mediapipe.tasks.python.metadata.metadata_writers import metadata_info from mediapipe.tasks.python.metadata.metadata_writers import writer_utils _INPUT_IMAGE_NAME = 'image' _INPUT_IMAGE_DESCRIPTION = 'Input image to be processed.' +_OUTPUT_CLASSIFICATION_NAME = 'score' +_OUTPUT_CLASSIFICATION_DESCRIPTION = 'Score of the labels respectively.' @dataclasses.dataclass @@ -140,26 +143,85 @@ class Labels(object): class ScoreCalibration: """Simple container holding score calibration related parameters.""" - # A shortcut to avoid client side code importing _metadata_fb - transformation_types = _metadata_fb.ScoreTransformationType + # A shortcut to avoid client side code importing metadata_fb + transformation_types = metadata_fb.ScoreTransformationType def __init__(self, - transformation_type: _metadata_fb.ScoreTransformationType, - parameters: List[CalibrationParameter], + transformation_type: metadata_fb.ScoreTransformationType, + parameters: List[Optional[CalibrationParameter]], default_score: int = 0): self.transformation_type = transformation_type self.parameters = parameters self.default_score = default_score + @classmethod + def create_from_file(cls, + transformation_type: metadata_fb.ScoreTransformationType, + file_path: str, + default_score: int = 0) -> 'ScoreCalibration': + """Creates ScoreCalibration from the file. + + Args: + transformation_type: type of the function used for transforming the + uncalibrated score before applying score calibration. + file_path: file_path of the score calibration file [1]. Contains + sigmoid-based score calibration parameters, formatted as CSV. Lines + contain for each index of an output tensor the scale, slope, offset and + (optional) min_score parameters to be used for sigmoid fitting (in this + order and in `strtof`-compatible [2] format). Scale should be a + non-negative value. A line may be left empty to default calibrated + scores for this index to default_score. In summary, each line should + thus contain 0, 3 or 4 comma-separated values. + default_score: the default calibrated score to apply if the uncalibrated + score is below min_score or if no parameters were specified for a given + index. + [1]: + https://github.com/google/mediapipe/blob/f8af41b1eb49ff4bdad756ff19d1d36f486be614/mediapipe/tasks/metadata/metadata_schema.fbs#L133 + [2]: + https://en.cppreference.com/w/c/string/byte/strtof + + Returns: + A ScoreCalibration object. + Raises: + ValueError: if the score_calibration file is malformed. + """ + with open(file_path, 'r') as calibration_file: + csv_reader = csv.reader(calibration_file, delimiter=',') + parameters = [] + for row in csv_reader: + if not row: + parameters.append(None) + continue + + if len(row) != 3 and len(row) != 4: + raise ValueError( + f'Expected empty lines or 3 or 4 parameters per line in score' + f' calibration file, but got {len(row)}.') + + if float(row[0]) < 0: + raise ValueError( + f'Expected scale to be a non-negative value, but got ' + f'{float(row[0])}.') + + parameters.append( + CalibrationParameter( + scale=float(row[0]), + slope=float(row[1]), + offset=float(row[2]), + min_score=None if len(row) == 3 else float(row[3]))) + + return cls(transformation_type, parameters, default_score) + def _fill_default_tensor_names( - tensor_metadata: List[_metadata_fb.TensorMetadataT], + tensor_metadata_list: List[metadata_fb.TensorMetadataT], tensor_names_from_model: List[str]): """Fills the default tensor names.""" # If tensor name in metadata is empty, default to the tensor name saved in # the model. - for metadata, name in zip(tensor_metadata, tensor_names_from_model): - metadata.name = metadata.name or name + for tensor_metadata, name in zip(tensor_metadata_list, + tensor_names_from_model): + tensor_metadata.name = tensor_metadata.name or name def _pair_tensor_metadata( @@ -212,7 +274,7 @@ def _create_metadata_buffer( input_metadata = [m.create_metadata() for m in input_md] else: num_input_tensors = writer_utils.get_subgraph(model_buffer).InputsLength() - input_metadata = [_metadata_fb.TensorMetadataT()] * num_input_tensors + input_metadata = [metadata_fb.TensorMetadataT()] * num_input_tensors _fill_default_tensor_names(input_metadata, writer_utils.get_input_tensor_names(model_buffer)) @@ -224,12 +286,12 @@ def _create_metadata_buffer( output_metadata = [m.create_metadata() for m in output_md] else: num_output_tensors = writer_utils.get_subgraph(model_buffer).OutputsLength() - output_metadata = [_metadata_fb.TensorMetadataT()] * num_output_tensors + output_metadata = [metadata_fb.TensorMetadataT()] * num_output_tensors _fill_default_tensor_names(output_metadata, writer_utils.get_output_tensor_names(model_buffer)) # Create the subgraph metadata. - subgraph_metadata = _metadata_fb.SubGraphMetadataT() + subgraph_metadata = metadata_fb.SubGraphMetadataT() subgraph_metadata.inputTensorMetadata = input_metadata subgraph_metadata.outputTensorMetadata = output_metadata @@ -243,7 +305,7 @@ def _create_metadata_buffer( b = flatbuffers.Builder(0) b.Finish( model_metadata.Pack(b), - _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER) + metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER) return b.Output() @@ -291,7 +353,7 @@ class MetadataWriter(object): name=model_name, description=model_description) return self - color_space_types = _metadata_fb.ColorSpaceType + color_space_types = metadata_fb.ColorSpaceType def add_feature_input(self, name: Optional[str] = None, @@ -305,7 +367,7 @@ class MetadataWriter(object): self, norm_mean: List[float], norm_std: List[float], - color_space_type: Optional[int] = _metadata_fb.ColorSpaceType.RGB, + color_space_type: Optional[int] = metadata_fb.ColorSpaceType.RGB, name: str = _INPUT_IMAGE_NAME, description: str = _INPUT_IMAGE_DESCRIPTION) -> 'MetadataWriter': """Adds an input image metadata for the image input. @@ -341,9 +403,6 @@ class MetadataWriter(object): self._input_mds.append(input_md) return self - _OUTPUT_CLASSIFICATION_NAME = 'score' - _OUTPUT_CLASSIFICATION_DESCRIPTION = 'Score of the labels respectively' - def add_classification_output( self, labels: Optional[Labels] = None, @@ -416,8 +475,7 @@ class MetadataWriter(object): A tuple of (model_with_metadata_in_bytes, metdata_json_content) """ # Populates metadata and associated files into TFLite model buffer. - populator = _metadata.MetadataPopulator.with_model_buffer( - self._model_buffer) + populator = metadata.MetadataPopulator.with_model_buffer(self._model_buffer) metadata_buffer = _create_metadata_buffer( model_buffer=self._model_buffer, general_md=self._general_md, @@ -429,7 +487,7 @@ class MetadataWriter(object): populator.populate() tflite_content = populator.get_model_buffer() - displayer = _metadata.MetadataDisplayer.with_model_buffer(tflite_content) + displayer = metadata.MetadataDisplayer.with_model_buffer(tflite_content) metadata_json_content = displayer.get_metadata_json() return tflite_content, metadata_json_content @@ -452,9 +510,7 @@ class MetadataWriter(object): """Stores calibration parameters in a csv file.""" filepath = os.path.join(self._temp_folder.name, filename) with open(filepath, 'w') as f: - for idx, item in enumerate(calibrations): - if idx != 0: - f.write('\n') + for item in calibrations: if item: if item.scale is None or item.slope is None or item.offset is None: raise ValueError('scale, slope and offset values can not be set to ' @@ -463,6 +519,30 @@ class MetadataWriter(object): f.write(f'{item.scale},{item.slope},{item.offset},{item.min_score}') else: f.write(f'{item.scale},{item.slope},{item.offset}') + f.write('\n') - self._associated_files.append(filepath) + self._associated_files.append(filepath) return filepath + + +class MetadataWriterBase: + """Base MetadataWriter class which contains the apis exposed to users. + + MetadataWriter for Tasks e.g. image classifier / object detector will inherit + this class for their own usage. + """ + + def __init__(self, writer: MetadataWriter) -> None: + self.writer = writer + + def populate(self) -> Tuple[bytearray, str]: + """Populates metadata into the TFLite file. + + Note that only the output tflite is used for deployment. The output JSON + content is used to interpret the metadata content. + + Returns: + A tuple of (model_with_metadata_in_bytes, metdata_json_content) + """ + return self.writer.populate() + diff --git a/mediapipe/tasks/python/test/metadata/metadata_writers/BUILD b/mediapipe/tasks/python/test/metadata/metadata_writers/BUILD index 8779d2fb6..a7bfd297d 100644 --- a/mediapipe/tasks/python/test/metadata/metadata_writers/BUILD +++ b/mediapipe/tasks/python/test/metadata/metadata_writers/BUILD @@ -28,9 +28,28 @@ py_test( py_test( name = "metadata_writer_test", srcs = ["metadata_writer_test.py"], - data = ["//mediapipe/tasks/testdata/metadata:model_files"], + data = [ + "//mediapipe/tasks/testdata/metadata:data_files", + "//mediapipe/tasks/testdata/metadata:model_files", + ], deps = [ "//mediapipe/tasks/python/metadata/metadata_writers:metadata_writer", "//mediapipe/tasks/python/test:test_utils", ], ) + +py_test( + name = "image_classifier_test", + srcs = ["image_classifier_test.py"], + data = [ + "//mediapipe/tasks/testdata/metadata:data_files", + "//mediapipe/tasks/testdata/metadata:model_files", + ], + deps = [ + "//mediapipe/tasks/metadata:metadata_schema_py", + "//mediapipe/tasks/python/metadata", + "//mediapipe/tasks/python/metadata/metadata_writers:image_classifier", + "//mediapipe/tasks/python/metadata/metadata_writers:metadata_writer", + "//mediapipe/tasks/python/test:test_utils", + ], +) diff --git a/mediapipe/tasks/python/test/metadata/metadata_writers/image_classifier_test.py b/mediapipe/tasks/python/test/metadata/metadata_writers/image_classifier_test.py new file mode 100644 index 000000000..4bbd91667 --- /dev/null +++ b/mediapipe/tasks/python/test/metadata/metadata_writers/image_classifier_test.py @@ -0,0 +1,76 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== +"""Tests for metadata_writer.image_classifier.""" + +from absl.testing import absltest +from absl.testing import parameterized + +from mediapipe.tasks.metadata import metadata_schema_py_generated as metadata_fb +from mediapipe.tasks.python.metadata import metadata +from mediapipe.tasks.python.metadata.metadata_writers import image_classifier +from mediapipe.tasks.python.metadata.metadata_writers import metadata_writer +from mediapipe.tasks.python.test import test_utils + +_FLOAT_MODEL = test_utils.get_test_data_path( + "mobilenet_v2_1.0_224_without_metadata.tflite") +_QUANT_MODEL = test_utils.get_test_data_path( + "mobilenet_v2_1.0_224_quant_without_metadata.tflite") +_LABEL_FILE = test_utils.get_test_data_path("labels.txt") +_SCORE_CALIBRATION_FILE = test_utils.get_test_data_path("score_calibration.txt") +_SCORE_CALIBRATION_FILENAME = "score_calibration.txt" +_DEFAULT_SCORE_CALIBRATION_VALUE = 0.2 +_NORM_MEAN = 127.5 +_NORM_STD = 127.5 +_FLOAT_JSON = test_utils.get_test_data_path("mobilenet_v2_1.0_224.json") +_QUANT_JSON = test_utils.get_test_data_path("mobilenet_v2_1.0_224_quant.json") + + +class ImageClassifierTest(parameterized.TestCase): + + @parameterized.named_parameters( + { + "testcase_name": "test_float_model", + "model_file": _FLOAT_MODEL, + "golden_json": _FLOAT_JSON + }, { + "testcase_name": "test_quant_model", + "model_file": _QUANT_MODEL, + "golden_json": _QUANT_JSON + }) + def test_write_metadata(self, model_file: str, golden_json: str): + with open(model_file, "rb") as f: + model_buffer = f.read() + writer = image_classifier.MetadataWriter.create( + model_buffer, [_NORM_MEAN], [_NORM_STD], + labels=metadata_writer.Labels().add_from_file(_LABEL_FILE), + score_calibration=metadata_writer.ScoreCalibration.create_from_file( + metadata_fb.ScoreTransformationType.LOG, _SCORE_CALIBRATION_FILE, + _DEFAULT_SCORE_CALIBRATION_VALUE)) + tflite_content, metadata_json = writer.populate() + + with open(golden_json, "r") as f: + expected_json = f.read() + self.assertEqual(metadata_json, expected_json) + + displayer = metadata.MetadataDisplayer.with_model_buffer(tflite_content) + file_buffer = displayer.get_associated_file_buffer( + _SCORE_CALIBRATION_FILENAME) + with open(_SCORE_CALIBRATION_FILE, "rb") as f: + expected_file_buffer = f.read() + self.assertEqual(file_buffer, expected_file_buffer) + + +if __name__ == "__main__": + absltest.main() diff --git a/mediapipe/tasks/python/test/metadata/metadata_writers/metadata_writer_test.py b/mediapipe/tasks/python/test/metadata/metadata_writers/metadata_writer_test.py index c39b4a555..51b043c7d 100644 --- a/mediapipe/tasks/python/test/metadata/metadata_writers/metadata_writer_test.py +++ b/mediapipe/tasks/python/test/metadata/metadata_writers/metadata_writer_test.py @@ -13,6 +13,9 @@ # limitations under the License. # ============================================================================== """Tests for metadata writer classes.""" +import os +import tempfile + from absl.testing import absltest from mediapipe.tasks.python.metadata.metadata_writers import metadata_writer @@ -20,6 +23,7 @@ from mediapipe.tasks.python.test import test_utils _IMAGE_CLASSIFIER_MODEL = test_utils.get_test_data_path( 'mobilenet_v1_0.25_224_1_default_1.tflite') +_SCORE_CALIBRATION_FILE = test_utils.get_test_data_path('score_calibration.txt') class LabelsTest(absltest.TestCase): @@ -49,6 +53,54 @@ class LabelsTest(absltest.TestCase): ]) +class ScoreCalibrationTest(absltest.TestCase): + + def test_create_from_file_successful(self): + score_calibration = metadata_writer.ScoreCalibration.create_from_file( + metadata_writer.ScoreCalibration.transformation_types.LOG, + _SCORE_CALIBRATION_FILE) + self.assertLen(score_calibration.parameters, 511) + self.assertIsNone(score_calibration.parameters[0]) + self.assertEqual( + score_calibration.parameters[1], + metadata_writer.CalibrationParameter( + scale=0.9876328110694885, + slope=0.36622241139411926, + offset=0.5352765321731567, + min_score=0.71484375)) + self.assertEqual( + score_calibration.parameters[510], + metadata_writer.CalibrationParameter( + scale=0.9901729226112366, + slope=0.8561913371086121, + offset=0.8783953189849854, + min_score=0.5859375)) + + def test_create_from_file_fail(self): + with tempfile.TemporaryDirectory() as temp_dir: + test_file = os.path.join(temp_dir, 'score_calibration.csv') + with open(test_file, 'w') as f: + f.write('0.98,0.5\n') + + with self.assertRaisesRegex( + ValueError, + 'Expected empty lines or 3 or 4 parameters per line in score ' + 'calibration file, but got 2.' + ): + metadata_writer.ScoreCalibration.create_from_file( + metadata_writer.ScoreCalibration.transformation_types.LOG, + test_file) + + with open(test_file, 'w') as f: + f.write('-0.98,0.5,0.34\n') + with self.assertRaisesRegex( + ValueError, + 'Expected scale to be a non-negative value, but got -0.98.'): + metadata_writer.ScoreCalibration.create_from_file( + metadata_writer.ScoreCalibration.transformation_types.LOG, + test_file) + + class MetadataWriterForTaskTest(absltest.TestCase): def setUp(self): @@ -197,7 +249,7 @@ class MetadataWriterForTaskTest(absltest.TestCase): "output_tensor_metadata": [ { "name": "score", - "description": "Score of the labels respectively", + "description": "Score of the labels respectively.", "content": { "content_properties_type": "FeatureProperties", "content_properties": { @@ -298,7 +350,7 @@ class MetadataWriterForTaskTest(absltest.TestCase): "output_tensor_metadata": [ { "name": "score", - "description": "Score of the labels respectively", + "description": "Score of the labels respectively.", "content": { "content_properties_type": "FeatureProperties", "content_properties": { diff --git a/mediapipe/tasks/testdata/metadata/BUILD b/mediapipe/tasks/testdata/metadata/BUILD index 9f50368b8..6d7bbab6a 100644 --- a/mediapipe/tasks/testdata/metadata/BUILD +++ b/mediapipe/tasks/testdata/metadata/BUILD @@ -29,6 +29,8 @@ mediapipe_files(srcs = [ "mobile_object_classifier_v0_2_3-metadata-no-name.tflite", "mobilenet_v1_0.25_224_1_default_1.tflite", "mobilenet_v2_1.0_224_quant.tflite", + "mobilenet_v2_1.0_224_quant_without_metadata.tflite", + "mobilenet_v2_1.0_224_without_metadata.tflite", ]) exports_files([ @@ -48,6 +50,9 @@ exports_files([ "score_calibration.txt", "score_calibration_file_meta.json", "score_calibration_tensor_meta.json", + "labels.txt", + "mobilenet_v2_1.0_224.json", + "mobilenet_v2_1.0_224_quant.json", ]) filegroup( @@ -59,6 +64,8 @@ filegroup( "mobile_object_classifier_v0_2_3-metadata-no-name.tflite", "mobilenet_v1_0.25_224_1_default_1.tflite", "mobilenet_v2_1.0_224_quant.tflite", + "mobilenet_v2_1.0_224_quant_without_metadata.tflite", + "mobilenet_v2_1.0_224_without_metadata.tflite", ], ) @@ -78,6 +85,9 @@ filegroup( "input_image_tensor_float_meta.json", "input_image_tensor_uint8_meta.json", "input_image_tensor_unsupported_meta.json", + "labels.txt", + "mobilenet_v2_1.0_224.json", + "mobilenet_v2_1.0_224_quant.json", "score_calibration.txt", "score_calibration_file_meta.json", "score_calibration_tensor_meta.json", diff --git a/mediapipe/tasks/testdata/metadata/labels.txt b/mediapipe/tasks/testdata/metadata/labels.txt new file mode 100644 index 000000000..fe811239d --- /dev/null +++ b/mediapipe/tasks/testdata/metadata/labels.txt @@ -0,0 +1,1001 @@ +background +tench +goldfish +great white shark +tiger shark +hammerhead +electric ray +stingray +cock +hen +ostrich +brambling +goldfinch +house finch +junco +indigo bunting +robin +bulbul +jay +magpie +chickadee +water ouzel +kite +bald eagle +vulture +great grey owl +European fire salamander +common newt +eft +spotted salamander +axolotl +bullfrog +tree frog +tailed frog +loggerhead +leatherback turtle +mud turtle +terrapin +box turtle +banded gecko +common iguana +American chameleon +whiptail +agama +frilled lizard +alligator lizard +Gila monster +green lizard +African chameleon +Komodo dragon +African crocodile +American alligator +triceratops +thunder snake +ringneck snake +hognose snake +green snake +king snake +garter snake +water snake +vine snake +night snake +boa constrictor +rock python +Indian cobra +green mamba +sea snake +horned viper +diamondback +sidewinder +trilobite +harvestman +scorpion +black and gold garden spider +barn spider +garden spider +black widow +tarantula +wolf spider +tick +centipede +black grouse +ptarmigan +ruffed grouse +prairie chicken +peacock +quail +partridge +African grey +macaw +sulphur-crested cockatoo +lorikeet +coucal +bee eater +hornbill +hummingbird +jacamar +toucan +drake +red-breasted merganser +goose +black swan +tusker +echidna +platypus +wallaby +koala +wombat +jellyfish +sea anemone +brain coral +flatworm +nematode +conch +snail +slug +sea slug +chiton +chambered nautilus +Dungeness crab +rock crab +fiddler crab +king crab +American lobster +spiny lobster +crayfish +hermit crab +isopod +white stork +black stork +spoonbill +flamingo +little blue heron +American egret +bittern +crane +limpkin +European gallinule +American coot +bustard +ruddy turnstone +red-backed sandpiper +redshank +dowitcher +oystercatcher +pelican +king penguin +albatross +grey whale +killer whale +dugong +sea lion +Chihuahua +Japanese spaniel +Maltese dog +Pekinese +Shih-Tzu +Blenheim spaniel +papillon +toy terrier +Rhodesian ridgeback +Afghan hound +basset +beagle +bloodhound +bluetick +black-and-tan coonhound +Walker hound +English foxhound +redbone +borzoi +Irish wolfhound +Italian greyhound +whippet +Ibizan hound +Norwegian elkhound +otterhound +Saluki +Scottish deerhound +Weimaraner +Staffordshire bullterrier +American Staffordshire terrier +Bedlington terrier +Border terrier +Kerry blue terrier +Irish terrier +Norfolk terrier +Norwich terrier +Yorkshire terrier +wire-haired fox terrier +Lakeland terrier +Sealyham terrier +Airedale +cairn +Australian terrier +Dandie Dinmont +Boston bull +miniature schnauzer +giant schnauzer +standard schnauzer +Scotch terrier +Tibetan terrier +silky terrier +soft-coated wheaten terrier +West Highland white terrier +Lhasa +flat-coated retriever +curly-coated retriever +golden retriever +Labrador retriever +Chesapeake Bay retriever +German short-haired pointer +vizsla +English setter +Irish setter +Gordon setter +Brittany spaniel +clumber +English springer +Welsh springer spaniel +cocker spaniel +Sussex spaniel +Irish water spaniel +kuvasz +schipperke +groenendael +malinois +briard +kelpie +komondor +Old English sheepdog +Shetland sheepdog +collie +Border collie +Bouvier des Flandres +Rottweiler +German shepherd +Doberman +miniature pinscher +Greater Swiss Mountain dog +Bernese mountain dog +Appenzeller +EntleBucher +boxer +bull mastiff +Tibetan mastiff +French bulldog +Great Dane +Saint Bernard +Eskimo dog +malamute +Siberian husky +dalmatian +affenpinscher +basenji +pug +Leonberg +Newfoundland +Great Pyrenees +Samoyed +Pomeranian +chow +keeshond +Brabancon griffon +Pembroke +Cardigan +toy poodle +miniature poodle +standard poodle +Mexican hairless +timber wolf +white wolf +red wolf +coyote +dingo +dhole +African hunting dog +hyena +red fox +kit fox +Arctic fox +grey fox +tabby +tiger cat +Persian cat +Siamese cat +Egyptian cat +cougar +lynx +leopard +snow leopard +jaguar +lion +tiger +cheetah +brown bear +American black bear +ice bear +sloth bear +mongoose +meerkat +tiger beetle +ladybug +ground beetle +long-horned beetle +leaf beetle +dung beetle +rhinoceros beetle +weevil +fly +bee +ant +grasshopper +cricket +walking stick +cockroach +mantis +cicada +leafhopper +lacewing +dragonfly +damselfly +admiral +ringlet +monarch +cabbage butterfly +sulphur butterfly +lycaenid +starfish +sea urchin +sea cucumber +wood rabbit +hare +Angora +hamster +porcupine +fox squirrel +marmot +beaver +guinea pig +sorrel +zebra +hog +wild boar +warthog +hippopotamus +ox +water buffalo +bison +ram +bighorn +ibex +hartebeest +impala +gazelle +Arabian camel +llama +weasel +mink +polecat +black-footed ferret +otter +skunk +badger +armadillo +three-toed sloth +orangutan +gorilla +chimpanzee +gibbon +siamang +guenon +patas +baboon +macaque +langur +colobus +proboscis monkey +marmoset +capuchin +howler monkey +titi +spider monkey +squirrel monkey +Madagascar cat +indri +Indian elephant +African elephant +lesser panda +giant panda +barracouta +eel +coho +rock beauty +anemone fish +sturgeon +gar +lionfish +puffer +abacus +abaya +academic gown +accordion +acoustic guitar +aircraft carrier +airliner +airship +altar +ambulance +amphibian +analog clock +apiary +apron +ashcan +assault rifle +backpack +bakery +balance beam +balloon +ballpoint +Band Aid +banjo +bannister +barbell +barber chair +barbershop +barn +barometer +barrel +barrow +baseball +basketball +bassinet +bassoon +bathing cap +bath towel +bathtub +beach wagon +beacon +beaker +bearskin +beer bottle +beer glass +bell cote +bib +bicycle-built-for-two +bikini +binder +binoculars +birdhouse +boathouse +bobsled +bolo tie +bonnet +bookcase +bookshop +bottlecap +bow +bow tie +brass +brassiere +breakwater +breastplate +broom +bucket +buckle +bulletproof vest +bullet train +butcher shop +cab +caldron +candle +cannon +canoe +can opener +cardigan +car mirror +carousel +carpenter's kit +carton +car wheel +cash machine +cassette +cassette player +castle +catamaran +CD player +cello +cellular telephone +chain +chainlink fence +chain mail +chain saw +chest +chiffonier +chime +china cabinet +Christmas stocking +church +cinema +cleaver +cliff dwelling +cloak +clog +cocktail shaker +coffee mug +coffeepot +coil +combination lock +computer keyboard +confectionery +container ship +convertible +corkscrew +cornet +cowboy boot +cowboy hat +cradle +crane +crash helmet +crate +crib +Crock Pot +croquet ball +crutch +cuirass +dam +desk +desktop computer +dial telephone +diaper +digital clock +digital watch +dining table +dishrag +dishwasher +disk brake +dock +dogsled +dome +doormat +drilling platform +drum +drumstick +dumbbell +Dutch oven +electric fan +electric guitar +electric locomotive +entertainment center +envelope +espresso maker +face powder +feather boa +file +fireboat +fire engine +fire screen +flagpole +flute +folding chair +football helmet +forklift +fountain +fountain pen +four-poster +freight car +French horn +frying pan +fur coat +garbage truck +gasmask +gas pump +goblet +go-kart +golf ball +golfcart +gondola +gong +gown +grand piano +greenhouse +grille +grocery store +guillotine +hair slide +hair spray +half track +hammer +hamper +hand blower +hand-held computer +handkerchief +hard disc +harmonica +harp +harvester +hatchet +holster +home theater +honeycomb +hook +hoopskirt +horizontal bar +horse cart +hourglass +iPod +iron +jack-o'-lantern +jean +jeep +jersey +jigsaw puzzle +jinrikisha +joystick +kimono +knee pad +knot +lab coat +ladle +lampshade +laptop +lawn mower +lens cap +letter opener +library +lifeboat +lighter +limousine +liner +lipstick +Loafer +lotion +loudspeaker +loupe +lumbermill +magnetic compass +mailbag +mailbox +maillot +maillot +manhole cover +maraca +marimba +mask +matchstick +maypole +maze +measuring cup +medicine chest +megalith +microphone +microwave +military uniform +milk can +minibus +miniskirt +minivan +missile +mitten +mixing bowl +mobile home +Model T +modem +monastery +monitor +moped +mortar +mortarboard +mosque +mosquito net +motor scooter +mountain bike +mountain tent +mouse +mousetrap +moving van +muzzle +nail +neck brace +necklace +nipple +notebook +obelisk +oboe +ocarina +odometer +oil filter +organ +oscilloscope +overskirt +oxcart +oxygen mask +packet +paddle +paddlewheel +padlock +paintbrush +pajama +palace +panpipe +paper towel +parachute +parallel bars +park bench +parking meter +passenger car +patio +pay-phone +pedestal +pencil box +pencil sharpener +perfume +Petri dish +photocopier +pick +pickelhaube +picket fence +pickup +pier +piggy bank +pill bottle +pillow +ping-pong ball +pinwheel +pirate +pitcher +plane +planetarium +plastic bag +plate rack +plow +plunger +Polaroid camera +pole +police van +poncho +pool table +pop bottle +pot +potter's wheel +power drill +prayer rug +printer +prison +projectile +projector +puck +punching bag +purse +quill +quilt +racer +racket +radiator +radio +radio telescope +rain barrel +recreational vehicle +reel +reflex camera +refrigerator +remote control +restaurant +revolver +rifle +rocking chair +rotisserie +rubber eraser +rugby ball +rule +running shoe +safe +safety pin +saltshaker +sandal +sarong +sax +scabbard +scale +school bus +schooner +scoreboard +screen +screw +screwdriver +seat belt +sewing machine +shield +shoe shop +shoji +shopping basket +shopping cart +shovel +shower cap +shower curtain +ski +ski mask +sleeping bag +slide rule +sliding door +slot +snorkel +snowmobile +snowplow +soap dispenser +soccer ball +sock +solar dish +sombrero +soup bowl +space bar +space heater +space shuttle +spatula +speedboat +spider web +spindle +sports car +spotlight +stage +steam locomotive +steel arch bridge +steel drum +stethoscope +stole +stone wall +stopwatch +stove +strainer +streetcar +stretcher +studio couch +stupa +submarine +suit +sundial +sunglass +sunglasses +sunscreen +suspension bridge +swab +sweatshirt +swimming trunks +swing +switch +syringe +table lamp +tank +tape player +teapot +teddy +television +tennis ball +thatch +theater curtain +thimble +thresher +throne +tile roof +toaster +tobacco shop +toilet seat +torch +totem pole +tow truck +toyshop +tractor +trailer truck +tray +trench coat +tricycle +trimaran +tripod +triumphal arch +trolleybus +trombone +tub +turnstile +typewriter keyboard +umbrella +unicycle +upright +vacuum +vase +vault +velvet +vending machine +vestment +viaduct +violin +volleyball +waffle iron +wall clock +wallet +wardrobe +warplane +washbasin +washer +water bottle +water jug +water tower +whiskey jug +whistle +wig +window screen +window shade +Windsor tie +wine bottle +wing +wok +wooden spoon +wool +worm fence +wreck +yawl +yurt +web site +comic book +crossword puzzle +street sign +traffic light +book jacket +menu +plate +guacamole +consomme +hot pot +trifle +ice cream +ice lolly +French loaf +bagel +pretzel +cheeseburger +hotdog +mashed potato +head cabbage +broccoli +cauliflower +zucchini +spaghetti squash +acorn squash +butternut squash +cucumber +artichoke +bell pepper +cardoon +mushroom +Granny Smith +strawberry +orange +lemon +fig +pineapple +banana +jackfruit +custard apple +pomegranate +hay +carbonara +chocolate sauce +dough +meat loaf +pizza +potpie +burrito +red wine +espresso +cup +eggnog +alp +bubble +cliff +coral reef +geyser +lakeside +promontory +sandbar +seashore +valley +volcano +ballplayer +groom +scuba diver +rapeseed +daisy +yellow lady's slipper +corn +acorn +hip +buckeye +coral fungus +agaric +gyromitra +stinkhorn +earthstar +hen-of-the-woods +bolete +ear +toilet tissue diff --git a/mediapipe/tasks/testdata/metadata/mobilenet_v2_1.0_224.json b/mediapipe/tasks/testdata/metadata/mobilenet_v2_1.0_224.json new file mode 100644 index 000000000..6f01f9f09 --- /dev/null +++ b/mediapipe/tasks/testdata/metadata/mobilenet_v2_1.0_224.json @@ -0,0 +1,82 @@ +{ + "name": "ImageClassifier", + "description": "Identify the most prominent object in the image from a known set of categories.", + "subgraph_metadata": [ + { + "input_tensor_metadata": [ + { + "name": "image", + "description": "Input image to be processed.", + "content": { + "content_properties_type": "ImageProperties", + "content_properties": { + "color_space": "RGB" + } + }, + "process_units": [ + { + "options_type": "NormalizationOptions", + "options": { + "mean": [ + 127.5 + ], + "std": [ + 127.5 + ] + } + } + ], + "stats": { + "max": [ + 1.0 + ], + "min": [ + -1.0 + ] + } + } + ], + "output_tensor_metadata": [ + { + "name": "score", + "description": "Score of the labels respectively.", + "content": { + "content_properties_type": "FeatureProperties", + "content_properties": { + } + }, + "process_units": [ + { + "options_type": "ScoreCalibrationOptions", + "options": { + "score_transformation": "LOG", + "default_score": 0.2 + } + } + ], + "stats": { + "max": [ + 1.0 + ], + "min": [ + 0.0 + ] + }, + "associated_files": [ + { + "name": "labels.txt", + "description": "Labels for categories that the model can recognize.", + "type": "TENSOR_AXIS_LABELS" + }, + { + "name": "score_calibration.txt", + "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.", + "type": "TENSOR_AXIS_SCORE_CALIBRATION" + } + ] + } + ] + } + ], + "min_parser_version": "1.0.0" +} diff --git a/mediapipe/tasks/testdata/metadata/mobilenet_v2_1.0_224_quant.json b/mediapipe/tasks/testdata/metadata/mobilenet_v2_1.0_224_quant.json new file mode 100644 index 000000000..e2ba42e3b --- /dev/null +++ b/mediapipe/tasks/testdata/metadata/mobilenet_v2_1.0_224_quant.json @@ -0,0 +1,82 @@ +{ + "name": "ImageClassifier", + "description": "Identify the most prominent object in the image from a known set of categories.", + "subgraph_metadata": [ + { + "input_tensor_metadata": [ + { + "name": "image", + "description": "Input image to be processed.", + "content": { + "content_properties_type": "ImageProperties", + "content_properties": { + "color_space": "RGB" + } + }, + "process_units": [ + { + "options_type": "NormalizationOptions", + "options": { + "mean": [ + 127.5 + ], + "std": [ + 127.5 + ] + } + } + ], + "stats": { + "max": [ + 255.0 + ], + "min": [ + 0.0 + ] + } + } + ], + "output_tensor_metadata": [ + { + "name": "score", + "description": "Score of the labels respectively.", + "content": { + "content_properties_type": "FeatureProperties", + "content_properties": { + } + }, + "process_units": [ + { + "options_type": "ScoreCalibrationOptions", + "options": { + "score_transformation": "LOG", + "default_score": 0.2 + } + } + ], + "stats": { + "max": [ + 255.0 + ], + "min": [ + 0.0 + ] + }, + "associated_files": [ + { + "name": "labels.txt", + "description": "Labels for categories that the model can recognize.", + "type": "TENSOR_AXIS_LABELS" + }, + { + "name": "score_calibration.txt", + "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.", + "type": "TENSOR_AXIS_SCORE_CALIBRATION" + } + ] + } + ] + } + ], + "min_parser_version": "1.0.0" +} diff --git a/third_party/external_files.bzl b/third_party/external_files.bzl index 54c0dde0a..84b354c99 100644 --- a/third_party/external_files.bzl +++ b/third_party/external_files.bzl @@ -364,6 +364,12 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/knift_labelmap.txt?generation=1661875792821628"], ) + http_file( + name = "com_google_mediapipe_labels_txt", + sha256 = "536feacc519de3d418de26b2effb4d75694a8c4c0063e36499a46fa8061e2da9", + urls = ["https://storage.googleapis.com/mediapipe-assets/labels.txt?generation=1665988394538324"], + ) + http_file( name = "com_google_mediapipe_left_hands_jpg", sha256 = "4b5134daa4cb60465535239535f9f74c2842aba3aa5fd30bf04ef5678f93d87f", @@ -448,18 +454,42 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v1_0.25_224_quant_without_subgraph_metadata.tflite?generation=1661875836078124"], ) + http_file( + name = "com_google_mediapipe_mobilenet_v2_1_0_224_json", + sha256 = "0eb285a857b4bb1815736d0902ace0af45ea62e90c1dac98844b9ca797cd0d7b", + urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224.json?generation=1665988398778178"], + ) + + http_file( + name = "com_google_mediapipe_mobilenet_v2_1_0_224_quant_json", + sha256 = "932f345ebe3d98daf0dc4c88b0f9e694e450390fb394fc217e851338dfec43e6", + urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224_quant.json?generation=1665988401522527"], + ) + http_file( name = "com_google_mediapipe_mobilenet_v2_1_0_224_quant_tflite", sha256 = "f08d447cde49b4e0446428aa921aff0a14ea589fa9c5817b31f83128e9a43c1d", urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224_quant.tflite?generation=1664340173966530"], ) + http_file( + name = "com_google_mediapipe_mobilenet_v2_1_0_224_quant_without_metadata_tflite", + sha256 = "f08d447cde49b4e0446428aa921aff0a14ea589fa9c5817b31f83128e9a43c1d", + urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224_quant_without_metadata.tflite?generation=1665988405130772"], + ) + http_file( name = "com_google_mediapipe_mobilenet_v2_1_0_224_tflite", sha256 = "ff5cb7f9e62c92ebdad971f8a98aa6b3106d82a64587a7787c6a385c9e791339", urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224.tflite?generation=1661875840611150"], ) + http_file( + name = "com_google_mediapipe_mobilenet_v2_1_0_224_without_metadata_tflite", + sha256 = "9f3bc29e38e90842a852bfed957dbf5e36f2d97a91dd17736b1e5c0aca8d3303", + urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224_without_metadata.tflite?generation=1665988408360823"], + ) + http_file( name = "com_google_mediapipe_mobilenet_v3_small_100_224_embedder_tflite", sha256 = "f7b9a563cb803bdcba76e8c7e82abde06f5c7a8e67b5e54e43e23095dfe79a78", From de93d06f8795c46e380f2adca15873b552597a93 Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Mon, 24 Oct 2022 00:43:45 -0700 Subject: [PATCH 061/125] Implement build rules and targets to create MediaPipe Tasks AARs PiperOrigin-RevId: 483297891 --- .../com/google/mediapipe/mediapipe_aar.bzl | 31 +-- mediapipe/tasks/java/BUILD | 16 +- .../java/com/google/mediapipe/tasks/BUILD | 15 ++ .../com/google/mediapipe/tasks/core/BUILD | 12 + .../mediapipe/tasks/mediapipe_tasks_aar.bzl | 211 ++++++++++++++++++ .../com/google/mediapipe/tasks/vision/BUILD | 8 + 6 files changed, 279 insertions(+), 14 deletions(-) create mode 100644 mediapipe/tasks/java/com/google/mediapipe/tasks/BUILD create mode 100644 mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl diff --git a/mediapipe/java/com/google/mediapipe/mediapipe_aar.bzl b/mediapipe/java/com/google/mediapipe/mediapipe_aar.bzl index 9b01e2f0b..645e8b722 100644 --- a/mediapipe/java/com/google/mediapipe/mediapipe_aar.bzl +++ b/mediapipe/java/com/google/mediapipe/mediapipe_aar.bzl @@ -1,4 +1,4 @@ -# Copyright 2019-2020 The MediaPipe Authors. +# Copyright 2019-2022 The MediaPipe Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -209,9 +209,9 @@ def _mediapipe_jni(name, gen_libmediapipe, calculators = []): def mediapipe_build_aar_with_jni(name, android_library): """Builds MediaPipe AAR with jni. - Args: - name: The bazel target name. - android_library: the android library that contains jni. + Args: + name: The bazel target name. + android_library: the android library that contains jni. """ # Generates dummy AndroidManifest.xml for dummy apk usage @@ -328,19 +328,14 @@ def mediapipe_java_proto_srcs(name = ""): src_out = "com/google/mediapipe/proto/MediaPipeOptionsProto.java", )) - proto_src_list.append(mediapipe_java_proto_src_extractor( - target = "//mediapipe/framework/formats:landmark_java_proto_lite", - src_out = "com/google/mediapipe/formats/proto/LandmarkProto.java", - )) - proto_src_list.append(mediapipe_java_proto_src_extractor( target = "//mediapipe/framework/formats/annotation:rasterization_java_proto_lite", src_out = "com/google/mediapipe/formats/annotation/proto/RasterizationProto.java", )) proto_src_list.append(mediapipe_java_proto_src_extractor( - target = "//mediapipe/framework/formats:location_data_java_proto_lite", - src_out = "com/google/mediapipe/formats/proto/LocationDataProto.java", + target = "//mediapipe/framework/formats:classification_java_proto_lite", + src_out = "com/google/mediapipe/formats/proto/ClassificationProto.java", )) proto_src_list.append(mediapipe_java_proto_src_extractor( @@ -349,8 +344,18 @@ def mediapipe_java_proto_srcs(name = ""): )) proto_src_list.append(mediapipe_java_proto_src_extractor( - target = "//mediapipe/framework/formats:classification_java_proto_lite", - src_out = "com/google/mediapipe/formats/proto/ClassificationProto.java", + target = "//mediapipe/framework/formats:landmark_java_proto_lite", + src_out = "com/google/mediapipe/formats/proto/LandmarkProto.java", + )) + + proto_src_list.append(mediapipe_java_proto_src_extractor( + target = "//mediapipe/framework/formats:location_data_java_proto_lite", + src_out = "com/google/mediapipe/formats/proto/LocationDataProto.java", + )) + + proto_src_list.append(mediapipe_java_proto_src_extractor( + target = "//mediapipe/framework/formats:rect_java_proto_lite", + src_out = "com/google/mediapipe/formats/proto/RectProto.java", )) return proto_src_list diff --git a/mediapipe/tasks/java/BUILD b/mediapipe/tasks/java/BUILD index 024510737..7e6283261 100644 --- a/mediapipe/tasks/java/BUILD +++ b/mediapipe/tasks/java/BUILD @@ -1 +1,15 @@ -# dummy file for tap test to find the pattern +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +licenses(["notice"]) diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/BUILD b/mediapipe/tasks/java/com/google/mediapipe/tasks/BUILD new file mode 100644 index 000000000..7e6283261 --- /dev/null +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/BUILD @@ -0,0 +1,15 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +licenses(["notice"]) diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/core/BUILD b/mediapipe/tasks/java/com/google/mediapipe/tasks/core/BUILD index b4ebfe8cc..cb9d67424 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/core/BUILD +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/core/BUILD @@ -36,3 +36,15 @@ android_library( "@maven//:com_google_guava_guava", ], ) + +load("//mediapipe/tasks/java/com/google/mediapipe/tasks:mediapipe_tasks_aar.bzl", "mediapipe_tasks_core_aar") + +mediapipe_tasks_core_aar( + name = "tasks_core", + srcs = glob(["*.java"]) + [ + "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:java_src", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/processors:java_src", + "//mediapipe/java/com/google/mediapipe/framework/image:java_src", + ], + manifest = "AndroidManifest.xml", +) diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl b/mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl new file mode 100644 index 000000000..e0b9c79ed --- /dev/null +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl @@ -0,0 +1,211 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Building MediaPipe Tasks AARs.""" + +load("//mediapipe/java/com/google/mediapipe:mediapipe_aar.bzl", "mediapipe_build_aar_with_jni", "mediapipe_java_proto_src_extractor", "mediapipe_java_proto_srcs") +load("@build_bazel_rules_android//android:rules.bzl", "android_library") + +_CORE_TASKS_JAVA_PROTO_LITE_TARGETS = [ + "//mediapipe/tasks/cc/components/containers/proto:category_java_proto_lite", + "//mediapipe/tasks/cc/components/containers/proto:classifications_java_proto_lite", + "//mediapipe/tasks/cc/components/containers/proto:embeddings_java_proto_lite", + "//mediapipe/tasks/cc/components/containers/proto:landmarks_detection_result_java_proto_lite", + "//mediapipe/tasks/cc/components/processors/proto:classifier_options_java_proto_lite", + "//mediapipe/tasks/cc/core/proto:acceleration_java_proto_lite", + "//mediapipe/tasks/cc/core/proto:base_options_java_proto_lite", + "//mediapipe/tasks/cc/core/proto:external_file_java_proto_lite", +] + +_VISION_TASKS_JAVA_PROTO_LITE_TARGETS = [ + "//mediapipe/tasks/cc/vision/object_detector/proto:object_detector_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_graph_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_classifier_graph_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_embedder_graph_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_java_proto_lite", + "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_java_proto_lite", +] + +def mediapipe_tasks_core_aar(name, srcs, manifest): + """Builds medaipipe tasks core AAR. + + Args: + name: The bazel target name. + srcs: MediaPipe Tasks' core layer source files. + manifest: The Android manifest. + """ + + mediapipe_tasks_java_proto_srcs = [] + for target in _CORE_TASKS_JAVA_PROTO_LITE_TARGETS: + mediapipe_tasks_java_proto_srcs.append( + _mediapipe_tasks_java_proto_src_extractor(target = target), + ) + + for target in _VISION_TASKS_JAVA_PROTO_LITE_TARGETS: + mediapipe_tasks_java_proto_srcs.append( + _mediapipe_tasks_java_proto_src_extractor(target = target), + ) + + mediapipe_tasks_java_proto_srcs.append(mediapipe_java_proto_src_extractor( + target = "//mediapipe/calculators/core:flow_limiter_calculator_java_proto_lite", + src_out = "com/google/mediapipe/calculator/proto/FlowLimiterCalculatorProto.java", + )) + + mediapipe_tasks_java_proto_srcs.append(mediapipe_java_proto_src_extractor( + target = "//mediapipe/calculators/tensor:inference_calculator_java_proto_lite", + src_out = "com/google/mediapipe/calculator/proto/InferenceCalculatorProto.java", + )) + + android_library( + name = name, + srcs = srcs + [ + "//mediapipe/java/com/google/mediapipe/framework:java_src", + ] + mediapipe_java_proto_srcs() + + mediapipe_tasks_java_proto_srcs, + javacopts = [ + "-Xep:AndroidJdkLibsChecker:OFF", + ], + manifest = manifest, + deps = [ + "//mediapipe/calculators/core:flow_limiter_calculator_java_proto_lite", + "//mediapipe/calculators/tensor:inference_calculator_java_proto_lite", + "//mediapipe/framework:calculator_java_proto_lite", + "//mediapipe/framework:calculator_profile_java_proto_lite", + "//mediapipe/framework:calculator_options_java_proto_lite", + "//mediapipe/framework:mediapipe_options_java_proto_lite", + "//mediapipe/framework:packet_factory_java_proto_lite", + "//mediapipe/framework:packet_generator_java_proto_lite", + "//mediapipe/framework:status_handler_java_proto_lite", + "//mediapipe/framework:stream_handler_java_proto_lite", + "//mediapipe/framework/formats:classification_java_proto_lite", + "//mediapipe/framework/formats:detection_java_proto_lite", + "//mediapipe/framework/formats:landmark_java_proto_lite", + "//mediapipe/framework/formats:location_data_java_proto_lite", + "//mediapipe/framework/formats:rect_java_proto_lite", + "//mediapipe/java/com/google/mediapipe/framework:android_framework", + "//mediapipe/java/com/google/mediapipe/framework/image", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/core/jni:model_resources_cache_jni", + "//third_party:androidx_annotation", + "//third_party:autovalue", + "@com_google_protobuf//:protobuf_javalite", + "@maven//:com_google_guava_guava", + "@maven//:com_google_flogger_flogger", + "@maven//:com_google_flogger_flogger_system_backend", + "@maven//:com_google_code_findbugs_jsr305", + ] + _CORE_TASKS_JAVA_PROTO_LITE_TARGETS + _VISION_TASKS_JAVA_PROTO_LITE_TARGETS, + ) + +def mediapipe_tasks_vision_aar(name, srcs, native_library): + """Builds medaipipe tasks vision AAR. + + Args: + name: The bazel target name. + srcs: MediaPipe Vision Tasks' source files. + native_library: The native library that contains vision tasks' graph and calculators. + """ + + native.genrule( + name = name + "tasks_manifest_generator", + outs = ["AndroidManifest.xml"], + cmd = """ +cat > $(OUTS) < + + + +EOF +""", + ) + + _mediapipe_tasks_aar( + name = name, + srcs = srcs, + manifest = "AndroidManifest.xml", + java_proto_lite_targets = _CORE_TASKS_JAVA_PROTO_LITE_TARGETS + _VISION_TASKS_JAVA_PROTO_LITE_TARGETS, + native_library = native_library, + ) + +def _mediapipe_tasks_aar(name, srcs, manifest, java_proto_lite_targets, native_library): + """Builds medaipipe tasks AAR.""" + + # When "--define EXCLUDE_OPENCV_SO_LIB=1" is set in the build command, + # the OpenCV so libraries will be excluded from the AAR package to + # save the package size. + native.config_setting( + name = "exclude_opencv_so_lib", + define_values = { + "EXCLUDE_OPENCV_SO_LIB": "1", + }, + visibility = ["//visibility:public"], + ) + + native.cc_library( + name = name + "_jni_opencv_cc_lib", + srcs = select({ + "//mediapipe:android_arm64": ["@android_opencv//:libopencv_java3_so_arm64-v8a"], + "//mediapipe:android_armeabi": ["@android_opencv//:libopencv_java3_so_armeabi-v7a"], + "//mediapipe:android_arm": ["@android_opencv//:libopencv_java3_so_armeabi-v7a"], + "//mediapipe:android_x86": ["@android_opencv//:libopencv_java3_so_x86"], + "//mediapipe:android_x86_64": ["@android_opencv//:libopencv_java3_so_x86_64"], + "//conditions:default": [], + }), + alwayslink = 1, + ) + + android_library( + name = name + "_android_lib", + srcs = srcs, + manifest = manifest, + proguard_specs = ["//mediapipe/java/com/google/mediapipe/framework:proguard.pgcfg"], + deps = java_proto_lite_targets + [native_library] + [ + "//mediapipe/java/com/google/mediapipe/framework:android_framework", + "//mediapipe/java/com/google/mediapipe/framework/image", + "//mediapipe/framework:calculator_options_java_proto_lite", + "//mediapipe/framework:calculator_java_proto_lite", + "//mediapipe/framework/formats:classification_java_proto_lite", + "//mediapipe/framework/formats:detection_java_proto_lite", + "//mediapipe/framework/formats:landmark_java_proto_lite", + "//mediapipe/framework/formats:location_data_java_proto_lite", + "//mediapipe/framework/formats:rect_java_proto_lite", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:detection", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:category", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:classification_entry", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:classifications", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:landmark", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/processors:classifieroptions", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/core", + "//third_party:autovalue", + "@maven//:com_google_guava_guava", + ] + select({ + "//conditions:default": [":" + name + "_jni_opencv_cc_lib"], + "//mediapipe/framework/port:disable_opencv": [], + "exclude_opencv_so_lib": [], + }), + ) + + mediapipe_build_aar_with_jni(name, name + "_android_lib") + +def _mediapipe_tasks_java_proto_src_extractor(target): + proto_path = "com/google/" + target.split(":")[0].replace("cc/", "").replace("//", "").replace("_", "") + "/" + proto_name = target.split(":")[-1].replace("_java_proto_lite", "").replace("_", " ").title().replace(" ", "") + "Proto.java" + return mediapipe_java_proto_src_extractor( + target = target, + src_out = proto_path + proto_name, + ) diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD index 2bdcc2522..5ea465d47 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD @@ -141,3 +141,11 @@ android_library( "@maven//:com_google_guava_guava", ], ) + +load("//mediapipe/tasks/java/com/google/mediapipe/tasks:mediapipe_tasks_aar.bzl", "mediapipe_tasks_vision_aar") + +mediapipe_tasks_vision_aar( + name = "tasks_vision", + srcs = glob(["**/*.java"]), + native_library = ":libmediapipe_tasks_vision_jni_lib", +) From af051dcb628782ec33188b425b64c5b516c33d59 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Mon, 24 Oct 2022 01:37:49 -0700 Subject: [PATCH 062/125] internal change PiperOrigin-RevId: 483308781 --- mediapipe/framework/calculator_base.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mediapipe/framework/calculator_base.h b/mediapipe/framework/calculator_base.h index f9f0d7a8a..19f37f9de 100644 --- a/mediapipe/framework/calculator_base.h +++ b/mediapipe/framework/calculator_base.h @@ -185,7 +185,7 @@ class CalculatorBaseFactory { // Functions for checking that the calculator has the required GetContract. template constexpr bool CalculatorHasGetContract(decltype(&T::GetContract) /*unused*/) { - typedef absl::Status (*GetContractType)(CalculatorContract * cc); + typedef absl::Status (*GetContractType)(CalculatorContract* cc); return std::is_same::value; } template From 9a1a9d4c136685962afc0a6bc81e4b458d57d2e0 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Mon, 24 Oct 2022 06:08:27 -0700 Subject: [PATCH 063/125] Added files needed for the GestureRecognizer API implementation --- mediapipe/python/BUILD | 1 + .../tasks/python/components/containers/BUILD | 37 ++ .../components/containers/classification.py | 128 ++++++ .../python/components/containers/gesture.py | 138 ++++++ .../python/components/containers/landmark.py | 250 ++++++++++ .../python/components/containers/rect.py | 141 ++++++ .../tasks/python/components/processors/BUILD | 28 ++ .../processors/classifier_options.py | 92 ++++ mediapipe/tasks/python/test/vision/BUILD | 19 + .../test/vision/gesture_recognizer_test.py | 91 ++++ mediapipe/tasks/python/vision/BUILD | 27 ++ .../tasks/python/vision/gesture_recognizer.py | 434 ++++++++++++++++++ 12 files changed, 1386 insertions(+) create mode 100644 mediapipe/tasks/python/components/containers/classification.py create mode 100644 mediapipe/tasks/python/components/containers/gesture.py create mode 100644 mediapipe/tasks/python/components/containers/landmark.py create mode 100644 mediapipe/tasks/python/components/containers/rect.py create mode 100644 mediapipe/tasks/python/components/processors/BUILD create mode 100644 mediapipe/tasks/python/components/processors/classifier_options.py create mode 100644 mediapipe/tasks/python/test/vision/gesture_recognizer_test.py create mode 100644 mediapipe/tasks/python/vision/gesture_recognizer.py diff --git a/mediapipe/python/BUILD b/mediapipe/python/BUILD index 2911e2fd6..50a1f5791 100644 --- a/mediapipe/python/BUILD +++ b/mediapipe/python/BUILD @@ -88,6 +88,7 @@ cc_library( name = "builtin_task_graphs", deps = [ "//mediapipe/tasks/cc/vision/object_detector:object_detector_graph", + "//mediapipe/tasks/cc/vision/gesture_recognizer:gesture_recognizer_graph", ], ) diff --git a/mediapipe/tasks/python/components/containers/BUILD b/mediapipe/tasks/python/components/containers/BUILD index fd25401f7..325dff5fc 100644 --- a/mediapipe/tasks/python/components/containers/BUILD +++ b/mediapipe/tasks/python/components/containers/BUILD @@ -27,6 +27,43 @@ py_library( ], ) +py_library( + name = "rect", + srcs = ["rect.py"], + deps = [ + "//mediapipe/framework/formats:rect_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) + +py_library( + name = "classification", + srcs = ["classification.py"], + deps = [ + "//mediapipe/framework/formats:classification_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) + +py_library( + name = "landmark", + srcs = ["landmark.py"], + deps = [ + "//mediapipe/framework/formats:landmark_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) + +py_library( + name = "gesture", + srcs = ["gesture.py"], + deps = [ + ":classification", + ":landmark", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) + py_library( name = "category", srcs = ["category.py"], diff --git a/mediapipe/tasks/python/components/containers/classification.py b/mediapipe/tasks/python/components/containers/classification.py new file mode 100644 index 000000000..157c34528 --- /dev/null +++ b/mediapipe/tasks/python/components/containers/classification.py @@ -0,0 +1,128 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Classification data class.""" + +import dataclasses +from typing import Any, List + +from mediapipe.framework.formats import classification_pb2 +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_ClassificationProto = classification_pb2.Classification +_ClassificationListProto = classification_pb2.ClassificationList +_ClassificationListCollectionProto = classification_pb2.ClassificationListCollection + + +@dataclasses.dataclass +class Classification: + """A classification. + + Attributes: + index: The index of the class in the corresponding label map. + score: The probability score for this class. + label_name: Label or name of the class. + display_name: Optional human-readable string for display purposes. + """ + + index: int + score: float + label_name: str + display_name: str + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ClassificationProto: + """Generates a Classification protobuf object.""" + return _ClassificationProto( + index=self.index, + score=self.score, + label_name=self.label_name, + display_name=self.display_name) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _ClassificationProto) -> 'Classification': + """Creates a `Classification` object from the given protobuf object.""" + return Classification( + index=pb2_obj.index, + score=pb2_obj.score, + label_name=pb2_obj.label_name, + display_name=pb2_obj.display_name) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, Classification): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class ClassificationList: + """Represents the classifications for a given classifier. + Attributes: + classification : A list of `Classification` objects. + tensor_index: Optional index of the tensor that produced these + classifications. + tensor_name: Optional name of the tensor that produced these + classifications tensor metadata name. + """ + + classifications: List[Classification] + tensor_index: int + tensor_name: str + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ClassificationListProto: + """Generates a ClassificationList protobuf object.""" + return _ClassificationListProto( + classification=[ + classification.to_pb2() + for classification in self.classifications + ], + tensor_index=self.tensor_index, + tensor_name=self.tensor_name) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, + pb2_obj: _ClassificationListProto + ) -> 'ClassificationList': + """Creates a `ClassificationList` object from the given protobuf object.""" + return ClassificationList( + classifications=[ + Classification.create_from_pb2(classification) + for classification in pb2_obj.classification + ], + tensor_index=pb2_obj.tensor_index, + tensor_name=pb2_obj.tensor_name) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + Args: + other: The object to be compared with. + Returns: + True if the objects are equal. + """ + if not isinstance(other, ClassificationList): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/components/containers/gesture.py b/mediapipe/tasks/python/components/containers/gesture.py new file mode 100644 index 000000000..f314d18bd --- /dev/null +++ b/mediapipe/tasks/python/components/containers/gesture.py @@ -0,0 +1,138 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Gesture data class.""" + +import dataclasses +from typing import Any, List + +from mediapipe.tasks.python.components.containers import classification +from mediapipe.tasks.python.components.containers import landmark +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + + +@dataclasses.dataclass +class GestureRecognitionResult: + """ The gesture recognition result from GestureRecognizer, where each vector + element represents a single hand detected in the image. + + Attributes: + gestures: Recognized hand gestures with sorted order such that the + winning label is the first item in the list. + handedness: Classification of handedness. + hand_landmarks: Detected hand landmarks in normalized image coordinates. + hand_world_landmarks: Detected hand landmarks in world coordinates. + """ + + gestures: List[classification.ClassificationList] + handedness: List[classification.ClassificationList] + hand_landmarks: List[landmark.NormalizedLandmarkList] + hand_world_landmarks: List[landmark.LandmarkList] + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _DetectionProto: + """Generates a Detection protobuf object.""" + labels = [] + label_ids = [] + scores = [] + display_names = [] + for category in self.categories: + scores.append(category.score) + if category.index: + label_ids.append(category.index) + if category.category_name: + labels.append(category.category_name) + if category.display_name: + display_names.append(category.display_name) + return _DetectionProto( + label=labels, + label_id=label_ids, + score=scores, + display_name=display_names, + location_data=_LocationDataProto( + format=_LocationDataProto.Format.BOUNDING_BOX, + bounding_box=self.bounding_box.to_pb2())) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _DetectionProto) -> 'Detection': + """Creates a `Detection` object from the given protobuf object.""" + categories = [] + for idx, score in enumerate(pb2_obj.score): + categories.append( + category_module.Category( + score=score, + index=pb2_obj.label_id[idx] + if idx < len(pb2_obj.label_id) else None, + category_name=pb2_obj.label[idx] + if idx < len(pb2_obj.label) else None, + display_name=pb2_obj.display_name[idx] + if idx < len(pb2_obj.display_name) else None)) + + return Detection( + bounding_box=bounding_box_module.BoundingBox.create_from_pb2( + pb2_obj.location_data.bounding_box), + categories=categories) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, Detection): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class DetectionResult: + """Represents the list of detected objects. + + Attributes: + detections: A list of `Detection` objects. + """ + + detections: List[Detection] + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _DetectionListProto: + """Generates a DetectionList protobuf object.""" + return _DetectionListProto( + detection=[detection.to_pb2() for detection in self.detections]) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _DetectionListProto) -> 'DetectionResult': + """Creates a `DetectionResult` object from the given protobuf object.""" + return DetectionResult(detections=[ + Detection.create_from_pb2(detection) for detection in pb2_obj.detection + ]) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, DetectionResult): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/components/containers/landmark.py b/mediapipe/tasks/python/components/containers/landmark.py new file mode 100644 index 000000000..a86c17f2f --- /dev/null +++ b/mediapipe/tasks/python/components/containers/landmark.py @@ -0,0 +1,250 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Landmark data class.""" + +import dataclasses +from typing import Any, Optional, List + +from mediapipe.framework.formats import landmark_pb2 +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_LandmarkProto = landmark_pb2.Landmark +_LandmarkListProto = landmark_pb2.LandmarkList +_NormalizedLandmarkProto = landmark_pb2.NormalizedLandmark +_NormalizedLandmarkListProto = landmark_pb2.NormalizedLandmarkList + + +@dataclasses.dataclass +class Landmark: + """A landmark that can have 1 to 3 dimensions. + + Use x for 1D points, (x, y) for 2D points and (x, y, z) for 3D points. + + Attributes: + x: The x coordinate of the 3D point. + y: The y coordinate of the 3D point. + z: The z coordinate of the 3D point. + visibility: Landmark visibility. Should stay unset if not supported. + Float score of whether landmark is visible or occluded by other objects. + Landmark considered as invisible also if it is not present on the screen + (out of scene bounds). Depending on the model, visibility value is either + a sigmoid or an argument of sigmoid. + presence: Landmark presence. Should stay unset if not supported. + Float score of whether landmark is present on the scene (located within + scene bounds). Depending on the model, presence value is either a result + of sigmoid or an argument of sigmoid function to get landmark presence + probability. + """ + + x: Optional[float] = None + y: Optional[float] = None + z: Optional[float] = None + visibility: Optional[float] = None + presence: Optional[float] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _LandmarkProto: + """Generates a Landmark protobuf object.""" + return _LandmarkProto( + x=self.x, + y=self.y, + z=self.z, + visibility=self.visibility, + presence=self.presence) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _LandmarkProto) -> 'Landmark': + """Creates a `Landmark` object from the given protobuf object.""" + return Landmark( + x=pb2_obj.x, + y=pb2_obj.y, + z=pb2_obj.z, + visibility=pb2_obj.visibility, + presence=pb2_obj.presence) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, Landmark): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class LandmarkList: + """Represents the list of landmarks. + + Attributes: + landmarks : A list of `Landmark` objects. + """ + + landmarks: List[Landmark] + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _LandmarkListProto: + """Generates a LandmarkList protobuf object.""" + return _LandmarkListProto( + landmark=[ + landmark.to_pb2() + for landmark in self.landmarks + ] + ) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, + pb2_obj: _LandmarkListProto + ) -> 'LandmarkList': + """Creates a `LandmarkList` object from the given protobuf object.""" + return LandmarkList( + landmarks=[ + Landmark.create_from_pb2(landmark) + for landmark in pb2_obj.landmark + ] + ) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + Args: + other: The object to be compared with. + Returns: + True if the objects are equal. + """ + if not isinstance(other, LandmarkList): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class NormalizedLandmark: + """A normalized version of above Landmark proto. + + All coordinates should be within [0, 1]. + + Attributes: + x: The normalized x coordinate of the 3D point. + y: The normalized y coordinate of the 3D point. + z: The normalized z coordinate of the 3D point. + visibility: Landmark visibility. Should stay unset if not supported. + Float score of whether landmark is visible or occluded by other objects. + Landmark considered as invisible also if it is not present on the screen + (out of scene bounds). Depending on the model, visibility value is either + a sigmoid or an argument of sigmoid. + presence: Landmark presence. Should stay unset if not supported. + Float score of whether landmark is present on the scene (located within + scene bounds). Depending on the model, presence value is either a result + of sigmoid or an argument of sigmoid function to get landmark presence + probability. + """ + + x: Optional[float] = None + y: Optional[float] = None + z: Optional[float] = None + visibility: Optional[float] = None + presence: Optional[float] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _NormalizedLandmarkProto: + """Generates a NormalizedLandmark protobuf object.""" + return _NormalizedLandmarkProto( + x=self.x, + y=self.y, + z=self.z, + visibility=self.visibility, + presence=self.presence) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, + pb2_obj: _NormalizedLandmarkProto + ) -> 'NormalizedLandmark': + """Creates a `NormalizedLandmark` object from the given protobuf object.""" + return NormalizedLandmark( + x=pb2_obj.x, + y=pb2_obj.y, + z=pb2_obj.z, + visibility=pb2_obj.visibility, + presence=pb2_obj.presence) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, NormalizedLandmark): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class NormalizedLandmarkList: + """Represents the list of normalized landmarks. + + Attributes: + landmarks : A list of `Landmark` objects. + """ + + landmarks: List[NormalizedLandmark] + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _NormalizedLandmarkListProto: + """Generates a NormalizedLandmarkList protobuf object.""" + return _NormalizedLandmarkListProto( + landmark=[ + landmark.to_pb2() + for landmark in self.landmarks + ] + ) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, + pb2_obj: _NormalizedLandmarkListProto + ) -> 'NormalizedLandmarkList': + """Creates a `NormalizedLandmarkList` object from the given protobuf object.""" + return NormalizedLandmarkList( + landmarks=[ + NormalizedLandmark.create_from_pb2(landmark) + for landmark in pb2_obj.landmark + ] + ) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + Args: + other: The object to be compared with. + Returns: + True if the objects are equal. + """ + if not isinstance(other, NormalizedLandmarkList): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/components/containers/rect.py b/mediapipe/tasks/python/components/containers/rect.py new file mode 100644 index 000000000..aadb404db --- /dev/null +++ b/mediapipe/tasks/python/components/containers/rect.py @@ -0,0 +1,141 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Rect data class.""" + +import dataclasses +from typing import Any, Optional + +from mediapipe.framework.formats import rect_pb2 +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_RectProto = rect_pb2.Rect +_NormalizedRectProto = rect_pb2.NormalizedRect + + +@dataclasses.dataclass +class Rect: + """A rectangle with rotation in image coordinates. + + Attributes: + x_center : The X coordinate of the top-left corner, in pixels. + y_center : The Y coordinate of the top-left corner, in pixels. + width: The width of the rectangle, in pixels. + height: The height of the rectangle, in pixels. + rotation: Rotation angle is clockwise in radians. + rect_id: Optional unique id to help associate different rectangles to each + other. + """ + + x_center: int + y_center: int + width: int + height: int + rotation: Optional[float] = 0.0 + rect_id: Optional[int] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _RectProto: + """Generates a Rect protobuf object.""" + return _RectProto( + x_center=self.x_center, + y_center=self.y_center, + width=self.width, + height=self.height, + ) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _RectProto) -> 'Rect': + """Creates a `Rect` object from the given protobuf object.""" + return Rect( + x_center=pb2_obj.x_center, + y_center=pb2_obj.y_center, + width=pb2_obj.width, + height=pb2_obj.height) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, Rect): + return False + + return self.to_pb2().__eq__(other.to_pb2()) + + +@dataclasses.dataclass +class NormalizedRect: + """A rectangle with rotation in normalized coordinates. The values of box + center location and size are within [0, 1]. + + Attributes: + x_center : The X normalized coordinate of the top-left corner. + y_center : The Y normalized coordinate of the top-left corner. + width: The width of the rectangle. + height: The height of the rectangle. + rotation: Rotation angle is clockwise in radians. + rect_id: Optional unique id to help associate different rectangles to each + other. + """ + + x_center: float + y_center: float + width: float + height: float + rotation: Optional[float] = 0.0 + rect_id: Optional[int] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _NormalizedRectProto: + """Generates a NormalizedRect protobuf object.""" + return _NormalizedRectProto( + x_center=self.x_center, + y_center=self.y_center, + width=self.width, + height=self.height, + rotation=self.rotation, + rect_id=self.rect_id + ) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2(cls, pb2_obj: _NormalizedRectProto) -> 'NormalizedRect': + """Creates a `NormalizedRect` object from the given protobuf object.""" + return NormalizedRect( + x_center=pb2_obj.x_center, + y_center=pb2_obj.y_center, + width=pb2_obj.width, + height=pb2_obj.height, + rotation=pb2_obj.rotation, + rect_id=pb2_obj.rect_id + ) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, NormalizedRect): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/components/processors/BUILD b/mediapipe/tasks/python/components/processors/BUILD new file mode 100644 index 000000000..814e15d1f --- /dev/null +++ b/mediapipe/tasks/python/components/processors/BUILD @@ -0,0 +1,28 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Placeholder for internal Python strict library compatibility macro. + +package(default_visibility = ["//mediapipe/tasks:internal"]) + +licenses(["notice"]) + +py_library( + name = "classifier_options", + srcs = ["classifier_options.py"], + deps = [ + "//mediapipe/tasks/cc/components/processors/proto:classifier_options_py_pb2", + "//mediapipe/tasks/python/core:optional_dependencies", + ], +) diff --git a/mediapipe/tasks/python/components/processors/classifier_options.py b/mediapipe/tasks/python/components/processors/classifier_options.py new file mode 100644 index 000000000..b4597e57a --- /dev/null +++ b/mediapipe/tasks/python/components/processors/classifier_options.py @@ -0,0 +1,92 @@ +# Copyright 2022 The TensorFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Classifier options data class.""" + +import dataclasses +from typing import Any, List, Optional + +from mediapipe.tasks.cc.components.processors.proto import classifier_options_pb2 +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_ClassifierOptionsProto = classifier_options_pb2.ClassifierOptions + + +@dataclasses.dataclass +class ClassifierOptions: + """Options for classification processor. + + Attributes: + display_names_locale: The locale to use for display names specified through + the TFLite Model Metadata. + max_results: The maximum number of top-scored classification results to + return. + score_threshold: Overrides the ones provided in the model metadata. Results + below this value are rejected. + category_allowlist: Allowlist of category names. If non-empty, detection + results whose category name is not in this set will be filtered out. + Duplicate or unknown category names are ignored. Mutually exclusive with + `category_denylist`. + category_denylist: Denylist of category names. If non-empty, detection + results whose category name is in this set will be filtered out. Duplicate + or unknown category names are ignored. Mutually exclusive with + `category_allowlist`. + """ + + display_names_locale: Optional[str] = None + max_results: Optional[int] = None + score_threshold: Optional[float] = None + category_allowlist: Optional[List[str]] = None + category_denylist: Optional[List[str]] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _ClassifierOptionsProto: + """Generates a ClassifierOptions protobuf object.""" + return _ClassifierOptionsProto( + score_threshold=self.score_threshold, + category_allowlist=self.category_allowlist, + category_denylist=self.category_denylist, + display_names_locale=self.display_names_locale, + max_results=self.max_results) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, + pb2_obj: _ClassifierOptionsProto + ) -> 'ClassifierOptions': + """Creates a `ClassifierOptions` object from the given protobuf object.""" + return ClassifierOptions( + score_threshold=pb2_obj.score_threshold, + category_allowlist=[ + str(name) for name in pb2_obj.class_name_allowlist + ], + category_denylist=[ + str(name) for name in pb2_obj.class_name_denylist + ], + display_names_locale=pb2_obj.display_names_locale, + max_results=pb2_obj.max_results) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + + Args: + other: The object to be compared with. + + Returns: + True if the objects are equal. + """ + if not isinstance(other, ClassifierOptions): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 290b665e7..0dd83edcf 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -36,3 +36,22 @@ py_test( "//mediapipe/tasks/python/vision/core:vision_task_running_mode", ], ) + +py_test( + name = "gesture_recognizer_test", + srcs = ["gesture_recognizer_test.py"], + data = [ + "//mediapipe/tasks/testdata/vision:test_images", + "//mediapipe/tasks/testdata/vision:test_models", + ], + deps = [ + "//mediapipe/python:_framework_bindings", + "//mediapipe/tasks/python/components/containers:classification", + "//mediapipe/tasks/python/components/containers:landmark", + "//mediapipe/tasks/python/components/containers:rect", + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/test:test_utils", + "//mediapipe/tasks/python/vision:gesture_recognizer", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + ], +) diff --git a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py new file mode 100644 index 000000000..288cfd1f5 --- /dev/null +++ b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py @@ -0,0 +1,91 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for gesture recognizer.""" + +import enum + +from absl.testing import absltest +from absl.testing import parameterized + +from mediapipe.python._framework_bindings import image as image_module +from mediapipe.tasks.python.components.containers import rect as rect_module +from mediapipe.tasks.python.components.containers import classification as classification_module +from mediapipe.tasks.python.components.containers import landmark as landmark_module +from mediapipe.tasks.python.core import base_options as base_options_module +from mediapipe.tasks.python.test import test_utils +from mediapipe.tasks.python.vision import gesture_recognizer +from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module + +_BaseOptions = base_options_module.BaseOptions +_NormalizedRect = rect_module.NormalizedRect +_ClassificationList = classification_module.ClassificationList +_LandmarkList = landmark_module.LandmarkList +_NormalizedLandmarkList = landmark_module.NormalizedLandmarkList +_Image = image_module.Image +_GestureRecognizer = gesture_recognizer.GestureRecognizer +_GestureRecognizerOptions = gesture_recognizer.GestureRecognizerOptions +_GestureRecognitionResult = gesture_recognizer.GestureRecognitionResult +_RUNNING_MODE = running_mode_module.VisionTaskRunningMode + +_GESTURE_RECOGNIZER_MODEL_FILE = 'gesture_recognizer.task' +_IMAGE_FILE = 'right_hands.jpg' +_EXPECTED_DETECTION_RESULT = _GestureRecognitionResult([], [], [], []) + + +class ModelFileType(enum.Enum): + FILE_CONTENT = 1 + FILE_NAME = 2 + + +class GestureRecognizerTest(parameterized.TestCase): + + def setUp(self): + super().setUp() + self.test_image = _Image.create_from_file( + test_utils.get_test_data_path(_IMAGE_FILE)) + self.gesture_recognizer_model_path = test_utils.get_test_data_path( + _GESTURE_RECOGNIZER_MODEL_FILE) + + @parameterized.parameters( + (ModelFileType.FILE_NAME, _EXPECTED_DETECTION_RESULT), + (ModelFileType.FILE_CONTENT, _EXPECTED_DETECTION_RESULT)) + def test_recognize(self, model_file_type, expected_recognition_result): + # Creates gesture recognizer. + if model_file_type is ModelFileType.FILE_NAME: + gesture_recognizer_base_options = _BaseOptions( + model_asset_path=self.gesture_recognizer_model_path) + elif model_file_type is ModelFileType.FILE_CONTENT: + with open(self.gesture_recognizer_model_path, 'rb') as f: + model_content = f.read() + gesture_recognizer_base_options = _BaseOptions( + model_asset_buffer=model_content) + else: + # Should never happen + raise ValueError('model_file_type is invalid.') + + options = _GestureRecognizerOptions( + base_options=gesture_recognizer_base_options) + recognizer = _GestureRecognizer.create_from_options(options) + + # Performs hand gesture recognition on the input. + recognition_result = recognizer.recognize(self.test_image) + # Comparing results. + self.assertEqual(recognition_result, expected_recognition_result) + # Closes the gesture recognizer explicitly when the detector is not used in + # a context. + recognizer.close() + + +if __name__ == '__main__': + absltest.main() diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index e7be51c8d..9a9ca3429 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -36,3 +36,30 @@ py_library( "//mediapipe/tasks/python/vision/core:vision_task_running_mode", ], ) + +py_library( + name = "gesture_recognizer", + srcs = [ + "gesture_recognizer.py", + ], + deps = [ + "//mediapipe/python:_framework_bindings", + "//mediapipe/python:packet_creator", + "//mediapipe/python:packet_getter", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_classifier_graph_options_py_pb2", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_py_pb2", + "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_py_pb2", + "//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_py_pb2", + "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_py_pb2", + "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_py_pb2", + "//mediapipe/tasks/python/components/containers:rect", + "//mediapipe/tasks/python/components/containers:classification", + "//mediapipe/tasks/python/components/containers:landmark", + "//mediapipe/tasks/python/components/processors:classifier_options", + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/core:optional_dependencies", + "//mediapipe/tasks/python/core:task_info", + "//mediapipe/tasks/python/vision/core:base_vision_task_api", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + ], +) diff --git a/mediapipe/tasks/python/vision/gesture_recognizer.py b/mediapipe/tasks/python/vision/gesture_recognizer.py new file mode 100644 index 000000000..aca7a5277 --- /dev/null +++ b/mediapipe/tasks/python/vision/gesture_recognizer.py @@ -0,0 +1,434 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""MediaPipe gesture recognizer task.""" + +import dataclasses +from typing import Callable, Mapping, Optional, List + +from mediapipe.python import packet_creator +from mediapipe.python import packet_getter +from mediapipe.python._framework_bindings import image as image_module +from mediapipe.python._framework_bindings import packet as packet_module +from mediapipe.python._framework_bindings import task_runner as task_runner_module +from mediapipe.tasks.cc.vision.gesture_recognizer.proto import gesture_classifier_graph_options_pb2 +from mediapipe.tasks.cc.vision.gesture_recognizer.proto import gesture_recognizer_graph_options_pb2 +from mediapipe.tasks.cc.vision.gesture_recognizer.proto import hand_gesture_recognizer_graph_options_pb2 +from mediapipe.tasks.cc.vision.hand_detector.proto import hand_detector_graph_options_pb2 +from mediapipe.tasks.cc.vision.hand_landmarker.proto import hand_landmarker_graph_options_pb2 +from mediapipe.tasks.cc.vision.hand_landmarker.proto import hand_landmarks_detector_graph_options_pb2 +from mediapipe.tasks.python.components.containers import rect as rect_module +from mediapipe.tasks.python.components.containers import classification as classification_module +from mediapipe.tasks.python.components.containers import landmark as landmark_module +from mediapipe.tasks.python.components.processors import classifier_options +from mediapipe.tasks.python.core import base_options as base_options_module +from mediapipe.tasks.python.core import task_info as task_info_module +from mediapipe.tasks.python.core.optional_dependencies import doc_controls +from mediapipe.tasks.python.vision.core import base_vision_task_api +from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module + +_NormalizedRect = rect_module.NormalizedRect +_BaseOptions = base_options_module.BaseOptions +_GestureClassifierGraphOptionsProto = gesture_classifier_graph_options_pb2.GestureClassifierGraphOptions +_GestureRecognizerGraphOptionsProto = gesture_recognizer_graph_options_pb2.GestureRecognizerGraphOptions +_HandGestureRecognizerGraphOptionsProto = hand_gesture_recognizer_graph_options_pb2.HandGestureRecognizerGraphOptions +_HandDetectorGraphOptionsProto = hand_detector_graph_options_pb2.HandDetectorGraphOptions +_HandLandmarkerGraphOptionsProto = hand_landmarker_graph_options_pb2.HandLandmarkerGraphOptions +_HandLandmarksDetectorGraphOptionsProto = hand_landmarks_detector_graph_options_pb2.HandLandmarksDetectorGraphOptions +_ClassifierOptions = classifier_options.ClassifierOptions +_RunningMode = running_mode_module.VisionTaskRunningMode +_TaskInfo = task_info_module.TaskInfo +_TaskRunner = task_runner_module.TaskRunner + +_IMAGE_IN_STREAM_NAME = 'image_in' +_IMAGE_OUT_STREAM_NAME = 'image_out' +_IMAGE_TAG = 'IMAGE' +_NORM_RECT_STREAM_NAME = 'norm_rect_in' +_NORM_RECT_TAG = 'NORM_RECT' +_HAND_GESTURE_STREAM_NAME = 'hand_gestures' +_HAND_GESTURE_TAG = 'HAND_GESTURES' +_HANDEDNESS_STREAM_NAME = 'handedness' +_HANDEDNESS_TAG = 'HANDEDNESS' +_HAND_LANDMARKS_STREAM_NAME = 'landmarks' +_HAND_LANDMARKS_TAG = 'LANDMARKS' +_HAND_WORLD_LANDMARKS_STREAM_NAME = 'world_landmarks' +_HAND_WORLD_LANDMARKS_TAG = 'WORLD_LANDMARKS' +_TASK_GRAPH_NAME = 'mediapipe.tasks.vision.gesture_recognizer.GestureRecognizerGraph' +_MICRO_SECONDS_PER_MILLISECOND = 1000 + + +def _build_full_image_norm_rect() -> _NormalizedRect: + # Builds a NormalizedRect covering the entire image. + return _NormalizedRect(x_center=0.5, y_center=0.5, width=1, height=1) + + +@dataclasses.dataclass +class GestureRecognitionResult: + """The gesture recognition result from GestureRecognizer, where each vector + element represents a single hand detected in the image. + + Attributes: + gestures: Recognized hand gestures with sorted order such that the + winning label is the first item in the list. + handedness: Classification of handedness. + hand_landmarks: Detected hand landmarks in normalized image coordinates. + hand_world_landmarks: Detected hand landmarks in world coordinates. + """ + + gestures: List[classification_module.ClassificationList] + handedness: List[classification_module.ClassificationList] + hand_landmarks: List[landmark_module.NormalizedLandmarkList] + hand_world_landmarks: List[landmark_module.LandmarkList] + + +@dataclasses.dataclass +class GestureRecognizerOptions: + """Options for the gesture recognizer task. + + Attributes: + base_options: Base options for the hand gesture recognizer task. + running_mode: The running mode of the task. Default to the image mode. + Gesture recognizer task has three running modes: + 1) The image mode for recognizing hand gestures on single image inputs. + 2) The video mode for recognizing hand gestures on the decoded frames of a + video. + 3) The live stream mode for recognizing hand gestures on a live stream of + input data, such as from camera. + num_hands: The maximum number of hands can be detected by the recognizer. + min_hand_detection_confidence: The minimum confidence score for the hand + detection to be considered successful. + min_hand_presence_confidence: The minimum confidence score of hand presence + score in the hand landmark detection. + min_tracking_confidence: The minimum confidence score for the hand tracking + to be considered successful. + min_gesture_confidence: The minimum confidence score for the gestures to be + considered successful. If < 0, the gesture confidence thresholds in the + model metadata are used. + TODO: Note this option is subject to change, after scoring merging + calculator is implemented. + result_callback: The user-defined result callback for processing live stream + data. The result callback should only be specified when the running mode + is set to the live stream mode. + """ + base_options: _BaseOptions + running_mode: _RunningMode = _RunningMode.IMAGE + num_hands: Optional[int] = 1 + min_hand_detection_confidence: Optional[int] = 0.5 + min_hand_presence_confidence: Optional[int] = 0.5 + min_tracking_confidence: Optional[int] = 0.5 + min_gesture_confidence: Optional[int] = -1 + result_callback: Optional[ + Callable[[GestureRecognitionResult, image_module.Image, + int], None]] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _GestureRecognizerGraphOptionsProto: + """Generates an GestureRecognizerOptions protobuf object.""" + base_options_proto = self.base_options.to_pb2() + base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True + # hand_landmark_detector_base_options_proto = self.hand_landmark_detector_base_options.to_pb2() + # hand_landmark_detector_base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True + + # Configure hand detector options. + hand_detector_options_proto = _HandDetectorGraphOptionsProto( + num_hands=self.num_hands, + min_detection_confidence=self.min_hand_detection_confidence) + + # Configure hand landmarker options. + hand_landmarks_detector_options_proto = _HandLandmarksDetectorGraphOptionsProto( + min_detection_confidence=self.min_hand_presence_confidence) + hand_landmarker_options_proto = _HandLandmarkerGraphOptionsProto( + hand_detector_graph_options=hand_detector_options_proto, + hand_landmarks_detector_graph_options=hand_landmarks_detector_options_proto, + min_tracking_confidence=self.min_tracking_confidence) + + # Configure hand gesture recognizer options. + hand_gesture_recognizer_options_proto = _HandGestureRecognizerGraphOptionsProto() + if self.min_gesture_confidence >= 0: + classifier_options = _ClassifierOptions( + score_threshold=self.min_gesture_confidence) + hand_gesture_recognizer_options_proto.canned_gesture_classifier_graph_options = \ + _GestureClassifierGraphOptionsProto( + classifier_options=classifier_options.to_pb2()) + + return _GestureRecognizerGraphOptionsProto( + base_options=base_options_proto, + hand_landmarker_graph_options=hand_landmarker_options_proto, + hand_gesture_recognizer_graph_options=hand_gesture_recognizer_options_proto + ) + + +class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): + """Class that performs gesture recognition on images.""" + + @classmethod + def create_from_model_path(cls, model_path: str) -> 'GestureRecognizer': + """Creates an `GestureRecognizer` object from a TensorFlow Lite model and + the default `GestureRecognizerOptions`. + + Note that the created `GestureRecognizer` instance is in image mode, for + recognizing hand gestures on single image inputs. + + Args: + model_path: Path to the model. + + Returns: + `GestureRecognizer` object that's created from the model file and the + default `GestureRecognizerOptions`. + + Raises: + ValueError: If failed to create `GestureRecognizer` object from the + provided file such as invalid file path. + RuntimeError: If other types of error occurred. + """ + base_options = _BaseOptions(model_asset_path=model_path) + options = GestureRecognizerOptions( + base_options=base_options, running_mode=_RunningMode.IMAGE) + return cls.create_from_options(options) + + @classmethod + def create_from_options( + cls, + options: GestureRecognizerOptions + ) -> 'GestureRecognizer': + """Creates the `GestureRecognizer` object from gesture recognizer options. + + Args: + options: Options for the gesture recognizer task. + + Returns: + `GestureRecognizer` object that's created from `options`. + + Raises: + ValueError: If failed to create `GestureRecognizer` object from + `GestureRecognizerOptions` such as missing the model. + RuntimeError: If other types of error occurred. + """ + + def packets_callback(output_packets: Mapping[str, packet_module.Packet]): + if output_packets[_IMAGE_OUT_STREAM_NAME].is_empty(): + return + + image = packet_getter.get_image(output_packets[_IMAGE_OUT_STREAM_NAME]) + + if output_packets[_HAND_GESTURE_STREAM_NAME].is_empty(): + empty_packet = output_packets[_HAND_GESTURE_STREAM_NAME] + options.result_callback( + GestureRecognitionResult([], [], [], []), image, + empty_packet.timestamp.value // _MICRO_SECONDS_PER_MILLISECOND) + return + + gestures_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_GESTURE_STREAM_NAME]) + handedness_proto_list = packet_getter.get_proto_list( + output_packets[_HANDEDNESS_STREAM_NAME]) + hand_landmarks_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_LANDMARKS_STREAM_NAME]) + hand_world_landmarks_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_WORLD_LANDMARKS_STREAM_NAME]) + + gesture_recognition_result = GestureRecognitionResult( + [ + classification_module.ClassificationList.create_from_pb2(gestures) + for gestures in gestures_proto_list + ], [ + classification_module.ClassificationList.create_from_pb2(handedness) + for handedness in handedness_proto_list + ], [ + landmark_module.NormalizedLandmarkList.create_from_pb2(hand_landmarks) + for hand_landmarks in hand_landmarks_proto_list + ], [ + landmark_module.LandmarkList.create_from_pb2(hand_world_landmarks) + for hand_world_landmarks in hand_world_landmarks_proto_list + ] + ) + timestamp = output_packets[_HAND_GESTURE_STREAM_NAME].timestamp + options.result_callback( + gesture_recognition_result, image, + timestamp.value // _MICRO_SECONDS_PER_MILLISECOND) + + task_info = _TaskInfo( + task_graph=_TASK_GRAPH_NAME, + input_streams=[ + ':'.join([_IMAGE_TAG, _IMAGE_IN_STREAM_NAME]), + ':'.join([_NORM_RECT_TAG, _NORM_RECT_STREAM_NAME]), + ], + output_streams=[ + ':'.join([_HAND_GESTURE_TAG, _HAND_GESTURE_STREAM_NAME]), + ':'.join([_HANDEDNESS_TAG, _HANDEDNESS_STREAM_NAME]), + ':'.join([_HAND_LANDMARKS_TAG, _HAND_LANDMARKS_STREAM_NAME]), + ':'.join([_HAND_WORLD_LANDMARKS_TAG, + _HAND_WORLD_LANDMARKS_STREAM_NAME]), + ':'.join([_IMAGE_TAG, _IMAGE_OUT_STREAM_NAME]) + ], + task_options=options) + return cls( + task_info.generate_graph_config( + enable_flow_limiting=options.running_mode == + _RunningMode.LIVE_STREAM), options.running_mode, + packets_callback if options.result_callback else None) + + def recognize( + self, + image: image_module.Image, + roi: Optional[_NormalizedRect] = None + ) -> GestureRecognitionResult: + """Performs hand gesture recognition on the given image. Only use this + method when the GestureRecognizer is created with the image running mode. + + The image can be of any size with format RGB or RGBA. + TODO: Describes how the input image will be preprocessed after the yuv + support is implemented. + + Args: + image: MediaPipe Image. + roi: The region of interest. + + Returns: + The hand gesture recognition results. + + Raises: + ValueError: If any of the input arguments is invalid. + RuntimeError: If gesture recognition failed to run. + """ + norm_rect = roi if roi is not None else _build_full_image_norm_rect() + output_packets = self._process_image_data({ + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image), + _NORM_RECT_STREAM_NAME: packet_creator.create_proto( + norm_rect.to_pb2())}) + gestures_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_GESTURE_STREAM_NAME]) + handedness_proto_list = packet_getter.get_proto_list( + output_packets[_HANDEDNESS_STREAM_NAME]) + hand_landmarks_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_LANDMARKS_STREAM_NAME]) + hand_world_landmarks_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_WORLD_LANDMARKS_STREAM_NAME]) + + return GestureRecognitionResult( + [ + classification_module.ClassificationList.create_from_pb2(gestures) + for gestures in gestures_proto_list + ], [ + classification_module.ClassificationList.create_from_pb2(handedness) + for handedness in handedness_proto_list + ], [ + landmark_module.NormalizedLandmarkList.create_from_pb2(hand_landmarks) + for hand_landmarks in hand_landmarks_proto_list + ], [ + landmark_module.LandmarkList.create_from_pb2(hand_world_landmarks) + for hand_world_landmarks in hand_world_landmarks_proto_list + ] + ) + + def recognize_for_video( + self, image: image_module.Image, + timestamp_ms: int, + roi: Optional[_NormalizedRect] = None + ) -> GestureRecognitionResult: + """Performs gesture recognition on the provided video frame. Only use this + method when the GestureRecognizer is created with the video running mode. + + Only use this method when the GestureRecognizer is created with the video + running mode. It's required to provide the video frame's timestamp (in + milliseconds) along with the video frame. The input timestamps should be + monotonically increasing for adjacent calls of this method. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input video frame in milliseconds. + roi: The region of interest. + + Returns: + The hand gesture recognition results. + + Raises: + ValueError: If any of the input arguments is invalid. + RuntimeError: If gesture recognition failed to run. + """ + norm_rect = roi if roi is not None else _build_full_image_norm_rect() + output_packets = self._process_video_data({ + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND), + _NORM_RECT_STREAM_NAME: packet_creator.create_proto( + norm_rect.to_pb2()).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) + }) + gestures_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_GESTURE_STREAM_NAME]) + handedness_proto_list = packet_getter.get_proto_list( + output_packets[_HANDEDNESS_STREAM_NAME]) + hand_landmarks_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_LANDMARKS_STREAM_NAME]) + hand_world_landmarks_proto_list = packet_getter.get_proto_list( + output_packets[_HAND_WORLD_LANDMARKS_STREAM_NAME]) + + return GestureRecognitionResult( + [ + classification_module.ClassificationList.create_from_pb2(gestures) + for gestures in gestures_proto_list + ], [ + classification_module.ClassificationList.create_from_pb2(handedness) + for handedness in handedness_proto_list + ], [ + landmark_module.NormalizedLandmarkList.create_from_pb2(hand_landmarks) + for hand_landmarks in hand_landmarks_proto_list + ], [ + landmark_module.LandmarkList.create_from_pb2(hand_world_landmarks) + for hand_world_landmarks in hand_world_landmarks_proto_list + ] + ) + + def recognize_async( + self, + image: image_module.Image, + timestamp_ms: int, + roi: Optional[_NormalizedRect] = None + ) -> None: + """Sends live image data to perform gesture recognition, and the results + will be available via the "result_callback" provided in the + GestureRecognizerOptions. Only use this method when the GestureRecognizer + is created with the live stream running mode. + + Only use this method when the GestureRecognizer is created with the live + stream running mode. The input timestamps should be monotonically increasing + for adjacent calls of this method. This method will return immediately after + the input image is accepted. The results will be available via the + `result_callback` provided in the `GestureRecognizerOptions`. The + `recognize_async` method is designed to process live stream data such as + camera input. To lower the overall latency, gesture recognizer may drop the + input images if needed. In other words, it's not guaranteed to have output + per input image. + + The `result_callback` provides: + - The hand gesture recognition results. + - The input image that the image classifier runs on. + - The input timestamp in milliseconds. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input image in milliseconds. + roi: The region of interest. + + Raises: + ValueError: If the current input timestamp is smaller than what the + gesture recognizer has already processed. + """ + norm_rect = roi if roi is not None else _build_full_image_norm_rect() + self._send_live_stream_data({ + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND), + _NORM_RECT_STREAM_NAME: packet_creator.create_proto( + norm_rect.to_pb2()).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) + }) From 0fd69e8d838d71e364e019f3eb29eb4389dbec7b Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Mon, 24 Oct 2022 09:09:42 -0700 Subject: [PATCH 064/125] Open-source some tokenizer unit tests. PiperOrigin-RevId: 483399326 --- mediapipe/tasks/cc/text/tokenizers/BUILD | 40 ++++++++++++++++++++++++ 1 file changed, 40 insertions(+) diff --git a/mediapipe/tasks/cc/text/tokenizers/BUILD b/mediapipe/tasks/cc/text/tokenizers/BUILD index e76d943c5..5ce08b2d7 100644 --- a/mediapipe/tasks/cc/text/tokenizers/BUILD +++ b/mediapipe/tasks/cc/text/tokenizers/BUILD @@ -73,6 +73,19 @@ cc_library( ], ) +cc_test( + name = "sentencepiece_tokenizer_test", + srcs = ["sentencepiece_tokenizer_test.cc"], + data = [ + "//mediapipe/tasks/testdata/text:albert_model", + ], + deps = [ + ":sentencepiece_tokenizer", + "//mediapipe/framework/port:gtest_main", + "//mediapipe/tasks/cc/core:utils", + ], +) + cc_library( name = "tokenizer_utils", srcs = ["tokenizer_utils.cc"], @@ -95,6 +108,33 @@ cc_library( ], ) +cc_test( + name = "tokenizer_utils_test", + srcs = ["tokenizer_utils_test.cc"], + data = [ + "//mediapipe/tasks/testdata/text:albert_model", + "//mediapipe/tasks/testdata/text:mobile_bert_model", + "//mediapipe/tasks/testdata/text:text_classifier_models", + ], + linkopts = ["-ldl"], + deps = [ + ":bert_tokenizer", + ":regex_tokenizer", + ":sentencepiece_tokenizer", + ":tokenizer_utils", + "//mediapipe/framework/port:gtest_main", + "//mediapipe/framework/port:status", + "//mediapipe/tasks/cc:common", + "//mediapipe/tasks/cc/core:utils", + "//mediapipe/tasks/cc/metadata:metadata_extractor", + "//mediapipe/tasks/metadata:metadata_schema_cc", + "@com_google_absl//absl/status", + "@com_google_absl//absl/status:statusor", + "@com_google_absl//absl/strings", + "@com_google_absl//absl/strings:cord", + ], +) + cc_library( name = "regex_tokenizer", srcs = [ From 2f2baeff6858bb8c5195910e41ca070bd8cda10f Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Mon, 24 Oct 2022 10:12:41 -0700 Subject: [PATCH 065/125] Add support for rotation in ImageEmbedder & ImageSegmenter C++ APIs PiperOrigin-RevId: 483416498 --- .../tasks/cc/vision/image_embedder/BUILD | 1 + .../vision/image_embedder/image_embedder.cc | 34 +++---- .../cc/vision/image_embedder/image_embedder.h | 56 ++++++++---- .../image_embedder/image_embedder_test.cc | 88 +++++++++++++++++-- .../tasks/cc/vision/image_segmenter/BUILD | 3 + .../vision/image_segmenter/image_segmenter.cc | 42 +++++++-- .../vision/image_segmenter/image_segmenter.h | 34 +++++-- .../image_segmenter/image_segmenter_graph.cc | 19 ++-- .../image_segmenter/image_segmenter_test.cc | 60 ++++++++++++- mediapipe/tasks/testdata/vision/BUILD | 4 + third_party/external_files.bzl | 32 ++++--- 11 files changed, 301 insertions(+), 72 deletions(-) diff --git a/mediapipe/tasks/cc/vision/image_embedder/BUILD b/mediapipe/tasks/cc/vision/image_embedder/BUILD index e619b8d1b..0f63f87e4 100644 --- a/mediapipe/tasks/cc/vision/image_embedder/BUILD +++ b/mediapipe/tasks/cc/vision/image_embedder/BUILD @@ -58,6 +58,7 @@ cc_library( "//mediapipe/tasks/cc/core:utils", "//mediapipe/tasks/cc/core/proto:base_options_cc_proto", "//mediapipe/tasks/cc/vision/core:base_vision_task_api", + "//mediapipe/tasks/cc/vision/core:image_processing_options", "//mediapipe/tasks/cc/vision/core:running_mode", "//mediapipe/tasks/cc/vision/core:vision_task_api_factory", "//mediapipe/tasks/cc/vision/image_embedder/proto:image_embedder_graph_options_cc_proto", diff --git a/mediapipe/tasks/cc/vision/image_embedder/image_embedder.cc b/mediapipe/tasks/cc/vision/image_embedder/image_embedder.cc index 24fd2862c..1dc316305 100644 --- a/mediapipe/tasks/cc/vision/image_embedder/image_embedder.cc +++ b/mediapipe/tasks/cc/vision/image_embedder/image_embedder.cc @@ -29,6 +29,7 @@ limitations under the License. #include "mediapipe/tasks/cc/core/proto/base_options.pb.h" #include "mediapipe/tasks/cc/core/task_runner.h" #include "mediapipe/tasks/cc/core/utils.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" #include "mediapipe/tasks/cc/vision/core/vision_task_api_factory.h" #include "mediapipe/tasks/cc/vision/image_embedder/proto/image_embedder_graph_options.pb.h" @@ -58,16 +59,6 @@ using ::mediapipe::tasks::core::PacketMap; using ::mediapipe::tasks::vision::image_embedder::proto:: ImageEmbedderGraphOptions; -// Builds a NormalizedRect covering the entire image. -NormalizedRect BuildFullImageNormRect() { - NormalizedRect norm_rect; - norm_rect.set_x_center(0.5); - norm_rect.set_y_center(0.5); - norm_rect.set_width(1); - norm_rect.set_height(1); - return norm_rect; -} - // Creates a MediaPipe graph config that contains a single node of type // "mediapipe.tasks.vision.image_embedder.ImageEmbedderGraph". If the task is // running in the live stream mode, a "FlowLimiterCalculator" will be added to @@ -148,15 +139,16 @@ absl::StatusOr> ImageEmbedder::Create( } absl::StatusOr ImageEmbedder::Embed( - Image image, std::optional roi) { + Image image, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, "GPU input images are currently not supported.", MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - NormalizedRect norm_rect = - roi.has_value() ? roi.value() : BuildFullImageNormRect(); + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options)); ASSIGN_OR_RETURN( auto output_packets, ProcessImageData( @@ -167,15 +159,16 @@ absl::StatusOr ImageEmbedder::Embed( } absl::StatusOr ImageEmbedder::EmbedForVideo( - Image image, int64 timestamp_ms, std::optional roi) { + Image image, int64 timestamp_ms, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, "GPU input images are currently not supported.", MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - NormalizedRect norm_rect = - roi.has_value() ? roi.value() : BuildFullImageNormRect(); + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options)); ASSIGN_OR_RETURN( auto output_packets, ProcessVideoData( @@ -188,16 +181,17 @@ absl::StatusOr ImageEmbedder::EmbedForVideo( return output_packets[kEmbeddingResultStreamName].Get(); } -absl::Status ImageEmbedder::EmbedAsync(Image image, int64 timestamp_ms, - std::optional roi) { +absl::Status ImageEmbedder::EmbedAsync( + Image image, int64 timestamp_ms, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, "GPU input images are currently not supported.", MediaPipeTasksStatus::kRunnerUnexpectedInputError); } - NormalizedRect norm_rect = - roi.has_value() ? roi.value() : BuildFullImageNormRect(); + ASSIGN_OR_RETURN(NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options)); return SendLiveStreamData( {{kImageInStreamName, MakePacket(std::move(image)) diff --git a/mediapipe/tasks/cc/vision/image_embedder/image_embedder.h b/mediapipe/tasks/cc/vision/image_embedder/image_embedder.h index 13f4702d1..3a2a1dbee 100644 --- a/mediapipe/tasks/cc/vision/image_embedder/image_embedder.h +++ b/mediapipe/tasks/cc/vision/image_embedder/image_embedder.h @@ -21,11 +21,11 @@ limitations under the License. #include "absl/status/statusor.h" #include "mediapipe/framework/formats/image.h" -#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/tasks/cc/components/containers/proto/embeddings.pb.h" #include "mediapipe/tasks/cc/components/embedder_options.h" #include "mediapipe/tasks/cc/core/base_options.h" #include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" namespace mediapipe { @@ -88,9 +88,17 @@ class ImageEmbedder : core::BaseVisionTaskApi { static absl::StatusOr> Create( std::unique_ptr options); - // Performs embedding extraction on the provided single image. Extraction - // is performed on the region of interest specified by the `roi` argument if - // provided, or on the entire image otherwise. + // Performs embedding extraction on the provided single image. + // + // The optional 'image_processing_options' parameter can be used to specify: + // - the rotation to apply to the image before performing embedding + // extraction, by setting its 'rotation_degrees' field. + // and/or + // - the region-of-interest on which to perform embedding extraction, by + // setting its 'region_of_interest' field. If not specified, the full image + // is used. + // If both are specified, the crop around the region-of-interest is extracted + // first, then the specified rotation is applied to the crop. // // Only use this method when the ImageEmbedder is created with the image // running mode. @@ -98,11 +106,20 @@ class ImageEmbedder : core::BaseVisionTaskApi { // The image can be of any size with format RGB or RGBA. absl::StatusOr Embed( mediapipe::Image image, - std::optional roi = std::nullopt); + std::optional image_processing_options = + std::nullopt); - // Performs embedding extraction on the provided video frame. Extraction - // is performed on the region of interested specified by the `roi` argument if - // provided, or on the entire image otherwise. + // Performs embedding extraction on the provided video frame. + // + // The optional 'image_processing_options' parameter can be used to specify: + // - the rotation to apply to the image before performing embedding + // extraction, by setting its 'rotation_degrees' field. + // and/or + // - the region-of-interest on which to perform embedding extraction, by + // setting its 'region_of_interest' field. If not specified, the full image + // is used. + // If both are specified, the crop around the region-of-interest is extracted + // first, then the specified rotation is applied to the crop. // // Only use this method when the ImageEmbedder is created with the video // running mode. @@ -112,12 +129,21 @@ class ImageEmbedder : core::BaseVisionTaskApi { // must be monotonically increasing. absl::StatusOr EmbedForVideo( mediapipe::Image image, int64 timestamp_ms, - std::optional roi = std::nullopt); + std::optional image_processing_options = + std::nullopt); // Sends live image data to embedder, and the results will be available via - // the "result_callback" provided in the ImageEmbedderOptions. Embedding - // extraction is performed on the region of interested specified by the `roi` - // argument if provided, or on the entire image otherwise. + // the "result_callback" provided in the ImageEmbedderOptions. + // + // The optional 'image_processing_options' parameter can be used to specify: + // - the rotation to apply to the image before performing embedding + // extraction, by setting its 'rotation_degrees' field. + // and/or + // - the region-of-interest on which to perform embedding extraction, by + // setting its 'region_of_interest' field. If not specified, the full image + // is used. + // If both are specified, the crop around the region-of-interest is extracted + // first, then the specified rotation is applied to the crop. // // Only use this method when the ImageEmbedder is created with the live // stream running mode. @@ -135,9 +161,9 @@ class ImageEmbedder : core::BaseVisionTaskApi { // longer be valid when the callback returns. To access the image data // outside of the callback, callers need to make a copy of the image. // - The input timestamp in milliseconds. - absl::Status EmbedAsync( - mediapipe::Image image, int64 timestamp_ms, - std::optional roi = std::nullopt); + absl::Status EmbedAsync(mediapipe::Image image, int64 timestamp_ms, + std::optional + image_processing_options = std::nullopt); // Shuts down the ImageEmbedder when all works are done. absl::Status Close() { return runner_->Close(); } diff --git a/mediapipe/tasks/cc/vision/image_embedder/image_embedder_test.cc b/mediapipe/tasks/cc/vision/image_embedder/image_embedder_test.cc index db1019b33..386b6c8eb 100644 --- a/mediapipe/tasks/cc/vision/image_embedder/image_embedder_test.cc +++ b/mediapipe/tasks/cc/vision/image_embedder/image_embedder_test.cc @@ -23,7 +23,6 @@ limitations under the License. #include "absl/status/statusor.h" #include "mediapipe/framework/deps/file_path.h" #include "mediapipe/framework/formats/image.h" -#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/port/gmock.h" #include "mediapipe/framework/port/gtest.h" #include "mediapipe/framework/port/status_matchers.h" @@ -42,7 +41,9 @@ namespace image_embedder { namespace { using ::mediapipe::file::JoinPath; +using ::mediapipe::tasks::components::containers::Rect; using ::mediapipe::tasks::components::containers::proto::EmbeddingResult; +using ::mediapipe::tasks::vision::core::ImageProcessingOptions; using ::testing::HasSubstr; using ::testing::Optional; @@ -326,16 +327,14 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterest) { MP_ASSERT_OK_AND_ASSIGN( Image crop, DecodeImageFromFile( JoinPath("./", kTestDataDirectory, "burger_crop.jpg"))); - // Bounding box in "burger.jpg" corresponding to "burger_crop.jpg". - NormalizedRect roi; - roi.set_x_center(200.0 / 480); - roi.set_y_center(0.5); - roi.set_width(400.0 / 480); - roi.set_height(1.0f); + // Region-of-interest in "burger.jpg" corresponding to "burger_crop.jpg". + Rect roi{/*left=*/0, /*top=*/0, /*right=*/0.833333, /*bottom=*/1}; + ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0}; // Extract both embeddings. - MP_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result, - image_embedder->Embed(image, roi)); + MP_ASSERT_OK_AND_ASSIGN( + const EmbeddingResult& image_result, + image_embedder->Embed(image, image_processing_options)); MP_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result, image_embedder->Embed(crop)); @@ -351,6 +350,77 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterest) { EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy); } +TEST_F(ImageModeTest, SucceedsWithRotation) { + auto options = std::make_unique(); + options->base_options.model_asset_path = + JoinPath("./", kTestDataDirectory, kMobileNetV3Embedder); + MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr image_embedder, + ImageEmbedder::Create(std::move(options))); + // Load images: one is a rotated version of the other. + MP_ASSERT_OK_AND_ASSIGN( + Image image, + DecodeImageFromFile(JoinPath("./", kTestDataDirectory, "burger.jpg"))); + MP_ASSERT_OK_AND_ASSIGN(Image rotated, + DecodeImageFromFile(JoinPath("./", kTestDataDirectory, + "burger_rotated.jpg"))); + ImageProcessingOptions image_processing_options; + image_processing_options.rotation_degrees = -90; + + // Extract both embeddings. + MP_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result, + image_embedder->Embed(image)); + MP_ASSERT_OK_AND_ASSIGN( + const EmbeddingResult& rotated_result, + image_embedder->Embed(rotated, image_processing_options)); + + // Check results. + CheckMobileNetV3Result(image_result, false); + CheckMobileNetV3Result(rotated_result, false); + // CheckCosineSimilarity. + MP_ASSERT_OK_AND_ASSIGN( + double similarity, + ImageEmbedder::CosineSimilarity(image_result.embeddings(0).entries(0), + rotated_result.embeddings(0).entries(0))); + double expected_similarity = 0.572265; + EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy); +} + +TEST_F(ImageModeTest, SucceedsWithRegionOfInterestAndRotation) { + auto options = std::make_unique(); + options->base_options.model_asset_path = + JoinPath("./", kTestDataDirectory, kMobileNetV3Embedder); + MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr image_embedder, + ImageEmbedder::Create(std::move(options))); + MP_ASSERT_OK_AND_ASSIGN( + Image crop, DecodeImageFromFile( + JoinPath("./", kTestDataDirectory, "burger_crop.jpg"))); + MP_ASSERT_OK_AND_ASSIGN(Image rotated, + DecodeImageFromFile(JoinPath("./", kTestDataDirectory, + "burger_rotated.jpg"))); + // Region-of-interest corresponding to burger_crop.jpg. + Rect roi{/*left=*/0, /*top=*/0, /*right=*/1, /*bottom=*/0.8333333}; + ImageProcessingOptions image_processing_options{roi, + /*rotation_degrees=*/-90}; + + // Extract both embeddings. + MP_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result, + image_embedder->Embed(crop)); + MP_ASSERT_OK_AND_ASSIGN( + const EmbeddingResult& rotated_result, + image_embedder->Embed(rotated, image_processing_options)); + + // Check results. + CheckMobileNetV3Result(crop_result, false); + CheckMobileNetV3Result(rotated_result, false); + // CheckCosineSimilarity. + MP_ASSERT_OK_AND_ASSIGN( + double similarity, + ImageEmbedder::CosineSimilarity(crop_result.embeddings(0).entries(0), + rotated_result.embeddings(0).entries(0))); + double expected_similarity = 0.62838; + EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy); +} + class VideoModeTest : public tflite_shims::testing::Test {}; TEST_F(VideoModeTest, FailsWithCallingWrongMethod) { diff --git a/mediapipe/tasks/cc/vision/image_segmenter/BUILD b/mediapipe/tasks/cc/vision/image_segmenter/BUILD index 6bdbf41da..81cd43e34 100644 --- a/mediapipe/tasks/cc/vision/image_segmenter/BUILD +++ b/mediapipe/tasks/cc/vision/image_segmenter/BUILD @@ -24,10 +24,12 @@ cc_library( ":image_segmenter_graph", "//mediapipe/framework/api2:builder", "//mediapipe/framework/formats:image", + "//mediapipe/framework/formats:rect_cc_proto", "//mediapipe/tasks/cc/components/proto:segmenter_options_cc_proto", "//mediapipe/tasks/cc/core:base_options", "//mediapipe/tasks/cc/core:utils", "//mediapipe/tasks/cc/vision/core:base_vision_task_api", + "//mediapipe/tasks/cc/vision/core:image_processing_options", "//mediapipe/tasks/cc/vision/core:running_mode", "//mediapipe/tasks/cc/vision/core:vision_task_api_factory", "//mediapipe/tasks/cc/vision/image_segmenter/proto:image_segmenter_options_cc_proto", @@ -48,6 +50,7 @@ cc_library( "//mediapipe/framework/api2:builder", "//mediapipe/framework/api2:port", "//mediapipe/framework/formats:image", + "//mediapipe/framework/formats:rect_cc_proto", "//mediapipe/framework/port:status", "//mediapipe/tasks/cc:common", "//mediapipe/tasks/cc/components:image_preprocessing", diff --git a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter.cc b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter.cc index 84ceea88a..209ee0df3 100644 --- a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter.cc +++ b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter.cc @@ -17,8 +17,10 @@ limitations under the License. #include "mediapipe/framework/api2/builder.h" #include "mediapipe/framework/formats/image.h" +#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/tasks/cc/components/proto/segmenter_options.pb.h" #include "mediapipe/tasks/cc/core/utils.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/core/running_mode.h" #include "mediapipe/tasks/cc/vision/core/vision_task_api_factory.h" @@ -32,6 +34,8 @@ constexpr char kGroupedSegmentationTag[] = "GROUPED_SEGMENTATION"; constexpr char kImageInStreamName[] = "image_in"; constexpr char kImageOutStreamName[] = "image_out"; constexpr char kImageTag[] = "IMAGE"; +constexpr char kNormRectStreamName[] = "norm_rect_in"; +constexpr char kNormRectTag[] = "NORM_RECT"; constexpr char kSubgraphTypeName[] = "mediapipe.tasks.vision.ImageSegmenterGraph"; constexpr int kMicroSecondsPerMilliSecond = 1000; @@ -51,15 +55,18 @@ CalculatorGraphConfig CreateGraphConfig( auto& task_subgraph = graph.AddNode(kSubgraphTypeName); task_subgraph.GetOptions().Swap(options.get()); graph.In(kImageTag).SetName(kImageInStreamName); + graph.In(kNormRectTag).SetName(kNormRectStreamName); task_subgraph.Out(kGroupedSegmentationTag).SetName(kSegmentationStreamName) >> graph.Out(kGroupedSegmentationTag); task_subgraph.Out(kImageTag).SetName(kImageOutStreamName) >> graph.Out(kImageTag); if (enable_flow_limiting) { - return tasks::core::AddFlowLimiterCalculator( - graph, task_subgraph, {kImageTag}, kGroupedSegmentationTag); + return tasks::core::AddFlowLimiterCalculator(graph, task_subgraph, + {kImageTag, kNormRectTag}, + kGroupedSegmentationTag); } graph.In(kImageTag) >> task_subgraph.In(kImageTag); + graph.In(kNormRectTag) >> task_subgraph.In(kNormRectTag); return graph.GetConfig(); } @@ -139,47 +146,68 @@ absl::StatusOr> ImageSegmenter::Create( } absl::StatusOr> ImageSegmenter::Segment( - mediapipe::Image image) { + mediapipe::Image image, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); ASSIGN_OR_RETURN( auto output_packets, - ProcessImageData({{kImageInStreamName, - mediapipe::MakePacket(std::move(image))}})); + ProcessImageData( + {{kImageInStreamName, mediapipe::MakePacket(std::move(image))}, + {kNormRectStreamName, + MakePacket(std::move(norm_rect))}})); return output_packets[kSegmentationStreamName].Get>(); } absl::StatusOr> ImageSegmenter::SegmentForVideo( - mediapipe::Image image, int64 timestamp_ms) { + mediapipe::Image image, int64 timestamp_ms, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); ASSIGN_OR_RETURN( auto output_packets, ProcessVideoData( {{kImageInStreamName, MakePacket(std::move(image)) + .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}, + {kNormRectStreamName, + MakePacket(std::move(norm_rect)) .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}})); return output_packets[kSegmentationStreamName].Get>(); } -absl::Status ImageSegmenter::SegmentAsync(Image image, int64 timestamp_ms) { +absl::Status ImageSegmenter::SegmentAsync( + Image image, int64 timestamp_ms, + std::optional image_processing_options) { if (image.UsesGpu()) { return CreateStatusWithPayload( absl::StatusCode::kInvalidArgument, absl::StrCat("GPU input images are currently not supported."), MediaPipeTasksStatus::kRunnerUnexpectedInputError); } + ASSIGN_OR_RETURN( + NormalizedRect norm_rect, + ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false)); return SendLiveStreamData( {{kImageInStreamName, MakePacket(std::move(image)) + .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}, + {kNormRectStreamName, + MakePacket(std::move(norm_rect)) .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}}); } diff --git a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter.h b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter.h index e2734c4e4..54269ec0e 100644 --- a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter.h +++ b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter.h @@ -25,6 +25,7 @@ limitations under the License. #include "mediapipe/framework/formats/image.h" #include "mediapipe/tasks/cc/core/base_options.h" #include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/image_segmenter/proto/image_segmenter_options.pb.h" #include "tensorflow/lite/kernels/register.h" @@ -116,14 +117,21 @@ class ImageSegmenter : tasks::vision::core::BaseVisionTaskApi { // running mode. // // The image can be of any size with format RGB or RGBA. - // TODO: Describes how the input image will be preprocessed - // after the yuv support is implemented. + // + // The optional 'image_processing_options' parameter can be used to specify + // the rotation to apply to the image before performing segmentation, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported + // and will result in an invalid argument error being returned. // // If the output_type is CATEGORY_MASK, the returned vector of images is // per-category segmented image mask. // If the output_type is CONFIDENCE_MASK, the returned vector of images // contains only one confidence image mask. - absl::StatusOr> Segment(mediapipe::Image image); + absl::StatusOr> Segment( + mediapipe::Image image, + std::optional image_processing_options = + std::nullopt); // Performs image segmentation on the provided video frame. // Only use this method when the ImageSegmenter is created with the video @@ -133,12 +141,20 @@ class ImageSegmenter : tasks::vision::core::BaseVisionTaskApi { // provide the video frame's timestamp (in milliseconds). The input timestamps // must be monotonically increasing. // + // The optional 'image_processing_options' parameter can be used to specify + // the rotation to apply to the image before performing segmentation, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported + // and will result in an invalid argument error being returned. + // // If the output_type is CATEGORY_MASK, the returned vector of images is // per-category segmented image mask. // If the output_type is CONFIDENCE_MASK, the returned vector of images // contains only one confidence image mask. absl::StatusOr> SegmentForVideo( - mediapipe::Image image, int64 timestamp_ms); + mediapipe::Image image, int64 timestamp_ms, + std::optional image_processing_options = + std::nullopt); // Sends live image data to perform image segmentation, and the results will // be available via the "result_callback" provided in the @@ -150,6 +166,12 @@ class ImageSegmenter : tasks::vision::core::BaseVisionTaskApi { // sent to the image segmenter. The input timestamps must be monotonically // increasing. // + // The optional 'image_processing_options' parameter can be used to specify + // the rotation to apply to the image before performing segmentation, by + // setting its 'rotation_degrees' field. Note that specifying a + // region-of-interest using the 'region_of_interest' field is NOT supported + // and will result in an invalid argument error being returned. + // // The "result_callback" prvoides // - A vector of segmented image masks. // If the output_type is CATEGORY_MASK, the returned vector of images is @@ -161,7 +183,9 @@ class ImageSegmenter : tasks::vision::core::BaseVisionTaskApi { // no longer be valid when the callback returns. To access the image data // outside of the callback, callers need to make a copy of the image. // - The input timestamp in milliseconds. - absl::Status SegmentAsync(mediapipe::Image image, int64 timestamp_ms); + absl::Status SegmentAsync(mediapipe::Image image, int64 timestamp_ms, + std::optional + image_processing_options = std::nullopt); // Shuts down the ImageSegmenter when all works are done. absl::Status Close() { return runner_->Close(); } diff --git a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_graph.cc b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_graph.cc index 1678dd083..629b940aa 100644 --- a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_graph.cc +++ b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_graph.cc @@ -23,6 +23,7 @@ limitations under the License. #include "mediapipe/framework/api2/builder.h" #include "mediapipe/framework/api2/port.h" #include "mediapipe/framework/formats/image.h" +#include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/port/status_macros.h" #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/components/calculators/tensor/tensors_to_segmentation_calculator.pb.h" @@ -62,6 +63,7 @@ using LabelItems = mediapipe::proto_ns::Map; constexpr char kSegmentationTag[] = "SEGMENTATION"; constexpr char kGroupedSegmentationTag[] = "GROUPED_SEGMENTATION"; constexpr char kImageTag[] = "IMAGE"; +constexpr char kNormRectTag[] = "NORM_RECT"; constexpr char kTensorsTag[] = "TENSORS"; constexpr char kOutputSizeTag[] = "OUTPUT_SIZE"; @@ -159,6 +161,10 @@ absl::StatusOr GetOutputTensor( // Inputs: // IMAGE - Image // Image to perform segmentation on. +// NORM_RECT - NormalizedRect @Optional +// Describes image rotation and region of image to perform detection +// on. +// @Optional: rect covering the whole image is used if not specified. // // Outputs: // SEGMENTATION - mediapipe::Image @Multiple @@ -196,10 +202,12 @@ class ImageSegmenterGraph : public core::ModelTaskGraph { ASSIGN_OR_RETURN(const auto* model_resources, CreateModelResources(sc)); Graph graph; - ASSIGN_OR_RETURN(auto output_streams, - BuildSegmentationTask( - sc->Options(), *model_resources, - graph[Input(kImageTag)], graph)); + ASSIGN_OR_RETURN( + auto output_streams, + BuildSegmentationTask( + sc->Options(), *model_resources, + graph[Input(kImageTag)], + graph[Input::Optional(kNormRectTag)], graph)); auto& merge_images_to_vector = graph.AddNode("MergeImagesToVectorCalculator"); @@ -228,7 +236,7 @@ class ImageSegmenterGraph : public core::ModelTaskGraph { absl::StatusOr BuildSegmentationTask( const ImageSegmenterOptions& task_options, const core::ModelResources& model_resources, Source image_in, - Graph& graph) { + Source norm_rect_in, Graph& graph) { MP_RETURN_IF_ERROR(SanityCheckOptions(task_options)); // Adds preprocessing calculators and connects them to the graph input image @@ -240,6 +248,7 @@ class ImageSegmenterGraph : public core::ModelTaskGraph { &preprocessing .GetOptions())); image_in >> preprocessing.In(kImageTag); + norm_rect_in >> preprocessing.In(kNormRectTag); // Adds inference subgraph and connects its input stream to the output // tensors produced by the ImageToTensorCalculator. diff --git a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_test.cc b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_test.cc index ab23a725c..07235563b 100644 --- a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_test.cc +++ b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_test.cc @@ -29,8 +29,10 @@ limitations under the License. #include "mediapipe/framework/port/opencv_imgcodecs_inc.h" #include "mediapipe/framework/port/status_matchers.h" #include "mediapipe/tasks/cc/components/calculators/tensor/tensors_to_segmentation_calculator.pb.h" +#include "mediapipe/tasks/cc/components/containers/rect.h" #include "mediapipe/tasks/cc/core/proto/base_options.pb.h" #include "mediapipe/tasks/cc/core/proto/external_file.pb.h" +#include "mediapipe/tasks/cc/vision/core/image_processing_options.h" #include "mediapipe/tasks/cc/vision/image_segmenter/proto/image_segmenter_options.pb.h" #include "mediapipe/tasks/cc/vision/utils/image_utils.h" #include "tensorflow/lite/core/shims/cc/shims_test_util.h" @@ -44,6 +46,8 @@ namespace { using ::mediapipe::Image; using ::mediapipe::file::JoinPath; +using ::mediapipe::tasks::components::containers::Rect; +using ::mediapipe::tasks::vision::core::ImageProcessingOptions; using ::testing::HasSubstr; using ::testing::Optional; @@ -237,7 +241,6 @@ TEST_F(ImageModeTest, SucceedsWithConfidenceMask) { MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr segmenter, ImageSegmenter::Create(std::move(options))); - MP_ASSERT_OK_AND_ASSIGN(auto results, segmenter->Segment(image)); MP_ASSERT_OK_AND_ASSIGN(auto confidence_masks, segmenter->Segment(image)); EXPECT_EQ(confidence_masks.size(), 21); @@ -253,6 +256,61 @@ TEST_F(ImageModeTest, SucceedsWithConfidenceMask) { SimilarToFloatMask(expected_mask_float, kGoldenMaskSimilarity)); } +TEST_F(ImageModeTest, SucceedsWithRotation) { + MP_ASSERT_OK_AND_ASSIGN( + Image image, DecodeImageFromFile( + JoinPath("./", kTestDataDirectory, "cat_rotated.jpg"))); + auto options = std::make_unique(); + options->base_options.model_asset_path = + JoinPath("./", kTestDataDirectory, kDeeplabV3WithMetadata); + options->output_type = ImageSegmenterOptions::OutputType::CONFIDENCE_MASK; + options->activation = ImageSegmenterOptions::Activation::SOFTMAX; + + MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr segmenter, + ImageSegmenter::Create(std::move(options))); + ImageProcessingOptions image_processing_options; + image_processing_options.rotation_degrees = -90; + MP_ASSERT_OK_AND_ASSIGN(auto confidence_masks, segmenter->Segment(image)); + EXPECT_EQ(confidence_masks.size(), 21); + + cv::Mat expected_mask = + cv::imread(JoinPath("./", kTestDataDirectory, "cat_rotated_mask.jpg"), + cv::IMREAD_GRAYSCALE); + cv::Mat expected_mask_float; + expected_mask.convertTo(expected_mask_float, CV_32FC1, 1 / 255.f); + + // Cat category index 8. + cv::Mat cat_mask = mediapipe::formats::MatView( + confidence_masks[8].GetImageFrameSharedPtr().get()); + EXPECT_THAT(cat_mask, + SimilarToFloatMask(expected_mask_float, kGoldenMaskSimilarity)); +} + +TEST_F(ImageModeTest, FailsWithRegionOfInterest) { + MP_ASSERT_OK_AND_ASSIGN( + Image image, + DecodeImageFromFile(JoinPath("./", kTestDataDirectory, "cat.jpg"))); + auto options = std::make_unique(); + options->base_options.model_asset_path = + JoinPath("./", kTestDataDirectory, kDeeplabV3WithMetadata); + options->output_type = ImageSegmenterOptions::OutputType::CONFIDENCE_MASK; + options->activation = ImageSegmenterOptions::Activation::SOFTMAX; + + MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr segmenter, + ImageSegmenter::Create(std::move(options))); + Rect roi{/*left=*/0.1, /*top=*/0, /*right=*/0.9, /*bottom=*/1}; + ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0}; + + auto results = segmenter->Segment(image, image_processing_options); + EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument); + EXPECT_THAT(results.status().message(), + HasSubstr("This task doesn't support region-of-interest")); + EXPECT_THAT( + results.status().GetPayload(kMediaPipeTasksPayload), + Optional(absl::Cord(absl::StrCat( + MediaPipeTasksStatus::kImageProcessingInvalidArgumentError)))); +} + TEST_F(ImageModeTest, SucceedsSelfie128x128Segmentation) { Image image = GetSRGBImage(JoinPath("./", kTestDataDirectory, "mozart_square.jpg")); diff --git a/mediapipe/tasks/testdata/vision/BUILD b/mediapipe/tasks/testdata/vision/BUILD index ebb8f05a6..c45cc6e69 100644 --- a/mediapipe/tasks/testdata/vision/BUILD +++ b/mediapipe/tasks/testdata/vision/BUILD @@ -28,6 +28,8 @@ mediapipe_files(srcs = [ "burger_rotated.jpg", "cat.jpg", "cat_mask.jpg", + "cat_rotated.jpg", + "cat_rotated_mask.jpg", "cats_and_dogs.jpg", "cats_and_dogs_no_resizing.jpg", "cats_and_dogs_rotated.jpg", @@ -84,6 +86,8 @@ filegroup( "burger_rotated.jpg", "cat.jpg", "cat_mask.jpg", + "cat_rotated.jpg", + "cat_rotated_mask.jpg", "cats_and_dogs.jpg", "cats_and_dogs_no_resizing.jpg", "cats_and_dogs_rotated.jpg", diff --git a/third_party/external_files.bzl b/third_party/external_files.bzl index 84b354c99..d460387aa 100644 --- a/third_party/external_files.bzl +++ b/third_party/external_files.bzl @@ -76,6 +76,18 @@ def external_files(): urls = ["https://storage.googleapis.com/mediapipe-assets/cat_mask.jpg?generation=1661875677203533"], ) + http_file( + name = "com_google_mediapipe_cat_rotated_jpg", + sha256 = "b78cee5ad14c9f36b1c25d103db371d81ca74d99030063c46a38e80bb8f38649", + urls = ["https://storage.googleapis.com/mediapipe-assets/cat_rotated.jpg?generation=1666304165042123"], + ) + + http_file( + name = "com_google_mediapipe_cat_rotated_mask_jpg", + sha256 = "f336973e7621d602f2ebc9a6ab1c62d8502272d391713f369d3b99541afda861", + urls = ["https://storage.googleapis.com/mediapipe-assets/cat_rotated_mask.jpg?generation=1666304167148173"], + ) + http_file( name = "com_google_mediapipe_cats_and_dogs_jpg", sha256 = "a2eaa7ad3a1aae4e623dd362a5f737e8a88d122597ecd1a02b3e1444db56df9c", @@ -162,8 +174,8 @@ def external_files(): http_file( name = "com_google_mediapipe_expected_left_down_hand_rotated_landmarks_prototxt", - sha256 = "a16d6cb8dd07d60f0678ddeb6a7447b73b9b03d4ddde365c8770b472205bb6cf", - urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_down_hand_rotated_landmarks.prototxt?generation=1666037061297507"], + sha256 = "c4dfdcc2e4cd366eb5f8ad227be94049eb593e3a528564611094687912463687", + urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_down_hand_rotated_landmarks.prototxt?generation=1666304169636598"], ) http_file( @@ -174,8 +186,8 @@ def external_files(): http_file( name = "com_google_mediapipe_expected_left_up_hand_rotated_landmarks_prototxt", - sha256 = "a9b9789c274d48a7cb9cc10af7bc644eb2512bb934529790d0a5404726daa86a", - urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_up_hand_rotated_landmarks.prototxt?generation=1666037063443676"], + sha256 = "7fb2d33cf69d2da50952a45bad0c0618f30859e608958fee95948a6e0de63ccb", + urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_up_hand_rotated_landmarks.prototxt?generation=1666304171758037"], ) http_file( @@ -258,8 +270,8 @@ def external_files(): http_file( name = "com_google_mediapipe_hand_detector_result_one_hand_rotated_pbtxt", - sha256 = "ff5ca0654028d78a3380df90054273cae79abe1b7369b164063fd1d5758ec370", - urls = ["https://storage.googleapis.com/mediapipe-assets/hand_detector_result_one_hand_rotated.pbtxt?generation=1666037065601724"], + sha256 = "555079c274ea91699757a0b9888c9993a8ab450069103b1bcd4ebb805a8e023c", + urls = ["https://storage.googleapis.com/mediapipe-assets/hand_detector_result_one_hand_rotated.pbtxt?generation=1666304174234283"], ) http_file( @@ -606,8 +618,8 @@ def external_files(): http_file( name = "com_google_mediapipe_pointing_up_rotated_landmarks_pbtxt", - sha256 = "ccf67e5867094ffb6c465a4dfbf2ef1eb3f9db2465803fc25a0b84c958e050de", - urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_rotated_landmarks.pbtxt?generation=1666037074376515"], + sha256 = "5ec37218d8b613436f5c10121dc689bf9ee69af0656a6ccf8c2e3e8b652e2ad6", + urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_rotated_landmarks.pbtxt?generation=1666304178388806"], ) http_file( @@ -798,8 +810,8 @@ def external_files(): http_file( name = "com_google_mediapipe_thumb_up_rotated_landmarks_pbtxt", - sha256 = "5d0a465959cacbd201ac8dd8fc8a66c5997a172b71809b12d27296db6a28a102", - urls = ["https://storage.googleapis.com/mediapipe-assets/thumb_up_rotated_landmarks.pbtxt?generation=1666037079490527"], + sha256 = "6645bbd98ea7f90b3e1ba297e16ea5280847fc5bf5400726d98c282f6c597257", + urls = ["https://storage.googleapis.com/mediapipe-assets/thumb_up_rotated_landmarks.pbtxt?generation=1666304181397432"], ) http_file( From 2cf9523468e280d736a92a1b681f2c96bb61c8f3 Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Mon, 24 Oct 2022 10:53:35 -0700 Subject: [PATCH 066/125] Fix the java_package name. PiperOrigin-RevId: 483428848 --- mediapipe/tasks/cc/components/containers/proto/category.proto | 2 +- .../cc/components/containers/proto/classifications.proto | 2 +- .../tasks/cc/components/containers/proto/embeddings.proto | 3 +++ .../tasks/text/textclassifier/TextClassificationResult.java | 4 ++-- .../mediapipe/tasks/text/textclassifier/TextClassifier.java | 2 +- .../vision/imageclassifier/ImageClassificationResult.java | 4 ++-- .../tasks/vision/imageclassifier/ImageClassifier.java | 2 +- 7 files changed, 11 insertions(+), 8 deletions(-) diff --git a/mediapipe/tasks/cc/components/containers/proto/category.proto b/mediapipe/tasks/cc/components/containers/proto/category.proto index a154e5f4e..2ba760e99 100644 --- a/mediapipe/tasks/cc/components/containers/proto/category.proto +++ b/mediapipe/tasks/cc/components/containers/proto/category.proto @@ -17,7 +17,7 @@ syntax = "proto2"; package mediapipe.tasks.components.containers.proto; -option java_package = "com.google.mediapipe.tasks.components.container.proto"; +option java_package = "com.google.mediapipe.tasks.components.containers.proto"; option java_outer_classname = "CategoryProto"; // A single classification result. diff --git a/mediapipe/tasks/cc/components/containers/proto/classifications.proto b/mediapipe/tasks/cc/components/containers/proto/classifications.proto index 0f5086b95..712607fa6 100644 --- a/mediapipe/tasks/cc/components/containers/proto/classifications.proto +++ b/mediapipe/tasks/cc/components/containers/proto/classifications.proto @@ -19,7 +19,7 @@ package mediapipe.tasks.components.containers.proto; import "mediapipe/tasks/cc/components/containers/proto/category.proto"; -option java_package = "com.google.mediapipe.tasks.components.container.proto"; +option java_package = "com.google.mediapipe.tasks.components.containers.proto"; option java_outer_classname = "ClassificationsProto"; // List of predicted categories with an optional timestamp. diff --git a/mediapipe/tasks/cc/components/containers/proto/embeddings.proto b/mediapipe/tasks/cc/components/containers/proto/embeddings.proto index d57b08b53..39811e6c0 100644 --- a/mediapipe/tasks/cc/components/containers/proto/embeddings.proto +++ b/mediapipe/tasks/cc/components/containers/proto/embeddings.proto @@ -17,6 +17,9 @@ syntax = "proto2"; package mediapipe.tasks.components.containers.proto; +option java_package = "com.google.mediapipe.tasks.components.containers.proto"; +option java_outer_classname = "EmbeddingsProto"; + // Defines a dense floating-point embedding. message FloatEmbedding { repeated float values = 1 [packed = true]; diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassificationResult.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassificationResult.java index dd9b9a1b3..c1e2446cd 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassificationResult.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassificationResult.java @@ -15,11 +15,11 @@ package com.google.mediapipe.tasks.text.textclassifier; import com.google.auto.value.AutoValue; -import com.google.mediapipe.tasks.components.container.proto.CategoryProto; -import com.google.mediapipe.tasks.components.container.proto.ClassificationsProto; import com.google.mediapipe.tasks.components.containers.Category; import com.google.mediapipe.tasks.components.containers.ClassificationEntry; import com.google.mediapipe.tasks.components.containers.Classifications; +import com.google.mediapipe.tasks.components.containers.proto.CategoryProto; +import com.google.mediapipe.tasks.components.containers.proto.ClassificationsProto; import com.google.mediapipe.tasks.core.TaskResult; import java.util.ArrayList; import java.util.Collections; diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassifier.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassifier.java index 76117d2e4..07a4fa48f 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassifier.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/text/textclassifier/TextClassifier.java @@ -22,7 +22,7 @@ import com.google.mediapipe.framework.MediaPipeException; import com.google.mediapipe.framework.Packet; import com.google.mediapipe.framework.PacketGetter; import com.google.mediapipe.framework.ProtoUtil; -import com.google.mediapipe.tasks.components.container.proto.ClassificationsProto; +import com.google.mediapipe.tasks.components.containers.proto.ClassificationsProto; import com.google.mediapipe.tasks.components.processors.ClassifierOptions; import com.google.mediapipe.tasks.core.BaseOptions; import com.google.mediapipe.tasks.core.OutputHandler; diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassificationResult.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassificationResult.java index 09f854caa..d82a47b86 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassificationResult.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassificationResult.java @@ -15,11 +15,11 @@ package com.google.mediapipe.tasks.vision.imageclassifier; import com.google.auto.value.AutoValue; -import com.google.mediapipe.tasks.components.container.proto.CategoryProto; -import com.google.mediapipe.tasks.components.container.proto.ClassificationsProto; import com.google.mediapipe.tasks.components.containers.Category; import com.google.mediapipe.tasks.components.containers.ClassificationEntry; import com.google.mediapipe.tasks.components.containers.Classifications; +import com.google.mediapipe.tasks.components.containers.proto.CategoryProto; +import com.google.mediapipe.tasks.components.containers.proto.ClassificationsProto; import com.google.mediapipe.tasks.core.TaskResult; import java.util.ArrayList; import java.util.Collections; diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java index e7d9e4ea1..75e2de13a 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java @@ -26,7 +26,7 @@ import com.google.mediapipe.framework.PacketGetter; import com.google.mediapipe.framework.ProtoUtil; import com.google.mediapipe.framework.image.BitmapImageBuilder; import com.google.mediapipe.framework.image.MPImage; -import com.google.mediapipe.tasks.components.container.proto.ClassificationsProto; +import com.google.mediapipe.tasks.components.containers.proto.ClassificationsProto; import com.google.mediapipe.tasks.components.processors.ClassifierOptions; import com.google.mediapipe.tasks.core.BaseOptions; import com.google.mediapipe.tasks.core.ErrorListener; From 3d88b1797a357e80ffd3a6e85a227d61795c8935 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Mon, 24 Oct 2022 11:25:18 -0700 Subject: [PATCH 067/125] Switch CHECK to a status in resource handling code. Expand error message. PiperOrigin-RevId: 483438131 --- mediapipe/util/resource_util_android.cc | 3 ++- mediapipe/util/resource_util_apple.cc | 3 ++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/mediapipe/util/resource_util_android.cc b/mediapipe/util/resource_util_android.cc index b18354d5f..1e970f212 100644 --- a/mediapipe/util/resource_util_android.cc +++ b/mediapipe/util/resource_util_android.cc @@ -82,7 +82,8 @@ absl::StatusOr PathToResourceAsFile(const std::string& path) { // If that fails, assume it was a relative path, and try just the base name. { const size_t last_slash_idx = path.find_last_of("\\/"); - CHECK_NE(last_slash_idx, std::string::npos); // Make sure it's a path. + RET_CHECK(last_slash_idx != std::string::npos) + << path << " doesn't have a slash in it"; // Make sure it's a path. auto base_name = path.substr(last_slash_idx + 1); auto status_or_path = PathToResourceAsFileInternal(base_name); if (status_or_path.ok()) { diff --git a/mediapipe/util/resource_util_apple.cc b/mediapipe/util/resource_util_apple.cc index c812dcb57..f64718348 100644 --- a/mediapipe/util/resource_util_apple.cc +++ b/mediapipe/util/resource_util_apple.cc @@ -71,7 +71,8 @@ absl::StatusOr PathToResourceAsFile(const std::string& path) { // If that fails, assume it was a relative path, and try just the base name. { const size_t last_slash_idx = path.find_last_of("\\/"); - CHECK_NE(last_slash_idx, std::string::npos); // Make sure it's a path. + RET_CHECK(last_slash_idx != std::string::npos) + << path << " doesn't have a slash in it"; // Make sure it's a path. auto base_name = path.substr(last_slash_idx + 1); auto status_or_path = PathToResourceAsFileInternal(base_name); if (status_or_path.ok()) { From b8502decff8f798b34d3b981b7dc8c3676cfc6f7 Mon Sep 17 00:00:00 2001 From: Sebastian Schmidt Date: Mon, 24 Oct 2022 12:13:11 -0700 Subject: [PATCH 068/125] Update model file upload script to verify full URL PiperOrigin-RevId: 483451219 --- third_party/external_files.bzl | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/third_party/external_files.bzl b/third_party/external_files.bzl index d460387aa..4b7309eef 100644 --- a/third_party/external_files.bzl +++ b/third_party/external_files.bzl @@ -175,7 +175,7 @@ def external_files(): http_file( name = "com_google_mediapipe_expected_left_down_hand_rotated_landmarks_prototxt", sha256 = "c4dfdcc2e4cd366eb5f8ad227be94049eb593e3a528564611094687912463687", - urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_down_hand_rotated_landmarks.prototxt?generation=1666304169636598"], + urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_down_hand_rotated_landmarks.prototxt?generation=1666629474155924"], ) http_file( @@ -187,7 +187,7 @@ def external_files(): http_file( name = "com_google_mediapipe_expected_left_up_hand_rotated_landmarks_prototxt", sha256 = "7fb2d33cf69d2da50952a45bad0c0618f30859e608958fee95948a6e0de63ccb", - urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_up_hand_rotated_landmarks.prototxt?generation=1666304171758037"], + urls = ["https://storage.googleapis.com/mediapipe-assets/expected_left_up_hand_rotated_landmarks.prototxt?generation=1666629476401757"], ) http_file( @@ -271,7 +271,7 @@ def external_files(): http_file( name = "com_google_mediapipe_hand_detector_result_one_hand_rotated_pbtxt", sha256 = "555079c274ea91699757a0b9888c9993a8ab450069103b1bcd4ebb805a8e023c", - urls = ["https://storage.googleapis.com/mediapipe-assets/hand_detector_result_one_hand_rotated.pbtxt?generation=1666304174234283"], + urls = ["https://storage.googleapis.com/mediapipe-assets/hand_detector_result_one_hand_rotated.pbtxt?generation=1666629478777955"], ) http_file( @@ -468,14 +468,14 @@ def external_files(): http_file( name = "com_google_mediapipe_mobilenet_v2_1_0_224_json", - sha256 = "0eb285a857b4bb1815736d0902ace0af45ea62e90c1dac98844b9ca797cd0d7b", - urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224.json?generation=1665988398778178"], + sha256 = "94613ea9539a20a3352604004be6d4d64d4d76250bc9042fcd8685c9a8498517", + urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224.json?generation=1666633416316646"], ) http_file( name = "com_google_mediapipe_mobilenet_v2_1_0_224_quant_json", - sha256 = "932f345ebe3d98daf0dc4c88b0f9e694e450390fb394fc217e851338dfec43e6", - urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224_quant.json?generation=1665988401522527"], + sha256 = "3703eadcf838b65bbc2b2aa11dbb1f1bc654c7a09a7aba5ca75a26096484a8ac", + urls = ["https://storage.googleapis.com/mediapipe-assets/mobilenet_v2_1.0_224_quant.json?generation=1666633418665507"], ) http_file( @@ -619,7 +619,7 @@ def external_files(): http_file( name = "com_google_mediapipe_pointing_up_rotated_landmarks_pbtxt", sha256 = "5ec37218d8b613436f5c10121dc689bf9ee69af0656a6ccf8c2e3e8b652e2ad6", - urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_rotated_landmarks.pbtxt?generation=1666304178388806"], + urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_rotated_landmarks.pbtxt?generation=1666629486774022"], ) http_file( @@ -811,7 +811,7 @@ def external_files(): http_file( name = "com_google_mediapipe_thumb_up_rotated_landmarks_pbtxt", sha256 = "6645bbd98ea7f90b3e1ba297e16ea5280847fc5bf5400726d98c282f6c597257", - urls = ["https://storage.googleapis.com/mediapipe-assets/thumb_up_rotated_landmarks.pbtxt?generation=1666304181397432"], + urls = ["https://storage.googleapis.com/mediapipe-assets/thumb_up_rotated_landmarks.pbtxt?generation=1666629489421733"], ) http_file( From 94cd1348096bae81f9cf6bdeb5ed5b5de96b66b3 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Mon, 24 Oct 2022 14:59:09 -0700 Subject: [PATCH 069/125] Add support for image rotation in Java vision tasks. PiperOrigin-RevId: 483493729 --- .../android/objectdetector/src/main/BUILD | 1 + .../examples/objectdetector/MainActivity.java | 38 ++-- .../com/google/mediapipe/tasks/vision/BUILD | 1 + .../tasks/vision/core/BaseVisionTaskApi.java | 181 ++++-------------- .../vision/core/ImageProcessingOptions.java | 92 +++++++++ .../gesturerecognizer/GestureRecognizer.java | 128 +++++++++++-- .../imageclassifier/ImageClassifier.java | 121 ++++++------ .../vision/objectdetector/ObjectDetector.java | 127 ++++++++++-- .../tasks/vision/core/AndroidManifest.xml | 24 +++ .../google/mediapipe/tasks/vision/core/BUILD | 19 ++ .../core/ImageProcessingOptionsTest.java | 70 +++++++ .../GestureRecognizerTest.java | 79 +++++++- .../imageclassifier/ImageClassifierTest.java | 79 +++++++- .../objectdetector/ObjectDetectorTest.java | 85 ++++++-- 14 files changed, 762 insertions(+), 283 deletions(-) create mode 100644 mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/ImageProcessingOptions.java create mode 100644 mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/AndroidManifest.xml create mode 100644 mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/BUILD create mode 100644 mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/ImageProcessingOptionsTest.java diff --git a/mediapipe/tasks/examples/android/objectdetector/src/main/BUILD b/mediapipe/tasks/examples/android/objectdetector/src/main/BUILD index acbdbd6eb..89c1edcb3 100644 --- a/mediapipe/tasks/examples/android/objectdetector/src/main/BUILD +++ b/mediapipe/tasks/examples/android/objectdetector/src/main/BUILD @@ -31,6 +31,7 @@ android_binary( multidex = "native", resource_files = ["//mediapipe/tasks/examples/android:resource_files"], deps = [ + "//mediapipe/java/com/google/mediapipe/framework:android_framework", "//mediapipe/java/com/google/mediapipe/framework/image", "//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:detection", "//mediapipe/tasks/java/com/google/mediapipe/tasks/core", diff --git a/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/MainActivity.java b/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/MainActivity.java index 11c8c1837..18c010a00 100644 --- a/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/MainActivity.java +++ b/mediapipe/tasks/examples/android/objectdetector/src/main/java/com/google/mediapipe/tasks/examples/objectdetector/MainActivity.java @@ -16,7 +16,6 @@ package com.google.mediapipe.tasks.examples.objectdetector; import android.content.Intent; import android.graphics.Bitmap; -import android.graphics.Matrix; import android.media.MediaMetadataRetriever; import android.os.Bundle; import android.provider.MediaStore; @@ -29,9 +28,11 @@ import androidx.activity.result.ActivityResultLauncher; import androidx.activity.result.contract.ActivityResultContracts; import androidx.exifinterface.media.ExifInterface; // ContentResolver dependency +import com.google.mediapipe.framework.MediaPipeException; import com.google.mediapipe.framework.image.BitmapImageBuilder; import com.google.mediapipe.framework.image.MPImage; import com.google.mediapipe.tasks.core.BaseOptions; +import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.objectdetector.ObjectDetectionResult; import com.google.mediapipe.tasks.vision.objectdetector.ObjectDetector; @@ -82,6 +83,7 @@ public class MainActivity extends AppCompatActivity { if (resultIntent != null) { if (result.getResultCode() == RESULT_OK) { Bitmap bitmap = null; + int rotation = 0; try { bitmap = downscaleBitmap( @@ -93,13 +95,16 @@ public class MainActivity extends AppCompatActivity { try { InputStream imageData = this.getContentResolver().openInputStream(resultIntent.getData()); - bitmap = rotateBitmap(bitmap, imageData); - } catch (IOException e) { + rotation = getImageRotation(imageData); + } catch (IOException | MediaPipeException e) { Log.e(TAG, "Bitmap rotation error:" + e); } if (bitmap != null) { MPImage image = new BitmapImageBuilder(bitmap).build(); - ObjectDetectionResult detectionResult = objectDetector.detect(image); + ObjectDetectionResult detectionResult = + objectDetector.detect( + image, + ImageProcessingOptions.builder().setRotationDegrees(rotation).build()); imageView.setData(image, detectionResult); runOnUiThread(() -> imageView.update()); } @@ -210,28 +215,25 @@ public class MainActivity extends AppCompatActivity { return Bitmap.createScaledBitmap(originalBitmap, width, height, false); } - private Bitmap rotateBitmap(Bitmap inputBitmap, InputStream imageData) throws IOException { + private int getImageRotation(InputStream imageData) throws IOException, MediaPipeException { int orientation = new ExifInterface(imageData) .getAttributeInt(ExifInterface.TAG_ORIENTATION, ExifInterface.ORIENTATION_NORMAL); - if (orientation == ExifInterface.ORIENTATION_NORMAL) { - return inputBitmap; - } - Matrix matrix = new Matrix(); switch (orientation) { + case ExifInterface.ORIENTATION_NORMAL: + return 0; case ExifInterface.ORIENTATION_ROTATE_90: - matrix.postRotate(90); - break; + return 90; case ExifInterface.ORIENTATION_ROTATE_180: - matrix.postRotate(180); - break; + return 180; case ExifInterface.ORIENTATION_ROTATE_270: - matrix.postRotate(270); - break; + return 270; default: - matrix.postRotate(0); + // TODO: use getRotationDegrees() and isFlipped() instead of switch once flip + // is supported. + throw new MediaPipeException( + MediaPipeException.StatusCode.UNIMPLEMENTED.ordinal(), + "Flipped images are not supported yet."); } - return Bitmap.createBitmap( - inputBitmap, 0, 0, inputBitmap.getWidth(), inputBitmap.getHeight(), matrix, true); } } diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD index 5ea465d47..ed65fbcac 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD @@ -28,6 +28,7 @@ android_library( "//mediapipe/java/com/google/mediapipe/framework:android_framework_no_mff", "//mediapipe/java/com/google/mediapipe/framework/image", "//mediapipe/tasks/java/com/google/mediapipe/tasks/core", + "//third_party:autovalue", "@maven//:com_google_guava_guava", ], ) diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/BaseVisionTaskApi.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/BaseVisionTaskApi.java index 49dab408c..0774b69a2 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/BaseVisionTaskApi.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/BaseVisionTaskApi.java @@ -24,7 +24,6 @@ import com.google.mediapipe.tasks.core.TaskResult; import com.google.mediapipe.tasks.core.TaskRunner; import java.util.HashMap; import java.util.Map; -import java.util.Optional; /** The base class of MediaPipe vision tasks. */ public class BaseVisionTaskApi implements AutoCloseable { @@ -32,7 +31,7 @@ public class BaseVisionTaskApi implements AutoCloseable { private final TaskRunner runner; private final RunningMode runningMode; private final String imageStreamName; - private final Optional normRectStreamName; + private final String normRectStreamName; static { System.loadLibrary("mediapipe_tasks_vision_jni"); @@ -40,27 +39,13 @@ public class BaseVisionTaskApi implements AutoCloseable { } /** - * Constructor to initialize a {@link BaseVisionTaskApi} only taking images as input. + * Constructor to initialize a {@link BaseVisionTaskApi}. * * @param runner a {@link TaskRunner}. * @param runningMode a mediapipe vision task {@link RunningMode}. * @param imageStreamName the name of the input image stream. - */ - public BaseVisionTaskApi(TaskRunner runner, RunningMode runningMode, String imageStreamName) { - this.runner = runner; - this.runningMode = runningMode; - this.imageStreamName = imageStreamName; - this.normRectStreamName = Optional.empty(); - } - - /** - * Constructor to initialize a {@link BaseVisionTaskApi} taking images and normalized rects as - * input. - * - * @param runner a {@link TaskRunner}. - * @param runningMode a mediapipe vision task {@link RunningMode}. - * @param imageStreamName the name of the input image stream. - * @param normRectStreamName the name of the input normalized rect image stream. + * @param normRectStreamName the name of the input normalized rect image stream used to provide + * (mandatory) rotation and (optional) region-of-interest. */ public BaseVisionTaskApi( TaskRunner runner, @@ -70,7 +55,7 @@ public class BaseVisionTaskApi implements AutoCloseable { this.runner = runner; this.runningMode = runningMode; this.imageStreamName = imageStreamName; - this.normRectStreamName = Optional.of(normRectStreamName); + this.normRectStreamName = normRectStreamName; } /** @@ -78,53 +63,23 @@ public class BaseVisionTaskApi implements AutoCloseable { * failure status or a successful result is returned. * * @param image a MediaPipe {@link MPImage} object for processing. - * @throws MediaPipeException if the task is not in the image mode or requires a normalized rect - * input. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. + * @throws MediaPipeException if the task is not in the image mode. */ - protected TaskResult processImageData(MPImage image) { + protected TaskResult processImageData( + MPImage image, ImageProcessingOptions imageProcessingOptions) { if (runningMode != RunningMode.IMAGE) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), "Task is not initialized with the image mode. Current running mode:" + runningMode.name()); } - if (normRectStreamName.isPresent()) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task expects a normalized rect as input."); - } - Map inputPackets = new HashMap<>(); - inputPackets.put(imageStreamName, runner.getPacketCreator().createImage(image)); - return runner.process(inputPackets); - } - - /** - * A synchronous method to process single image inputs. The call blocks the current thread until a - * failure status or a successful result is returned. - * - * @param image a MediaPipe {@link MPImage} object for processing. - * @param roi a {@link RectF} defining the region-of-interest to process in the image. Coordinates - * are expected to be specified as normalized values in [0,1]. - * @throws MediaPipeException if the task is not in the image mode or doesn't require a normalized - * rect. - */ - protected TaskResult processImageData(MPImage image, RectF roi) { - if (runningMode != RunningMode.IMAGE) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task is not initialized with the image mode. Current running mode:" - + runningMode.name()); - } - if (!normRectStreamName.isPresent()) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task doesn't expect a normalized rect as input."); - } Map inputPackets = new HashMap<>(); inputPackets.put(imageStreamName, runner.getPacketCreator().createImage(image)); inputPackets.put( - normRectStreamName.get(), - runner.getPacketCreator().createProto(convertToNormalizedRect(roi))); + normRectStreamName, + runner.getPacketCreator().createProto(convertToNormalizedRect(imageProcessingOptions))); return runner.process(inputPackets); } @@ -133,55 +88,24 @@ public class BaseVisionTaskApi implements AutoCloseable { * until a failure status or a successful result is returned. * * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. * @param timestampMs the corresponding timestamp of the input image in milliseconds. - * @throws MediaPipeException if the task is not in the video mode or requires a normalized rect - * input. + * @throws MediaPipeException if the task is not in the video mode. */ - protected TaskResult processVideoData(MPImage image, long timestampMs) { + protected TaskResult processVideoData( + MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) { if (runningMode != RunningMode.VIDEO) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), "Task is not initialized with the video mode. Current running mode:" + runningMode.name()); } - if (normRectStreamName.isPresent()) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task expects a normalized rect as input."); - } - Map inputPackets = new HashMap<>(); - inputPackets.put(imageStreamName, runner.getPacketCreator().createImage(image)); - return runner.process(inputPackets, timestampMs * MICROSECONDS_PER_MILLISECOND); - } - - /** - * A synchronous method to process continuous video frames. The call blocks the current thread - * until a failure status or a successful result is returned. - * - * @param image a MediaPipe {@link MPImage} object for processing. - * @param roi a {@link RectF} defining the region-of-interest to process in the image. Coordinates - * are expected to be specified as normalized values in [0,1]. - * @param timestampMs the corresponding timestamp of the input image in milliseconds. - * @throws MediaPipeException if the task is not in the video mode or doesn't require a normalized - * rect. - */ - protected TaskResult processVideoData(MPImage image, RectF roi, long timestampMs) { - if (runningMode != RunningMode.VIDEO) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task is not initialized with the video mode. Current running mode:" - + runningMode.name()); - } - if (!normRectStreamName.isPresent()) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task doesn't expect a normalized rect as input."); - } Map inputPackets = new HashMap<>(); inputPackets.put(imageStreamName, runner.getPacketCreator().createImage(image)); inputPackets.put( - normRectStreamName.get(), - runner.getPacketCreator().createProto(convertToNormalizedRect(roi))); + normRectStreamName, + runner.getPacketCreator().createProto(convertToNormalizedRect(imageProcessingOptions))); return runner.process(inputPackets, timestampMs * MICROSECONDS_PER_MILLISECOND); } @@ -190,55 +114,24 @@ public class BaseVisionTaskApi implements AutoCloseable { * available in the user-defined result listener. * * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. * @param timestampMs the corresponding timestamp of the input image in milliseconds. - * @throws MediaPipeException if the task is not in the video mode or requires a normalized rect - * input. + * @throws MediaPipeException if the task is not in the stream mode. */ - protected void sendLiveStreamData(MPImage image, long timestampMs) { + protected void sendLiveStreamData( + MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) { if (runningMode != RunningMode.LIVE_STREAM) { throw new MediaPipeException( MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), "Task is not initialized with the live stream mode. Current running mode:" + runningMode.name()); } - if (normRectStreamName.isPresent()) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task expects a normalized rect as input."); - } - Map inputPackets = new HashMap<>(); - inputPackets.put(imageStreamName, runner.getPacketCreator().createImage(image)); - runner.send(inputPackets, timestampMs * MICROSECONDS_PER_MILLISECOND); - } - - /** - * An asynchronous method to send live stream data to the {@link TaskRunner}. The results will be - * available in the user-defined result listener. - * - * @param image a MediaPipe {@link MPImage} object for processing. - * @param roi a {@link RectF} defining the region-of-interest to process in the image. Coordinates - * are expected to be specified as normalized values in [0,1]. - * @param timestampMs the corresponding timestamp of the input image in milliseconds. - * @throws MediaPipeException if the task is not in the video mode or doesn't require a normalized - * rect. - */ - protected void sendLiveStreamData(MPImage image, RectF roi, long timestampMs) { - if (runningMode != RunningMode.LIVE_STREAM) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task is not initialized with the live stream mode. Current running mode:" - + runningMode.name()); - } - if (!normRectStreamName.isPresent()) { - throw new MediaPipeException( - MediaPipeException.StatusCode.FAILED_PRECONDITION.ordinal(), - "Task doesn't expect a normalized rect as input."); - } Map inputPackets = new HashMap<>(); inputPackets.put(imageStreamName, runner.getPacketCreator().createImage(image)); inputPackets.put( - normRectStreamName.get(), - runner.getPacketCreator().createProto(convertToNormalizedRect(roi))); + normRectStreamName, + runner.getPacketCreator().createProto(convertToNormalizedRect(imageProcessingOptions))); runner.send(inputPackets, timestampMs * MICROSECONDS_PER_MILLISECOND); } @@ -248,13 +141,23 @@ public class BaseVisionTaskApi implements AutoCloseable { runner.close(); } - /** Converts a {@link RectF} object into a {@link NormalizedRect} protobuf message. */ - private static NormalizedRect convertToNormalizedRect(RectF rect) { + /** + * Converts an {@link ImageProcessingOptions} instance into a {@link NormalizedRect} protobuf + * message. + */ + private static NormalizedRect convertToNormalizedRect( + ImageProcessingOptions imageProcessingOptions) { + RectF regionOfInterest = + imageProcessingOptions.regionOfInterest().isPresent() + ? imageProcessingOptions.regionOfInterest().get() + : new RectF(0, 0, 1, 1); return NormalizedRect.newBuilder() - .setXCenter(rect.centerX()) - .setYCenter(rect.centerY()) - .setWidth(rect.width()) - .setHeight(rect.height()) + .setXCenter(regionOfInterest.centerX()) + .setYCenter(regionOfInterest.centerY()) + .setWidth(regionOfInterest.width()) + .setHeight(regionOfInterest.height()) + // Convert to radians anti-clockwise. + .setRotation(-(float) Math.PI * imageProcessingOptions.rotationDegrees() / 180.0f) .build(); } } diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/ImageProcessingOptions.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/ImageProcessingOptions.java new file mode 100644 index 000000000..a34a9787d --- /dev/null +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/core/ImageProcessingOptions.java @@ -0,0 +1,92 @@ +// Copyright 2022 The MediaPipe Authors. All Rights Reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +package com.google.mediapipe.tasks.vision.core; + +import android.graphics.RectF; +import com.google.auto.value.AutoValue; +import java.util.Optional; + +// TODO: add support for image flipping. +/** Options for image processing. */ +@AutoValue +public abstract class ImageProcessingOptions { + + /** + * Builder for {@link ImageProcessingOptions}. + * + *

    If both region-of-interest and rotation are specified, the crop around the + * region-of-interest is extracted first, then the specified rotation is applied to the crop. + */ + @AutoValue.Builder + public abstract static class Builder { + /** + * Sets the optional region-of-interest to crop from the image. If not specified, the full image + * is used. + * + *

    Coordinates must be in [0,1], {@code left} must be < {@code right} and {@code top} must be + * < {@code bottom}, otherwise an IllegalArgumentException will be thrown when {@link #build()} + * is called. + */ + public abstract Builder setRegionOfInterest(RectF value); + + /** + * Sets the rotation to apply to the image (or cropped region-of-interest), in degrees + * clockwise. Defaults to 0. + * + *

    The rotation must be a multiple (positive or negative) of 90°, otherwise an + * IllegalArgumentException will be thrown when {@link #build()} is called. + */ + public abstract Builder setRotationDegrees(int value); + + abstract ImageProcessingOptions autoBuild(); + + /** + * Validates and builds the {@link ImageProcessingOptions} instance. + * + * @throws IllegalArgumentException if some of the provided values do not meet their + * requirements. + */ + public final ImageProcessingOptions build() { + ImageProcessingOptions options = autoBuild(); + if (options.regionOfInterest().isPresent()) { + RectF roi = options.regionOfInterest().get(); + if (roi.left >= roi.right || roi.top >= roi.bottom) { + throw new IllegalArgumentException( + String.format( + "Expected left < right and top < bottom, found: %s.", roi.toShortString())); + } + if (roi.left < 0 || roi.right > 1 || roi.top < 0 || roi.bottom > 1) { + throw new IllegalArgumentException( + String.format("Expected RectF values in [0,1], found: %s.", roi.toShortString())); + } + } + if (options.rotationDegrees() % 90 != 0) { + throw new IllegalArgumentException( + String.format( + "Expected rotation to be a multiple of 90°, found: %d.", + options.rotationDegrees())); + } + return options; + } + } + + public abstract Optional regionOfInterest(); + + public abstract int rotationDegrees(); + + public static Builder builder() { + return new AutoValue_ImageProcessingOptions.Builder().setRotationDegrees(0); + } +} diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java index 55cf275e9..8e5a30eab 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizer.java @@ -15,7 +15,6 @@ package com.google.mediapipe.tasks.vision.gesturerecognizer; import android.content.Context; -import android.graphics.RectF; import android.os.ParcelFileDescriptor; import com.google.auto.value.AutoValue; import com.google.mediapipe.formats.proto.LandmarkProto.LandmarkList; @@ -37,6 +36,7 @@ import com.google.mediapipe.tasks.core.TaskOptions; import com.google.mediapipe.tasks.core.TaskRunner; import com.google.mediapipe.tasks.core.proto.BaseOptionsProto; import com.google.mediapipe.tasks.vision.core.BaseVisionTaskApi; +import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.gesturerecognizer.proto.GestureClassifierGraphOptionsProto; import com.google.mediapipe.tasks.vision.gesturerecognizer.proto.GestureRecognizerGraphOptionsProto; @@ -212,6 +212,25 @@ public final class GestureRecognizer extends BaseVisionTaskApi { super(taskRunner, runningMode, IMAGE_IN_STREAM_NAME, NORM_RECT_IN_STREAM_NAME); } + /** + * Performs gesture recognition on the provided single image with default image processing + * options, i.e. without any rotation applied. Only use this method when the {@link + * GestureRecognizer} is created with {@link RunningMode.IMAGE}. TODO update java doc + * for input image format. + * + *

    {@link GestureRecognizer} supports the following color space types: + * + *

      + *
    • {@link Bitmap.Config.ARGB_8888} + *
    + * + * @param image a MediaPipe {@link MPImage} object for processing. + * @throws MediaPipeException if there is an internal error. + */ + public GestureRecognitionResult recognize(MPImage image) { + return recognize(image, ImageProcessingOptions.builder().build()); + } + /** * Performs gesture recognition on the provided single image. Only use this method when the {@link * GestureRecognizer} is created with {@link RunningMode.IMAGE}. TODO update java doc @@ -223,12 +242,41 @@ public final class GestureRecognizer extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. Note that region-of-interest is not supported + * by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in + * this method throwing an IllegalArgumentException. + * @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a + * region-of-interest. * @throws MediaPipeException if there is an internal error. */ - public GestureRecognitionResult recognize(MPImage inputImage) { - // TODO: add proper support for rotations. - return (GestureRecognitionResult) processImageData(inputImage, buildFullImageRectF()); + public GestureRecognitionResult recognize( + MPImage image, ImageProcessingOptions imageProcessingOptions) { + validateImageProcessingOptions(imageProcessingOptions); + return (GestureRecognitionResult) processImageData(image, imageProcessingOptions); + } + + /** + * Performs gesture recognition on the provided video frame with default image processing options, + * i.e. without any rotation applied. Only use this method when the {@link GestureRecognizer} is + * created with {@link RunningMode.VIDEO}. + * + *

    It's required to provide the video frame's timestamp (in milliseconds). The input timestamps + * must be monotonically increasing. + * + *

    {@link GestureRecognizer} supports the following color space types: + * + *

      + *
    • {@link Bitmap.Config.ARGB_8888} + *
    + * + * @param image a MediaPipe {@link MPImage} object for processing. + * @param timestampMs the input timestamp (in milliseconds). + * @throws MediaPipeException if there is an internal error. + */ + public GestureRecognitionResult recognizeForVideo(MPImage image, long timestampMs) { + return recognizeForVideo(image, ImageProcessingOptions.builder().build(), timestampMs); } /** @@ -244,14 +292,43 @@ public final class GestureRecognizer extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param inputTimestampMs the input timestamp (in milliseconds). + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. Note that region-of-interest is not supported + * by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in + * this method throwing an IllegalArgumentException. + * @param timestampMs the input timestamp (in milliseconds). + * @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a + * region-of-interest. * @throws MediaPipeException if there is an internal error. */ - public GestureRecognitionResult recognizeForVideo(MPImage inputImage, long inputTimestampMs) { - // TODO: add proper support for rotations. - return (GestureRecognitionResult) - processVideoData(inputImage, buildFullImageRectF(), inputTimestampMs); + public GestureRecognitionResult recognizeForVideo( + MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) { + validateImageProcessingOptions(imageProcessingOptions); + return (GestureRecognitionResult) processVideoData(image, imageProcessingOptions, timestampMs); + } + + /** + * Sends live image data to perform gesture recognition with default image processing options, + * i.e. without any rotation applied, and the results will be available via the {@link + * ResultListener} provided in the {@link GestureRecognizerOptions}. Only use this method when the + * {@link GestureRecognition} is created with {@link RunningMode.LIVE_STREAM}. + * + *

    It's required to provide a timestamp (in milliseconds) to indicate when the input image is + * sent to the gesture recognizer. The input timestamps must be monotonically increasing. + * + *

    {@link GestureRecognizer} supports the following color space types: + * + *

      + *
    • {@link Bitmap.Config.ARGB_8888} + *
    + * + * @param image a MediaPipe {@link MPImage} object for processing. + * @param timestampMs the input timestamp (in milliseconds). + * @throws MediaPipeException if there is an internal error. + */ + public void recognizeAsync(MPImage image, long timestampMs) { + recognizeAsync(image, ImageProcessingOptions.builder().build(), timestampMs); } /** @@ -268,13 +345,20 @@ public final class GestureRecognizer extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param inputTimestampMs the input timestamp (in milliseconds). + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. Note that region-of-interest is not supported + * by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in + * this method throwing an IllegalArgumentException. + * @param timestampMs the input timestamp (in milliseconds). + * @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a + * region-of-interest. * @throws MediaPipeException if there is an internal error. */ - public void recognizeAsync(MPImage inputImage, long inputTimestampMs) { - // TODO: add proper support for rotations. - sendLiveStreamData(inputImage, buildFullImageRectF(), inputTimestampMs); + public void recognizeAsync( + MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) { + validateImageProcessingOptions(imageProcessingOptions); + sendLiveStreamData(image, imageProcessingOptions, timestampMs); } /** Options for setting up an {@link GestureRecognizer}. */ @@ -445,8 +529,14 @@ public final class GestureRecognizer extends BaseVisionTaskApi { } } - /** Creates a RectF covering the full image. */ - private static RectF buildFullImageRectF() { - return new RectF(0, 0, 1, 1); + /** + * Validates that the provided {@link ImageProcessingOptions} doesn't contain a + * region-of-interest. + */ + private static void validateImageProcessingOptions( + ImageProcessingOptions imageProcessingOptions) { + if (imageProcessingOptions.regionOfInterest().isPresent()) { + throw new IllegalArgumentException("GestureRecognizer doesn't support region-of-interest."); + } } } diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java index 75e2de13a..3863b6fe0 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifier.java @@ -15,7 +15,6 @@ package com.google.mediapipe.tasks.vision.imageclassifier; import android.content.Context; -import android.graphics.RectF; import android.os.ParcelFileDescriptor; import com.google.auto.value.AutoValue; import com.google.mediapipe.proto.CalculatorOptionsProto.CalculatorOptions; @@ -37,6 +36,7 @@ import com.google.mediapipe.tasks.core.TaskOptions; import com.google.mediapipe.tasks.core.TaskRunner; import com.google.mediapipe.tasks.core.proto.BaseOptionsProto; import com.google.mediapipe.tasks.vision.core.BaseVisionTaskApi; +import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.imageclassifier.proto.ImageClassifierGraphOptionsProto; import java.io.File; @@ -215,6 +215,24 @@ public final class ImageClassifier extends BaseVisionTaskApi { super(taskRunner, runningMode, IMAGE_IN_STREAM_NAME, NORM_RECT_IN_STREAM_NAME); } + /** + * Performs classification on the provided single image with default image processing options, + * i.e. using the whole image as region-of-interest and without any rotation applied. Only use + * this method when the {@link ImageClassifier} is created with {@link RunningMode.IMAGE}. + * + *

    {@link ImageClassifier} supports the following color space types: + * + *

      + *
    • {@link Bitmap.Config.ARGB_8888} + *
    + * + * @param image a MediaPipe {@link MPImage} object for processing. + * @throws MediaPipeException if there is an internal error. + */ + public ImageClassificationResult classify(MPImage image) { + return classify(image, ImageProcessingOptions.builder().build()); + } + /** * Performs classification on the provided single image. Only use this method when the {@link * ImageClassifier} is created with {@link RunningMode.IMAGE}. @@ -225,16 +243,23 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. * @throws MediaPipeException if there is an internal error. */ - public ImageClassificationResult classify(MPImage inputImage) { - return (ImageClassificationResult) processImageData(inputImage, buildFullImageRectF()); + public ImageClassificationResult classify( + MPImage image, ImageProcessingOptions imageProcessingOptions) { + return (ImageClassificationResult) processImageData(image, imageProcessingOptions); } /** - * Performs classification on the provided single image and region-of-interest. Only use this - * method when the {@link ImageClassifier} is created with {@link RunningMode.IMAGE}. + * Performs classification on the provided video frame with default image processing options, i.e. + * using the whole image as region-of-interest and without any rotation applied. Only use this + * method when the {@link ImageClassifier} is created with {@link RunningMode.VIDEO}. + * + *

    It's required to provide the video frame's timestamp (in milliseconds). The input timestamps + * must be monotonically increasing. * *

    {@link ImageClassifier} supports the following color space types: * @@ -242,13 +267,12 @@ public final class ImageClassifier extends BaseVisionTaskApi { *

  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param roi a {@link RectF} specifying the region of interest on which to perform - * classification. Coordinates are expected to be specified as normalized values in [0,1]. + * @param image a MediaPipe {@link MPImage} object for processing. + * @param timestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public ImageClassificationResult classify(MPImage inputImage, RectF roi) { - return (ImageClassificationResult) processImageData(inputImage, roi); + public ImageClassificationResult classifyForVideo(MPImage image, long timestampMs) { + return classifyForVideo(image, ImageProcessingOptions.builder().build(), timestampMs); } /** @@ -264,21 +288,26 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param inputTimestampMs the input timestamp (in milliseconds). + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. + * @param timestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public ImageClassificationResult classifyForVideo(MPImage inputImage, long inputTimestampMs) { - return (ImageClassificationResult) - processVideoData(inputImage, buildFullImageRectF(), inputTimestampMs); + public ImageClassificationResult classifyForVideo( + MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) { + return (ImageClassificationResult) processVideoData(image, imageProcessingOptions, timestampMs); } /** - * Performs classification on the provided video frame with additional region-of-interest. Only - * use this method when the {@link ImageClassifier} is created with {@link RunningMode.VIDEO}. + * Sends live image data to perform classification with default image processing options, i.e. + * using the whole image as region-of-interest and without any rotation applied, and the results + * will be available via the {@link ResultListener} provided in the {@link + * ImageClassifierOptions}. Only use this method when the {@link ImageClassifier} is created with + * {@link RunningMode.LIVE_STREAM}. * - *

    It's required to provide the video frame's timestamp (in milliseconds). The input timestamps - * must be monotonically increasing. + *

    It's required to provide a timestamp (in milliseconds) to indicate when the input image is + * sent to the object detector. The input timestamps must be monotonically increasing. * *

    {@link ImageClassifier} supports the following color space types: * @@ -286,15 +315,12 @@ public final class ImageClassifier extends BaseVisionTaskApi { *

  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param roi a {@link RectF} specifying the region of interest on which to perform - * classification. Coordinates are expected to be specified as normalized values in [0,1]. - * @param inputTimestampMs the input timestamp (in milliseconds). + * @param image a MediaPipe {@link MPImage} object for processing. + * @param timestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public ImageClassificationResult classifyForVideo( - MPImage inputImage, RectF roi, long inputTimestampMs) { - return (ImageClassificationResult) processVideoData(inputImage, roi, inputTimestampMs); + public void classifyAsync(MPImage image, long timestampMs) { + classifyAsync(image, ImageProcessingOptions.builder().build(), timestampMs); } /** @@ -311,37 +337,15 @@ public final class ImageClassifier extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param inputTimestampMs the input timestamp (in milliseconds). + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. + * @param timestampMs the input timestamp (in milliseconds). * @throws MediaPipeException if there is an internal error. */ - public void classifyAsync(MPImage inputImage, long inputTimestampMs) { - sendLiveStreamData(inputImage, buildFullImageRectF(), inputTimestampMs); - } - - /** - * Sends live image data and additional region-of-interest to perform classification, and the - * results will be available via the {@link ResultListener} provided in the {@link - * ImageClassifierOptions}. Only use this method when the {@link ImageClassifier} is created with - * {@link RunningMode.LIVE_STREAM}. - * - *

    It's required to provide a timestamp (in milliseconds) to indicate when the input image is - * sent to the object detector. The input timestamps must be monotonically increasing. - * - *

    {@link ImageClassifier} supports the following color space types: - * - *

      - *
    • {@link Bitmap.Config.ARGB_8888} - *
    - * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param roi a {@link RectF} specifying the region of interest on which to perform - * classification. Coordinates are expected to be specified as normalized values in [0,1]. - * @param inputTimestampMs the input timestamp (in milliseconds). - * @throws MediaPipeException if there is an internal error. - */ - public void classifyAsync(MPImage inputImage, RectF roi, long inputTimestampMs) { - sendLiveStreamData(inputImage, roi, inputTimestampMs); + public void classifyAsync( + MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) { + sendLiveStreamData(image, imageProcessingOptions, timestampMs); } /** Options for setting up and {@link ImageClassifier}. */ @@ -447,9 +451,4 @@ public final class ImageClassifier extends BaseVisionTaskApi { .build(); } } - - /** Creates a RectF covering the full image. */ - private static RectF buildFullImageRectF() { - return new RectF(0, 0, 1, 1); - } } diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetector.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetector.java index 0f2e7b540..3f944eaee 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetector.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetector.java @@ -32,6 +32,7 @@ import com.google.mediapipe.tasks.core.TaskOptions; import com.google.mediapipe.tasks.core.TaskRunner; import com.google.mediapipe.tasks.core.proto.BaseOptionsProto; import com.google.mediapipe.tasks.vision.core.BaseVisionTaskApi; +import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.objectdetector.proto.ObjectDetectorOptionsProto; import com.google.mediapipe.formats.proto.DetectionProto.Detection; @@ -96,8 +97,10 @@ import java.util.Optional; public final class ObjectDetector extends BaseVisionTaskApi { private static final String TAG = ObjectDetector.class.getSimpleName(); private static final String IMAGE_IN_STREAM_NAME = "image_in"; + private static final String NORM_RECT_IN_STREAM_NAME = "norm_rect_in"; private static final List INPUT_STREAMS = - Collections.unmodifiableList(Arrays.asList("IMAGE:" + IMAGE_IN_STREAM_NAME)); + Collections.unmodifiableList( + Arrays.asList("IMAGE:" + IMAGE_IN_STREAM_NAME, "NORM_RECT:" + NORM_RECT_IN_STREAM_NAME)); private static final List OUTPUT_STREAMS = Collections.unmodifiableList(Arrays.asList("DETECTIONS:detections_out", "IMAGE:image_out")); private static final int DETECTIONS_OUT_STREAM_INDEX = 0; @@ -204,7 +207,25 @@ public final class ObjectDetector extends BaseVisionTaskApi { * @param runningMode a mediapipe vision task {@link RunningMode}. */ private ObjectDetector(TaskRunner taskRunner, RunningMode runningMode) { - super(taskRunner, runningMode, IMAGE_IN_STREAM_NAME); + super(taskRunner, runningMode, IMAGE_IN_STREAM_NAME, NORM_RECT_IN_STREAM_NAME); + } + + /** + * Performs object detection on the provided single image with default image processing options, + * i.e. without any rotation applied. Only use this method when the {@link ObjectDetector} is + * created with {@link RunningMode.IMAGE}. + * + *

    {@link ObjectDetector} supports the following color space types: + * + *

      + *
    • {@link Bitmap.Config.ARGB_8888} + *
    + * + * @param image a MediaPipe {@link MPImage} object for processing. + * @throws MediaPipeException if there is an internal error. + */ + public ObjectDetectionResult detect(MPImage image) { + return detect(image, ImageProcessingOptions.builder().build()); } /** @@ -217,11 +238,41 @@ public final class ObjectDetector extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. Note that region-of-interest is not supported + * by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in + * this method throwing an IllegalArgumentException. + * @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a + * region-of-interest. * @throws MediaPipeException if there is an internal error. */ - public ObjectDetectionResult detect(MPImage inputImage) { - return (ObjectDetectionResult) processImageData(inputImage); + public ObjectDetectionResult detect( + MPImage image, ImageProcessingOptions imageProcessingOptions) { + validateImageProcessingOptions(imageProcessingOptions); + return (ObjectDetectionResult) processImageData(image, imageProcessingOptions); + } + + /** + * Performs object detection on the provided video frame with default image processing options, + * i.e. without any rotation applied. Only use this method when the {@link ObjectDetector} is + * created with {@link RunningMode.VIDEO}. + * + *

    It's required to provide the video frame's timestamp (in milliseconds). The input timestamps + * must be monotonically increasing. + * + *

    {@link ObjectDetector} supports the following color space types: + * + *

      + *
    • {@link Bitmap.Config.ARGB_8888} + *
    + * + * @param image a MediaPipe {@link MPImage} object for processing. + * @param timestampMs the input timestamp (in milliseconds). + * @throws MediaPipeException if there is an internal error. + */ + public ObjectDetectionResult detectForVideo(MPImage image, long timestampMs) { + return detectForVideo(image, ImageProcessingOptions.builder().build(), timestampMs); } /** @@ -237,12 +288,43 @@ public final class ObjectDetector extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param inputTimestampMs the input timestamp (in milliseconds). + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. Note that region-of-interest is not supported + * by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in + * this method throwing an IllegalArgumentException. + * @param timestampMs the input timestamp (in milliseconds). + * @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a + * region-of-interest. * @throws MediaPipeException if there is an internal error. */ - public ObjectDetectionResult detectForVideo(MPImage inputImage, long inputTimestampMs) { - return (ObjectDetectionResult) processVideoData(inputImage, inputTimestampMs); + public ObjectDetectionResult detectForVideo( + MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) { + validateImageProcessingOptions(imageProcessingOptions); + return (ObjectDetectionResult) processVideoData(image, imageProcessingOptions, timestampMs); + } + + /** + * Sends live image data to perform object detection with default image processing options, i.e. + * without any rotation applied, and the results will be available via the {@link ResultListener} + * provided in the {@link ObjectDetectorOptions}. Only use this method when the {@link + * ObjectDetector} is created with {@link RunningMode.LIVE_STREAM}. + * + *

    It's required to provide a timestamp (in milliseconds) to indicate when the input image is + * sent to the object detector. The input timestamps must be monotonically increasing. + * + *

    {@link ObjectDetector} supports the following color space types: + * + *

      + *
    • {@link Bitmap.Config.ARGB_8888} + *
    + * + * @param image a MediaPipe {@link MPImage} object for processing. + * @param timestampMs the input timestamp (in milliseconds). + * @throws MediaPipeException if there is an internal error. + */ + public void detectAsync(MPImage image, long timestampMs) { + detectAsync(image, ImageProcessingOptions.builder().build(), timestampMs); } /** @@ -259,12 +341,20 @@ public final class ObjectDetector extends BaseVisionTaskApi { *
  • {@link Bitmap.Config.ARGB_8888} * * - * @param inputImage a MediaPipe {@link MPImage} object for processing. - * @param inputTimestampMs the input timestamp (in milliseconds). + * @param image a MediaPipe {@link MPImage} object for processing. + * @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the + * input image before running inference. Note that region-of-interest is not supported + * by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in + * this method throwing an IllegalArgumentException. + * @param timestampMs the input timestamp (in milliseconds). + * @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a + * region-of-interest. * @throws MediaPipeException if there is an internal error. */ - public void detectAsync(MPImage inputImage, long inputTimestampMs) { - sendLiveStreamData(inputImage, inputTimestampMs); + public void detectAsync( + MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) { + validateImageProcessingOptions(imageProcessingOptions); + sendLiveStreamData(image, imageProcessingOptions, timestampMs); } /** Options for setting up an {@link ObjectDetector}. */ @@ -415,4 +505,15 @@ public final class ObjectDetector extends BaseVisionTaskApi { .build(); } } + + /** + * Validates that the provided {@link ImageProcessingOptions} doesn't contain a + * region-of-interest. + */ + private static void validateImageProcessingOptions( + ImageProcessingOptions imageProcessingOptions) { + if (imageProcessingOptions.regionOfInterest().isPresent()) { + throw new IllegalArgumentException("ObjectDetector doesn't support region-of-interest."); + } + } } diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/AndroidManifest.xml b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/AndroidManifest.xml new file mode 100644 index 000000000..aa2df6baf --- /dev/null +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/AndroidManifest.xml @@ -0,0 +1,24 @@ + + + + + + + + + + + + + + + diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/BUILD b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/BUILD new file mode 100644 index 000000000..a7f804c64 --- /dev/null +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/BUILD @@ -0,0 +1,19 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +package(default_visibility = ["//mediapipe/tasks:internal"]) + +licenses(["notice"]) + +# TODO: Enable this in OSS diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/ImageProcessingOptionsTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/ImageProcessingOptionsTest.java new file mode 100644 index 000000000..078b62af1 --- /dev/null +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/core/ImageProcessingOptionsTest.java @@ -0,0 +1,70 @@ +// Copyright 2022 The MediaPipe Authors. All Rights Reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +package com.google.mediapipe.tasks.vision.core; + +import static com.google.common.truth.Truth.assertThat; +import static org.junit.Assert.assertThrows; + +import android.graphics.RectF; +import androidx.test.ext.junit.runners.AndroidJUnit4; +import org.junit.Test; +import org.junit.runner.RunWith; + +/** Test for {@link ImageProcessingOptions}/ */ +@RunWith(AndroidJUnit4.class) +public final class ImageProcessingOptionsTest { + + @Test + public void succeedsWithValidInputs() throws Exception { + ImageProcessingOptions options = + ImageProcessingOptions.builder() + .setRegionOfInterest(new RectF(0.0f, 0.1f, 1.0f, 0.9f)) + .setRotationDegrees(270) + .build(); + } + + @Test + public void failsWithLeftHigherThanRight() { + IllegalArgumentException exception = + assertThrows( + IllegalArgumentException.class, + () -> + ImageProcessingOptions.builder() + .setRegionOfInterest(new RectF(0.9f, 0.0f, 0.1f, 1.0f)) + .build()); + assertThat(exception).hasMessageThat().contains("Expected left < right and top < bottom"); + } + + @Test + public void failsWithBottomHigherThanTop() { + IllegalArgumentException exception = + assertThrows( + IllegalArgumentException.class, + () -> + ImageProcessingOptions.builder() + .setRegionOfInterest(new RectF(0.0f, 0.9f, 1.0f, 0.1f)) + .build()); + assertThat(exception).hasMessageThat().contains("Expected left < right and top < bottom"); + } + + @Test + public void failsWithInvalidRotation() { + IllegalArgumentException exception = + assertThrows( + IllegalArgumentException.class, + () -> ImageProcessingOptions.builder().setRotationDegrees(1).build()); + assertThat(exception).hasMessageThat().contains("Expected rotation to be a multiple of 90°"); + } +} diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java index 31e59a259..eca5d35c2 100644 --- a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java @@ -19,6 +19,7 @@ import static org.junit.Assert.assertThrows; import android.content.res.AssetManager; import android.graphics.BitmapFactory; +import android.graphics.RectF; import androidx.test.core.app.ApplicationProvider; import androidx.test.ext.junit.runners.AndroidJUnit4; import com.google.common.truth.Correspondence; @@ -30,6 +31,7 @@ import com.google.mediapipe.tasks.components.containers.Category; import com.google.mediapipe.tasks.components.containers.Landmark; import com.google.mediapipe.tasks.components.containers.proto.LandmarksDetectionResultProto.LandmarksDetectionResult; import com.google.mediapipe.tasks.core.BaseOptions; +import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.gesturerecognizer.GestureRecognizer.GestureRecognizerOptions; import java.io.InputStream; @@ -46,11 +48,14 @@ public class GestureRecognizerTest { private static final String GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE = "gesture_recognizer.task"; private static final String TWO_HANDS_IMAGE = "right_hands.jpg"; private static final String THUMB_UP_IMAGE = "thumb_up.jpg"; + private static final String POINTING_UP_ROTATED_IMAGE = "pointing_up_rotated.jpg"; private static final String NO_HANDS_IMAGE = "cats_and_dogs.jpg"; private static final String THUMB_UP_LANDMARKS = "thumb_up_landmarks.pb"; private static final String TAG = "Gesture Recognizer Test"; private static final String THUMB_UP_LABEL = "Thumb_Up"; private static final int THUMB_UP_INDEX = 5; + private static final String POINTING_UP_LABEL = "Pointing_Up"; + private static final int POINTING_UP_INDEX = 3; private static final float LANDMARKS_ERROR_TOLERANCE = 0.03f; private static final int IMAGE_WIDTH = 382; private static final int IMAGE_HEIGHT = 406; @@ -135,6 +140,53 @@ public class GestureRecognizerTest { gestureRecognizer.recognize(getImageFromAsset(TWO_HANDS_IMAGE)); assertThat(actualResult.handednesses()).hasSize(2); } + + @Test + public void recognize_successWithRotation() throws Exception { + GestureRecognizerOptions options = + GestureRecognizerOptions.builder() + .setBaseOptions( + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) + .setNumHands(1) + .build(); + GestureRecognizer gestureRecognizer = + GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); + ImageProcessingOptions imageProcessingOptions = + ImageProcessingOptions.builder().setRotationDegrees(-90).build(); + GestureRecognitionResult actualResult = + gestureRecognizer.recognize( + getImageFromAsset(POINTING_UP_ROTATED_IMAGE), imageProcessingOptions); + assertThat(actualResult.gestures()).hasSize(1); + assertThat(actualResult.gestures().get(0).get(0).index()).isEqualTo(POINTING_UP_INDEX); + assertThat(actualResult.gestures().get(0).get(0).categoryName()).isEqualTo(POINTING_UP_LABEL); + } + + @Test + public void recognize_failsWithRegionOfInterest() throws Exception { + GestureRecognizerOptions options = + GestureRecognizerOptions.builder() + .setBaseOptions( + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) + .setNumHands(1) + .build(); + GestureRecognizer gestureRecognizer = + GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); + ImageProcessingOptions imageProcessingOptions = + ImageProcessingOptions.builder().setRegionOfInterest(new RectF(0, 0, 1, 1)).build(); + IllegalArgumentException exception = + assertThrows( + IllegalArgumentException.class, + () -> + gestureRecognizer.recognize( + getImageFromAsset(THUMB_UP_IMAGE), imageProcessingOptions)); + assertThat(exception) + .hasMessageThat() + .contains("GestureRecognizer doesn't support region-of-interest"); + } } @RunWith(AndroidJUnit4.class) @@ -195,12 +247,16 @@ public class GestureRecognizerTest { MediaPipeException exception = assertThrows( MediaPipeException.class, - () -> gestureRecognizer.recognizeForVideo(getImageFromAsset(THUMB_UP_IMAGE), 0)); + () -> + gestureRecognizer.recognizeForVideo( + getImageFromAsset(THUMB_UP_IMAGE), /*timestampsMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the video mode"); exception = assertThrows( MediaPipeException.class, - () -> gestureRecognizer.recognizeAsync(getImageFromAsset(THUMB_UP_IMAGE), 0)); + () -> + gestureRecognizer.recognizeAsync( + getImageFromAsset(THUMB_UP_IMAGE), /*timestampsMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode"); } @@ -225,7 +281,9 @@ public class GestureRecognizerTest { exception = assertThrows( MediaPipeException.class, - () -> gestureRecognizer.recognizeAsync(getImageFromAsset(THUMB_UP_IMAGE), 0)); + () -> + gestureRecognizer.recognizeAsync( + getImageFromAsset(THUMB_UP_IMAGE), /*timestampsMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode"); } @@ -251,7 +309,9 @@ public class GestureRecognizerTest { exception = assertThrows( MediaPipeException.class, - () -> gestureRecognizer.recognizeForVideo(getImageFromAsset(THUMB_UP_IMAGE), 0)); + () -> + gestureRecognizer.recognizeForVideo( + getImageFromAsset(THUMB_UP_IMAGE), /*timestampsMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the video mode"); } @@ -291,7 +351,8 @@ public class GestureRecognizerTest { getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); for (int i = 0; i < 3; i++) { GestureRecognitionResult actualResult = - gestureRecognizer.recognizeForVideo(getImageFromAsset(THUMB_UP_IMAGE), i); + gestureRecognizer.recognizeForVideo( + getImageFromAsset(THUMB_UP_IMAGE), /*timestampsMs=*/ i); assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult); } } @@ -317,9 +378,11 @@ public class GestureRecognizerTest { .build(); try (GestureRecognizer gestureRecognizer = GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options)) { - gestureRecognizer.recognizeAsync(image, 1); + gestureRecognizer.recognizeAsync(image, /*timestampsMs=*/ 1); MediaPipeException exception = - assertThrows(MediaPipeException.class, () -> gestureRecognizer.recognizeAsync(image, 0)); + assertThrows( + MediaPipeException.class, + () -> gestureRecognizer.recognizeAsync(image, /*timestampsMs=*/ 0)); assertThat(exception) .hasMessageThat() .contains("having a smaller timestamp than the processed timestamp"); @@ -348,7 +411,7 @@ public class GestureRecognizerTest { try (GestureRecognizer gestureRecognizer = GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options)) { for (int i = 0; i < 3; i++) { - gestureRecognizer.recognizeAsync(image, i); + gestureRecognizer.recognizeAsync(image, /*timestampsMs=*/ i); } } } diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifierTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifierTest.java index 966e4ff4a..99ebd9777 100644 --- a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifierTest.java +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imageclassifier/ImageClassifierTest.java @@ -29,6 +29,7 @@ import com.google.mediapipe.tasks.components.containers.Category; import com.google.mediapipe.tasks.components.processors.ClassifierOptions; import com.google.mediapipe.tasks.core.BaseOptions; import com.google.mediapipe.tasks.core.TestUtils; +import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.imageclassifier.ImageClassifier.ImageClassifierOptions; import java.io.InputStream; @@ -47,7 +48,9 @@ public class ImageClassifierTest { private static final String FLOAT_MODEL_FILE = "mobilenet_v2_1.0_224.tflite"; private static final String QUANTIZED_MODEL_FILE = "mobilenet_v1_0.25_224_quant.tflite"; private static final String BURGER_IMAGE = "burger.jpg"; + private static final String BURGER_ROTATED_IMAGE = "burger_rotated.jpg"; private static final String MULTI_OBJECTS_IMAGE = "multi_objects.jpg"; + private static final String MULTI_OBJECTS_ROTATED_IMAGE = "multi_objects_rotated.jpg"; @RunWith(AndroidJUnit4.class) public static final class General extends ImageClassifierTest { @@ -209,13 +212,60 @@ public class ImageClassifierTest { ImageClassifier.createFromOptions(ApplicationProvider.getApplicationContext(), options); // RectF around the soccer ball. RectF roi = new RectF(0.450f, 0.308f, 0.614f, 0.734f); + ImageProcessingOptions imageProcessingOptions = + ImageProcessingOptions.builder().setRegionOfInterest(roi).build(); ImageClassificationResult results = - imageClassifier.classify(getImageFromAsset(MULTI_OBJECTS_IMAGE), roi); + imageClassifier.classify(getImageFromAsset(MULTI_OBJECTS_IMAGE), imageProcessingOptions); assertHasOneHeadAndOneTimestamp(results, 0); assertCategoriesAre( results, Arrays.asList(Category.create(0.9969325f, 806, "soccer ball", ""))); } + + @Test + public void classify_succeedsWithRotation() throws Exception { + ImageClassifierOptions options = + ImageClassifierOptions.builder() + .setBaseOptions(BaseOptions.builder().setModelAssetPath(FLOAT_MODEL_FILE).build()) + .setClassifierOptions(ClassifierOptions.builder().setMaxResults(3).build()) + .build(); + ImageClassifier imageClassifier = + ImageClassifier.createFromOptions(ApplicationProvider.getApplicationContext(), options); + ImageProcessingOptions imageProcessingOptions = + ImageProcessingOptions.builder().setRotationDegrees(-90).build(); + ImageClassificationResult results = + imageClassifier.classify(getImageFromAsset(BURGER_ROTATED_IMAGE), imageProcessingOptions); + + assertHasOneHeadAndOneTimestamp(results, 0); + assertCategoriesAre( + results, + Arrays.asList( + Category.create(0.6390683f, 934, "cheeseburger", ""), + Category.create(0.0495407f, 963, "meat loaf", ""), + Category.create(0.0469720f, 925, "guacamole", ""))); + } + + @Test + public void classify_succeedsWithRegionOfInterestAndRotation() throws Exception { + ImageClassifierOptions options = + ImageClassifierOptions.builder() + .setBaseOptions(BaseOptions.builder().setModelAssetPath(FLOAT_MODEL_FILE).build()) + .setClassifierOptions(ClassifierOptions.builder().setMaxResults(1).build()) + .build(); + ImageClassifier imageClassifier = + ImageClassifier.createFromOptions(ApplicationProvider.getApplicationContext(), options); + // RectF around the chair. + RectF roi = new RectF(0.0f, 0.1763f, 0.5642f, 0.3049f); + ImageProcessingOptions imageProcessingOptions = + ImageProcessingOptions.builder().setRegionOfInterest(roi).setRotationDegrees(-90).build(); + ImageClassificationResult results = + imageClassifier.classify( + getImageFromAsset(MULTI_OBJECTS_ROTATED_IMAGE), imageProcessingOptions); + + assertHasOneHeadAndOneTimestamp(results, 0); + assertCategoriesAre( + results, Arrays.asList(Category.create(0.686824f, 560, "folding chair", ""))); + } } @RunWith(AndroidJUnit4.class) @@ -269,12 +319,16 @@ public class ImageClassifierTest { MediaPipeException exception = assertThrows( MediaPipeException.class, - () -> imageClassifier.classifyForVideo(getImageFromAsset(BURGER_IMAGE), 0)); + () -> + imageClassifier.classifyForVideo( + getImageFromAsset(BURGER_IMAGE), /*timestampMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the video mode"); exception = assertThrows( MediaPipeException.class, - () -> imageClassifier.classifyAsync(getImageFromAsset(BURGER_IMAGE), 0)); + () -> + imageClassifier.classifyAsync( + getImageFromAsset(BURGER_IMAGE), /*timestampMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode"); } @@ -296,7 +350,9 @@ public class ImageClassifierTest { exception = assertThrows( MediaPipeException.class, - () -> imageClassifier.classifyAsync(getImageFromAsset(BURGER_IMAGE), 0)); + () -> + imageClassifier.classifyAsync( + getImageFromAsset(BURGER_IMAGE), /*timestampMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode"); } @@ -320,7 +376,9 @@ public class ImageClassifierTest { exception = assertThrows( MediaPipeException.class, - () -> imageClassifier.classifyForVideo(getImageFromAsset(BURGER_IMAGE), 0)); + () -> + imageClassifier.classifyForVideo( + getImageFromAsset(BURGER_IMAGE), /*timestampMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the video mode"); } @@ -352,7 +410,8 @@ public class ImageClassifierTest { ImageClassifier imageClassifier = ImageClassifier.createFromOptions(ApplicationProvider.getApplicationContext(), options); for (int i = 0; i < 3; i++) { - ImageClassificationResult results = imageClassifier.classifyForVideo(image, i); + ImageClassificationResult results = + imageClassifier.classifyForVideo(image, /*timestampMs=*/ i); assertHasOneHeadAndOneTimestamp(results, i); assertCategoriesAre( results, Arrays.asList(Category.create(0.7952058f, 934, "cheeseburger", ""))); @@ -377,9 +436,11 @@ public class ImageClassifierTest { .build(); try (ImageClassifier imageClassifier = ImageClassifier.createFromOptions(ApplicationProvider.getApplicationContext(), options)) { - imageClassifier.classifyAsync(getImageFromAsset(BURGER_IMAGE), 1); + imageClassifier.classifyAsync(getImageFromAsset(BURGER_IMAGE), /*timestampMs=*/ 1); MediaPipeException exception = - assertThrows(MediaPipeException.class, () -> imageClassifier.classifyAsync(image, 0)); + assertThrows( + MediaPipeException.class, + () -> imageClassifier.classifyAsync(image, /*timestampMs=*/ 0)); assertThat(exception) .hasMessageThat() .contains("having a smaller timestamp than the processed timestamp"); @@ -405,7 +466,7 @@ public class ImageClassifierTest { try (ImageClassifier imageClassifier = ImageClassifier.createFromOptions(ApplicationProvider.getApplicationContext(), options)) { for (int i = 0; i < 3; ++i) { - imageClassifier.classifyAsync(image, i); + imageClassifier.classifyAsync(image, /*timestampMs=*/ i); } } } diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetectorTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetectorTest.java index 91ffa9273..2878c380d 100644 --- a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetectorTest.java +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/objectdetector/ObjectDetectorTest.java @@ -29,6 +29,7 @@ import com.google.mediapipe.tasks.components.containers.Category; import com.google.mediapipe.tasks.components.containers.Detection; import com.google.mediapipe.tasks.core.BaseOptions; import com.google.mediapipe.tasks.core.TestUtils; +import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions; import com.google.mediapipe.tasks.vision.core.RunningMode; import com.google.mediapipe.tasks.vision.objectdetector.ObjectDetector.ObjectDetectorOptions; import java.io.InputStream; @@ -45,10 +46,11 @@ import org.junit.runners.Suite.SuiteClasses; public class ObjectDetectorTest { private static final String MODEL_FILE = "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite"; private static final String CAT_AND_DOG_IMAGE = "cats_and_dogs.jpg"; + private static final String CAT_AND_DOG_ROTATED_IMAGE = "cats_and_dogs_rotated.jpg"; private static final int IMAGE_WIDTH = 1200; private static final int IMAGE_HEIGHT = 600; private static final float CAT_SCORE = 0.69f; - private static final RectF catBoundingBox = new RectF(611, 164, 986, 596); + private static final RectF CAT_BOUNDING_BOX = new RectF(611, 164, 986, 596); // TODO: Figure out why android_x86 and android_arm tests have slightly different // scores (0.6875 vs 0.69921875). private static final float SCORE_DIFF_TOLERANCE = 0.01f; @@ -67,7 +69,7 @@ public class ObjectDetectorTest { ObjectDetector objectDetector = ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options); ObjectDetectionResult results = objectDetector.detect(getImageFromAsset(CAT_AND_DOG_IMAGE)); - assertContainsOnlyCat(results, catBoundingBox, CAT_SCORE); + assertContainsOnlyCat(results, CAT_BOUNDING_BOX, CAT_SCORE); } @Test @@ -104,7 +106,7 @@ public class ObjectDetectorTest { ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options); ObjectDetectionResult results = objectDetector.detect(getImageFromAsset(CAT_AND_DOG_IMAGE)); // The score threshold should block all other other objects, except cat. - assertContainsOnlyCat(results, catBoundingBox, CAT_SCORE); + assertContainsOnlyCat(results, CAT_BOUNDING_BOX, CAT_SCORE); } @Test @@ -175,7 +177,7 @@ public class ObjectDetectorTest { ObjectDetector objectDetector = ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options); ObjectDetectionResult results = objectDetector.detect(getImageFromAsset(CAT_AND_DOG_IMAGE)); - assertContainsOnlyCat(results, catBoundingBox, CAT_SCORE); + assertContainsOnlyCat(results, CAT_BOUNDING_BOX, CAT_SCORE); } @Test @@ -228,6 +230,46 @@ public class ObjectDetectorTest { .contains("`category_allowlist` and `category_denylist` are mutually exclusive options."); } + @Test + public void detect_succeedsWithRotation() throws Exception { + ObjectDetectorOptions options = + ObjectDetectorOptions.builder() + .setBaseOptions(BaseOptions.builder().setModelAssetPath(MODEL_FILE).build()) + .setMaxResults(1) + .setCategoryAllowlist(Arrays.asList("cat")) + .build(); + ObjectDetector objectDetector = + ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options); + ImageProcessingOptions imageProcessingOptions = + ImageProcessingOptions.builder().setRotationDegrees(-90).build(); + ObjectDetectionResult results = + objectDetector.detect( + getImageFromAsset(CAT_AND_DOG_ROTATED_IMAGE), imageProcessingOptions); + + assertContainsOnlyCat(results, new RectF(22.0f, 611.0f, 452.0f, 890.0f), 0.7109375f); + } + + @Test + public void detect_failsWithRegionOfInterest() throws Exception { + ObjectDetectorOptions options = + ObjectDetectorOptions.builder() + .setBaseOptions(BaseOptions.builder().setModelAssetPath(MODEL_FILE).build()) + .build(); + ObjectDetector objectDetector = + ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options); + ImageProcessingOptions imageProcessingOptions = + ImageProcessingOptions.builder().setRegionOfInterest(new RectF(0, 0, 1, 1)).build(); + IllegalArgumentException exception = + assertThrows( + IllegalArgumentException.class, + () -> + objectDetector.detect( + getImageFromAsset(CAT_AND_DOG_IMAGE), imageProcessingOptions)); + assertThat(exception) + .hasMessageThat() + .contains("ObjectDetector doesn't support region-of-interest"); + } + // TODO: Implement detect_succeedsWithFloatImages, detect_succeedsWithOrientation, // detect_succeedsWithNumThreads, detect_successWithNumThreadsFromBaseOptions, // detect_failsWithInvalidNegativeNumThreads, detect_failsWithInvalidNumThreadsAsZero. @@ -282,12 +324,16 @@ public class ObjectDetectorTest { MediaPipeException exception = assertThrows( MediaPipeException.class, - () -> objectDetector.detectForVideo(getImageFromAsset(CAT_AND_DOG_IMAGE), 0)); + () -> + objectDetector.detectForVideo( + getImageFromAsset(CAT_AND_DOG_IMAGE), /*timestampsMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the video mode"); exception = assertThrows( MediaPipeException.class, - () -> objectDetector.detectAsync(getImageFromAsset(CAT_AND_DOG_IMAGE), 0)); + () -> + objectDetector.detectAsync( + getImageFromAsset(CAT_AND_DOG_IMAGE), /*timestampsMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode"); } @@ -309,7 +355,9 @@ public class ObjectDetectorTest { exception = assertThrows( MediaPipeException.class, - () -> objectDetector.detectAsync(getImageFromAsset(CAT_AND_DOG_IMAGE), 0)); + () -> + objectDetector.detectAsync( + getImageFromAsset(CAT_AND_DOG_IMAGE), /*timestampsMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode"); } @@ -333,7 +381,9 @@ public class ObjectDetectorTest { exception = assertThrows( MediaPipeException.class, - () -> objectDetector.detectForVideo(getImageFromAsset(CAT_AND_DOG_IMAGE), 0)); + () -> + objectDetector.detectForVideo( + getImageFromAsset(CAT_AND_DOG_IMAGE), /*timestampsMs=*/ 0)); assertThat(exception).hasMessageThat().contains("not initialized with the video mode"); } @@ -348,7 +398,7 @@ public class ObjectDetectorTest { ObjectDetector objectDetector = ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options); ObjectDetectionResult results = objectDetector.detect(getImageFromAsset(CAT_AND_DOG_IMAGE)); - assertContainsOnlyCat(results, catBoundingBox, CAT_SCORE); + assertContainsOnlyCat(results, CAT_BOUNDING_BOX, CAT_SCORE); } @Test @@ -363,8 +413,9 @@ public class ObjectDetectorTest { ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options); for (int i = 0; i < 3; i++) { ObjectDetectionResult results = - objectDetector.detectForVideo(getImageFromAsset(CAT_AND_DOG_IMAGE), i); - assertContainsOnlyCat(results, catBoundingBox, CAT_SCORE); + objectDetector.detectForVideo( + getImageFromAsset(CAT_AND_DOG_IMAGE), /*timestampsMs=*/ i); + assertContainsOnlyCat(results, CAT_BOUNDING_BOX, CAT_SCORE); } } @@ -377,16 +428,18 @@ public class ObjectDetectorTest { .setRunningMode(RunningMode.LIVE_STREAM) .setResultListener( (objectDetectionResult, inputImage) -> { - assertContainsOnlyCat(objectDetectionResult, catBoundingBox, CAT_SCORE); + assertContainsOnlyCat(objectDetectionResult, CAT_BOUNDING_BOX, CAT_SCORE); assertImageSizeIsExpected(inputImage); }) .setMaxResults(1) .build(); try (ObjectDetector objectDetector = ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options)) { - objectDetector.detectAsync(image, 1); + objectDetector.detectAsync(image, /*timestampsMs=*/ 1); MediaPipeException exception = - assertThrows(MediaPipeException.class, () -> objectDetector.detectAsync(image, 0)); + assertThrows( + MediaPipeException.class, + () -> objectDetector.detectAsync(image, /*timestampsMs=*/ 0)); assertThat(exception) .hasMessageThat() .contains("having a smaller timestamp than the processed timestamp"); @@ -402,7 +455,7 @@ public class ObjectDetectorTest { .setRunningMode(RunningMode.LIVE_STREAM) .setResultListener( (objectDetectionResult, inputImage) -> { - assertContainsOnlyCat(objectDetectionResult, catBoundingBox, CAT_SCORE); + assertContainsOnlyCat(objectDetectionResult, CAT_BOUNDING_BOX, CAT_SCORE); assertImageSizeIsExpected(inputImage); }) .setMaxResults(1) @@ -410,7 +463,7 @@ public class ObjectDetectorTest { try (ObjectDetector objectDetector = ObjectDetector.createFromOptions(ApplicationProvider.getApplicationContext(), options)) { for (int i = 0; i < 3; i++) { - objectDetector.detectAsync(image, i); + objectDetector.detectAsync(image, /*timestampsMs=*/ i); } } } From 6b0a7fb281657960ac4078ae5c72617eb00fe156 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Mon, 24 Oct 2022 15:44:08 -0700 Subject: [PATCH 070/125] Reverting back to special handling for Egl Thread Exit on Android PiperOrigin-RevId: 483505151 --- mediapipe/gpu/gl_context_egl.cc | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/mediapipe/gpu/gl_context_egl.cc b/mediapipe/gpu/gl_context_egl.cc index 13710a688..78b196b08 100644 --- a/mediapipe/gpu/gl_context_egl.cc +++ b/mediapipe/gpu/gl_context_egl.cc @@ -38,13 +38,20 @@ static pthread_key_t egl_release_thread_key; static pthread_once_t egl_release_key_once = PTHREAD_ONCE_INIT; static void EglThreadExitCallback(void* key_value) { +#if defined(__ANDROID__) + eglMakeCurrent(EGL_NO_DISPLAY, EGL_NO_SURFACE, EGL_NO_SURFACE, + EGL_NO_CONTEXT); +#else // Some implementations have chosen to allow EGL_NO_DISPLAY as a valid display // parameter for eglMakeCurrent. This behavior is not portable to all EGL // implementations, and should be considered as an undocumented vendor // extension. // https://www.khronos.org/registry/EGL/sdk/docs/man/html/eglMakeCurrent.xhtml + // + // NOTE: crashes on some Android devices (occurs with libGLES_meow.so). eglMakeCurrent(eglGetDisplay(EGL_DEFAULT_DISPLAY), EGL_NO_SURFACE, EGL_NO_SURFACE, EGL_NO_CONTEXT); +#endif eglReleaseThread(); } From 18eb089d39356ade117fbc629c5e19bef35f2d22 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 25 Oct 2022 07:38:04 -0700 Subject: [PATCH 071/125] Added a simple test to verify gesture recognition results --- .../tasks/python/components/containers/BUILD | 6 +- .../components/containers/classification.py | 19 ++- .../python/components/containers/gesture.py | 138 ------------------ .../containers/landmark_detection_result.py | 82 +++++++++++ mediapipe/tasks/python/test/vision/BUILD | 6 +- .../test/vision/gesture_recognizer_test.py | 85 ++++++++++- .../tasks/python/vision/gesture_recognizer.py | 15 +- mediapipe/tasks/testdata/vision/BUILD | 1 + 8 files changed, 184 insertions(+), 168 deletions(-) delete mode 100644 mediapipe/tasks/python/components/containers/gesture.py create mode 100644 mediapipe/tasks/python/components/containers/landmark_detection_result.py diff --git a/mediapipe/tasks/python/components/containers/BUILD b/mediapipe/tasks/python/components/containers/BUILD index 325dff5fc..8aaa64cc9 100644 --- a/mediapipe/tasks/python/components/containers/BUILD +++ b/mediapipe/tasks/python/components/containers/BUILD @@ -55,11 +55,13 @@ py_library( ) py_library( - name = "gesture", - srcs = ["gesture.py"], + name = "landmark_detection_result", + srcs = ["landmark_detection_result.py"], deps = [ + ":rect", ":classification", ":landmark", + "//mediapipe/tasks/cc/components/containers/proto:landmarks_detection_result_py_pb2", "//mediapipe/tasks/python/core:optional_dependencies", ], ) diff --git a/mediapipe/tasks/python/components/containers/classification.py b/mediapipe/tasks/python/components/containers/classification.py index 157c34528..465e2dd28 100644 --- a/mediapipe/tasks/python/components/containers/classification.py +++ b/mediapipe/tasks/python/components/containers/classification.py @@ -14,14 +14,13 @@ """Classification data class.""" import dataclasses -from typing import Any, List +from typing import Any, List, Optional from mediapipe.framework.formats import classification_pb2 from mediapipe.tasks.python.core.optional_dependencies import doc_controls _ClassificationProto = classification_pb2.Classification _ClassificationListProto = classification_pb2.ClassificationList -_ClassificationListCollectionProto = classification_pb2.ClassificationListCollection @dataclasses.dataclass @@ -35,10 +34,10 @@ class Classification: display_name: Optional human-readable string for display purposes. """ - index: int - score: float - label_name: str - display_name: str + index: Optional[int] = None + score: Optional[float] = None + label: Optional[str] = None + display_name: Optional[str] = None @doc_controls.do_not_generate_docs def to_pb2(self) -> _ClassificationProto: @@ -46,7 +45,7 @@ class Classification: return _ClassificationProto( index=self.index, score=self.score, - label_name=self.label_name, + label=self.label, display_name=self.display_name) @classmethod @@ -56,7 +55,7 @@ class Classification: return Classification( index=pb2_obj.index, score=pb2_obj.score, - label_name=pb2_obj.label_name, + label=pb2_obj.label, display_name=pb2_obj.display_name) def __eq__(self, other: Any) -> bool: @@ -86,8 +85,8 @@ class ClassificationList: """ classifications: List[Classification] - tensor_index: int - tensor_name: str + tensor_index: Optional[int] = None + tensor_name: Optional[str] = None @doc_controls.do_not_generate_docs def to_pb2(self) -> _ClassificationListProto: diff --git a/mediapipe/tasks/python/components/containers/gesture.py b/mediapipe/tasks/python/components/containers/gesture.py deleted file mode 100644 index f314d18bd..000000000 --- a/mediapipe/tasks/python/components/containers/gesture.py +++ /dev/null @@ -1,138 +0,0 @@ -# Copyright 2022 The MediaPipe Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -"""Gesture data class.""" - -import dataclasses -from typing import Any, List - -from mediapipe.tasks.python.components.containers import classification -from mediapipe.tasks.python.components.containers import landmark -from mediapipe.tasks.python.core.optional_dependencies import doc_controls - - -@dataclasses.dataclass -class GestureRecognitionResult: - """ The gesture recognition result from GestureRecognizer, where each vector - element represents a single hand detected in the image. - - Attributes: - gestures: Recognized hand gestures with sorted order such that the - winning label is the first item in the list. - handedness: Classification of handedness. - hand_landmarks: Detected hand landmarks in normalized image coordinates. - hand_world_landmarks: Detected hand landmarks in world coordinates. - """ - - gestures: List[classification.ClassificationList] - handedness: List[classification.ClassificationList] - hand_landmarks: List[landmark.NormalizedLandmarkList] - hand_world_landmarks: List[landmark.LandmarkList] - - @doc_controls.do_not_generate_docs - def to_pb2(self) -> _DetectionProto: - """Generates a Detection protobuf object.""" - labels = [] - label_ids = [] - scores = [] - display_names = [] - for category in self.categories: - scores.append(category.score) - if category.index: - label_ids.append(category.index) - if category.category_name: - labels.append(category.category_name) - if category.display_name: - display_names.append(category.display_name) - return _DetectionProto( - label=labels, - label_id=label_ids, - score=scores, - display_name=display_names, - location_data=_LocationDataProto( - format=_LocationDataProto.Format.BOUNDING_BOX, - bounding_box=self.bounding_box.to_pb2())) - - @classmethod - @doc_controls.do_not_generate_docs - def create_from_pb2(cls, pb2_obj: _DetectionProto) -> 'Detection': - """Creates a `Detection` object from the given protobuf object.""" - categories = [] - for idx, score in enumerate(pb2_obj.score): - categories.append( - category_module.Category( - score=score, - index=pb2_obj.label_id[idx] - if idx < len(pb2_obj.label_id) else None, - category_name=pb2_obj.label[idx] - if idx < len(pb2_obj.label) else None, - display_name=pb2_obj.display_name[idx] - if idx < len(pb2_obj.display_name) else None)) - - return Detection( - bounding_box=bounding_box_module.BoundingBox.create_from_pb2( - pb2_obj.location_data.bounding_box), - categories=categories) - - def __eq__(self, other: Any) -> bool: - """Checks if this object is equal to the given object. - - Args: - other: The object to be compared with. - - Returns: - True if the objects are equal. - """ - if not isinstance(other, Detection): - return False - - return self.to_pb2().__eq__(other.to_pb2()) - - -@dataclasses.dataclass -class DetectionResult: - """Represents the list of detected objects. - - Attributes: - detections: A list of `Detection` objects. - """ - - detections: List[Detection] - - @doc_controls.do_not_generate_docs - def to_pb2(self) -> _DetectionListProto: - """Generates a DetectionList protobuf object.""" - return _DetectionListProto( - detection=[detection.to_pb2() for detection in self.detections]) - - @classmethod - @doc_controls.do_not_generate_docs - def create_from_pb2(cls, pb2_obj: _DetectionListProto) -> 'DetectionResult': - """Creates a `DetectionResult` object from the given protobuf object.""" - return DetectionResult(detections=[ - Detection.create_from_pb2(detection) for detection in pb2_obj.detection - ]) - - def __eq__(self, other: Any) -> bool: - """Checks if this object is equal to the given object. - - Args: - other: The object to be compared with. - - Returns: - True if the objects are equal. - """ - if not isinstance(other, DetectionResult): - return False - - return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/components/containers/landmark_detection_result.py b/mediapipe/tasks/python/components/containers/landmark_detection_result.py new file mode 100644 index 000000000..c3d93d414 --- /dev/null +++ b/mediapipe/tasks/python/components/containers/landmark_detection_result.py @@ -0,0 +1,82 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Landmark Detection Result data class.""" + +import dataclasses +from typing import Any, Optional + +from mediapipe.tasks.cc.components.containers.proto import landmarks_detection_result_pb2 +from mediapipe.tasks.python.components.containers import rect as rect_module +from mediapipe.tasks.python.components.containers import classification as classification_module +from mediapipe.tasks.python.components.containers import landmark as landmark_module +from mediapipe.tasks.python.core.optional_dependencies import doc_controls + +_LandmarksDetectionResultProto = landmarks_detection_result_pb2.LandmarksDetectionResult +_NormalizedRect = rect_module.NormalizedRect +_ClassificationList = classification_module.ClassificationList +_NormalizedLandmarkList = landmark_module.NormalizedLandmarkList +_LandmarkList = landmark_module.LandmarkList + + +@dataclasses.dataclass +class LandmarksDetectionResult: + """Represents the landmarks detection result. + + Attributes: + landmarks : A `NormalizedLandmarkList` object. + classifications : A `ClassificationList` object. + world_landmarks : A `LandmarkList` object. + rect : A `NormalizedRect` object. + """ + + landmarks: Optional[_NormalizedLandmarkList] + classifications: Optional[_ClassificationList] + world_landmarks: Optional[_LandmarkList] + rect: _NormalizedRect + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _LandmarksDetectionResultProto: + """Generates a LandmarksDetectionResult protobuf object.""" + return _LandmarksDetectionResultProto( + landmarks=self.landmarks.to_pb2(), + classifications=self.classifications.to_pb2(), + world_landmarks=self.world_landmarks.to_pb2(), + rect=self.rect.to_pb2()) + + @classmethod + @doc_controls.do_not_generate_docs + def create_from_pb2( + cls, + pb2_obj: _LandmarksDetectionResultProto + ) -> 'LandmarksDetectionResult': + """Creates a `LandmarksDetectionResult` object from the given protobuf + object.""" + return LandmarksDetectionResult( + landmarks=_NormalizedLandmarkList.create_from_pb2(pb2_obj.landmarks), + classifications=_ClassificationList.create_from_pb2( + pb2_obj.classifications), + world_landmarks=_LandmarkList.create_from_pb2(pb2_obj.world_landmarks), + rect=_NormalizedRect.create_from_pb2(pb2_obj.rect)) + + def __eq__(self, other: Any) -> bool: + """Checks if this object is equal to the given object. + Args: + other: The object to be compared with. + Returns: + True if the objects are equal. + """ + if not isinstance(other, LandmarksDetectionResult): + return False + + return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 0dd83edcf..0d8b99984 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -43,15 +43,19 @@ py_test( data = [ "//mediapipe/tasks/testdata/vision:test_images", "//mediapipe/tasks/testdata/vision:test_models", + "//mediapipe/tasks/testdata/vision:test_protos", ], deps = [ "//mediapipe/python:_framework_bindings", + "//mediapipe/tasks/cc/components/containers/proto:landmarks_detection_result_py_pb2", + "//mediapipe/tasks/python/components/containers:rect", "//mediapipe/tasks/python/components/containers:classification", "//mediapipe/tasks/python/components/containers:landmark", - "//mediapipe/tasks/python/components/containers:rect", + "//mediapipe/tasks/python/components/containers:landmark_detection_result", "//mediapipe/tasks/python/core:base_options", "//mediapipe/tasks/python/test:test_utils", "//mediapipe/tasks/python/vision:gesture_recognizer", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + "@com_google_protobuf//:protobuf_python" ], ) diff --git a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py index 288cfd1f5..7d731d805 100644 --- a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py +++ b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py @@ -15,23 +15,31 @@ import enum +from google.protobuf import text_format from absl.testing import absltest from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module +from mediapipe.tasks.cc.components.containers.proto import landmarks_detection_result_pb2 from mediapipe.tasks.python.components.containers import rect as rect_module from mediapipe.tasks.python.components.containers import classification as classification_module from mediapipe.tasks.python.components.containers import landmark as landmark_module +from mediapipe.tasks.python.components.containers import landmark_detection_result as landmark_detection_result_module from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_utils from mediapipe.tasks.python.vision import gesture_recognizer from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module +_LandmarksDetectionResultProto = landmarks_detection_result_pb2.LandmarksDetectionResult _BaseOptions = base_options_module.BaseOptions _NormalizedRect = rect_module.NormalizedRect +_Classification = classification_module.Classification _ClassificationList = classification_module.ClassificationList +_Landmark = landmark_module.Landmark _LandmarkList = landmark_module.LandmarkList +_NormalizedLandmark = landmark_module.NormalizedLandmark _NormalizedLandmarkList = landmark_module.NormalizedLandmarkList +_LandmarksDetectionResult = landmark_detection_result_module.LandmarksDetectionResult _Image = image_module.Image _GestureRecognizer = gesture_recognizer.GestureRecognizer _GestureRecognizerOptions = gesture_recognizer.GestureRecognizerOptions @@ -39,8 +47,35 @@ _GestureRecognitionResult = gesture_recognizer.GestureRecognitionResult _RUNNING_MODE = running_mode_module.VisionTaskRunningMode _GESTURE_RECOGNIZER_MODEL_FILE = 'gesture_recognizer.task' -_IMAGE_FILE = 'right_hands.jpg' -_EXPECTED_DETECTION_RESULT = _GestureRecognitionResult([], [], [], []) +_THUMB_UP_IMAGE = 'thumb_up.jpg' +_THUMB_UP_LANDMARKS = "thumb_up_landmarks.pbtxt" +_THUMB_UP_LABEL = "Thumb_Up" +_THUMB_UP_INDEX = 5 +_LANDMARKS_ERROR_TOLERANCE = 0.03 + + +def _get_expected_gesture_recognition_result( + file_path: str, gesture_label: str, gesture_index: int +) -> _GestureRecognitionResult: + landmarks_detection_result_file_path = test_utils.get_test_data_path( + file_path) + with open(landmarks_detection_result_file_path, "rb") as f: + landmarks_detection_result_proto = _LandmarksDetectionResultProto() + # # Use this if a .pb file is available. + # landmarks_detection_result_proto.ParseFromString(f.read()) + text_format.Parse(f.read(), landmarks_detection_result_proto) + landmarks_detection_result = _LandmarksDetectionResult.create_from_pb2( + landmarks_detection_result_proto) + gesture = _ClassificationList( + classifications=[ + _Classification(label=gesture_label, index=gesture_index, + display_name='') + ], tensor_index=0, tensor_name='') + return _GestureRecognitionResult( + gestures=[gesture], + handedness=[landmarks_detection_result.classifications], + hand_landmarks=[landmarks_detection_result.landmarks], + hand_world_landmarks=[landmarks_detection_result.world_landmarks]) class ModelFileType(enum.Enum): @@ -53,14 +88,45 @@ class GestureRecognizerTest(parameterized.TestCase): def setUp(self): super().setUp() self.test_image = _Image.create_from_file( - test_utils.get_test_data_path(_IMAGE_FILE)) + test_utils.get_test_data_path(_THUMB_UP_IMAGE)) self.gesture_recognizer_model_path = test_utils.get_test_data_path( _GESTURE_RECOGNIZER_MODEL_FILE) + def _assert_actual_result_approximately_matches_expected_result( + self, + actual_result: _GestureRecognitionResult, + expected_result: _GestureRecognitionResult + ): + # Expects to have the same number of hands detected. + self.assertLen(actual_result.hand_landmarks, + len(expected_result.hand_landmarks)) + self.assertLen(actual_result.hand_world_landmarks, + len(expected_result.hand_world_landmarks)) + self.assertLen(actual_result.handedness, len(expected_result.handedness)) + self.assertLen(actual_result.gestures, len(expected_result.gestures)) + # Actual landmarks match expected landmarks. + self.assertEqual(actual_result.hand_landmarks, + expected_result.hand_landmarks) + # Actual handedness matches expected handedness. + actual_top_handedness = actual_result.handedness[0].classifications[0] + expected_top_handedness = expected_result.handedness[0].classifications[0] + self.assertEqual(actual_top_handedness.index, expected_top_handedness.index) + self.assertEqual(actual_top_handedness.label, expected_top_handedness.label) + # Actual gesture with top score matches expected gesture. + actual_top_gesture = actual_result.gestures[0].classifications[0] + expected_top_gesture = expected_result.gestures[0].classifications[0] + self.assertEqual(actual_top_gesture.index, expected_top_gesture.index) + self.assertEqual(actual_top_gesture.label, expected_top_gesture.label) + @parameterized.parameters( - (ModelFileType.FILE_NAME, _EXPECTED_DETECTION_RESULT), - (ModelFileType.FILE_CONTENT, _EXPECTED_DETECTION_RESULT)) - def test_recognize(self, model_file_type, expected_recognition_result): + (ModelFileType.FILE_NAME, 0.3, _get_expected_gesture_recognition_result( + _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX + )), + (ModelFileType.FILE_CONTENT, 0.3, _get_expected_gesture_recognition_result( + _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX + ))) + def test_recognize(self, model_file_type, min_gesture_confidence, + expected_recognition_result): # Creates gesture recognizer. if model_file_type is ModelFileType.FILE_NAME: gesture_recognizer_base_options = _BaseOptions( @@ -75,13 +141,16 @@ class GestureRecognizerTest(parameterized.TestCase): raise ValueError('model_file_type is invalid.') options = _GestureRecognizerOptions( - base_options=gesture_recognizer_base_options) + base_options=gesture_recognizer_base_options, + min_gesture_confidence=min_gesture_confidence + ) recognizer = _GestureRecognizer.create_from_options(options) # Performs hand gesture recognition on the input. recognition_result = recognizer.recognize(self.test_image) # Comparing results. - self.assertEqual(recognition_result, expected_recognition_result) + self._assert_actual_result_approximately_matches_expected_result( + recognition_result, expected_recognition_result) # Closes the gesture recognizer explicitly when the detector is not used in # a context. recognizer.close() diff --git a/mediapipe/tasks/python/vision/gesture_recognizer.py b/mediapipe/tasks/python/vision/gesture_recognizer.py index aca7a5277..c00508b36 100644 --- a/mediapipe/tasks/python/vision/gesture_recognizer.py +++ b/mediapipe/tasks/python/vision/gesture_recognizer.py @@ -136,8 +136,6 @@ class GestureRecognizerOptions: """Generates an GestureRecognizerOptions protobuf object.""" base_options_proto = self.base_options.to_pb2() base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True - # hand_landmark_detector_base_options_proto = self.hand_landmark_detector_base_options.to_pb2() - # hand_landmark_detector_base_options_proto.use_stream_mode = False if self.running_mode == _RunningMode.IMAGE else True # Configure hand detector options. hand_detector_options_proto = _HandDetectorGraphOptionsProto( @@ -153,13 +151,12 @@ class GestureRecognizerOptions: min_tracking_confidence=self.min_tracking_confidence) # Configure hand gesture recognizer options. - hand_gesture_recognizer_options_proto = _HandGestureRecognizerGraphOptionsProto() - if self.min_gesture_confidence >= 0: - classifier_options = _ClassifierOptions( - score_threshold=self.min_gesture_confidence) - hand_gesture_recognizer_options_proto.canned_gesture_classifier_graph_options = \ - _GestureClassifierGraphOptionsProto( - classifier_options=classifier_options.to_pb2()) + classifier_options = _ClassifierOptions( + score_threshold=self.min_gesture_confidence) + gesture_classifier_options = _GestureClassifierGraphOptionsProto( + classifier_options=classifier_options.to_pb2()) + hand_gesture_recognizer_options_proto = _HandGestureRecognizerGraphOptionsProto( + canned_gesture_classifier_graph_options=gesture_classifier_options) return _GestureRecognizerGraphOptionsProto( base_options=base_options_proto, diff --git a/mediapipe/tasks/testdata/vision/BUILD b/mediapipe/tasks/testdata/vision/BUILD index ebb8f05a6..365921bc1 100644 --- a/mediapipe/tasks/testdata/vision/BUILD +++ b/mediapipe/tasks/testdata/vision/BUILD @@ -121,6 +121,7 @@ filegroup( "hand_landmark_full.tflite", "hand_landmark_lite.tflite", "hand_landmarker.task", + "gesture_recognizer.task", "mobilenet_v1_0.25_192_quantized_1_default_1.tflite", "mobilenet_v1_0.25_224_1_default_1.tflite", "mobilenet_v1_0.25_224_1_metadata_1.tflite", From d240c009e2afa2849836498d129eca6e0d78f637 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Tue, 25 Oct 2022 08:20:42 -0700 Subject: [PATCH 072/125] Remove unnecessary location_data_proto dependency on rect_proto. PiperOrigin-RevId: 483679555 --- mediapipe/framework/formats/BUILD | 1 - 1 file changed, 1 deletion(-) diff --git a/mediapipe/framework/formats/BUILD b/mediapipe/framework/formats/BUILD index b967b27fb..c3241d911 100644 --- a/mediapipe/framework/formats/BUILD +++ b/mediapipe/framework/formats/BUILD @@ -293,7 +293,6 @@ mediapipe_proto_library( name = "rect_proto", srcs = ["rect.proto"], visibility = ["//visibility:public"], - deps = ["//mediapipe/framework/formats:location_data_proto"], ) mediapipe_register_type( From 8762d15c81ee201188cfc482f0bbcc8b18ec0530 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 25 Oct 2022 11:11:15 -0700 Subject: [PATCH 073/125] Added remaining tests for the GestureRecognizer Python MediaPipe Tasks API --- .../containers/landmark_detection_result.py | 2 +- mediapipe/tasks/python/test/vision/BUILD | 1 + .../test/vision/gesture_recognizer_test.py | 311 ++++++++++++++++-- mediapipe/tasks/python/vision/BUILD | 1 - mediapipe/tasks/python/vision/core/BUILD | 9 + .../vision/core/base_vision_task_api.py | 49 +++ .../vision/core/image_processing_options.py | 39 +++ .../tasks/python/vision/gesture_recognizer.py | 44 +-- 8 files changed, 414 insertions(+), 42 deletions(-) create mode 100644 mediapipe/tasks/python/vision/core/image_processing_options.py diff --git a/mediapipe/tasks/python/components/containers/landmark_detection_result.py b/mediapipe/tasks/python/components/containers/landmark_detection_result.py index c3d93d414..02ca5a918 100644 --- a/mediapipe/tasks/python/components/containers/landmark_detection_result.py +++ b/mediapipe/tasks/python/components/containers/landmark_detection_result.py @@ -11,7 +11,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. -"""Landmark Detection Result data class.""" +"""Landmarks Detection Result data class.""" import dataclasses from typing import Any, Optional diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 0d8b99984..6455d7fcf 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -56,6 +56,7 @@ py_test( "//mediapipe/tasks/python/test:test_utils", "//mediapipe/tasks/python/vision:gesture_recognizer", "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + "//mediapipe/tasks/python/vision/core:image_processing_options", "@com_google_protobuf//:protobuf_python" ], ) diff --git a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py index 7d731d805..a8316c528 100644 --- a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py +++ b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py @@ -14,7 +14,9 @@ """Tests for gesture recognizer.""" import enum +from unittest import mock +import numpy as np from google.protobuf import text_format from absl.testing import absltest from absl.testing import parameterized @@ -29,10 +31,11 @@ from mediapipe.tasks.python.core import base_options as base_options_module from mediapipe.tasks.python.test import test_utils from mediapipe.tasks.python.vision import gesture_recognizer from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module +from mediapipe.tasks.python.vision.core import image_processing_options as image_processing_options_module _LandmarksDetectionResultProto = landmarks_detection_result_pb2.LandmarksDetectionResult _BaseOptions = base_options_module.BaseOptions -_NormalizedRect = rect_module.NormalizedRect +_Rect = rect_module.Rect _Classification = classification_module.Classification _ClassificationList = classification_module.ClassificationList _Landmark = landmark_module.Landmark @@ -45,12 +48,19 @@ _GestureRecognizer = gesture_recognizer.GestureRecognizer _GestureRecognizerOptions = gesture_recognizer.GestureRecognizerOptions _GestureRecognitionResult = gesture_recognizer.GestureRecognitionResult _RUNNING_MODE = running_mode_module.VisionTaskRunningMode +_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions _GESTURE_RECOGNIZER_MODEL_FILE = 'gesture_recognizer.task' +_NO_HANDS_IMAGE = 'cats_and_dogs.jpg' +_TWO_HANDS_IMAGE = 'right_hands.jpg' _THUMB_UP_IMAGE = 'thumb_up.jpg' -_THUMB_UP_LANDMARKS = "thumb_up_landmarks.pbtxt" -_THUMB_UP_LABEL = "Thumb_Up" +_THUMB_UP_LANDMARKS = 'thumb_up_landmarks.pbtxt' +_THUMB_UP_LABEL = 'Thumb_Up' _THUMB_UP_INDEX = 5 +_POINTING_UP_ROTATED_IMAGE = 'pointing_up_rotated.jpg' +_POINTING_UP_LANDMARKS = 'pointing_up_rotated_landmarks.pbtxt' +_POINTING_UP_LABEL = 'Pointing_Up' +_POINTING_UP_INDEX = 3 _LANDMARKS_ERROR_TOLERANCE = 0.03 @@ -89,7 +99,7 @@ class GestureRecognizerTest(parameterized.TestCase): super().setUp() self.test_image = _Image.create_from_file( test_utils.get_test_data_path(_THUMB_UP_IMAGE)) - self.gesture_recognizer_model_path = test_utils.get_test_data_path( + self.model_path = test_utils.get_test_data_path( _GESTURE_RECOGNIZER_MODEL_FILE) def _assert_actual_result_approximately_matches_expected_result( @@ -105,8 +115,15 @@ class GestureRecognizerTest(parameterized.TestCase): self.assertLen(actual_result.handedness, len(expected_result.handedness)) self.assertLen(actual_result.gestures, len(expected_result.gestures)) # Actual landmarks match expected landmarks. - self.assertEqual(actual_result.hand_landmarks, - expected_result.hand_landmarks) + self.assertLen(actual_result.hand_landmarks[0].landmarks, + len(expected_result.hand_landmarks[0].landmarks)) + actual_landmarks = actual_result.hand_landmarks[0].landmarks + expected_landmarks = expected_result.hand_landmarks[0].landmarks + for i in range(len(actual_landmarks)): + self.assertAlmostEqual(actual_landmarks[i].x, expected_landmarks[i].x, + delta=_LANDMARKS_ERROR_TOLERANCE) + self.assertAlmostEqual(actual_landmarks[i].y, expected_landmarks[i].y, + delta=_LANDMARKS_ERROR_TOLERANCE) # Actual handedness matches expected handedness. actual_top_handedness = actual_result.handedness[0].classifications[0] expected_top_handedness = expected_result.handedness[0].classifications[0] @@ -118,32 +135,56 @@ class GestureRecognizerTest(parameterized.TestCase): self.assertEqual(actual_top_gesture.index, expected_top_gesture.index) self.assertEqual(actual_top_gesture.label, expected_top_gesture.label) + def test_create_from_file_succeeds_with_valid_model_path(self): + # Creates with default option and valid model file successfully. + with _GestureRecognizer.create_from_model_path(self.model_path) as recognizer: + self.assertIsInstance(recognizer, _GestureRecognizer) + + def test_create_from_options_succeeds_with_valid_model_path(self): + # Creates with options containing model file successfully. + base_options = _BaseOptions(model_asset_path=self.model_path) + options = _GestureRecognizerOptions(base_options=base_options) + with _GestureRecognizer.create_from_options(options) as recognizer: + self.assertIsInstance(recognizer, _GestureRecognizer) + + def test_create_from_options_fails_with_invalid_model_path(self): + # Invalid empty model path. + with self.assertRaisesRegex( + ValueError, + r"ExternalFile must specify at least one of 'file_content', " + r"'file_name', 'file_pointer_meta' or 'file_descriptor_meta'."): + base_options = _BaseOptions(model_asset_path='') + options = _GestureRecognizerOptions(base_options=base_options) + _GestureRecognizer.create_from_options(options) + + def test_create_from_options_succeeds_with_valid_model_content(self): + # Creates with options containing model content successfully. + with open(self.model_path, 'rb') as f: + base_options = _BaseOptions(model_asset_buffer=f.read()) + options = _GestureRecognizerOptions(base_options=base_options) + recognizer = _GestureRecognizer.create_from_options(options) + self.assertIsInstance(recognizer, _GestureRecognizer) + @parameterized.parameters( - (ModelFileType.FILE_NAME, 0.3, _get_expected_gesture_recognition_result( + (ModelFileType.FILE_NAME, _get_expected_gesture_recognition_result( _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX )), - (ModelFileType.FILE_CONTENT, 0.3, _get_expected_gesture_recognition_result( + (ModelFileType.FILE_CONTENT, _get_expected_gesture_recognition_result( _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX ))) - def test_recognize(self, model_file_type, min_gesture_confidence, - expected_recognition_result): + def test_recognize(self, model_file_type, expected_recognition_result): # Creates gesture recognizer. if model_file_type is ModelFileType.FILE_NAME: - gesture_recognizer_base_options = _BaseOptions( - model_asset_path=self.gesture_recognizer_model_path) + base_options = _BaseOptions(model_asset_path=self.model_path) elif model_file_type is ModelFileType.FILE_CONTENT: - with open(self.gesture_recognizer_model_path, 'rb') as f: + with open(self.model_path, 'rb') as f: model_content = f.read() - gesture_recognizer_base_options = _BaseOptions( - model_asset_buffer=model_content) + base_options = _BaseOptions(model_asset_buffer=model_content) else: # Should never happen raise ValueError('model_file_type is invalid.') - options = _GestureRecognizerOptions( - base_options=gesture_recognizer_base_options, - min_gesture_confidence=min_gesture_confidence - ) + options = _GestureRecognizerOptions(base_options=base_options) recognizer = _GestureRecognizer.create_from_options(options) # Performs hand gesture recognition on the input. @@ -151,10 +192,238 @@ class GestureRecognizerTest(parameterized.TestCase): # Comparing results. self._assert_actual_result_approximately_matches_expected_result( recognition_result, expected_recognition_result) - # Closes the gesture recognizer explicitly when the detector is not used in - # a context. + # Closes the gesture recognizer explicitly when the gesture recognizer is + # not used in a context. recognizer.close() + @parameterized.parameters( + (ModelFileType.FILE_NAME, _get_expected_gesture_recognition_result( + _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX + )), + (ModelFileType.FILE_CONTENT, _get_expected_gesture_recognition_result( + _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX + ))) + def test_recognize_in_context(self, model_file_type, + expected_recognition_result): + # Creates gesture recognizer. + if model_file_type is ModelFileType.FILE_NAME: + base_options = _BaseOptions(model_asset_path=self.model_path) + elif model_file_type is ModelFileType.FILE_CONTENT: + with open(self.model_path, 'rb') as f: + model_content = f.read() + base_options = _BaseOptions(model_asset_buffer=model_content) + else: + # Should never happen + raise ValueError('model_file_type is invalid.') + + options = _GestureRecognizerOptions(base_options=base_options) + with _GestureRecognizer.create_from_options(options) as recognizer: + # Performs hand gesture recognition on the input. + recognition_result = recognizer.recognize(self.test_image) + # Comparing results. + self._assert_actual_result_approximately_matches_expected_result( + recognition_result, expected_recognition_result) + + def test_recognize_succeeds_with_num_hands(self): + # Creates gesture recognizer. + base_options = _BaseOptions(model_asset_path=self.model_path) + options = _GestureRecognizerOptions(base_options=base_options, num_hands=2) + with _GestureRecognizer.create_from_options(options) as recognizer: + # Load the pointing up rotated image. + test_image = _Image.create_from_file( + test_utils.get_test_data_path(_TWO_HANDS_IMAGE)) + # Performs hand gesture recognition on the input. + recognition_result = recognizer.recognize(test_image) + # Comparing results. + self.assertLen(recognition_result.handedness, 2) + + def test_recognize_succeeds_with_rotation(self): + # Creates gesture recognizer. + base_options = _BaseOptions(model_asset_path=self.model_path) + options = _GestureRecognizerOptions(base_options=base_options, num_hands=1) + with _GestureRecognizer.create_from_options(options) as recognizer: + # Load the pointing up rotated image. + test_image = _Image.create_from_file( + test_utils.get_test_data_path(_POINTING_UP_ROTATED_IMAGE)) + # Set rotation parameters using ImageProcessingOptions. + image_processing_options = _ImageProcessingOptions(rotation_degrees=-90) + # Performs hand gesture recognition on the input. + recognition_result = recognizer.recognize(test_image, + image_processing_options) + expected_recognition_result = _get_expected_gesture_recognition_result( + _POINTING_UP_LANDMARKS, _POINTING_UP_LABEL, _POINTING_UP_INDEX) + # Comparing results. + self._assert_actual_result_approximately_matches_expected_result( + recognition_result, expected_recognition_result) + + def test_recognize_fails_with_region_of_interest(self): + # Creates gesture recognizer. + base_options = _BaseOptions(model_asset_path=self.model_path) + options = _GestureRecognizerOptions(base_options=base_options, num_hands=1) + with self.assertRaisesRegex( + ValueError, "This task doesn't support region-of-interest."): + with _GestureRecognizer.create_from_options(options) as recognizer: + # Set the `region_of_interest` parameter using `ImageProcessingOptions`. + image_processing_options = _ImageProcessingOptions( + region_of_interest=_Rect(0, 0, 1, 1)) + # Attempt to perform hand gesture recognition on the cropped input. + recognizer.recognize(self.test_image, image_processing_options) + + def test_empty_recognition_outputs(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path)) + with _GestureRecognizer.create_from_options(options) as recognizer: + # Load the image with no hands. + no_hands_test_image = _Image.create_from_file( + test_utils.get_test_data_path(_NO_HANDS_IMAGE)) + # Performs gesture recognition on the input. + recognition_result = recognizer.recognize(no_hands_test_image) + self.assertEmpty(recognition_result.hand_landmarks) + self.assertEmpty(recognition_result.hand_world_landmarks) + self.assertEmpty(recognition_result.handedness) + self.assertEmpty(recognition_result.gestures) + + def test_missing_result_callback(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM) + with self.assertRaisesRegex(ValueError, + r'result callback must be provided'): + with _GestureRecognizer.create_from_options(options) as unused_recognizer: + pass + + @parameterized.parameters((_RUNNING_MODE.IMAGE), (_RUNNING_MODE.VIDEO)) + def test_illegal_result_callback(self, running_mode): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=running_mode, + result_callback=mock.MagicMock()) + with self.assertRaisesRegex(ValueError, + r'result callback should not be provided'): + with _GestureRecognizer.create_from_options(options) as unused_recognizer: + pass + + def test_calling_recognize_for_video_in_image_mode(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.IMAGE) + with _GestureRecognizer.create_from_options(options) as recognizer: + with self.assertRaisesRegex(ValueError, + r'not initialized with the video mode'): + recognizer.recognize_for_video(self.test_image, 0) + + def test_calling_recognize_async_in_image_mode(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.IMAGE) + with _GestureRecognizer.create_from_options(options) as recognizer: + with self.assertRaisesRegex(ValueError, + r'not initialized with the live stream mode'): + recognizer.recognize_async(self.test_image, 0) + + def test_calling_recognize_in_video_mode(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _GestureRecognizer.create_from_options(options) as recognizer: + with self.assertRaisesRegex(ValueError, + r'not initialized with the image mode'): + recognizer.recognize(self.test_image) + + def test_calling_recognize_async_in_video_mode(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _GestureRecognizer.create_from_options(options) as recognizer: + with self.assertRaisesRegex(ValueError, + r'not initialized with the live stream mode'): + recognizer.recognize_async(self.test_image, 0) + + def test_recognize_for_video_with_out_of_order_timestamp(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _GestureRecognizer.create_from_options(options) as recognizer: + unused_result = recognizer.recognize_for_video(self.test_image, 1) + with self.assertRaisesRegex( + ValueError, r'Input timestamp must be monotonically increasing'): + recognizer.recognize_for_video(self.test_image, 0) + + def test_recognize_for_video(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.VIDEO) + with _GestureRecognizer.create_from_options(options) as recognizer: + for timestamp in range(0, 300, 30): + recognition_result = recognizer.recognize_for_video(self.test_image, + timestamp) + expected_recognition_result = _get_expected_gesture_recognition_result( + _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX) + self._assert_actual_result_approximately_matches_expected_result( + recognition_result, expected_recognition_result) + + def test_calling_recognize_in_live_stream_mode(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=mock.MagicMock()) + with _GestureRecognizer.create_from_options(options) as recognizer: + with self.assertRaisesRegex(ValueError, + r'not initialized with the image mode'): + recognizer.recognize(self.test_image) + + def test_calling_recognize_for_video_in_live_stream_mode(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=mock.MagicMock()) + with _GestureRecognizer.create_from_options(options) as recognizer: + with self.assertRaisesRegex(ValueError, + r'not initialized with the video mode'): + recognizer.recognize_for_video(self.test_image, 0) + + def test_recognize_async_calls_with_illegal_timestamp(self): + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=mock.MagicMock()) + with _GestureRecognizer.create_from_options(options) as recognizer: + recognizer.recognize_async(self.test_image, 100) + with self.assertRaisesRegex( + ValueError, r'Input timestamp must be monotonically increasing'): + recognizer.recognize_async(self.test_image, 0) + + @parameterized.parameters( + (_THUMB_UP_IMAGE, _get_expected_gesture_recognition_result( + _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX)), + (_NO_HANDS_IMAGE, _GestureRecognitionResult([], [], [], []))) + def test_recognize_async_calls(self, image_path, expected_result): + test_image = _Image.create_from_file( + test_utils.get_test_data_path(image_path)) + observed_timestamp_ms = -1 + + def check_result(result: _GestureRecognitionResult, output_image: _Image, + timestamp_ms: int): + if result.hand_landmarks and result.hand_world_landmarks and \ + result.handedness and result.gestures: + self._assert_actual_result_approximately_matches_expected_result( + result, expected_result) + else: + self.assertEqual(result, expected_result) + self.assertTrue( + np.array_equal(output_image.numpy_view(), + test_image.numpy_view())) + self.assertLess(observed_timestamp_ms, timestamp_ms) + self.observed_timestamp_ms = timestamp_ms + + options = _GestureRecognizerOptions( + base_options=_BaseOptions(model_asset_path=self.model_path), + running_mode=_RUNNING_MODE.LIVE_STREAM, + result_callback=check_result) + with _GestureRecognizer.create_from_options(options) as recognizer: + for timestamp in range(0, 300, 30): + recognizer.recognize_async(test_image, timestamp) + if __name__ == '__main__': absltest.main() diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 9a9ca3429..3b2a7e50d 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -52,7 +52,6 @@ py_library( "//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_py_pb2", "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_py_pb2", "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_py_pb2", - "//mediapipe/tasks/python/components/containers:rect", "//mediapipe/tasks/python/components/containers:classification", "//mediapipe/tasks/python/components/containers:landmark", "//mediapipe/tasks/python/components/processors:classifier_options", diff --git a/mediapipe/tasks/python/vision/core/BUILD b/mediapipe/tasks/python/vision/core/BUILD index df1b06f4c..ddb7c024e 100644 --- a/mediapipe/tasks/python/vision/core/BUILD +++ b/mediapipe/tasks/python/vision/core/BUILD @@ -23,6 +23,14 @@ py_library( srcs = ["vision_task_running_mode.py"], ) +py_library( + name = "image_processing_options", + srcs = ["image_processing_options.py"], + deps = [ + "//mediapipe/tasks/python/components/containers:rect", + ], +) + py_library( name = "base_vision_task_api", srcs = [ @@ -30,6 +38,7 @@ py_library( ], deps = [ ":vision_task_running_mode", + ":image_processing_options", "//mediapipe/framework:calculator_py_pb2", "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/python/core:optional_dependencies", diff --git a/mediapipe/tasks/python/vision/core/base_vision_task_api.py b/mediapipe/tasks/python/vision/core/base_vision_task_api.py index b2f8a366a..be290c83c 100644 --- a/mediapipe/tasks/python/vision/core/base_vision_task_api.py +++ b/mediapipe/tasks/python/vision/core/base_vision_task_api.py @@ -13,17 +13,22 @@ # limitations under the License. """MediaPipe vision task base api.""" +import math from typing import Callable, Mapping, Optional from mediapipe.framework import calculator_pb2 from mediapipe.python._framework_bindings import packet as packet_module from mediapipe.python._framework_bindings import task_runner as task_runner_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls +from mediapipe.tasks.python.components.containers import rect as rect_module from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module +from mediapipe.tasks.python.vision.core import image_processing_options as image_processing_options_module _TaskRunner = task_runner_module.TaskRunner _Packet = packet_module.Packet +_NormalizedRect = rect_module.NormalizedRect _RunningMode = running_mode_module.VisionTaskRunningMode +_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions class BaseVisionTaskApi(object): @@ -122,6 +127,50 @@ class BaseVisionTaskApi(object): + self._running_mode.name) self._runner.send(inputs) + @staticmethod + def convert_to_normalized_rect( + options: _ImageProcessingOptions, + roi_allowed: bool = True + ) -> _NormalizedRect: + """ + Convert from ImageProcessingOptions to NormalizedRect, performing sanity + checks on-the-fly. If the input ImageProcessingOptions is not present, + returns a default NormalizedRect covering the whole image with rotation set + to 0. If 'roi_allowed' is false, an error will be returned if the input + ImageProcessingOptions has its 'region_of_interest' field set. + + Args: + options: Options for image processing. + roi_allowed: Indicates if the `region_of_interest` field is allowed to be + set. By default, it's set to True. + + """ + normalized_rect = _NormalizedRect(rotation=0, x_center=0.5, y_center=0.5, + width=1, height=1) + if options is None: + return normalized_rect + + if options.rotation_degrees % 90 != 0: + raise ValueError("Expected rotation to be a multiple of 90°.") + + # Convert to radians counter-clockwise. + normalized_rect.rotation = -options.rotation_degrees * math.pi / 180.0 + + if options.region_of_interest: + if not roi_allowed: + raise ValueError("This task doesn't support region-of-interest.") + roi = options.region_of_interest + if roi.x_center >= roi.width or roi.y_center >= roi.height: + raise ValueError( + "Expected Rect with x_center < width and y_center < height.") + if roi.x_center < 0 or roi.y_center < 0 or roi.width > 1 or roi.height > 1: + raise ValueError("Expected Rect values to be in [0,1].") + normalized_rect.x_center = roi.x_center + roi.width / 2.0 + normalized_rect.y_center = roi.y_center + roi.height / 2.0 + normalized_rect.width = roi.width - roi.x_center + normalized_rect.height = roi.height - roi.y_center + return normalized_rect + def close(self) -> None: """Shuts down the mediapipe vision task instance. diff --git a/mediapipe/tasks/python/vision/core/image_processing_options.py b/mediapipe/tasks/python/vision/core/image_processing_options.py new file mode 100644 index 000000000..2a3a13088 --- /dev/null +++ b/mediapipe/tasks/python/vision/core/image_processing_options.py @@ -0,0 +1,39 @@ +# Copyright 2022 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""MediaPipe vision options for image processing.""" + +import dataclasses +from typing import Optional + +from mediapipe.tasks.python.components.containers import rect as rect_module + + +@dataclasses.dataclass +class ImageProcessingOptions: + """Options for image processing. + + If both region-of-interest and rotation are specified, the crop around the + region-of-interest is extracted first, then the specified rotation is applied + to the crop. + + Attributes: + region_of_interest: The optional region-of-interest to crop from the image. + If not specified, the full image is used. Coordinates must be in [0,1] + with 'left' < 'right' and 'top' < bottom. + rotation_degress: The rotation to apply to the image (or cropped + region-of-interest), in degrees clockwise. The rotation must be a + multiple (positive or negative) of 90°. + """ + region_of_interest: Optional[rect_module.Rect] = None + rotation_degrees: int = 0 diff --git a/mediapipe/tasks/python/vision/gesture_recognizer.py b/mediapipe/tasks/python/vision/gesture_recognizer.py index c00508b36..0036aa877 100644 --- a/mediapipe/tasks/python/vision/gesture_recognizer.py +++ b/mediapipe/tasks/python/vision/gesture_recognizer.py @@ -27,7 +27,6 @@ from mediapipe.tasks.cc.vision.gesture_recognizer.proto import hand_gesture_reco from mediapipe.tasks.cc.vision.hand_detector.proto import hand_detector_graph_options_pb2 from mediapipe.tasks.cc.vision.hand_landmarker.proto import hand_landmarker_graph_options_pb2 from mediapipe.tasks.cc.vision.hand_landmarker.proto import hand_landmarks_detector_graph_options_pb2 -from mediapipe.tasks.python.components.containers import rect as rect_module from mediapipe.tasks.python.components.containers import classification as classification_module from mediapipe.tasks.python.components.containers import landmark as landmark_module from mediapipe.tasks.python.components.processors import classifier_options @@ -36,8 +35,8 @@ from mediapipe.tasks.python.core import task_info as task_info_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls from mediapipe.tasks.python.vision.core import base_vision_task_api from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module +from mediapipe.tasks.python.vision.core import image_processing_options as image_processing_options_module -_NormalizedRect = rect_module.NormalizedRect _BaseOptions = base_options_module.BaseOptions _GestureClassifierGraphOptionsProto = gesture_classifier_graph_options_pb2.GestureClassifierGraphOptions _GestureRecognizerGraphOptionsProto = gesture_recognizer_graph_options_pb2.GestureRecognizerGraphOptions @@ -47,6 +46,7 @@ _HandLandmarkerGraphOptionsProto = hand_landmarker_graph_options_pb2.HandLandmar _HandLandmarksDetectorGraphOptionsProto = hand_landmarks_detector_graph_options_pb2.HandLandmarksDetectorGraphOptions _ClassifierOptions = classifier_options.ClassifierOptions _RunningMode = running_mode_module.VisionTaskRunningMode +_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions _TaskInfo = task_info_module.TaskInfo _TaskRunner = task_runner_module.TaskRunner @@ -67,11 +67,6 @@ _TASK_GRAPH_NAME = 'mediapipe.tasks.vision.gesture_recognizer.GestureRecognizerG _MICRO_SECONDS_PER_MILLISECOND = 1000 -def _build_full_image_norm_rect() -> _NormalizedRect: - # Builds a NormalizedRect covering the entire image. - return _NormalizedRect(x_center=0.5, y_center=0.5, width=1, height=1) - - @dataclasses.dataclass class GestureRecognitionResult: """The gesture recognition result from GestureRecognizer, where each vector @@ -278,7 +273,7 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): def recognize( self, image: image_module.Image, - roi: Optional[_NormalizedRect] = None + image_processing_options: Optional[_ImageProcessingOptions] = None ) -> GestureRecognitionResult: """Performs hand gesture recognition on the given image. Only use this method when the GestureRecognizer is created with the image running mode. @@ -289,7 +284,7 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): Args: image: MediaPipe Image. - roi: The region of interest. + image_processing_options: Options for image processing. Returns: The hand gesture recognition results. @@ -298,11 +293,16 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): ValueError: If any of the input arguments is invalid. RuntimeError: If gesture recognition failed to run. """ - norm_rect = roi if roi is not None else _build_full_image_norm_rect() + normalized_rect = self.convert_to_normalized_rect(image_processing_options, + roi_allowed=False) output_packets = self._process_image_data({ _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image), _NORM_RECT_STREAM_NAME: packet_creator.create_proto( - norm_rect.to_pb2())}) + normalized_rect.to_pb2())}) + + if output_packets[_HAND_GESTURE_STREAM_NAME].is_empty(): + return GestureRecognitionResult([], [], [], []) + gestures_proto_list = packet_getter.get_proto_list( output_packets[_HAND_GESTURE_STREAM_NAME]) handedness_proto_list = packet_getter.get_proto_list( @@ -331,7 +331,7 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): def recognize_for_video( self, image: image_module.Image, timestamp_ms: int, - roi: Optional[_NormalizedRect] = None + image_processing_options: Optional[_ImageProcessingOptions] = None ) -> GestureRecognitionResult: """Performs gesture recognition on the provided video frame. Only use this method when the GestureRecognizer is created with the video running mode. @@ -344,7 +344,7 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): Args: image: MediaPipe Image. timestamp_ms: The timestamp of the input video frame in milliseconds. - roi: The region of interest. + image_processing_options: Options for image processing. Returns: The hand gesture recognition results. @@ -353,14 +353,19 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): ValueError: If any of the input arguments is invalid. RuntimeError: If gesture recognition failed to run. """ - norm_rect = roi if roi is not None else _build_full_image_norm_rect() + normalized_rect = self.convert_to_normalized_rect(image_processing_options, + roi_allowed=False) output_packets = self._process_video_data({ _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image).at( timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND), _NORM_RECT_STREAM_NAME: packet_creator.create_proto( - norm_rect.to_pb2()).at( + normalized_rect.to_pb2()).at( timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) }) + + if output_packets[_HAND_GESTURE_STREAM_NAME].is_empty(): + return GestureRecognitionResult([], [], [], []) + gestures_proto_list = packet_getter.get_proto_list( output_packets[_HAND_GESTURE_STREAM_NAME]) handedness_proto_list = packet_getter.get_proto_list( @@ -390,7 +395,7 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): self, image: image_module.Image, timestamp_ms: int, - roi: Optional[_NormalizedRect] = None + image_processing_options: Optional[_ImageProcessingOptions] = None ) -> None: """Sends live image data to perform gesture recognition, and the results will be available via the "result_callback" provided in the @@ -415,17 +420,18 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): Args: image: MediaPipe Image. timestamp_ms: The timestamp of the input image in milliseconds. - roi: The region of interest. + image_processing_options: Options for image processing. Raises: ValueError: If the current input timestamp is smaller than what the gesture recognizer has already processed. """ - norm_rect = roi if roi is not None else _build_full_image_norm_rect() + normalized_rect = self.convert_to_normalized_rect(image_processing_options, + roi_allowed=False) self._send_live_stream_data({ _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image).at( timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND), _NORM_RECT_STREAM_NAME: packet_creator.create_proto( - norm_rect.to_pb2()).at( + normalized_rect.to_pb2()).at( timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND) }) From 21abfc9125cb69f4c029420732cd4d4958904ca7 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Tue, 25 Oct 2022 12:12:18 -0700 Subject: [PATCH 074/125] Update gpu origin. PiperOrigin-RevId: 483742652 --- mediapipe/tasks/cc/components/BUILD | 1 + mediapipe/tasks/cc/components/image_preprocessing.cc | 4 ++++ 2 files changed, 5 insertions(+) diff --git a/mediapipe/tasks/cc/components/BUILD b/mediapipe/tasks/cc/components/BUILD index e4905546a..f563fbf64 100644 --- a/mediapipe/tasks/cc/components/BUILD +++ b/mediapipe/tasks/cc/components/BUILD @@ -46,6 +46,7 @@ cc_library( "//mediapipe/framework/formats:image", "//mediapipe/framework/formats:rect_cc_proto", "//mediapipe/framework/formats:tensor", + "//mediapipe/gpu:gpu_origin_cc_proto", "//mediapipe/tasks/cc:common", "//mediapipe/tasks/cc/core:model_resources", "//mediapipe/tasks/cc/vision/utils:image_tensor_specs", diff --git a/mediapipe/tasks/cc/components/image_preprocessing.cc b/mediapipe/tasks/cc/components/image_preprocessing.cc index 046a97e4d..f3f3b6863 100644 --- a/mediapipe/tasks/cc/components/image_preprocessing.cc +++ b/mediapipe/tasks/cc/components/image_preprocessing.cc @@ -30,6 +30,7 @@ limitations under the License. #include "mediapipe/framework/formats/image.h" #include "mediapipe/framework/formats/rect.pb.h" #include "mediapipe/framework/formats/tensor.h" +#include "mediapipe/gpu/gpu_origin.pb.h" #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/components/image_preprocessing_options.pb.h" #include "mediapipe/tasks/cc/core/model_resources.h" @@ -128,6 +129,9 @@ absl::Status ConfigureImageToTensorCalculator( options->mutable_output_tensor_float_range()->set_max((255.0f - mean) / std); } + // TODO: need to.support different GPU origin on differnt + // platforms or applications. + options->set_gpu_origin(mediapipe::GpuOrigin::TOP_LEFT); return absl::OkStatus(); } From 36bd9abb8f3f7c0dd4e5d54ebf573c2484cae666 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Tue, 25 Oct 2022 12:51:22 -0700 Subject: [PATCH 075/125] Internal change PiperOrigin-RevId: 483751427 --- .../tensors_to_classification_calculator.cc | 7 ----- ...tensors_to_classification_calculator.proto | 5 ---- ...nsors_to_classification_calculator_test.cc | 30 ------------------- .../framework/formats/classification.proto | 4 --- 4 files changed, 46 deletions(-) diff --git a/mediapipe/calculators/tensor/tensors_to_classification_calculator.cc b/mediapipe/calculators/tensor/tensors_to_classification_calculator.cc index 76d2869e8..5bfc00ed7 100644 --- a/mediapipe/calculators/tensor/tensors_to_classification_calculator.cc +++ b/mediapipe/calculators/tensor/tensors_to_classification_calculator.cc @@ -163,7 +163,6 @@ absl::Status TensorsToClassificationCalculator::Open(CalculatorContext* cc) { } absl::Status TensorsToClassificationCalculator::Process(CalculatorContext* cc) { - const auto& options = cc->Options(); const auto& input_tensors = *kInTensors(cc); RET_CHECK_EQ(input_tensors.size(), 1); RET_CHECK(input_tensors[0].element_type() == Tensor::ElementType::kFloat32); @@ -182,12 +181,6 @@ absl::Status TensorsToClassificationCalculator::Process(CalculatorContext* cc) { auto raw_scores = view.buffer(); auto classification_list = absl::make_unique(); - if (options.has_tensor_index()) { - classification_list->set_tensor_index(options.tensor_index()); - } - if (options.has_tensor_name()) { - classification_list->set_tensor_name(options.tensor_name()); - } if (is_binary_classification_) { Classification* class_first = classification_list->add_classification(); Classification* class_second = classification_list->add_classification(); diff --git a/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto b/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto index f0f7727ba..32bc4b63a 100644 --- a/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto +++ b/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto @@ -72,9 +72,4 @@ message TensorsToClassificationCalculatorOptions { // that are not in the `allow_classes` field will be completely ignored. // `ignore_classes` and `allow_classes` are mutually exclusive. repeated int32 allow_classes = 8 [packed = true]; - - // The optional index of the tensor these classifications originate from. - optional int32 tensor_index = 10; - // The optional name of the tensor these classifications originate from. - optional string tensor_name = 11; } diff --git a/mediapipe/calculators/tensor/tensors_to_classification_calculator_test.cc b/mediapipe/calculators/tensor/tensors_to_classification_calculator_test.cc index b20f2768c..9634635f0 100644 --- a/mediapipe/calculators/tensor/tensors_to_classification_calculator_test.cc +++ b/mediapipe/calculators/tensor/tensors_to_classification_calculator_test.cc @@ -240,36 +240,6 @@ TEST_F(TensorsToClassificationCalculatorTest, } } -TEST_F(TensorsToClassificationCalculatorTest, - CorrectOutputWithTensorNameAndIndex) { - mediapipe::CalculatorRunner runner(ParseTextProtoOrDie(R"pb( - calculator: "TensorsToClassificationCalculator" - input_stream: "TENSORS:tensors" - output_stream: "CLASSIFICATIONS:classifications" - options { - [mediapipe.TensorsToClassificationCalculatorOptions.ext] { - tensor_index: 1 - tensor_name: "foo" - } - } - )pb")); - - BuildGraph(&runner, {0, 0.5, 1}); - MP_ASSERT_OK(runner.Run()); - - const auto& output_packets_ = runner.Outputs().Tag("CLASSIFICATIONS").packets; - - EXPECT_EQ(1, output_packets_.size()); - - const auto& classification_list = - output_packets_[0].Get(); - EXPECT_EQ(3, classification_list.classification_size()); - - // Verify that the tensor_index and tensor_name fields are correctly set. - EXPECT_EQ(classification_list.tensor_index(), 1); - EXPECT_EQ(classification_list.tensor_name(), "foo"); -} - TEST_F(TensorsToClassificationCalculatorTest, ClassNameAllowlistWithLabelItems) { mediapipe::CalculatorRunner runner(ParseTextProtoOrDie(R"pb( diff --git a/mediapipe/framework/formats/classification.proto b/mediapipe/framework/formats/classification.proto index c3eea07ff..7efd9074d 100644 --- a/mediapipe/framework/formats/classification.proto +++ b/mediapipe/framework/formats/classification.proto @@ -37,10 +37,6 @@ message Classification { // Group of Classification protos. message ClassificationList { repeated Classification classification = 1; - // Optional index of the tensor that produced these classifications. - optional int32 tensor_index = 2; - // Optional name of the tensor that produced these classifications. - optional string tensor_name = 3; } // Group of ClassificationList protos. From a28c9d2c2697a387795d0cd721c99024923dbd18 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Tue, 25 Oct 2022 13:41:41 -0700 Subject: [PATCH 076/125] Set `steps_per_epoch` to None when calling model.fit() method for image classifier. PiperOrigin-RevId: 483764377 --- .../python/vision/image_classifier/train_image_classifier_lib.py | 1 - 1 file changed, 1 deletion(-) diff --git a/mediapipe/model_maker/python/vision/image_classifier/train_image_classifier_lib.py b/mediapipe/model_maker/python/vision/image_classifier/train_image_classifier_lib.py index 704d71a5a..265c36a6e 100644 --- a/mediapipe/model_maker/python/vision/image_classifier/train_image_classifier_lib.py +++ b/mediapipe/model_maker/python/vision/image_classifier/train_image_classifier_lib.py @@ -98,6 +98,5 @@ def train_model(model: tf.keras.Model, hparams: hp.HParams, return model.fit( x=train_ds, epochs=hparams.train_epochs, - steps_per_epoch=hparams.steps_per_epoch, validation_data=validation_ds, callbacks=callbacks) From 75af46d2739245bb46de9fd30e541e2b6de3b077 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 25 Oct 2022 23:13:12 -0700 Subject: [PATCH 077/125] Revised API to align with recent changes --- .../python/components/containers/classification.py | 10 ++-------- .../python/test/vision/gesture_recognizer_test.py | 2 +- 2 files changed, 3 insertions(+), 9 deletions(-) diff --git a/mediapipe/tasks/python/components/containers/classification.py b/mediapipe/tasks/python/components/containers/classification.py index 465e2dd28..a9225e804 100644 --- a/mediapipe/tasks/python/components/containers/classification.py +++ b/mediapipe/tasks/python/components/containers/classification.py @@ -85,8 +85,6 @@ class ClassificationList: """ classifications: List[Classification] - tensor_index: Optional[int] = None - tensor_name: Optional[str] = None @doc_controls.do_not_generate_docs def to_pb2(self) -> _ClassificationListProto: @@ -95,9 +93,7 @@ class ClassificationList: classification=[ classification.to_pb2() for classification in self.classifications - ], - tensor_index=self.tensor_index, - tensor_name=self.tensor_name) + ]) @classmethod @doc_controls.do_not_generate_docs @@ -110,9 +106,7 @@ class ClassificationList: classifications=[ Classification.create_from_pb2(classification) for classification in pb2_obj.classification - ], - tensor_index=pb2_obj.tensor_index, - tensor_name=pb2_obj.tensor_name) + ]) def __eq__(self, other: Any) -> bool: """Checks if this object is equal to the given object. diff --git a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py index a8316c528..3bf994a1d 100644 --- a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py +++ b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py @@ -80,7 +80,7 @@ def _get_expected_gesture_recognition_result( classifications=[ _Classification(label=gesture_label, index=gesture_index, display_name='') - ], tensor_index=0, tensor_name='') + ]) return _GestureRecognitionResult( gestures=[gesture], handedness=[landmarks_detection_result.classifications], From fbf7ba6f1a5259c93ff3b32a968643e2f7b4b454 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 25 Oct 2022 23:15:16 -0700 Subject: [PATCH 078/125] Reverted some changes to rect --- mediapipe/tasks/python/components/containers/rect.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/mediapipe/tasks/python/components/containers/rect.py b/mediapipe/tasks/python/components/containers/rect.py index 4b943a551..510561592 100644 --- a/mediapipe/tasks/python/components/containers/rect.py +++ b/mediapipe/tasks/python/components/containers/rect.py @@ -26,6 +26,7 @@ _NormalizedRectProto = rect_pb2.NormalizedRect @dataclasses.dataclass class Rect: """A rectangle with rotation in image coordinates. + Attributes: x_center : The X coordinate of the top-left corner, in pixels. y_center : The Y coordinate of the top-left corner, in pixels. width: The width of the rectangle, in pixels. @@ -80,8 +81,11 @@ class Rect: @dataclasses.dataclass class NormalizedRect: """A rectangle with rotation in normalized coordinates. + The values of box + center location and size are within [0, 1]. + Attributes: x_center : The X normalized coordinate of the top-left corner. y_center : The Y normalized coordinate of the top-left corner. width: The width of the rectangle. From f8a98ccba432ec8be3c28eea9cad84556f153b45 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Tue, 25 Oct 2022 23:38:32 -0700 Subject: [PATCH 079/125] Added a test utility method to compare protos directly --- mediapipe/tasks/python/test/test_utils.py | 112 ++++++++++++++++++ .../test/vision/image_classifier_test.py | 20 ++-- 2 files changed, 122 insertions(+), 10 deletions(-) diff --git a/mediapipe/tasks/python/test/test_utils.py b/mediapipe/tasks/python/test/test_utils.py index b428f8302..a9b961944 100644 --- a/mediapipe/tasks/python/test/test_utils.py +++ b/mediapipe/tasks/python/test/test_utils.py @@ -14,7 +14,12 @@ """Test util for MediaPipe Tasks.""" import os +import difflib +import six +from google.protobuf import descriptor +from google.protobuf import descriptor_pool +from google.protobuf import text_format from absl import flags from mediapipe.python._framework_bindings import image as image_module @@ -53,3 +58,110 @@ def create_calibration_file(file_dir: str, with open(calibration_file, mode="w") as file: file.write(content) return calibration_file + + +def assertProtoEqual(self, a, b, check_initialized=True, + normalize_numbers=False, msg=None): + """Fails with a useful error if a and b aren't equal. + Comparison of repeated fields matches the semantics of + unittest.TestCase.assertEqual(), ie order and extra duplicates fields matter. + Args: + self: absltest.testing.parameterized.TestCase + a: proto2 PB instance, or text string representing one. + b: proto2 PB instance -- message.Message or subclass thereof. + check_initialized: boolean, whether to fail if either a or b isn't + initialized. + normalize_numbers: boolean, whether to normalize types and precision of + numbers before comparison. + msg: if specified, is used as the error message on failure. + """ + pool = descriptor_pool.Default() + if isinstance(a, six.string_types): + a = text_format.Merge(a, b.__class__(), descriptor_pool=pool) + + for pb in a, b: + if check_initialized: + errors = pb.FindInitializationErrors() + if errors: + self.fail('Initialization errors: %s\n%s' % (errors, pb)) + if normalize_numbers: + _normalize_number_fields(pb) + + a_str = text_format.MessageToString(a, descriptor_pool=pool) + b_str = text_format.MessageToString(b, descriptor_pool=pool) + + # Some Python versions would perform regular diff instead of multi-line + # diff if string is longer than 2**16. We substitute this behavior + # with a call to unified_diff instead to have easier-to-read diffs. + # For context, see: https://bugs.python.org/issue11763. + if len(a_str) < 2**16 and len(b_str) < 2**16: + self.assertMultiLineEqual(a_str, b_str, msg=msg) + else: + diff = ''.join( + difflib.unified_diff(a_str.splitlines(True), b_str.splitlines(True))) + if diff: + self.fail('%s :\n%s' % (msg, diff)) + + +def _normalize_number_fields(pb): + """Normalizes types and precisions of number fields in a protocol buffer. + Due to subtleties in the python protocol buffer implementation, it is possible + for values to have different types and precision depending on whether they + were set and retrieved directly or deserialized from a protobuf. This function + normalizes integer values to ints and longs based on width, 32-bit floats to + five digits of precision to account for python always storing them as 64-bit, + and ensures doubles are floating point for when they're set to integers. + Modifies pb in place. Recurses into nested objects. + Args: + pb: proto2 message. + Returns: + the given pb, modified in place. + """ + for desc, values in pb.ListFields(): + is_repeated = True + if desc.label != descriptor.FieldDescriptor.LABEL_REPEATED: + is_repeated = False + values = [values] + + normalized_values = None + + # We force 32-bit values to int and 64-bit values to long to make + # alternate implementations where the distinction is more significant + # (e.g. the C++ implementation) simpler. + if desc.type in (descriptor.FieldDescriptor.TYPE_INT64, + descriptor.FieldDescriptor.TYPE_UINT64, + descriptor.FieldDescriptor.TYPE_SINT64): + normalized_values = [int(x) for x in values] + elif desc.type in (descriptor.FieldDescriptor.TYPE_INT32, + descriptor.FieldDescriptor.TYPE_UINT32, + descriptor.FieldDescriptor.TYPE_SINT32, + descriptor.FieldDescriptor.TYPE_ENUM): + normalized_values = [int(x) for x in values] + elif desc.type == descriptor.FieldDescriptor.TYPE_FLOAT: + normalized_values = [round(x, 6) for x in values] + elif desc.type == descriptor.FieldDescriptor.TYPE_DOUBLE: + normalized_values = [round(float(x), 7) for x in values] + + if normalized_values is not None: + if is_repeated: + pb.ClearField(desc.name) + getattr(pb, desc.name).extend(normalized_values) + else: + setattr(pb, desc.name, normalized_values[0]) + + if (desc.type == descriptor.FieldDescriptor.TYPE_MESSAGE or + desc.type == descriptor.FieldDescriptor.TYPE_GROUP): + if (desc.type == descriptor.FieldDescriptor.TYPE_MESSAGE and + desc.message_type.has_options and + desc.message_type.GetOptions().map_entry): + # This is a map, only recurse if the values have a message type. + if (desc.message_type.fields_by_number[2].type == + descriptor.FieldDescriptor.TYPE_MESSAGE): + for v in six.itervalues(values): + _normalize_number_fields(v) + else: + for v in values: + # recursive step + _normalize_number_fields(v) + + return pb diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index afaf921a7..4ebc113bd 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -51,8 +51,8 @@ _MAX_RESULTS = 3 # TODO: Port assertProtoEquals -def _assert_proto_equals(expected, actual): # pylint: disable=unused-argument - pass +def _assert_proto_equals(self, expected, actual): # pylint: disable=unused-argument + test_utils.assertProtoEqual(self, expected, actual) def _generate_empty_results(timestamp_ms: int) -> _ClassificationResult: @@ -186,7 +186,7 @@ class ImageClassifierTest(parameterized.TestCase): # Performs image classification on the input. image_result = classifier.classify(self.test_image) # Comparing results. - _assert_proto_equals(image_result.to_pb2(), + _assert_proto_equals(self, image_result.to_pb2(), expected_classification_result.to_pb2()) # Closes the classifier explicitly when the classifier is not used in # a context. @@ -214,7 +214,7 @@ class ImageClassifierTest(parameterized.TestCase): # Performs image classification on the input. image_result = classifier.classify(self.test_image) # Comparing results. - _assert_proto_equals(image_result.to_pb2(), + _assert_proto_equals(self, image_result.to_pb2(), expected_classification_result.to_pb2()) def test_classify_succeeds_with_region_of_interest(self): @@ -232,7 +232,7 @@ class ImageClassifierTest(parameterized.TestCase): # Performs image classification on the input. image_result = classifier.classify(test_image, roi) # Comparing results. - _assert_proto_equals(image_result.to_pb2(), + _assert_proto_equals(self, image_result.to_pb2(), _generate_soccer_ball_results(0).to_pb2()) def test_score_threshold_option(self): @@ -401,7 +401,7 @@ class ImageClassifierTest(parameterized.TestCase): for timestamp in range(0, 300, 30): classification_result = classifier.classify_for_video( self.test_image, timestamp) - _assert_proto_equals(classification_result.to_pb2(), + _assert_proto_equals(self, classification_result.to_pb2(), _generate_burger_results(timestamp).to_pb2()) def test_classify_for_video_succeeds_with_region_of_interest(self): @@ -420,8 +420,8 @@ class ImageClassifierTest(parameterized.TestCase): for timestamp in range(0, 300, 30): classification_result = classifier.classify_for_video( test_image, timestamp, roi) - self.assertEqual(classification_result, - _generate_soccer_ball_results(timestamp)) + _assert_proto_equals(self, classification_result.to_pb2(), + _generate_soccer_ball_results(timestamp).to_pb2()) def test_calling_classify_in_live_stream_mode(self): options = _ImageClassifierOptions( @@ -463,7 +463,7 @@ class ImageClassifierTest(parameterized.TestCase): def check_result(result: _ClassificationResult, output_image: _Image, timestamp_ms: int): - _assert_proto_equals(result.to_pb2(), + _assert_proto_equals(self, result.to_pb2(), expected_result_fn(timestamp_ms).to_pb2()) self.assertTrue( np.array_equal(output_image.numpy_view(), @@ -493,7 +493,7 @@ class ImageClassifierTest(parameterized.TestCase): def check_result(result: _ClassificationResult, output_image: _Image, timestamp_ms: int): - _assert_proto_equals(result.to_pb2(), + _assert_proto_equals(self, result.to_pb2(), _generate_soccer_ball_results(timestamp_ms).to_pb2()) self.assertEqual(output_image.width, test_image.width) self.assertEqual(output_image.height, test_image.height) From 254f7866249cee0f30194046019d1d758a92be5e Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Wed, 26 Oct 2022 00:44:18 -0700 Subject: [PATCH 080/125] Add an option to set image preprocessing backend as gpu. PiperOrigin-RevId: 483888202 --- mediapipe/tasks/cc/components/BUILD | 1 + .../tasks/cc/components/image_preprocessing.cc | 13 +++++++++++-- .../tasks/cc/components/image_preprocessing.h | 15 +++++++++++++-- .../vision/hand_detector/hand_detector_graph.cc | 4 +++- .../hand_landmarks_detector_graph.cc | 4 +++- .../image_classifier/image_classifier_graph.cc | 4 +++- .../vision/image_embedder/image_embedder_graph.cc | 4 +++- .../image_segmenter/image_segmenter_graph.cc | 4 +++- .../object_detector/object_detector_graph.cc | 4 +++- 9 files changed, 43 insertions(+), 10 deletions(-) diff --git a/mediapipe/tasks/cc/components/BUILD b/mediapipe/tasks/cc/components/BUILD index f563fbf64..344fafb4e 100644 --- a/mediapipe/tasks/cc/components/BUILD +++ b/mediapipe/tasks/cc/components/BUILD @@ -49,6 +49,7 @@ cc_library( "//mediapipe/gpu:gpu_origin_cc_proto", "//mediapipe/tasks/cc:common", "//mediapipe/tasks/cc/core:model_resources", + "//mediapipe/tasks/cc/core/proto:acceleration_cc_proto", "//mediapipe/tasks/cc/vision/utils:image_tensor_specs", "@com_google_absl//absl/status", "@com_google_absl//absl/status:statusor", diff --git a/mediapipe/tasks/cc/components/image_preprocessing.cc b/mediapipe/tasks/cc/components/image_preprocessing.cc index f3f3b6863..7940080e1 100644 --- a/mediapipe/tasks/cc/components/image_preprocessing.cc +++ b/mediapipe/tasks/cc/components/image_preprocessing.cc @@ -34,6 +34,7 @@ limitations under the License. #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/components/image_preprocessing_options.pb.h" #include "mediapipe/tasks/cc/core/model_resources.h" +#include "mediapipe/tasks/cc/core/proto/acceleration.pb.h" #include "mediapipe/tasks/cc/vision/utils/image_tensor_specs.h" #include "tensorflow/lite/schema/schema_generated.h" @@ -129,7 +130,7 @@ absl::Status ConfigureImageToTensorCalculator( options->mutable_output_tensor_float_range()->set_max((255.0f - mean) / std); } - // TODO: need to.support different GPU origin on differnt + // TODO: need to support different GPU origin on differnt // platforms or applications. options->set_gpu_origin(mediapipe::GpuOrigin::TOP_LEFT); return absl::OkStatus(); @@ -137,7 +138,13 @@ absl::Status ConfigureImageToTensorCalculator( } // namespace +bool DetermineImagePreprocessingGpuBackend( + const core::proto::Acceleration& acceleration) { + return acceleration.has_gpu(); +} + absl::Status ConfigureImagePreprocessing(const ModelResources& model_resources, + bool use_gpu, ImagePreprocessingOptions* options) { ASSIGN_OR_RETURN(auto image_tensor_specs, BuildImageTensorSpecs(model_resources)); @@ -145,7 +152,9 @@ absl::Status ConfigureImagePreprocessing(const ModelResources& model_resources, image_tensor_specs, options->mutable_image_to_tensor_options())); // The GPU backend isn't able to process int data. If the input tensor is // quantized, forces the image preprocessing graph to use CPU backend. - if (image_tensor_specs.tensor_type == tflite::TensorType_UINT8) { + if (use_gpu && image_tensor_specs.tensor_type != tflite::TensorType_UINT8) { + options->set_backend(ImagePreprocessingOptions::GPU_BACKEND); + } else { options->set_backend(ImagePreprocessingOptions::CPU_BACKEND); } return absl::OkStatus(); diff --git a/mediapipe/tasks/cc/components/image_preprocessing.h b/mediapipe/tasks/cc/components/image_preprocessing.h index a5b767f3a..6963b6556 100644 --- a/mediapipe/tasks/cc/components/image_preprocessing.h +++ b/mediapipe/tasks/cc/components/image_preprocessing.h @@ -19,20 +19,26 @@ limitations under the License. #include "absl/status/status.h" #include "mediapipe/tasks/cc/components/image_preprocessing_options.pb.h" #include "mediapipe/tasks/cc/core/model_resources.h" +#include "mediapipe/tasks/cc/core/proto/acceleration.pb.h" namespace mediapipe { namespace tasks { namespace components { -// Configures an ImagePreprocessing subgraph using the provided model resources. +// Configures an ImagePreprocessing subgraph using the provided model resources +// When use_gpu is true, use GPU as backend to convert image to tensor. // - Accepts CPU input images and outputs CPU tensors. // // Example usage: // // auto& preprocessing = // graph.AddNode("mediapipe.tasks.components.ImagePreprocessingSubgraph"); +// core::proto::Acceleration acceleration; +// acceleration.mutable_xnnpack(); +// bool use_gpu = DetermineImagePreprocessingGpuBackend(acceleration); // MP_RETURN_IF_ERROR(ConfigureImagePreprocessing( // model_resources, +// use_gpu, // &preprocessing.GetOptions())); // // The resulting ImagePreprocessing subgraph has the following I/O: @@ -56,9 +62,14 @@ namespace components { // The image that has the pixel data stored on the target storage (CPU vs // GPU). absl::Status ConfigureImagePreprocessing( - const core::ModelResources& model_resources, + const core::ModelResources& model_resources, bool use_gpu, ImagePreprocessingOptions* options); +// Determine if the image preprocessing subgraph should use GPU as the backend +// according to the given acceleration setting. +bool DetermineImagePreprocessingGpuBackend( + const core::proto::Acceleration& acceleration); + } // namespace components } // namespace tasks } // namespace mediapipe diff --git a/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph.cc b/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph.cc index e876d7d09..06bb2e549 100644 --- a/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph.cc +++ b/mediapipe/tasks/cc/vision/hand_detector/hand_detector_graph.cc @@ -235,8 +235,10 @@ class HandDetectorGraph : public core::ModelTaskGraph { image_to_tensor_options.set_keep_aspect_ratio(true); image_to_tensor_options.set_border_mode( mediapipe::ImageToTensorCalculatorOptions::BORDER_ZERO); + bool use_gpu = components::DetermineImagePreprocessingGpuBackend( + subgraph_options.base_options().acceleration()); MP_RETURN_IF_ERROR(ConfigureImagePreprocessing( - model_resources, + model_resources, use_gpu, &preprocessing .GetOptions())); image_in >> preprocessing.In("IMAGE"); diff --git a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarks_detector_graph.cc b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarks_detector_graph.cc index 23521790d..1f127deb8 100644 --- a/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarks_detector_graph.cc +++ b/mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarks_detector_graph.cc @@ -283,8 +283,10 @@ class SingleHandLandmarksDetectorGraph : public core::ModelTaskGraph { auto& preprocessing = graph.AddNode("mediapipe.tasks.components.ImagePreprocessingSubgraph"); + bool use_gpu = components::DetermineImagePreprocessingGpuBackend( + subgraph_options.base_options().acceleration()); MP_RETURN_IF_ERROR(ConfigureImagePreprocessing( - model_resources, + model_resources, use_gpu, &preprocessing .GetOptions())); image_in >> preprocessing.In("IMAGE"); diff --git a/mediapipe/tasks/cc/vision/image_classifier/image_classifier_graph.cc b/mediapipe/tasks/cc/vision/image_classifier/image_classifier_graph.cc index 9a0078c5c..8a1b17ce9 100644 --- a/mediapipe/tasks/cc/vision/image_classifier/image_classifier_graph.cc +++ b/mediapipe/tasks/cc/vision/image_classifier/image_classifier_graph.cc @@ -138,8 +138,10 @@ class ImageClassifierGraph : public core::ModelTaskGraph { // stream. auto& preprocessing = graph.AddNode("mediapipe.tasks.components.ImagePreprocessingSubgraph"); + bool use_gpu = components::DetermineImagePreprocessingGpuBackend( + task_options.base_options().acceleration()); MP_RETURN_IF_ERROR(ConfigureImagePreprocessing( - model_resources, + model_resources, use_gpu, &preprocessing .GetOptions())); image_in >> preprocessing.In(kImageTag); diff --git a/mediapipe/tasks/cc/vision/image_embedder/image_embedder_graph.cc b/mediapipe/tasks/cc/vision/image_embedder/image_embedder_graph.cc index fff0f4366..f0f440986 100644 --- a/mediapipe/tasks/cc/vision/image_embedder/image_embedder_graph.cc +++ b/mediapipe/tasks/cc/vision/image_embedder/image_embedder_graph.cc @@ -134,8 +134,10 @@ class ImageEmbedderGraph : public core::ModelTaskGraph { // stream. auto& preprocessing = graph.AddNode("mediapipe.tasks.components.ImagePreprocessingSubgraph"); + bool use_gpu = components::DetermineImagePreprocessingGpuBackend( + task_options.base_options().acceleration()); MP_RETURN_IF_ERROR(ConfigureImagePreprocessing( - model_resources, + model_resources, use_gpu, &preprocessing .GetOptions())); image_in >> preprocessing.In(kImageTag); diff --git a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_graph.cc b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_graph.cc index 629b940aa..d3e522d92 100644 --- a/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_graph.cc +++ b/mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_graph.cc @@ -243,8 +243,10 @@ class ImageSegmenterGraph : public core::ModelTaskGraph { // stream. auto& preprocessing = graph.AddNode("mediapipe.tasks.components.ImagePreprocessingSubgraph"); + bool use_gpu = components::DetermineImagePreprocessingGpuBackend( + task_options.base_options().acceleration()); MP_RETURN_IF_ERROR(ConfigureImagePreprocessing( - model_resources, + model_resources, use_gpu, &preprocessing .GetOptions())); image_in >> preprocessing.In(kImageTag); diff --git a/mediapipe/tasks/cc/vision/object_detector/object_detector_graph.cc b/mediapipe/tasks/cc/vision/object_detector/object_detector_graph.cc index 07e912cfc..b149cea0f 100644 --- a/mediapipe/tasks/cc/vision/object_detector/object_detector_graph.cc +++ b/mediapipe/tasks/cc/vision/object_detector/object_detector_graph.cc @@ -563,8 +563,10 @@ class ObjectDetectorGraph : public core::ModelTaskGraph { // stream. auto& preprocessing = graph.AddNode("mediapipe.tasks.components.ImagePreprocessingSubgraph"); + bool use_gpu = components::DetermineImagePreprocessingGpuBackend( + task_options.base_options().acceleration()); MP_RETURN_IF_ERROR(ConfigureImagePreprocessing( - model_resources, + model_resources, use_gpu, &preprocessing .GetOptions())); image_in >> preprocessing.In(kImageTag); From a941c5cdd11be51fcd8e0b1a7bde17b6130c37bf Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Wed, 26 Oct 2022 10:16:20 -0700 Subject: [PATCH 081/125] Create MediaPipe "tasks-text" AAR. PiperOrigin-RevId: 484004494 --- .../mediapipe/tasks/mediapipe_tasks_aar.bzl | 97 ++++++++++++++----- .../com/google/mediapipe/tasks/text/BUILD | 8 ++ 2 files changed, 79 insertions(+), 26 deletions(-) diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl b/mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl index e0b9c79ed..0260e3fab 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl @@ -40,6 +40,10 @@ _VISION_TASKS_JAVA_PROTO_LITE_TARGETS = [ "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_java_proto_lite", ] +_TEXT_TASKS_JAVA_PROTO_LITE_TARGETS = [ + "//mediapipe/tasks/cc/text/text_classifier/proto:text_classifier_graph_options_java_proto_lite", +] + def mediapipe_tasks_core_aar(name, srcs, manifest): """Builds medaipipe tasks core AAR. @@ -60,6 +64,11 @@ def mediapipe_tasks_core_aar(name, srcs, manifest): _mediapipe_tasks_java_proto_src_extractor(target = target), ) + for target in _TEXT_TASKS_JAVA_PROTO_LITE_TARGETS: + mediapipe_tasks_java_proto_srcs.append( + _mediapipe_tasks_java_proto_src_extractor(target = target), + ) + mediapipe_tasks_java_proto_srcs.append(mediapipe_java_proto_src_extractor( target = "//mediapipe/calculators/core:flow_limiter_calculator_java_proto_lite", src_out = "com/google/mediapipe/calculator/proto/FlowLimiterCalculatorProto.java", @@ -81,32 +90,35 @@ def mediapipe_tasks_core_aar(name, srcs, manifest): ], manifest = manifest, deps = [ - "//mediapipe/calculators/core:flow_limiter_calculator_java_proto_lite", - "//mediapipe/calculators/tensor:inference_calculator_java_proto_lite", - "//mediapipe/framework:calculator_java_proto_lite", - "//mediapipe/framework:calculator_profile_java_proto_lite", - "//mediapipe/framework:calculator_options_java_proto_lite", - "//mediapipe/framework:mediapipe_options_java_proto_lite", - "//mediapipe/framework:packet_factory_java_proto_lite", - "//mediapipe/framework:packet_generator_java_proto_lite", - "//mediapipe/framework:status_handler_java_proto_lite", - "//mediapipe/framework:stream_handler_java_proto_lite", - "//mediapipe/framework/formats:classification_java_proto_lite", - "//mediapipe/framework/formats:detection_java_proto_lite", - "//mediapipe/framework/formats:landmark_java_proto_lite", - "//mediapipe/framework/formats:location_data_java_proto_lite", - "//mediapipe/framework/formats:rect_java_proto_lite", - "//mediapipe/java/com/google/mediapipe/framework:android_framework", - "//mediapipe/java/com/google/mediapipe/framework/image", - "//mediapipe/tasks/java/com/google/mediapipe/tasks/core/jni:model_resources_cache_jni", - "//third_party:androidx_annotation", - "//third_party:autovalue", - "@com_google_protobuf//:protobuf_javalite", - "@maven//:com_google_guava_guava", - "@maven//:com_google_flogger_flogger", - "@maven//:com_google_flogger_flogger_system_backend", - "@maven//:com_google_code_findbugs_jsr305", - ] + _CORE_TASKS_JAVA_PROTO_LITE_TARGETS + _VISION_TASKS_JAVA_PROTO_LITE_TARGETS, + "//mediapipe/calculators/core:flow_limiter_calculator_java_proto_lite", + "//mediapipe/calculators/tensor:inference_calculator_java_proto_lite", + "//mediapipe/framework:calculator_java_proto_lite", + "//mediapipe/framework:calculator_profile_java_proto_lite", + "//mediapipe/framework:calculator_options_java_proto_lite", + "//mediapipe/framework:mediapipe_options_java_proto_lite", + "//mediapipe/framework:packet_factory_java_proto_lite", + "//mediapipe/framework:packet_generator_java_proto_lite", + "//mediapipe/framework:status_handler_java_proto_lite", + "//mediapipe/framework:stream_handler_java_proto_lite", + "//mediapipe/framework/formats:classification_java_proto_lite", + "//mediapipe/framework/formats:detection_java_proto_lite", + "//mediapipe/framework/formats:landmark_java_proto_lite", + "//mediapipe/framework/formats:location_data_java_proto_lite", + "//mediapipe/framework/formats:rect_java_proto_lite", + "//mediapipe/java/com/google/mediapipe/framework:android_framework", + "//mediapipe/java/com/google/mediapipe/framework/image", + "//mediapipe/tasks/java/com/google/mediapipe/tasks/core/jni:model_resources_cache_jni", + "//third_party:androidx_annotation", + "//third_party:autovalue", + "@com_google_protobuf//:protobuf_javalite", + "@maven//:com_google_guava_guava", + "@maven//:com_google_flogger_flogger", + "@maven//:com_google_flogger_flogger_system_backend", + "@maven//:com_google_code_findbugs_jsr305", + ] + + _CORE_TASKS_JAVA_PROTO_LITE_TARGETS + + _VISION_TASKS_JAVA_PROTO_LITE_TARGETS + + _TEXT_TASKS_JAVA_PROTO_LITE_TARGETS, ) def mediapipe_tasks_vision_aar(name, srcs, native_library): @@ -142,6 +154,39 @@ EOF native_library = native_library, ) +def mediapipe_tasks_text_aar(name, srcs, native_library): + """Builds medaipipe tasks text AAR. + + Args: + name: The bazel target name. + srcs: MediaPipe Text Tasks' source files. + native_library: The native library that contains text tasks' graph and calculators. + """ + + native.genrule( + name = name + "tasks_manifest_generator", + outs = ["AndroidManifest.xml"], + cmd = """ +cat > $(OUTS) < + + + +EOF +""", + ) + + _mediapipe_tasks_aar( + name = name, + srcs = srcs, + manifest = "AndroidManifest.xml", + java_proto_lite_targets = _CORE_TASKS_JAVA_PROTO_LITE_TARGETS + _TEXT_TASKS_JAVA_PROTO_LITE_TARGETS, + native_library = native_library, + ) + def _mediapipe_tasks_aar(name, srcs, manifest, java_proto_lite_targets, native_library): """Builds medaipipe tasks AAR.""" diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/text/BUILD b/mediapipe/tasks/java/com/google/mediapipe/tasks/text/BUILD index 1719707d8..fa2a547c2 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/text/BUILD +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/text/BUILD @@ -61,3 +61,11 @@ android_library( "@maven//:com_google_guava_guava", ], ) + +load("//mediapipe/tasks/java/com/google/mediapipe/tasks:mediapipe_tasks_aar.bzl", "mediapipe_tasks_text_aar") + +mediapipe_tasks_text_aar( + name = "tasks_text", + srcs = glob(["**/*.java"]), + native_library = ":libmediapipe_tasks_text_jni_lib", +) From 81945139343eab841aa0acec70a25da4bd92f3c1 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Wed, 26 Oct 2022 23:56:54 -0700 Subject: [PATCH 082/125] Updated docstrings and removed the redundant private helper method --- mediapipe/tasks/python/test/test_utils.py | 11 +++-- .../test/vision/image_classifier_test.py | 46 +++++++++---------- 2 files changed, 30 insertions(+), 27 deletions(-) diff --git a/mediapipe/tasks/python/test/test_utils.py b/mediapipe/tasks/python/test/test_utils.py index a9b961944..b2387eb2c 100644 --- a/mediapipe/tasks/python/test/test_utils.py +++ b/mediapipe/tasks/python/test/test_utils.py @@ -61,10 +61,13 @@ def create_calibration_file(file_dir: str, def assertProtoEqual(self, a, b, check_initialized=True, - normalize_numbers=False, msg=None): - """Fails with a useful error if a and b aren't equal. - Comparison of repeated fields matches the semantics of + normalize_numbers=True, msg=None): + """assertProtoEqual() is useful for unit tests. It produces much more helpful + output than assertEqual() for proto2 messages. Fails with a useful error if a + and b aren't equal. Comparison of repeated fields matches the semantics of unittest.TestCase.assertEqual(), ie order and extra duplicates fields matter. + https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/util/protobuf/compare.py#L73 + Args: self: absltest.testing.parameterized.TestCase a: proto2 PB instance, or text string representing one. @@ -112,6 +115,8 @@ def _normalize_number_fields(pb): five digits of precision to account for python always storing them as 64-bit, and ensures doubles are floating point for when they're set to integers. Modifies pb in place. Recurses into nested objects. + https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/util/protobuf/compare.py#L118 + Args: pb: proto2 message. Returns: diff --git a/mediapipe/tasks/python/test/vision/image_classifier_test.py b/mediapipe/tasks/python/test/vision/image_classifier_test.py index 4ebc113bd..9b8c5e94e 100644 --- a/mediapipe/tasks/python/test/vision/image_classifier_test.py +++ b/mediapipe/tasks/python/test/vision/image_classifier_test.py @@ -50,11 +50,6 @@ _SCORE_THRESHOLD = 0.5 _MAX_RESULTS = 3 -# TODO: Port assertProtoEquals -def _assert_proto_equals(self, expected, actual): # pylint: disable=unused-argument - test_utils.assertProtoEqual(self, expected, actual) - - def _generate_empty_results(timestamp_ms: int) -> _ClassificationResult: return _ClassificationResult(classifications=[ _Classifications( @@ -74,22 +69,22 @@ def _generate_burger_results(timestamp_ms: int) -> _ClassificationResult: categories=[ _Category( index=934, - score=0.7939587831497192, + score=0.793959, display_name='', category_name='cheeseburger'), _Category( index=932, - score=0.02739289402961731, + score=0.0273929, display_name='', category_name='bagel'), _Category( index=925, - score=0.01934075355529785, + score=0.0193408, display_name='', category_name='guacamole'), _Category( index=963, - score=0.006327860057353973, + score=0.00632786, display_name='', category_name='meat loaf') ], @@ -108,7 +103,7 @@ def _generate_soccer_ball_results(timestamp_ms: int) -> _ClassificationResult: categories=[ _Category( index=806, - score=0.9965274930000305, + score=0.996527, display_name='', category_name='soccer ball') ], @@ -186,8 +181,8 @@ class ImageClassifierTest(parameterized.TestCase): # Performs image classification on the input. image_result = classifier.classify(self.test_image) # Comparing results. - _assert_proto_equals(self, image_result.to_pb2(), - expected_classification_result.to_pb2()) + test_utils.assertProtoEqual(self, image_result.to_pb2(), + expected_classification_result.to_pb2()) # Closes the classifier explicitly when the classifier is not used in # a context. classifier.close() @@ -214,8 +209,8 @@ class ImageClassifierTest(parameterized.TestCase): # Performs image classification on the input. image_result = classifier.classify(self.test_image) # Comparing results. - _assert_proto_equals(self, image_result.to_pb2(), - expected_classification_result.to_pb2()) + test_utils.assertProtoEqual(self, image_result.to_pb2(), + expected_classification_result.to_pb2()) def test_classify_succeeds_with_region_of_interest(self): base_options = _BaseOptions(model_asset_path=self.model_path) @@ -232,8 +227,8 @@ class ImageClassifierTest(parameterized.TestCase): # Performs image classification on the input. image_result = classifier.classify(test_image, roi) # Comparing results. - _assert_proto_equals(self, image_result.to_pb2(), - _generate_soccer_ball_results(0).to_pb2()) + test_utils.assertProtoEqual(self, image_result.to_pb2(), + _generate_soccer_ball_results(0).to_pb2()) def test_score_threshold_option(self): custom_classifier_options = _ClassifierOptions( @@ -401,8 +396,9 @@ class ImageClassifierTest(parameterized.TestCase): for timestamp in range(0, 300, 30): classification_result = classifier.classify_for_video( self.test_image, timestamp) - _assert_proto_equals(self, classification_result.to_pb2(), - _generate_burger_results(timestamp).to_pb2()) + test_utils.assertProtoEqual( + self, classification_result.to_pb2(), + _generate_burger_results(timestamp).to_pb2()) def test_classify_for_video_succeeds_with_region_of_interest(self): custom_classifier_options = _ClassifierOptions(max_results=1) @@ -420,8 +416,9 @@ class ImageClassifierTest(parameterized.TestCase): for timestamp in range(0, 300, 30): classification_result = classifier.classify_for_video( test_image, timestamp, roi) - _assert_proto_equals(self, classification_result.to_pb2(), - _generate_soccer_ball_results(timestamp).to_pb2()) + test_utils.assertProtoEqual( + self, classification_result.to_pb2(), + _generate_soccer_ball_results(timestamp).to_pb2()) def test_calling_classify_in_live_stream_mode(self): options = _ImageClassifierOptions( @@ -463,8 +460,8 @@ class ImageClassifierTest(parameterized.TestCase): def check_result(result: _ClassificationResult, output_image: _Image, timestamp_ms: int): - _assert_proto_equals(self, result.to_pb2(), - expected_result_fn(timestamp_ms).to_pb2()) + test_utils.assertProtoEqual( + self, result.to_pb2(), expected_result_fn(timestamp_ms).to_pb2()) self.assertTrue( np.array_equal(output_image.numpy_view(), self.test_image.numpy_view())) @@ -493,8 +490,9 @@ class ImageClassifierTest(parameterized.TestCase): def check_result(result: _ClassificationResult, output_image: _Image, timestamp_ms: int): - _assert_proto_equals(self, result.to_pb2(), - _generate_soccer_ball_results(timestamp_ms).to_pb2()) + test_utils.assertProtoEqual( + self, result.to_pb2(), + _generate_soccer_ball_results(timestamp_ms).to_pb2()) self.assertEqual(output_image.width, test_image.width) self.assertEqual(output_image.height, test_image.height) self.assertLess(observed_timestamp_ms, timestamp_ms) From f315e6dc5824dcb3fe8cd39655b4441806ecc1eb Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Thu, 27 Oct 2022 10:14:34 -0700 Subject: [PATCH 083/125] Workaround to solve "-lphtread" linker error on Android. PiperOrigin-RevId: 484285361 --- WORKSPACE | 4 +++ ...oogle_sentencepiece_no_gflag_no_gtest.diff | 34 +++++++++++++++++++ 2 files changed, 38 insertions(+) create mode 100644 third_party/com_google_sentencepiece_no_gflag_no_gtest.diff diff --git a/WORKSPACE b/WORKSPACE index 146916c5c..5a47cf6b7 100644 --- a/WORKSPACE +++ b/WORKSPACE @@ -172,6 +172,10 @@ http_archive( urls = [ "https://github.com/google/sentencepiece/archive/1.0.0.zip", ], + patches = [ + "//third_party:com_google_sentencepiece_no_gflag_no_gtest.diff", + ], + patch_args = ["-p1"], repo_mapping = {"@com_google_glog" : "@com_github_glog_glog"}, ) diff --git a/third_party/com_google_sentencepiece_no_gflag_no_gtest.diff b/third_party/com_google_sentencepiece_no_gflag_no_gtest.diff new file mode 100644 index 000000000..a084d9262 --- /dev/null +++ b/third_party/com_google_sentencepiece_no_gflag_no_gtest.diff @@ -0,0 +1,34 @@ +diff --git a/src/BUILD b/src/BUILD +index b4298d2..f3877a3 100644 +--- a/src/BUILD ++++ b/src/BUILD +@@ -71,9 +71,7 @@ cc_library( + ":common", + ":sentencepiece_cc_proto", + ":sentencepiece_model_cc_proto", +- "@com_github_gflags_gflags//:gflags", + "@com_google_glog//:glog", +- "@com_google_googletest//:gtest", + "@com_google_absl//absl/memory", + "@com_google_absl//absl/strings", + "@com_google_absl//absl/container:flat_hash_map", +diff --git a/src/normalizer.h b/src/normalizer.h +index c16ac16..2af58be 100644 +--- a/src/normalizer.h ++++ b/src/normalizer.h +@@ -21,7 +21,6 @@ + #include + #include + +-#include "gtest/gtest_prod.h" + #include "absl/strings/string_view.h" + #include "third_party/darts_clone/include/darts.h" + #include "src/common.h" +@@ -97,7 +96,6 @@ class Normalizer { + friend class Builder; + + private: +- FRIEND_TEST(NormalizerTest, EncodeDecodePrecompiledCharsMapTest); + + void Init(); + From ee84e447b281342776b0aaf21826794f5b9ecdf7 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 27 Oct 2022 11:06:44 -0700 Subject: [PATCH 084/125] Internal change PiperOrigin-RevId: 484299808 --- mediapipe/framework/api2/builder.h | 18 ++++++++++++++++-- 1 file changed, 16 insertions(+), 2 deletions(-) diff --git a/mediapipe/framework/api2/builder.h b/mediapipe/framework/api2/builder.h index 82905d2f5..7dce211c8 100644 --- a/mediapipe/framework/api2/builder.h +++ b/mediapipe/framework/api2/builder.h @@ -289,8 +289,15 @@ class NodeBase { template T& GetOptions() { + return GetOptions(T::ext); + } + + // Use this API when the proto extension does not follow the "ext" naming + // convention. + template + auto& GetOptions(const E& extension) { options_used_ = true; - return *options_.MutableExtension(T::ext); + return *options_.MutableExtension(extension); } protected: @@ -386,8 +393,15 @@ class PacketGenerator { template T& GetOptions() { + return GetOptions(T::ext); + } + + // Use this API when the proto extension does not follow the "ext" naming + // convention. + template + auto& GetOptions(const E& extension) { options_used_ = true; - return *options_.MutableExtension(T::ext); + return *options_.MutableExtension(extension); } template From fc1d75cc99dc4bfc619225e2dd476a64fd357cc7 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 27 Oct 2022 11:14:42 -0700 Subject: [PATCH 085/125] Add CombinedPredictionCalculator. PiperOrigin-RevId: 484301880 --- .../gesture_recognizer/calculators/BUILD | 43 +++ .../combined_prediction_calculator.cc | 187 +++++++++++ .../combined_prediction_calculator.proto | 41 +++ .../combined_prediction_calculator_test.cc | 315 ++++++++++++++++++ 4 files changed, 586 insertions(+) create mode 100644 mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.cc create mode 100644 mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.proto create mode 100644 mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator_test.cc diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/BUILD b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/BUILD index 08f7f45d0..8c2c2e593 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/BUILD +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/BUILD @@ -93,3 +93,46 @@ cc_test( "@com_google_absl//absl/strings", ], ) + +mediapipe_proto_library( + name = "combined_prediction_calculator_proto", + srcs = ["combined_prediction_calculator.proto"], + visibility = ["//visibility:public"], + deps = [ + "//mediapipe/framework:calculator_options_proto", + "//mediapipe/framework:calculator_proto", + ], +) + +cc_library( + name = "combined_prediction_calculator", + srcs = ["combined_prediction_calculator.cc"], + deps = [ + ":combined_prediction_calculator_cc_proto", + "//mediapipe/framework:calculator_framework", + "//mediapipe/framework:collection", + "//mediapipe/framework/api2:node", + "//mediapipe/framework/api2:packet", + "//mediapipe/framework/api2:port", + "//mediapipe/framework/formats:classification_cc_proto", + "@com_google_absl//absl/container:btree", + "@com_google_absl//absl/memory", + "@com_google_absl//absl/status", + "@com_google_absl//absl/strings:str_format", + ], + alwayslink = 1, +) + +cc_test( + name = "combined_prediction_calculator_test", + srcs = ["combined_prediction_calculator_test.cc"], + deps = [ + ":combined_prediction_calculator", + "//mediapipe/framework:calculator_framework", + "//mediapipe/framework:calculator_runner", + "//mediapipe/framework/formats:classification_cc_proto", + "//mediapipe/framework/port:gtest", + "//mediapipe/framework/port:gtest_main", + "@com_google_absl//absl/strings", + ], +) diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.cc new file mode 100644 index 000000000..c7147ea6e --- /dev/null +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.cc @@ -0,0 +1,187 @@ +/* Copyright 2022 The MediaPipe Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +#include +#include +#include +#include + +#include "absl/container/btree_map.h" +#include "absl/memory/memory.h" +#include "absl/status/status.h" +#include "absl/strings/str_format.h" +#include "mediapipe/framework/api2/node.h" +#include "mediapipe/framework/api2/packet.h" +#include "mediapipe/framework/api2/port.h" +#include "mediapipe/framework/calculator_framework.h" +#include "mediapipe/framework/collection.h" +#include "mediapipe/framework/formats/classification.pb.h" +#include "mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.pb.h" + +namespace mediapipe { +namespace api2 { +namespace { + +constexpr char kPredictionTag[] = "PREDICTION"; + +Classification GetMaxScoringClassification( + const ClassificationList& classifications) { + Classification max_classification; + max_classification.set_score(0); + for (const auto& input : classifications.classification()) { + if (max_classification.score() < input.score()) { + max_classification = input; + } + } + return max_classification; +} + +float GetScoreThreshold( + const std::string& input_label, + const absl::btree_map& classwise_thresholds, + const std::string& background_label, const float default_threshold) { + float threshold = default_threshold; + auto it = classwise_thresholds.find(input_label); + if (it != classwise_thresholds.end()) { + threshold = it->second; + } + return threshold; +} + +std::unique_ptr GetWinningPrediction( + const ClassificationList& classification_list, + const absl::btree_map& classwise_thresholds, + const std::string& background_label, const float default_threshold) { + auto prediction_list = std::make_unique(); + if (classification_list.classification().empty()) { + return prediction_list; + } + Classification& prediction = *prediction_list->add_classification(); + auto argmax_prediction = GetMaxScoringClassification(classification_list); + float argmax_prediction_thresh = + GetScoreThreshold(argmax_prediction.label(), classwise_thresholds, + background_label, default_threshold); + if (argmax_prediction.score() >= argmax_prediction_thresh) { + prediction.set_label(argmax_prediction.label()); + prediction.set_score(argmax_prediction.score()); + } else { + for (const auto& input : classification_list.classification()) { + if (input.label() == background_label) { + prediction.set_label(input.label()); + prediction.set_score(input.score()); + break; + } + } + } + return prediction_list; +} + +} // namespace + +// This calculator accepts multiple ClassificationList input streams. Each +// ClassificationList should contain classifications with labels and +// corresponding softmax scores. The calculator computes the best prediction for +// each ClassificationList input stream via argmax and thresholding. Thresholds +// for all classes can be specified in the +// `CombinedPredictionCalculatorOptions`, along with a default global +// threshold. +// Please note that for this calculator to work as designed, the class names +// other than the background class in the ClassificationList objects must be +// different, but the background class name has to be the same. This background +// label name can be set via `background_label` in +// `CombinedPredictionCalculatorOptions`. +// The ClassificationList in the PREDICTION output stream contains the label of +// the winning class and corresponding softmax score. If none of the +// ClassificationList objects has a non-background winning class, the output +// contains the background class and score of the background class in the first +// ClassificationList. If multiple ClassificationList objects have a +// non-background winning class, the output contains the winning prediction from +// the ClassificationList with the highest priority. Priority is in decreasing +// order of input streams to the graph node using this calculator. +// Input: +// At least one stream with ClassificationList. +// Output: +// PREDICTION - A ClassificationList with the winning label as the only item. +// +// Usage example: +// node { +// calculator: "CombinedPredictionCalculator" +// input_stream: "classification_list_0" +// input_stream: "classification_list_1" +// output_stream: "PREDICTION:prediction" +// options { +// [mediapipe.CombinedPredictionCalculatorOptions.ext] { +// class { +// label: "A" +// score_threshold: 0.7 +// } +// default_global_threshold: 0.1 +// background_label: "B" +// } +// } +// } + +class CombinedPredictionCalculator : public Node { + public: + static constexpr Input::Multiple kClassificationListIn{ + ""}; + static constexpr Output kPredictionOut{"PREDICTION"}; + MEDIAPIPE_NODE_CONTRACT(kClassificationListIn, kPredictionOut); + + absl::Status Open(CalculatorContext* cc) override { + options_ = cc->Options(); + for (const auto& input : options_.class_()) { + classwise_thresholds_[input.label()] = input.score_threshold(); + } + classwise_thresholds_[options_.background_label()] = 0; + return absl::OkStatus(); + } + + absl::Status Process(CalculatorContext* cc) override { + // After loop, if have winning prediction return. Otherwise empty packet. + std::unique_ptr first_winning_prediction = nullptr; + auto collection = kClassificationListIn(cc); + for (int idx = 0; idx < collection.Count(); ++idx) { + const auto& packet = collection[idx]; + if (packet.IsEmpty()) { + continue; + } + auto prediction = GetWinningPrediction( + packet.Get(), classwise_thresholds_, options_.background_label(), + options_.default_global_threshold()); + if (prediction->classification(0).label() != + options_.background_label()) { + kPredictionOut(cc).Send(std::move(prediction)); + return absl::OkStatus(); + } + if (first_winning_prediction == nullptr) { + first_winning_prediction = std::move(prediction); + } + } + if (first_winning_prediction != nullptr) { + kPredictionOut(cc).Send(std::move(first_winning_prediction)); + } + return absl::OkStatus(); + } + + private: + CombinedPredictionCalculatorOptions options_; + absl::btree_map classwise_thresholds_; +}; + +MEDIAPIPE_REGISTER_NODE(CombinedPredictionCalculator); + +} // namespace api2 +} // namespace mediapipe diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.proto b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.proto new file mode 100644 index 000000000..730e7dd78 --- /dev/null +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.proto @@ -0,0 +1,41 @@ +/* Copyright 2022 The MediaPipe Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +syntax = "proto2"; + +package mediapipe; + +import "mediapipe/framework/calculator.proto"; + +message CombinedPredictionCalculatorOptions { + extend mediapipe.CalculatorOptions { + optional CombinedPredictionCalculatorOptions ext = 483738635; + } + + message Class { + optional string label = 1; + optional float score_threshold = 2; + } + + // List of classes with score thresholds. + repeated Class class = 1; + + // Default score threshold applied to a label. + optional float default_global_threshold = 2 [default = 0]; + + // Name of the background class whose input scores will be ignored while + // thresholding. + optional string background_label = 3; +} diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator_test.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator_test.cc new file mode 100644 index 000000000..ecf49795b --- /dev/null +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator_test.cc @@ -0,0 +1,315 @@ +/* Copyright 2022 The MediaPipe Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +#include +#include +#include +#include +#include +#include + +#include "absl/strings/string_view.h" +#include "absl/strings/substitute.h" +#include "mediapipe/framework/calculator_framework.h" +#include "mediapipe/framework/calculator_runner.h" +#include "mediapipe/framework/formats/classification.pb.h" +#include "mediapipe/framework/port/status_matchers.h" + +namespace mediapipe { + +namespace { + +constexpr char kPredictionTag[] = "PREDICTION"; + +std::unique_ptr BuildNodeRunnerWithOptions( + float drama_thresh, float llama_thresh, float bazinga_thresh, + float joy_thresh, float peace_thresh) { + constexpr absl::string_view kCalculatorProto = R"pb( + calculator: "CombinedPredictionCalculator" + input_stream: "custom_softmax_scores" + input_stream: "canned_softmax_scores" + output_stream: "PREDICTION:prediction" + options { + [mediapipe.CombinedPredictionCalculatorOptions.ext] { + class { label: "CustomDrama" score_threshold: $0 } + class { label: "CustomLlama" score_threshold: $1 } + class { label: "CannedBazinga" score_threshold: $2 } + class { label: "CannedJoy" score_threshold: $3 } + class { label: "CannedPeace" score_threshold: $4 } + background_label: "Negative" + } + } + )pb"; + auto runner = std::make_unique( + absl::Substitute(kCalculatorProto, drama_thresh, llama_thresh, + bazinga_thresh, joy_thresh, peace_thresh)); + return runner; +} + +std::unique_ptr BuildCustomScoreInput( + const float negative_score, const float drama_score, + const float llama_score) { + auto custom_scores = std::make_unique(); + auto custom_negative = custom_scores->add_classification(); + custom_negative->set_label("Negative"); + custom_negative->set_score(negative_score); + auto drama = custom_scores->add_classification(); + drama->set_label("CustomDrama"); + drama->set_score(drama_score); + auto llama = custom_scores->add_classification(); + llama->set_label("CustomLlama"); + llama->set_score(llama_score); + return custom_scores; +} + +std::unique_ptr BuildCannedScoreInput( + const float negative_score, const float bazinga_score, + const float joy_score, const float peace_score) { + auto canned_scores = std::make_unique(); + auto canned_negative = canned_scores->add_classification(); + canned_negative->set_label("Negative"); + canned_negative->set_score(negative_score); + auto bazinga = canned_scores->add_classification(); + bazinga->set_label("CannedBazinga"); + bazinga->set_score(bazinga_score); + auto joy = canned_scores->add_classification(); + joy->set_label("CannedJoy"); + joy->set_score(joy_score); + auto peace = canned_scores->add_classification(); + peace->set_label("CannedPeace"); + peace->set_score(peace_score); + return canned_scores; +} + +TEST(CombinedPredictionCalculatorPacketTest, + CustomEmpty_CannedEmpty_ResultIsEmpty) { + auto runner = BuildNodeRunnerWithOptions( + /*drama_thresh=*/0.0, /*llama_thresh=*/0.0, /*bazinga_thresh=*/0.0, + /*joy_thresh=*/0.0, /*peace_thresh=*/0.0); + MP_ASSERT_OK(runner->Run()) << "Calculator execution failed."; + EXPECT_THAT(runner->Outputs().Tag("PREDICTION").packets, testing::IsEmpty()); +} + +TEST(CombinedPredictionCalculatorPacketTest, + CustomEmpty_CannedNotEmpty_ResultIsCanned) { + auto runner = BuildNodeRunnerWithOptions( + /*drama_thresh=*/0.0, /*llama_thresh=*/0.0, /*bazinga_thresh=*/0.9, + /*joy_thresh=*/0.5, /*peace_thresh=*/0.8); + auto canned_scores = BuildCannedScoreInput( + /*negative_score=*/0.1, + /*bazinga_score=*/0.1, /*joy_score=*/0.6, /*peace_score=*/0.2); + runner->MutableInputs()->Index(1).packets.push_back( + Adopt(canned_scores.release()).At(Timestamp(1))); + MP_ASSERT_OK(runner->Run()) << "Calculator execution failed."; + + auto output_prediction_packets = + runner->Outputs().Tag(kPredictionTag).packets; + ASSERT_EQ(output_prediction_packets.size(), 1); + Classification output_prediction = + output_prediction_packets[0].Get().classification(0); + + EXPECT_EQ(output_prediction.label(), "CannedJoy"); + EXPECT_NEAR(output_prediction.score(), 0.6, 1e-4); +} + +TEST(CombinedPredictionCalculatorPacketTest, + CustomNotEmpty_CannedEmpty_ResultIsCustom) { + auto runner = BuildNodeRunnerWithOptions( + /*drama_thresh=*/0.3, /*llama_thresh=*/0.5, /*bazinga_thresh=*/0.0, + /*joy_thresh=*/0.0, /*peace_thresh=*/0.0); + auto custom_scores = + BuildCustomScoreInput(/*negative_score=*/0.1, + /*drama_score=*/0.2, /*llama_score=*/0.7); + runner->MutableInputs()->Index(0).packets.push_back( + Adopt(custom_scores.release()).At(Timestamp(1))); + MP_ASSERT_OK(runner->Run()) << "Calculator execution failed."; + + auto output_prediction_packets = + runner->Outputs().Tag(kPredictionTag).packets; + ASSERT_EQ(output_prediction_packets.size(), 1); + Classification output_prediction = + output_prediction_packets[0].Get().classification(0); + + EXPECT_EQ(output_prediction.label(), "CustomLlama"); + EXPECT_NEAR(output_prediction.score(), 0.7, 1e-4); +} + +struct CombinedPredictionCalculatorTestCase { + std::string test_name; + float custom_negative_score; + float drama_score; + float llama_score; + float drama_thresh; + float llama_thresh; + float canned_negative_score; + float bazinga_score; + float joy_score; + float peace_score; + float bazinga_thresh; + float joy_thresh; + float peace_thresh; + std::string max_scoring_label; + float max_score; +}; + +using CombinedPredictionCalculatorTest = + testing::TestWithParam; + +TEST_P(CombinedPredictionCalculatorTest, OutputsCorrectResult) { + const CombinedPredictionCalculatorTestCase& test_case = GetParam(); + + auto runner = BuildNodeRunnerWithOptions( + test_case.drama_thresh, test_case.llama_thresh, test_case.bazinga_thresh, + test_case.joy_thresh, test_case.peace_thresh); + + auto custom_scores = + BuildCustomScoreInput(test_case.custom_negative_score, + test_case.drama_score, test_case.llama_score); + + runner->MutableInputs()->Index(0).packets.push_back( + Adopt(custom_scores.release()).At(Timestamp(1))); + + auto canned_scores = BuildCannedScoreInput( + test_case.canned_negative_score, test_case.bazinga_score, + test_case.joy_score, test_case.peace_score); + runner->MutableInputs()->Index(1).packets.push_back( + Adopt(canned_scores.release()).At(Timestamp(1))); + + MP_ASSERT_OK(runner->Run()) << "Calculator execution failed."; + + auto output_prediction_packets = + runner->Outputs().Tag(kPredictionTag).packets; + ASSERT_EQ(output_prediction_packets.size(), 1); + Classification output_prediction = + output_prediction_packets[0].Get().classification(0); + + EXPECT_EQ(output_prediction.label(), test_case.max_scoring_label); + EXPECT_NEAR(output_prediction.score(), test_case.max_score, 1e-4); +} + +INSTANTIATE_TEST_CASE_P( + CombinedPredictionCalculatorTests, CombinedPredictionCalculatorTest, + testing::ValuesIn({ + { + .test_name = "TestCustomDramaWinnnerWith_HighCanned_Thresh", + .custom_negative_score = 0.1, + .drama_score = 0.5, + .llama_score = 0.3, + .drama_thresh = 0.25, + .llama_thresh = 0.7, + .canned_negative_score = 0.1, + .bazinga_score = 0.3, + .joy_score = 0.3, + .peace_score = 0.3, + .bazinga_thresh = 0.7, + .joy_thresh = 0.7, + .peace_thresh = 0.7, + .max_scoring_label = "CustomDrama", + .max_score = 0.5, + }, + { + .test_name = "TestCannedWinnerWith_HighCustom_ZeroCanned_Thresh", + .custom_negative_score = 0.1, + .drama_score = 0.3, + .llama_score = 0.6, + .drama_thresh = 0.4, + .llama_thresh = 0.8, + .canned_negative_score = 0.1, + .bazinga_score = 0.4, + .joy_score = 0.3, + .peace_score = 0.2, + .bazinga_thresh = 0.0, + .joy_thresh = 0.0, + .peace_thresh = 0.0, + .max_scoring_label = "CannedBazinga", + .max_score = 0.4, + }, + { + .test_name = "TestNegativeWinnerWith_LowCustom_HighCanned_Thresh", + .custom_negative_score = 0.5, + .drama_score = 0.1, + .llama_score = 0.4, + .drama_thresh = 0.1, + .llama_thresh = 0.05, + .canned_negative_score = 0.1, + .bazinga_score = 0.3, + .joy_score = 0.3, + .peace_score = 0.3, + .bazinga_thresh = 0.7, + .joy_thresh = 0.7, + .peace_thresh = 0.7, + .max_scoring_label = "Negative", + .max_score = 0.5, + }, + { + .test_name = "TestNegativeWinnerWith_HighCustom_HighCanned_Thresh", + .custom_negative_score = 0.8, + .drama_score = 0.1, + .llama_score = 0.1, + .drama_thresh = 0.25, + .llama_thresh = 0.7, + .canned_negative_score = 0.1, + .bazinga_score = 0.3, + .joy_score = 0.3, + .peace_score = 0.3, + .bazinga_thresh = 0.7, + .joy_thresh = 0.7, + .peace_thresh = 0.7, + .max_scoring_label = "Negative", + .max_score = 0.8, + }, + { + .test_name = "TestNegativeWinnerWith_HighCustom_HighCannedThresh2", + .custom_negative_score = 0.1, + .drama_score = 0.2, + .llama_score = 0.7, + .drama_thresh = 1.1, + .llama_thresh = 1.1, + .canned_negative_score = 0.1, + .bazinga_score = 0.3, + .joy_score = 0.3, + .peace_score = 0.3, + .bazinga_thresh = 0.7, + .joy_thresh = 0.7, + .peace_thresh = 0.7, + .max_scoring_label = "Negative", + .max_score = 0.1, + }, + { + .test_name = "TestNegativeWinnerWith_HighCustom_HighCanned_Thresh3", + .custom_negative_score = 0.1, + .drama_score = 0.3, + .llama_score = 0.6, + .drama_thresh = 0.4, + .llama_thresh = 0.8, + .canned_negative_score = 0.3, + .bazinga_score = 0.2, + .joy_score = 0.3, + .peace_score = 0.2, + .bazinga_thresh = 0.5, + .joy_thresh = 0.5, + .peace_thresh = 0.5, + .max_scoring_label = "Negative", + .max_score = 0.1, + }, + }), + [](const testing::TestParamInfo< + CombinedPredictionCalculatorTest::ParamType>& info) { + return info.param.test_name; + }); + +} // namespace + +} // namespace mediapipe From abd1ff66c869bc4543f646c9bffcb5ed89c26d98 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 27 Oct 2022 15:30:56 -0700 Subject: [PATCH 086/125] Fix https://github.com/google/mediapipe/issues/3784 PiperOrigin-RevId: 484365654 --- mediapipe/modules/face_geometry/libs/effect_renderer.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mediapipe/modules/face_geometry/libs/effect_renderer.cc b/mediapipe/modules/face_geometry/libs/effect_renderer.cc index 27a54e011..73f473084 100644 --- a/mediapipe/modules/face_geometry/libs/effect_renderer.cc +++ b/mediapipe/modules/face_geometry/libs/effect_renderer.cc @@ -161,7 +161,7 @@ class Texture { ~Texture() { if (is_owned_) { - glDeleteProgram(handle_); + glDeleteTextures(1, &handle_); } } From de5fe27e05f20b52b5394e681f116210db9715d3 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 27 Oct 2022 19:06:04 -0700 Subject: [PATCH 087/125] Modified internal dependencies. PiperOrigin-RevId: 484407262 --- mediapipe/util/tflite/BUILD | 47 ++++++++++------------ mediapipe/util/tflite/tflite_gpu_runner.cc | 17 ++++---- mediapipe/util/tflite/tflite_gpu_runner.h | 17 ++++---- 3 files changed, 39 insertions(+), 42 deletions(-) diff --git a/mediapipe/util/tflite/BUILD b/mediapipe/util/tflite/BUILD index 9d37b60a0..e9b8bfa03 100644 --- a/mediapipe/util/tflite/BUILD +++ b/mediapipe/util/tflite/BUILD @@ -84,33 +84,28 @@ cc_library( "//conditions:default": ["tflite_gpu_runner.h"], }), deps = select({ - "//mediapipe:ios": [], - "//mediapipe:macos": [], - "//conditions:default": [ - "@com_google_absl//absl/strings", - "//mediapipe/framework/port:ret_check", - "//mediapipe/framework/port:status", - "//mediapipe/framework/port:statusor", - "@org_tensorflow//tensorflow/lite:framework", - "@org_tensorflow//tensorflow/lite/delegates/gpu:api", - "@org_tensorflow//tensorflow/lite/delegates/gpu/common:model", - "@org_tensorflow//tensorflow/lite/delegates/gpu/common:model_builder", - "@org_tensorflow//tensorflow/lite/delegates/gpu/gl:api2", - ], - "//mediapipe:android": [ - "@com_google_absl//absl/strings", - "//mediapipe/framework/port:ret_check", - "//mediapipe/framework/port:status", - "//mediapipe/framework/port:statusor", - "@org_tensorflow//tensorflow/lite:framework", - "@org_tensorflow//tensorflow/lite/delegates/gpu:api", - "@org_tensorflow//tensorflow/lite/delegates/gpu/cl:api", - "@org_tensorflow//tensorflow/lite/delegates/gpu/common:model", - "@org_tensorflow//tensorflow/lite/delegates/gpu/common:model_builder", - "@org_tensorflow//tensorflow/lite/delegates/gpu/gl:api2", - ], - }) + [ + "//mediapipe:ios": [], + "//mediapipe:macos": [], + "//conditions:default": [ + "@com_google_absl//absl/strings", + "//mediapipe/framework/port:ret_check", + "//mediapipe/framework/port:status", + "//mediapipe/framework/port:statusor", + "@org_tensorflow//tensorflow/lite:framework", + "@org_tensorflow//tensorflow/lite/delegates/gpu:api", + "@org_tensorflow//tensorflow/lite/delegates/gpu/common:model", + "@org_tensorflow//tensorflow/lite/delegates/gpu/common:model_builder", + "@org_tensorflow//tensorflow/lite/delegates/gpu/gl:api2", + ], + }) + + select({ + "//mediapipe:android": [ + "@org_tensorflow//tensorflow/lite/delegates/gpu/cl:api", + ], + "//conditions:default": [], + }) + [ "@com_google_absl//absl/status", + "//mediapipe/framework:port", "@org_tensorflow//tensorflow/lite/core/api", ], ) diff --git a/mediapipe/util/tflite/tflite_gpu_runner.cc b/mediapipe/util/tflite/tflite_gpu_runner.cc index 4c422835a..4e40975cb 100644 --- a/mediapipe/util/tflite/tflite_gpu_runner.cc +++ b/mediapipe/util/tflite/tflite_gpu_runner.cc @@ -34,7 +34,7 @@ // This code should be enabled as soon as TensorFlow version, which mediapipe // uses, will include this module. -#ifdef __ANDROID__ +#if defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) #include "tensorflow/lite/delegates/gpu/cl/api.h" #endif @@ -82,7 +82,7 @@ ObjectDef GetSSBOObjectDef(int channels) { return gpu_object_def; } -#ifdef __ANDROID__ +#if defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) cl::InferenceOptions GetClInferenceOptions(const InferenceOptions& options) { cl::InferenceOptions result{}; @@ -106,7 +106,7 @@ absl::Status VerifyShapes(const std::vector& actual, return absl::OkStatus(); } -#endif // __ANDROID__ +#endif // defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) } // namespace @@ -225,7 +225,7 @@ absl::Status TFLiteGPURunner::InitializeOpenGL( absl::Status TFLiteGPURunner::InitializeOpenCL( std::unique_ptr* builder) { -#ifdef __ANDROID__ +#if defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) cl::InferenceEnvironmentOptions env_options; if (!serialized_binary_cache_.empty()) { env_options.serialized_binary_cache = serialized_binary_cache_; @@ -254,11 +254,12 @@ absl::Status TFLiteGPURunner::InitializeOpenCL( return absl::OkStatus(); #else - return mediapipe::UnimplementedError("Currently only Android is supported"); -#endif // __ANDROID__ + return mediapipe::UnimplementedError( + "Currently only Android & ChromeOS are supported"); +#endif // defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) } -#ifdef __ANDROID__ +#if defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) absl::Status TFLiteGPURunner::InitializeOpenCLFromSerializedModel( std::unique_ptr* builder) { @@ -283,7 +284,7 @@ absl::StatusOr> TFLiteGPURunner::GetSerializedModel() { return serialized_model; } -#endif // __ANDROID__ +#endif // defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) } // namespace gpu } // namespace tflite diff --git a/mediapipe/util/tflite/tflite_gpu_runner.h b/mediapipe/util/tflite/tflite_gpu_runner.h index 88d3914f7..dfbc8d659 100644 --- a/mediapipe/util/tflite/tflite_gpu_runner.h +++ b/mediapipe/util/tflite/tflite_gpu_runner.h @@ -20,6 +20,7 @@ #include #include "absl/status/status.h" +#include "mediapipe/framework/port.h" #include "mediapipe/framework/port/status.h" #include "mediapipe/framework/port/statusor.h" #include "tensorflow/lite/core/api/op_resolver.h" @@ -28,9 +29,9 @@ #include "tensorflow/lite/delegates/gpu/gl/api2.h" #include "tensorflow/lite/model.h" -#ifdef __ANDROID__ +#if defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) #include "tensorflow/lite/delegates/gpu/cl/api.h" -#endif // __ANDROID__ +#endif // defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) namespace tflite { namespace gpu { @@ -83,7 +84,7 @@ class TFLiteGPURunner { return output_shape_from_model_; } -#ifdef __ANDROID__ +#if defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) void SetSerializedBinaryCache(std::vector&& cache) { serialized_binary_cache_ = std::move(cache); } @@ -98,26 +99,26 @@ class TFLiteGPURunner { } absl::StatusOr> GetSerializedModel(); -#endif // __ANDROID__ +#endif // defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) private: absl::Status InitializeOpenGL(std::unique_ptr* builder); absl::Status InitializeOpenCL(std::unique_ptr* builder); -#ifdef __ANDROID__ +#if defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) absl::Status InitializeOpenCLFromSerializedModel( std::unique_ptr* builder); -#endif // __ANDROID__ +#endif // defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) InferenceOptions options_; std::unique_ptr gl_environment_; -#ifdef __ANDROID__ +#if defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) std::unique_ptr cl_environment_; std::vector serialized_binary_cache_; std::vector serialized_model_; bool serialized_model_used_ = false; -#endif // __ANDROID__ +#endif // defined(__ANDROID__) || defined(MEDIAPIPE_CHROMIUMOS) // graph_gl_ is maintained temporarily and becomes invalid after runner_ is // ready From 87b201b1a38c63dc8bfb2c7dc535de095e53c7ed Mon Sep 17 00:00:00 2001 From: Mark McDonald Date: Thu, 27 Oct 2022 21:11:48 -0700 Subject: [PATCH 088/125] Adds a basic script for generating API docs from the `mediapipe` Python package This is pretty bare-bones for now, but I need something to start wiring up the rest of the automation. Plus this should be easy enough for anyone to riff on once it's in place. I couldn't find a great location within the existing directory structure for this, so LMK if it should be re-homed. PiperOrigin-RevId: 484426543 --- docs/BUILD | 14 +++++++ docs/build_py_api_docs.py | 85 +++++++++++++++++++++++++++++++++++++++ 2 files changed, 99 insertions(+) create mode 100644 docs/BUILD create mode 100644 docs/build_py_api_docs.py diff --git a/docs/BUILD b/docs/BUILD new file mode 100644 index 000000000..cb8794dab --- /dev/null +++ b/docs/BUILD @@ -0,0 +1,14 @@ +# Placeholder for internal Python strict binary compatibility macro. + +py_binary( + name = "build_py_api_docs", + srcs = ["build_py_api_docs.py"], + deps = [ + "//mediapipe", + "//third_party/py/absl:app", + "//third_party/py/absl/flags", + "//third_party/py/tensorflow_docs", + "//third_party/py/tensorflow_docs/api_generator:generate_lib", + "//third_party/py/tensorflow_docs/api_generator:public_api", + ], +) diff --git a/docs/build_py_api_docs.py b/docs/build_py_api_docs.py new file mode 100644 index 000000000..9911d0736 --- /dev/null +++ b/docs/build_py_api_docs.py @@ -0,0 +1,85 @@ +# Copyright 2022 The TensorFlow Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# ============================================================================== +r"""MediaPipe reference docs generation script. + +This script generates API reference docs for the `mediapipe` PIP package. + +$> pip install -U git+https://github.com/tensorflow/docs mediapipe +$> python build_py_api_docs.py +""" + +import os + +from absl import app +from absl import flags + +from tensorflow_docs.api_generator import generate_lib +from tensorflow_docs.api_generator import public_api + +try: + # mediapipe has not been set up to work with bazel yet, so catch & report. + import mediapipe # pytype: disable=import-error +except ImportError as e: + raise ImportError('Please `pip install mediapipe`.') from e + + +PROJECT_SHORT_NAME = 'mp' +PROJECT_FULL_NAME = 'MediaPipe' + +_OUTPUT_DIR = flags.DEFINE_string( + 'output_dir', + default='/tmp/generated_docs', + help='Where to write the resulting docs.') + +_URL_PREFIX = flags.DEFINE_string( + 'code_url_prefix', + 'https://github.com/google/mediapipe/tree/master/mediapipe', + 'The url prefix for links to code.') + +_SEARCH_HINTS = flags.DEFINE_bool( + 'search_hints', True, + 'Include metadata search hints in the generated files') + +_SITE_PATH = flags.DEFINE_string('site_path', '/mediapipe/api_docs/python', + 'Path prefix in the _toc.yaml') + + +def gen_api_docs(): + """Generates API docs for the mediapipe package.""" + + doc_generator = generate_lib.DocGenerator( + root_title=PROJECT_FULL_NAME, + py_modules=[(PROJECT_SHORT_NAME, mediapipe)], + base_dir=os.path.dirname(mediapipe.__file__), + code_url_prefix=_URL_PREFIX.value, + search_hints=_SEARCH_HINTS.value, + site_path=_SITE_PATH.value, + # This callback ensures that docs are only generated for objects that + # are explicitly imported in your __init__.py files. There are other + # options but this is a good starting point. + callbacks=[public_api.explicit_package_contents_filter], + ) + + doc_generator.build(_OUTPUT_DIR.value) + + print('Docs output to:', _OUTPUT_DIR.value) + + +def main(_): + gen_api_docs() + + +if __name__ == '__main__': + app.run(main) From b81b5a90354b079fd564aa23d31008e43377a2d3 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Fri, 28 Oct 2022 01:38:15 -0700 Subject: [PATCH 089/125] Added a test for min_gesture_confidence --- .../test/vision/gesture_recognizer_test.py | 18 ++++++++++++++++++ .../vision/core/image_processing_options.py | 2 +- .../tasks/python/vision/gesture_recognizer.py | 8 ++++---- 3 files changed, 23 insertions(+), 5 deletions(-) diff --git a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py index 3bf994a1d..cbee18170 100644 --- a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py +++ b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py @@ -224,6 +224,24 @@ class GestureRecognizerTest(parameterized.TestCase): self._assert_actual_result_approximately_matches_expected_result( recognition_result, expected_recognition_result) + def test_recognize_succeeds_with_min_gesture_confidence(self): + # Creates gesture recognizer. + base_options = _BaseOptions(model_asset_path=self.model_path) + options = _GestureRecognizerOptions(base_options=base_options, + min_gesture_confidence=2) + with _GestureRecognizer.create_from_options(options) as recognizer: + # Performs hand gesture recognition on the input. + recognition_result = recognizer.recognize(self.test_image) + expected_result = _get_expected_gesture_recognition_result( + _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX) + # Only contains one top scoring gesture. + self.assertLen(recognition_result.gestures[0].classifications, 1) + # Actual gesture with top score matches expected gesture. + actual_top_gesture = recognition_result.gestures[0].classifications[0] + expected_top_gesture = expected_result.gestures[0].classifications[0] + self.assertEqual(actual_top_gesture.index, expected_top_gesture.index) + self.assertEqual(actual_top_gesture.label, expected_top_gesture.label) + def test_recognize_succeeds_with_num_hands(self): # Creates gesture recognizer. base_options = _BaseOptions(model_asset_path=self.model_path) diff --git a/mediapipe/tasks/python/vision/core/image_processing_options.py b/mediapipe/tasks/python/vision/core/image_processing_options.py index 2a3a13088..1a519809c 100644 --- a/mediapipe/tasks/python/vision/core/image_processing_options.py +++ b/mediapipe/tasks/python/vision/core/image_processing_options.py @@ -30,7 +30,7 @@ class ImageProcessingOptions: Attributes: region_of_interest: The optional region-of-interest to crop from the image. If not specified, the full image is used. Coordinates must be in [0,1] - with 'left' < 'right' and 'top' < bottom. + with 'x_center' < 'width' and 'y_center' < height. rotation_degress: The rotation to apply to the image (or cropped region-of-interest), in degrees clockwise. The rotation must be a multiple (positive or negative) of 90°. diff --git a/mediapipe/tasks/python/vision/gesture_recognizer.py b/mediapipe/tasks/python/vision/gesture_recognizer.py index 0036aa877..11cb5c7b2 100644 --- a/mediapipe/tasks/python/vision/gesture_recognizer.py +++ b/mediapipe/tasks/python/vision/gesture_recognizer.py @@ -118,10 +118,10 @@ class GestureRecognizerOptions: base_options: _BaseOptions running_mode: _RunningMode = _RunningMode.IMAGE num_hands: Optional[int] = 1 - min_hand_detection_confidence: Optional[int] = 0.5 - min_hand_presence_confidence: Optional[int] = 0.5 - min_tracking_confidence: Optional[int] = 0.5 - min_gesture_confidence: Optional[int] = -1 + min_hand_detection_confidence: Optional[float] = 0.5 + min_hand_presence_confidence: Optional[float] = 0.5 + min_tracking_confidence: Optional[float] = 0.5 + min_gesture_confidence: Optional[float] = -1 result_callback: Optional[ Callable[[GestureRecognitionResult, image_module.Image, int], None]] = None From f4f8b11ffc43f276dbdf21309768073b68990411 Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Fri, 28 Oct 2022 10:53:01 -0700 Subject: [PATCH 090/125] Fix the comment. PiperOrigin-RevId: 484571254 --- mediapipe/calculators/core/end_loop_calculator.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mediapipe/calculators/core/end_loop_calculator.h b/mediapipe/calculators/core/end_loop_calculator.h index e40301e81..9f56657d0 100644 --- a/mediapipe/calculators/core/end_loop_calculator.h +++ b/mediapipe/calculators/core/end_loop_calculator.h @@ -50,7 +50,7 @@ namespace mediapipe { // calculator: "EndLoopWithOutputCalculator" // input_stream: "ITEM:output_of_loop_body" # ItemU @loop_internal_ts // input_stream: "BATCH_END:ext_ts" # Timestamp @loop_internal_ts -// output_stream: "OUTPUT:aggregated_result" # IterableU @ext_ts +// output_stream: "ITERABLE:aggregated_result" # IterableU @ext_ts // } template class EndLoopCalculator : public CalculatorBase { From c5c639d6348073f88c8e34fd322ce2385eac9019 Mon Sep 17 00:00:00 2001 From: Hadon Nash Date: Fri, 28 Oct 2022 11:44:31 -0700 Subject: [PATCH 091/125] Internal change PiperOrigin-RevId: 484583911 --- .../core/bypass_calculator_test.cc | 2 + mediapipe/framework/tool/switch_container.cc | 12 +- .../framework/tool/switch_container.proto | 5 +- .../framework/tool/switch_container_test.cc | 6 +- .../framework/tool/switch_demux_calculator.cc | 108 ++++++++++++++++-- .../framework/tool/switch_mux_calculator.cc | 2 +- 6 files changed, 114 insertions(+), 21 deletions(-) diff --git a/mediapipe/calculators/core/bypass_calculator_test.cc b/mediapipe/calculators/core/bypass_calculator_test.cc index 4d1cd8f79..224742a13 100644 --- a/mediapipe/calculators/core/bypass_calculator_test.cc +++ b/mediapipe/calculators/core/bypass_calculator_test.cc @@ -75,6 +75,7 @@ constexpr char kTestGraphConfig2[] = R"pb( output_stream: "FEDERATED_GAZE_OUTPUT:federated_gaze_output" options { [mediapipe.SwitchContainerOptions.ext] { + async_selection: true contained_node: { calculator: "AppearancesPassThroughSubgraph" } } } @@ -101,6 +102,7 @@ constexpr char kTestGraphConfig3[] = R"pb( output_stream: "FEDERATED_GAZE_OUTPUT:federated_gaze_output" options { [mediapipe.SwitchContainerOptions.ext] { + async_selection: true contained_node: { calculator: "BypassCalculator" node_options: { diff --git a/mediapipe/framework/tool/switch_container.cc b/mediapipe/framework/tool/switch_container.cc index 9439acf96..24a1e6fe7 100644 --- a/mediapipe/framework/tool/switch_container.cc +++ b/mediapipe/framework/tool/switch_container.cc @@ -105,10 +105,10 @@ CalculatorGraphConfig::Node* BuildMuxNode( // Returns a PacketSequencerCalculator node. CalculatorGraphConfig::Node* BuildTimestampNode(CalculatorGraphConfig* config, - bool synchronize_io) { + bool async_selection) { CalculatorGraphConfig::Node* result = config->add_node(); *result->mutable_calculator() = "PacketSequencerCalculator"; - if (synchronize_io) { + if (!async_selection) { *result->mutable_input_stream_handler()->mutable_input_stream_handler() = "DefaultInputStreamHandler"; } @@ -263,17 +263,17 @@ absl::StatusOr SwitchContainer::GetConfig( std::string enable_stream = "ENABLE:gate_enable"; // Add a PacketSequencerCalculator node for "SELECT" or "ENABLE" streams. - bool synchronize_io = + bool async_selection = Subgraph::GetOptions(options) - .synchronize_io(); + .async_selection(); if (HasTag(container_node.input_stream(), "SELECT")) { - select_node = BuildTimestampNode(&config, synchronize_io); + select_node = BuildTimestampNode(&config, async_selection); select_node->add_input_stream("INPUT:gate_select"); select_node->add_output_stream("OUTPUT:gate_select_timed"); select_stream = "SELECT:gate_select_timed"; } if (HasTag(container_node.input_stream(), "ENABLE")) { - enable_node = BuildTimestampNode(&config, synchronize_io); + enable_node = BuildTimestampNode(&config, async_selection); enable_node->add_input_stream("INPUT:gate_enable"); enable_node->add_output_stream("OUTPUT:gate_enable_timed"); enable_stream = "ENABLE:gate_enable_timed"; diff --git a/mediapipe/framework/tool/switch_container.proto b/mediapipe/framework/tool/switch_container.proto index a9c2d9094..2de5a7abf 100644 --- a/mediapipe/framework/tool/switch_container.proto +++ b/mediapipe/framework/tool/switch_container.proto @@ -25,6 +25,9 @@ message SwitchContainerOptions { // Activates channel 1 for enable = true, channel 0 otherwise. optional bool enable = 4; - // Use DefaultInputStreamHandler for muxing & demuxing. + // Use DefaultInputStreamHandler for demuxing. optional bool synchronize_io = 5; + + // Use ImmediateInputStreamHandler for channel selection. + optional bool async_selection = 6; } diff --git a/mediapipe/framework/tool/switch_container_test.cc b/mediapipe/framework/tool/switch_container_test.cc index de4aa0b14..b20979b10 100644 --- a/mediapipe/framework/tool/switch_container_test.cc +++ b/mediapipe/framework/tool/switch_container_test.cc @@ -252,6 +252,9 @@ TEST(SwitchContainerTest, ApplyToSubnodes) { input_stream: "INPUT:enable" input_stream: "TICK:foo" output_stream: "OUTPUT:switchcontainer__gate_enable_timed" + input_stream_handler { + input_stream_handler: "DefaultInputStreamHandler" + } } node { name: "switchcontainer__SwitchDemuxCalculator" @@ -306,7 +309,8 @@ TEST(SwitchContainerTest, ApplyToSubnodes) { // Shows the SwitchContainer container runs with a pair of simple subnodes. TEST(SwitchContainerTest, RunsWithSubnodes) { EXPECT_TRUE(SubgraphRegistry::IsRegistered("SwitchContainer")); - CalculatorGraphConfig supergraph = SubnodeContainerExample(); + CalculatorGraphConfig supergraph = + SubnodeContainerExample("async_selection: true"); MP_EXPECT_OK(tool::ExpandSubgraphs(&supergraph)); RunTestContainer(supergraph); } diff --git a/mediapipe/framework/tool/switch_demux_calculator.cc b/mediapipe/framework/tool/switch_demux_calculator.cc index b9ba2a0fb..c066d470a 100644 --- a/mediapipe/framework/tool/switch_demux_calculator.cc +++ b/mediapipe/framework/tool/switch_demux_calculator.cc @@ -14,6 +14,7 @@ #include #include +#include #include #include @@ -54,21 +55,47 @@ namespace mediapipe { // contained subgraph or calculator nodes. // class SwitchDemuxCalculator : public CalculatorBase { - static constexpr char kSelectTag[] = "SELECT"; - static constexpr char kEnableTag[] = "ENABLE"; - public: static absl::Status GetContract(CalculatorContract* cc); absl::Status Open(CalculatorContext* cc) override; absl::Status Process(CalculatorContext* cc) override; + private: + absl::Status RecordPackets(CalculatorContext* cc); + int ChannelIndex(Timestamp timestamp); + absl::Status SendActivePackets(CalculatorContext* cc); + private: int channel_index_; std::set channel_tags_; + using PacketQueue = std::map>; + PacketQueue input_queue_; + std::map channel_history_; }; REGISTER_CALCULATOR(SwitchDemuxCalculator); +namespace { +static constexpr char kSelectTag[] = "SELECT"; +static constexpr char kEnableTag[] = "ENABLE"; + +// Returns the last received timestamp for an input stream. +inline Timestamp SettledTimestamp(const InputStreamShard& input) { + return input.Value().Timestamp(); +} + +// Returns the last received timestamp for channel selection. +inline Timestamp ChannelSettledTimestamp(CalculatorContext* cc) { + Timestamp result = Timestamp::Done(); + if (cc->Inputs().HasTag(kEnableTag)) { + result = SettledTimestamp(cc->Inputs().Tag(kEnableTag)); + } else if (cc->Inputs().HasTag(kSelectTag)) { + result = SettledTimestamp(cc->Inputs().Tag(kSelectTag)); + } + return result; +} +} // namespace + absl::Status SwitchDemuxCalculator::GetContract(CalculatorContract* cc) { // Allow any one of kSelectTag, kEnableTag. cc->Inputs().Tag(kSelectTag).Set().Optional(); @@ -125,6 +152,7 @@ absl::Status SwitchDemuxCalculator::GetContract(CalculatorContract* cc) { absl::Status SwitchDemuxCalculator::Open(CalculatorContext* cc) { channel_index_ = tool::GetChannelIndex(*cc, channel_index_); channel_tags_ = ChannelTags(cc->Outputs().TagMap()); + channel_history_[Timestamp::Unstarted()] = channel_index_; // Relay side packets to all channels. // Note: This is necessary because Calculator::Open only proceeds when every @@ -164,21 +192,77 @@ absl::Status SwitchDemuxCalculator::Open(CalculatorContext* cc) { } absl::Status SwitchDemuxCalculator::Process(CalculatorContext* cc) { - // Update the input channel index if specified. - channel_index_ = tool::GetChannelIndex(*cc, channel_index_); + MP_RETURN_IF_ERROR(RecordPackets(cc)); + MP_RETURN_IF_ERROR(SendActivePackets(cc)); + return absl::OkStatus(); +} - // Relay packets and timestamps only to channel_index_. +// Enqueue all arriving packets and bounds. +absl::Status SwitchDemuxCalculator::RecordPackets(CalculatorContext* cc) { + // Enqueue any new arriving packets. for (const std::string& tag : channel_tags_) { for (int index = 0; index < cc->Inputs().NumEntries(tag); ++index) { - auto& input = cc->Inputs().Get(tag, index); - std::string output_tag = tool::ChannelTag(tag, channel_index_); - auto output_id = cc->Outputs().GetId(output_tag, index); - if (output_id.IsValid()) { - auto& output = cc->Outputs().Get(output_tag, index); - tool::Relay(input, &output); + auto input_id = cc->Inputs().GetId(tag, index); + Packet packet = cc->Inputs().Get(input_id).Value(); + if (packet.Timestamp() == cc->InputTimestamp()) { + input_queue_[input_id].push(packet); } } } + + // Enque any new input channel and its activation timestamp. + Timestamp channel_settled = ChannelSettledTimestamp(cc); + int new_channel_index = tool::GetChannelIndex(*cc, channel_index_); + if (channel_settled == cc->InputTimestamp() && + new_channel_index != channel_index_) { + channel_index_ = new_channel_index; + channel_history_[channel_settled] = channel_index_; + } + return absl::OkStatus(); +} + +// Returns the channel index for a Timestamp. +int SwitchDemuxCalculator::ChannelIndex(Timestamp timestamp) { + auto it = std::prev(channel_history_.upper_bound(timestamp)); + return it->second; +} + +// Dispatches all queued input packets with known channels. +absl::Status SwitchDemuxCalculator::SendActivePackets(CalculatorContext* cc) { + // Dispatch any queued input packets with a defined channel_index. + Timestamp channel_settled = ChannelSettledTimestamp(cc); + for (const std::string& tag : channel_tags_) { + for (int index = 0; index < cc->Inputs().NumEntries(tag); ++index) { + auto input_id = cc->Inputs().GetId(tag, index); + auto& queue = input_queue_[input_id]; + while (!queue.empty() && queue.front().Timestamp() <= channel_settled) { + int channel_index = ChannelIndex(queue.front().Timestamp()); + std::string output_tag = tool::ChannelTag(tag, channel_index); + auto output_id = cc->Outputs().GetId(output_tag, index); + if (output_id.IsValid()) { + cc->Outputs().Get(output_id).AddPacket(queue.front()); + } + queue.pop(); + } + } + } + + // Discard all select packets not needed for any remaining input packets. + Timestamp input_settled = Timestamp::Done(); + for (const std::string& tag : channel_tags_) { + for (int index = 0; index < cc->Inputs().NumEntries(tag); ++index) { + auto input_id = cc->Inputs().GetId(tag, index); + Timestamp stream_settled = SettledTimestamp(cc->Inputs().Get(input_id)); + if (!input_queue_[input_id].empty()) { + Timestamp stream_bound = input_queue_[input_id].front().Timestamp(); + stream_settled = + std::min(stream_settled, stream_bound.PreviousAllowedInStream()); + } + } + } + Timestamp input_bound = input_settled.NextAllowedInStream(); + auto history_bound = std::prev(channel_history_.upper_bound(input_bound)); + channel_history_.erase(channel_history_.begin(), history_bound); return absl::OkStatus(); } diff --git a/mediapipe/framework/tool/switch_mux_calculator.cc b/mediapipe/framework/tool/switch_mux_calculator.cc index 1a3136620..230544b6b 100644 --- a/mediapipe/framework/tool/switch_mux_calculator.cc +++ b/mediapipe/framework/tool/switch_mux_calculator.cc @@ -164,7 +164,7 @@ absl::Status SwitchMuxCalculator::Open(CalculatorContext* cc) { options_ = cc->Options(); channel_index_ = tool::GetChannelIndex(*cc, channel_index_); channel_tags_ = ChannelTags(cc->Inputs().TagMap()); - channel_history_[Timestamp::Unset()] = channel_index_; + channel_history_[Timestamp::Unstarted()] = channel_index_; // Relay side packets only from channel_index_. for (const std::string& tag : ChannelTags(cc->InputSidePackets().TagMap())) { From e16be2e8fa1275e4833f3001f79a4732d7dfb1ad Mon Sep 17 00:00:00 2001 From: Jiuqiang Tang Date: Fri, 28 Oct 2022 13:16:38 -0700 Subject: [PATCH 092/125] Implement the initial version of TensorsToAudioCalculator that supports ifft and inverse hann windowing. PiperOrigin-RevId: 484605092 --- mediapipe/calculators/tensor/BUILD | 50 +++++ .../tensor/audio_to_tensor_calculator.cc | 2 +- .../tensor/tensors_to_audio_calculator.cc | 197 ++++++++++++++++++ .../tensor/tensors_to_audio_calculator.proto | 29 +++ .../tensors_to_audio_calculator_test.cc | 149 +++++++++++++ 5 files changed, 426 insertions(+), 1 deletion(-) create mode 100644 mediapipe/calculators/tensor/tensors_to_audio_calculator.cc create mode 100644 mediapipe/calculators/tensor/tensors_to_audio_calculator.proto create mode 100644 mediapipe/calculators/tensor/tensors_to_audio_calculator_test.cc diff --git a/mediapipe/calculators/tensor/BUILD b/mediapipe/calculators/tensor/BUILD index 99b5b3e91..a966dd3fc 100644 --- a/mediapipe/calculators/tensor/BUILD +++ b/mediapipe/calculators/tensor/BUILD @@ -109,6 +109,56 @@ cc_test( ], ) +mediapipe_proto_library( + name = "tensors_to_audio_calculator_proto", + srcs = ["tensors_to_audio_calculator.proto"], + visibility = [ + "//mediapipe/framework:mediapipe_internal", + ], + deps = [ + "//mediapipe/framework:calculator_options_proto", + "//mediapipe/framework:calculator_proto", + ], +) + +cc_library( + name = "tensors_to_audio_calculator", + srcs = ["tensors_to_audio_calculator.cc"], + visibility = [ + "//mediapipe/framework:mediapipe_internal", + ], + deps = [ + ":tensors_to_audio_calculator_cc_proto", + "//mediapipe/framework:calculator_framework", + "//mediapipe/framework/api2:node", + "//mediapipe/framework/formats:matrix", + "//mediapipe/framework/formats:tensor", + "//mediapipe/framework/port:ret_check", + "@com_google_absl//absl/algorithm:container", + "@com_google_absl//absl/status", + "@com_google_audio_tools//audio/dsp:window_functions", + "@pffft", + ], + alwayslink = 1, +) + +cc_test( + name = "tensors_to_audio_calculator_test", + srcs = ["tensors_to_audio_calculator_test.cc"], + deps = [ + ":audio_to_tensor_calculator", + ":audio_to_tensor_calculator_cc_proto", + ":tensors_to_audio_calculator", + ":tensors_to_audio_calculator_cc_proto", + "//mediapipe/framework:calculator_framework", + "//mediapipe/framework/formats:matrix", + "//mediapipe/framework/port:gtest_main", + "//mediapipe/framework/port:parse_text_proto", + "@com_google_absl//absl/status", + "@com_google_absl//absl/strings", + ], +) + mediapipe_proto_library( name = "feedback_tensors_calculator_proto", srcs = ["feedback_tensors_calculator.proto"], diff --git a/mediapipe/calculators/tensor/audio_to_tensor_calculator.cc b/mediapipe/calculators/tensor/audio_to_tensor_calculator.cc index 59c129191..d0513518a 100644 --- a/mediapipe/calculators/tensor/audio_to_tensor_calculator.cc +++ b/mediapipe/calculators/tensor/audio_to_tensor_calculator.cc @@ -133,7 +133,7 @@ bool IsValidFftSize(int size) { // invocation. In the non-streaming mode, the vector contains all of the // output timestamps for an input audio buffer. // DC_AND_NYQUIST - std::pair @Optional. -// A pair of dc component and nyquest component. Only can be connected when +// A pair of dc component and nyquist component. Only can be connected when // the calculator performs fft (the fft_size is set in the calculator // options). // diff --git a/mediapipe/calculators/tensor/tensors_to_audio_calculator.cc b/mediapipe/calculators/tensor/tensors_to_audio_calculator.cc new file mode 100644 index 000000000..8da29bb69 --- /dev/null +++ b/mediapipe/calculators/tensor/tensors_to_audio_calculator.cc @@ -0,0 +1,197 @@ +// Copyright 2022 The MediaPipe Authors. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include +#include +#include +#include +#include +#include + +#include "absl/algorithm/container.h" +#include "absl/status/status.h" +#include "audio/dsp/window_functions.h" +#include "mediapipe/calculators/tensor/tensors_to_audio_calculator.pb.h" +#include "mediapipe/framework/api2/node.h" +#include "mediapipe/framework/calculator_framework.h" +#include "mediapipe/framework/formats/matrix.h" +#include "mediapipe/framework/formats/tensor.h" +#include "mediapipe/framework/port/ret_check.h" +#include "pffft.h" + +namespace mediapipe { +namespace api2 { +namespace { + +std::vector HannWindow(int window_size, bool sqrt_hann) { + std::vector hann_window(window_size); + audio_dsp::HannWindow().GetPeriodicSamples(window_size, &hann_window); + if (sqrt_hann) { + absl::c_transform(hann_window, hann_window.begin(), + [](double x) { return std::sqrt(x); }); + } + return hann_window; +} + +// Note that the InvHannWindow function may only work for 50% overlapping case. +std::vector InvHannWindow(int window_size, bool sqrt_hann) { + std::vector window = HannWindow(window_size, sqrt_hann); + std::vector inv_window(window.size()); + if (sqrt_hann) { + absl::c_copy(window, inv_window.begin()); + } else { + const int kHalfWindowSize = window.size() / 2; + absl::c_transform(window, inv_window.begin(), + [](double x) { return x * x; }); + for (int i = 0; i < kHalfWindowSize; ++i) { + double sum = inv_window[i] + inv_window[kHalfWindowSize + i]; + inv_window[i] = window[i] / sum; + inv_window[kHalfWindowSize + i] = window[kHalfWindowSize + i] / sum; + } + } + return inv_window; +} + +// PFFFT only supports transforms for inputs of length N of the form +// N = (2^a)*(3^b)*(5^c) where b >=0 and c >= 0 and a >= 5 for the real FFT. +bool IsValidFftSize(int size) { + if (size <= 0) { + return false; + } + constexpr int kFactors[] = {2, 3, 5}; + int factorization[] = {0, 0, 0}; + int n = static_cast(size); + for (int i = 0; i < 3; ++i) { + while (n % kFactors[i] == 0) { + n = n / kFactors[i]; + ++factorization[i]; + } + } + return factorization[0] >= 5 && n == 1; +} + +} // namespace + +// Converts 2D MediaPipe float Tensors to audio buffers. +// The calculator will perform ifft on the complex DFT and apply the window +// function (Inverse Hann) afterwards. The input 2D MediaPipe Tensor must +// have the DFT real parts in its first row and the DFT imagery parts in its +// second row. A valid "fft_size" must be set in the CalculatorOptions. +// +// Inputs: +// TENSORS - std::vector +// Vector containing a single Tensor that represents the audio's complex DFT +// results. +// DC_AND_NYQUIST - std::pair +// A pair of dc component and nyquist component. +// +// Outputs: +// AUDIO - mediapipe::Matrix +// The audio data represented as mediapipe::Matrix. +// +// Example: +// node { +// calculator: "TensorsToAudioCalculator" +// input_stream: "TENSORS:tensors" +// input_stream: "DC_AND_NYQUIST:dc_and_nyquist" +// output_stream: "AUDIO:audio" +// options { +// [mediapipe.AudioToTensorCalculatorOptions.ext] { +// fft_size: 256 +// } +// } +// } +class TensorsToAudioCalculator : public Node { + public: + static constexpr Input> kTensorsIn{"TENSORS"}; + static constexpr Input> kDcAndNyquistIn{ + "DC_AND_NYQUIST"}; + static constexpr Output kAudioOut{"AUDIO"}; + MEDIAPIPE_NODE_CONTRACT(kTensorsIn, kDcAndNyquistIn, kAudioOut); + + absl::Status Open(CalculatorContext* cc) override; + absl::Status Process(CalculatorContext* cc) override; + absl::Status Close(CalculatorContext* cc) override; + + private: + // The internal state of the FFT library. + PFFFT_Setup* fft_state_ = nullptr; + int fft_size_ = 0; + float inverse_fft_size_ = 0; + std::vector> input_dft_; + std::vector inv_fft_window_; + std::vector> fft_input_buffer_; + // pffft requires memory to work with to avoid using the stack. + std::vector> fft_workplace_; + std::vector> fft_output_; +}; + +absl::Status TensorsToAudioCalculator::Open(CalculatorContext* cc) { + const auto& options = + cc->Options(); + RET_CHECK(options.has_fft_size()) << "FFT size must be specified."; + RET_CHECK(IsValidFftSize(options.fft_size())) + << "FFT size must be of the form fft_size = (2^a)*(3^b)*(5^c) where b " + ">=0 and c >= 0 and a >= 5, the requested fft size is " + << options.fft_size(); + fft_size_ = options.fft_size(); + inverse_fft_size_ = 1.0f / fft_size_; + fft_state_ = pffft_new_setup(fft_size_, PFFFT_REAL); + input_dft_.resize(fft_size_); + inv_fft_window_ = InvHannWindow(fft_size_, /* sqrt_hann = */ false); + fft_input_buffer_.resize(fft_size_); + fft_workplace_.resize(fft_size_); + fft_output_.resize(fft_size_); + return absl::OkStatus(); +} + +absl::Status TensorsToAudioCalculator::Process(CalculatorContext* cc) { + if (kTensorsIn(cc).IsEmpty() || kDcAndNyquistIn(cc).IsEmpty()) { + return absl::OkStatus(); + } + const auto& input_tensors = *kTensorsIn(cc); + RET_CHECK_EQ(input_tensors.size(), 1); + RET_CHECK(input_tensors[0].element_type() == Tensor::ElementType::kFloat32); + auto view = input_tensors[0].GetCpuReadView(); + // DC's real part. + input_dft_[0] = kDcAndNyquistIn(cc)->first; + // Nyquist's real part is the penultimate element of the tensor buffer. + // pffft ignores the Nyquist's imagery part. No need to fetch the last value + // from the tensor buffer. + input_dft_[1] = *(view.buffer() + (fft_size_ - 2)); + std::memcpy(input_dft_.data() + 2, view.buffer(), + (fft_size_ - 2) * sizeof(float)); + pffft_transform_ordered(fft_state_, input_dft_.data(), fft_output_.data(), + fft_workplace_.data(), PFFFT_BACKWARD); + // Applies the inverse window function. + std::transform( + fft_output_.begin(), fft_output_.end(), inv_fft_window_.begin(), + fft_output_.begin(), + [this](float a, float b) { return a * b * inverse_fft_size_; }); + Matrix matrix = Eigen::Map(fft_output_.data(), 1, fft_output_.size()); + kAudioOut(cc).Send(std::move(matrix)); + return absl::OkStatus(); +} + +absl::Status TensorsToAudioCalculator::Close(CalculatorContext* cc) { + if (fft_state_) { + pffft_destroy_setup(fft_state_); + } + return absl::OkStatus(); +} + +MEDIAPIPE_REGISTER_NODE(TensorsToAudioCalculator); + +} // namespace api2 +} // namespace mediapipe diff --git a/mediapipe/calculators/tensor/tensors_to_audio_calculator.proto b/mediapipe/calculators/tensor/tensors_to_audio_calculator.proto new file mode 100644 index 000000000..907627125 --- /dev/null +++ b/mediapipe/calculators/tensor/tensors_to_audio_calculator.proto @@ -0,0 +1,29 @@ +// Copyright 2022 The MediaPipe Authors. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +syntax = "proto2"; + +package mediapipe; + +import "mediapipe/framework/calculator.proto"; + +message TensorsToAudioCalculatorOptions { + extend mediapipe.CalculatorOptions { + optional TensorsToAudioCalculatorOptions ext = 484297136; + } + + // Size of the fft in number of bins. If set, the calculator will do ifft + // on the input tensor. + optional int64 fft_size = 1; +} diff --git a/mediapipe/calculators/tensor/tensors_to_audio_calculator_test.cc b/mediapipe/calculators/tensor/tensors_to_audio_calculator_test.cc new file mode 100644 index 000000000..b332381c6 --- /dev/null +++ b/mediapipe/calculators/tensor/tensors_to_audio_calculator_test.cc @@ -0,0 +1,149 @@ +// Copyright 2022 The MediaPipe Authors. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include +#include +#include +#include + +#include "absl/status/status.h" +#include "absl/strings/substitute.h" +#include "mediapipe/calculators/tensor/audio_to_tensor_calculator.pb.h" +#include "mediapipe/calculators/tensor/tensors_to_audio_calculator.pb.h" +#include "mediapipe/framework/calculator_framework.h" +#include "mediapipe/framework/formats/matrix.h" +#include "mediapipe/framework/port/gtest.h" +#include "mediapipe/framework/port/parse_text_proto.h" +#include "mediapipe/framework/port/status_matchers.h" + +namespace mediapipe { +namespace { + +class TensorsToAudioCalculatorFftTest : public ::testing::Test { + protected: + // Creates an audio matrix containing a single sample of 1.0 at a specified + // offset. + Matrix CreateImpulseSignalData(int64 num_samples, int impulse_offset_idx) { + Matrix impulse = Matrix::Zero(1, num_samples); + impulse(0, impulse_offset_idx) = 1.0; + return impulse; + } + + void ConfigGraph(int num_samples, double sample_rate, int fft_size) { + graph_config_ = ParseTextProtoOrDie( + absl::Substitute(R"( + input_stream: "audio_in" + input_stream: "sample_rate" + output_stream: "audio_out" + node { + calculator: "AudioToTensorCalculator" + input_stream: "AUDIO:audio_in" + input_stream: "SAMPLE_RATE:sample_rate" + output_stream: "TENSORS:tensors" + output_stream: "DC_AND_NYQUIST:dc_and_nyquist" + options { + [mediapipe.AudioToTensorCalculatorOptions.ext] { + num_channels: 1 + num_samples: $0 + num_overlapping_samples: 0 + target_sample_rate: $1 + fft_size: $2 + } + } + } + node { + calculator: "TensorsToAudioCalculator" + input_stream: "TENSORS:tensors" + input_stream: "DC_AND_NYQUIST:dc_and_nyquist" + output_stream: "AUDIO:audio_out" + options { + [mediapipe.TensorsToAudioCalculatorOptions.ext] { + fft_size: $2 + } + } + } + )", + /*$0=*/num_samples, + /*$1=*/sample_rate, + /*$2=*/fft_size)); + tool::AddVectorSink("audio_out", &graph_config_, &audio_out_packets_); + } + + void RunGraph(const Matrix& input_data, double sample_rate) { + MP_ASSERT_OK(graph_.Initialize(graph_config_)); + MP_ASSERT_OK(graph_.StartRun({})); + MP_ASSERT_OK(graph_.AddPacketToInputStream( + "sample_rate", MakePacket(sample_rate).At(Timestamp(0)))); + MP_ASSERT_OK(graph_.AddPacketToInputStream( + "audio_in", MakePacket(input_data).At(Timestamp(0)))); + MP_ASSERT_OK(graph_.CloseAllInputStreams()); + MP_ASSERT_OK(graph_.WaitUntilDone()); + } + + std::vector audio_out_packets_; + CalculatorGraphConfig graph_config_; + CalculatorGraph graph_; +}; + +TEST_F(TensorsToAudioCalculatorFftTest, TestInvalidFftSize) { + ConfigGraph(320, 16000, 103); + MP_ASSERT_OK(graph_.Initialize(graph_config_)); + MP_ASSERT_OK(graph_.StartRun({})); + auto status = graph_.WaitUntilIdle(); + EXPECT_EQ(status.code(), absl::StatusCode::kInternal); + EXPECT_THAT(status.message(), + ::testing::HasSubstr("FFT size must be of the form")); +} + +TEST_F(TensorsToAudioCalculatorFftTest, TestImpulseSignalAtTheCenter) { + constexpr int sample_size = 320; + constexpr double sample_rate = 16000; + ConfigGraph(sample_size, sample_rate, 320); + + Matrix impulse_data = CreateImpulseSignalData(sample_size, sample_size / 2); + RunGraph(impulse_data, sample_rate); + ASSERT_EQ(1, audio_out_packets_.size()); + MP_ASSERT_OK(audio_out_packets_[0].ValidateAsType()); + // The impulse signal at the center is not affected by the window function. + EXPECT_EQ(audio_out_packets_[0].Get(), impulse_data); +} + +TEST_F(TensorsToAudioCalculatorFftTest, TestWindowedImpulseSignal) { + constexpr int sample_size = 320; + constexpr double sample_rate = 16000; + ConfigGraph(sample_size, sample_rate, 320); + Matrix impulse_data = CreateImpulseSignalData(sample_size, sample_size / 4); + RunGraph(impulse_data, sample_rate); + ASSERT_EQ(1, audio_out_packets_.size()); + MP_ASSERT_OK(audio_out_packets_[0].ValidateAsType()); + // As the impulse signal sits at the 1/4 of the hann window, the inverse + // window function reduces it by half. + EXPECT_EQ(audio_out_packets_[0].Get(), impulse_data / 2); +} + +TEST_F(TensorsToAudioCalculatorFftTest, TestImpulseSignalAtBeginning) { + constexpr int sample_size = 320; + constexpr double sample_rate = 16000; + ConfigGraph(sample_size, sample_rate, 320); + Matrix impulse_data = CreateImpulseSignalData(sample_size, 0); + RunGraph(impulse_data, sample_rate); + ASSERT_EQ(1, audio_out_packets_.size()); + MP_ASSERT_OK(audio_out_packets_[0].ValidateAsType()); + // As the impulse signal sits at the beginning of the hann window, the inverse + // window function completely removes it. + EXPECT_EQ(audio_out_packets_[0].Get(), Matrix::Zero(1, sample_size)); +} + +} // namespace +} // namespace mediapipe From 313b387cedb5b3357139ff0c14f1f847bece9512 Mon Sep 17 00:00:00 2001 From: Hadon Nash Date: Fri, 28 Oct 2022 14:02:07 -0700 Subject: [PATCH 093/125] Adding SwitchContainer option "tick_input_stream" to specify which input streams indicate the output timestamps to expect from the contained graphs. PiperOrigin-RevId: 484615286 --- mediapipe/framework/tool/switch_container.cc | 23 +++++++++++++++---- .../framework/tool/switch_container.proto | 5 ++++ 2 files changed, 24 insertions(+), 4 deletions(-) diff --git a/mediapipe/framework/tool/switch_container.cc b/mediapipe/framework/tool/switch_container.cc index 24a1e6fe7..daa129928 100644 --- a/mediapipe/framework/tool/switch_container.cc +++ b/mediapipe/framework/tool/switch_container.cc @@ -239,6 +239,15 @@ bool HasTag(const proto_ns::RepeatedPtrField& streams, return tags.count({tag, 0}) > 0; } +// Returns true if a set of "TAG::index" includes a TagIndex. +bool ContainsTag(const proto_ns::RepeatedPtrField& tags, + TagIndex item) { + for (const std::string& t : tags) { + if (ParseTagIndex(t) == item) return true; + } + return false; +} + absl::StatusOr SwitchContainer::GetConfig( const Subgraph::SubgraphOptions& options) { CalculatorGraphConfig config; @@ -263,9 +272,9 @@ absl::StatusOr SwitchContainer::GetConfig( std::string enable_stream = "ENABLE:gate_enable"; // Add a PacketSequencerCalculator node for "SELECT" or "ENABLE" streams. - bool async_selection = - Subgraph::GetOptions(options) - .async_selection(); + const auto& switch_options = + Subgraph::GetOptions(options); + bool async_selection = switch_options.async_selection(); if (HasTag(container_node.input_stream(), "SELECT")) { select_node = BuildTimestampNode(&config, async_selection); select_node->add_input_stream("INPUT:gate_select"); @@ -296,7 +305,7 @@ absl::StatusOr SwitchContainer::GetConfig( mux->add_input_side_packet("SELECT:gate_select"); mux->add_input_side_packet("ENABLE:gate_enable"); - // Add input streams for graph and demux and the timestamper. + // Add input streams for graph and demux. config.add_input_stream("SELECT:gate_select"); config.add_input_stream("ENABLE:gate_enable"); config.add_input_side_packet("SELECT:gate_select"); @@ -306,6 +315,12 @@ absl::StatusOr SwitchContainer::GetConfig( std::string stream = CatStream(p.first, p.second); config.add_input_stream(stream); demux->add_input_stream(stream); + } + + // Add input streams for the timestamper. + auto& tick_streams = switch_options.tick_input_stream(); + for (const auto& p : input_tags) { + if (!tick_streams.empty() && !ContainsTag(tick_streams, p.first)) continue; TagIndex tick_tag{"TICK", tick_index++}; if (select_node) { select_node->add_input_stream(CatStream(tick_tag, p.second)); diff --git a/mediapipe/framework/tool/switch_container.proto b/mediapipe/framework/tool/switch_container.proto index 2de5a7abf..16050ef6f 100644 --- a/mediapipe/framework/tool/switch_container.proto +++ b/mediapipe/framework/tool/switch_container.proto @@ -30,4 +30,9 @@ message SwitchContainerOptions { // Use ImmediateInputStreamHandler for channel selection. optional bool async_selection = 6; + + // Specifies an input stream, "TAG:index", that defines the processed + // timestamps. SwitchContainer awaits output at the last processed + // timestamp before advancing from one selected channel to the next. + repeated string tick_input_stream = 7; } From f62cfd169005a37362a8d177a3e36372b14aa791 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Sun, 30 Oct 2022 08:23:14 -0700 Subject: [PATCH 094/125] Removed classification proto to use the existing category dataclass instead and removed NormalizedLandmarkList and LandmarkList dataclasses --- .../tasks/python/components/containers/BUILD | 13 +- .../python/components/containers/category.py | 10 +- .../components/containers/classification.py | 121 ------------------ .../python/components/containers/landmark.py | 96 -------------- .../containers/landmark_detection_result.py | 61 ++++++--- mediapipe/tasks/python/test/vision/BUILD | 2 +- .../test/vision/gesture_recognizer_test.py | 49 ++++--- mediapipe/tasks/python/vision/BUILD | 2 +- .../tasks/python/vision/gesture_recognizer.py | 76 +++++++---- 9 files changed, 127 insertions(+), 303 deletions(-) delete mode 100644 mediapipe/tasks/python/components/containers/classification.py diff --git a/mediapipe/tasks/python/components/containers/BUILD b/mediapipe/tasks/python/components/containers/BUILD index 85f5b61c6..de3b7352c 100644 --- a/mediapipe/tasks/python/components/containers/BUILD +++ b/mediapipe/tasks/python/components/containers/BUILD @@ -36,15 +36,6 @@ py_library( ], ) -py_library( - name = "classification", - srcs = ["classification.py"], - deps = [ - "//mediapipe/framework/formats:classification_py_pb2", - "//mediapipe/tasks/python/core:optional_dependencies", - ], -) - py_library( name = "landmark", srcs = ["landmark.py"], @@ -59,9 +50,11 @@ py_library( srcs = ["landmark_detection_result.py"], deps = [ ":rect", - ":classification", ":landmark", + "//mediapipe/framework/formats:classification_py_pb2", + "//mediapipe/framework/formats:landmark_py_pb2", "//mediapipe/tasks/cc/components/containers/proto:landmarks_detection_result_py_pb2", + "//mediapipe/tasks/python/components/containers:category", "//mediapipe/tasks/python/core:optional_dependencies", ], ) diff --git a/mediapipe/tasks/python/components/containers/category.py b/mediapipe/tasks/python/components/containers/category.py index 0b347fc10..cfdb83740 100644 --- a/mediapipe/tasks/python/components/containers/category.py +++ b/mediapipe/tasks/python/components/containers/category.py @@ -14,7 +14,7 @@ """Category data class.""" import dataclasses -from typing import Any +from typing import Any, Optional from mediapipe.tasks.cc.components.containers.proto import category_pb2 from mediapipe.tasks.python.core.optional_dependencies import doc_controls @@ -39,10 +39,10 @@ class Category: category_name: The label of this category object. """ - index: int - score: float - display_name: str - category_name: str + index: Optional[int] = None + score: Optional[float] = None + display_name: Optional[str] = None + category_name: Optional[str] = None @doc_controls.do_not_generate_docs def to_pb2(self) -> _CategoryProto: diff --git a/mediapipe/tasks/python/components/containers/classification.py b/mediapipe/tasks/python/components/containers/classification.py deleted file mode 100644 index a9225e804..000000000 --- a/mediapipe/tasks/python/components/containers/classification.py +++ /dev/null @@ -1,121 +0,0 @@ -# Copyright 2022 The MediaPipe Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -"""Classification data class.""" - -import dataclasses -from typing import Any, List, Optional - -from mediapipe.framework.formats import classification_pb2 -from mediapipe.tasks.python.core.optional_dependencies import doc_controls - -_ClassificationProto = classification_pb2.Classification -_ClassificationListProto = classification_pb2.ClassificationList - - -@dataclasses.dataclass -class Classification: - """A classification. - - Attributes: - index: The index of the class in the corresponding label map. - score: The probability score for this class. - label_name: Label or name of the class. - display_name: Optional human-readable string for display purposes. - """ - - index: Optional[int] = None - score: Optional[float] = None - label: Optional[str] = None - display_name: Optional[str] = None - - @doc_controls.do_not_generate_docs - def to_pb2(self) -> _ClassificationProto: - """Generates a Classification protobuf object.""" - return _ClassificationProto( - index=self.index, - score=self.score, - label=self.label, - display_name=self.display_name) - - @classmethod - @doc_controls.do_not_generate_docs - def create_from_pb2(cls, pb2_obj: _ClassificationProto) -> 'Classification': - """Creates a `Classification` object from the given protobuf object.""" - return Classification( - index=pb2_obj.index, - score=pb2_obj.score, - label=pb2_obj.label, - display_name=pb2_obj.display_name) - - def __eq__(self, other: Any) -> bool: - """Checks if this object is equal to the given object. - - Args: - other: The object to be compared with. - - Returns: - True if the objects are equal. - """ - if not isinstance(other, Classification): - return False - - return self.to_pb2().__eq__(other.to_pb2()) - - -@dataclasses.dataclass -class ClassificationList: - """Represents the classifications for a given classifier. - Attributes: - classification : A list of `Classification` objects. - tensor_index: Optional index of the tensor that produced these - classifications. - tensor_name: Optional name of the tensor that produced these - classifications tensor metadata name. - """ - - classifications: List[Classification] - - @doc_controls.do_not_generate_docs - def to_pb2(self) -> _ClassificationListProto: - """Generates a ClassificationList protobuf object.""" - return _ClassificationListProto( - classification=[ - classification.to_pb2() - for classification in self.classifications - ]) - - @classmethod - @doc_controls.do_not_generate_docs - def create_from_pb2( - cls, - pb2_obj: _ClassificationListProto - ) -> 'ClassificationList': - """Creates a `ClassificationList` object from the given protobuf object.""" - return ClassificationList( - classifications=[ - Classification.create_from_pb2(classification) - for classification in pb2_obj.classification - ]) - - def __eq__(self, other: Any) -> bool: - """Checks if this object is equal to the given object. - Args: - other: The object to be compared with. - Returns: - True if the objects are equal. - """ - if not isinstance(other, ClassificationList): - return False - - return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/components/containers/landmark.py b/mediapipe/tasks/python/components/containers/landmark.py index a86c17f2f..2c87ee676 100644 --- a/mediapipe/tasks/python/components/containers/landmark.py +++ b/mediapipe/tasks/python/components/containers/landmark.py @@ -20,9 +20,7 @@ from mediapipe.framework.formats import landmark_pb2 from mediapipe.tasks.python.core.optional_dependencies import doc_controls _LandmarkProto = landmark_pb2.Landmark -_LandmarkListProto = landmark_pb2.LandmarkList _NormalizedLandmarkProto = landmark_pb2.NormalizedLandmark -_NormalizedLandmarkListProto = landmark_pb2.NormalizedLandmarkList @dataclasses.dataclass @@ -89,53 +87,6 @@ class Landmark: return self.to_pb2().__eq__(other.to_pb2()) -@dataclasses.dataclass -class LandmarkList: - """Represents the list of landmarks. - - Attributes: - landmarks : A list of `Landmark` objects. - """ - - landmarks: List[Landmark] - - @doc_controls.do_not_generate_docs - def to_pb2(self) -> _LandmarkListProto: - """Generates a LandmarkList protobuf object.""" - return _LandmarkListProto( - landmark=[ - landmark.to_pb2() - for landmark in self.landmarks - ] - ) - - @classmethod - @doc_controls.do_not_generate_docs - def create_from_pb2( - cls, - pb2_obj: _LandmarkListProto - ) -> 'LandmarkList': - """Creates a `LandmarkList` object from the given protobuf object.""" - return LandmarkList( - landmarks=[ - Landmark.create_from_pb2(landmark) - for landmark in pb2_obj.landmark - ] - ) - - def __eq__(self, other: Any) -> bool: - """Checks if this object is equal to the given object. - Args: - other: The object to be compared with. - Returns: - True if the objects are equal. - """ - if not isinstance(other, LandmarkList): - return False - - return self.to_pb2().__eq__(other.to_pb2()) - - @dataclasses.dataclass class NormalizedLandmark: """A normalized version of above Landmark proto. @@ -201,50 +152,3 @@ class NormalizedLandmark: return False return self.to_pb2().__eq__(other.to_pb2()) - - -@dataclasses.dataclass -class NormalizedLandmarkList: - """Represents the list of normalized landmarks. - - Attributes: - landmarks : A list of `Landmark` objects. - """ - - landmarks: List[NormalizedLandmark] - - @doc_controls.do_not_generate_docs - def to_pb2(self) -> _NormalizedLandmarkListProto: - """Generates a NormalizedLandmarkList protobuf object.""" - return _NormalizedLandmarkListProto( - landmark=[ - landmark.to_pb2() - for landmark in self.landmarks - ] - ) - - @classmethod - @doc_controls.do_not_generate_docs - def create_from_pb2( - cls, - pb2_obj: _NormalizedLandmarkListProto - ) -> 'NormalizedLandmarkList': - """Creates a `NormalizedLandmarkList` object from the given protobuf object.""" - return NormalizedLandmarkList( - landmarks=[ - NormalizedLandmark.create_from_pb2(landmark) - for landmark in pb2_obj.landmark - ] - ) - - def __eq__(self, other: Any) -> bool: - """Checks if this object is equal to the given object. - Args: - other: The object to be compared with. - Returns: - True if the objects are equal. - """ - if not isinstance(other, NormalizedLandmarkList): - return False - - return self.to_pb2().__eq__(other.to_pb2()) diff --git a/mediapipe/tasks/python/components/containers/landmark_detection_result.py b/mediapipe/tasks/python/components/containers/landmark_detection_result.py index 02ca5a918..ad21812c7 100644 --- a/mediapipe/tasks/python/components/containers/landmark_detection_result.py +++ b/mediapipe/tasks/python/components/containers/landmark_detection_result.py @@ -14,19 +14,25 @@ """Landmarks Detection Result data class.""" import dataclasses -from typing import Any, Optional +from typing import Any, Optional, List from mediapipe.tasks.cc.components.containers.proto import landmarks_detection_result_pb2 +from mediapipe.framework.formats import classification_pb2 +from mediapipe.framework.formats import landmark_pb2 from mediapipe.tasks.python.components.containers import rect as rect_module -from mediapipe.tasks.python.components.containers import classification as classification_module +from mediapipe.tasks.python.components.containers import category as category_module from mediapipe.tasks.python.components.containers import landmark as landmark_module from mediapipe.tasks.python.core.optional_dependencies import doc_controls _LandmarksDetectionResultProto = landmarks_detection_result_pb2.LandmarksDetectionResult +_ClassificationProto = classification_pb2.Classification +_ClassificationListProto = classification_pb2.ClassificationList +_LandmarkListProto = landmark_pb2.LandmarkList +_NormalizedLandmarkListProto = landmark_pb2.NormalizedLandmarkList _NormalizedRect = rect_module.NormalizedRect -_ClassificationList = classification_module.ClassificationList -_NormalizedLandmarkList = landmark_module.NormalizedLandmarkList -_LandmarkList = landmark_module.LandmarkList +_Category = category_module.Category +_NormalizedLandmark = landmark_module.NormalizedLandmark +_Landmark = landmark_module.Landmark @dataclasses.dataclass @@ -34,25 +40,32 @@ class LandmarksDetectionResult: """Represents the landmarks detection result. Attributes: - landmarks : A `NormalizedLandmarkList` object. - classifications : A `ClassificationList` object. - world_landmarks : A `LandmarkList` object. + landmarks : A list of `NormalizedLandmark` objects. + categories : A list of `Category` objects. + world_landmarks : A list of `Landmark` objects. rect : A `NormalizedRect` object. """ - landmarks: Optional[_NormalizedLandmarkList] - classifications: Optional[_ClassificationList] - world_landmarks: Optional[_LandmarkList] + landmarks: Optional[List[_NormalizedLandmark]] + categories: Optional[List[_Category]] + world_landmarks: Optional[List[_Landmark]] rect: _NormalizedRect @doc_controls.do_not_generate_docs def to_pb2(self) -> _LandmarksDetectionResultProto: """Generates a LandmarksDetectionResult protobuf object.""" return _LandmarksDetectionResultProto( - landmarks=self.landmarks.to_pb2(), - classifications=self.classifications.to_pb2(), - world_landmarks=self.world_landmarks.to_pb2(), - rect=self.rect.to_pb2()) + landmarks=_NormalizedLandmarkListProto(landmarks=self.landmarks), + classifications=_ClassificationListProto( + classification=[ + _ClassificationProto( + index=category.index, + score=category.score, + label=category.category_name, + display_name=category.display_name) + for category in self.categories]), + world_landmarks=_LandmarkListProto(landmarks=self.world_landmarks), + rect=self.rect.to_pb2()) @classmethod @doc_controls.do_not_generate_docs @@ -63,11 +76,19 @@ class LandmarksDetectionResult: """Creates a `LandmarksDetectionResult` object from the given protobuf object.""" return LandmarksDetectionResult( - landmarks=_NormalizedLandmarkList.create_from_pb2(pb2_obj.landmarks), - classifications=_ClassificationList.create_from_pb2( - pb2_obj.classifications), - world_landmarks=_LandmarkList.create_from_pb2(pb2_obj.world_landmarks), - rect=_NormalizedRect.create_from_pb2(pb2_obj.rect)) + landmarks=[ + _NormalizedLandmark.create_from_pb2(landmark) + for landmark in pb2_obj.landmarks.landmark], + categories=[category_module.Category( + score=classification.score, + index=classification.index, + category_name=classification.label, + display_name=classification.display_name) + for classification in pb2_obj.classifications.classification], + world_landmarks=[ + _Landmark.create_from_pb2(landmark) + for landmark in pb2_obj.world_landmarks.landmark], + rect=_NormalizedRect.create_from_pb2(pb2_obj.rect)) def __eq__(self, other: Any) -> bool: """Checks if this object is equal to the given object. diff --git a/mediapipe/tasks/python/test/vision/BUILD b/mediapipe/tasks/python/test/vision/BUILD index 5ba91e6a9..9b0fab6cb 100644 --- a/mediapipe/tasks/python/test/vision/BUILD +++ b/mediapipe/tasks/python/test/vision/BUILD @@ -69,7 +69,7 @@ py_test( "//mediapipe/python:_framework_bindings", "//mediapipe/tasks/cc/components/containers/proto:landmarks_detection_result_py_pb2", "//mediapipe/tasks/python/components/containers:rect", - "//mediapipe/tasks/python/components/containers:classification", + "//mediapipe/tasks/python/components/containers:category", "//mediapipe/tasks/python/components/containers:landmark", "//mediapipe/tasks/python/components/containers:landmark_detection_result", "//mediapipe/tasks/python/core:base_options", diff --git a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py index cbee18170..8f7c66519 100644 --- a/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py +++ b/mediapipe/tasks/python/test/vision/gesture_recognizer_test.py @@ -24,7 +24,7 @@ from absl.testing import parameterized from mediapipe.python._framework_bindings import image as image_module from mediapipe.tasks.cc.components.containers.proto import landmarks_detection_result_pb2 from mediapipe.tasks.python.components.containers import rect as rect_module -from mediapipe.tasks.python.components.containers import classification as classification_module +from mediapipe.tasks.python.components.containers import category as category_module from mediapipe.tasks.python.components.containers import landmark as landmark_module from mediapipe.tasks.python.components.containers import landmark_detection_result as landmark_detection_result_module from mediapipe.tasks.python.core import base_options as base_options_module @@ -36,12 +36,9 @@ from mediapipe.tasks.python.vision.core import image_processing_options as image _LandmarksDetectionResultProto = landmarks_detection_result_pb2.LandmarksDetectionResult _BaseOptions = base_options_module.BaseOptions _Rect = rect_module.Rect -_Classification = classification_module.Classification -_ClassificationList = classification_module.ClassificationList +_Category = category_module.Category _Landmark = landmark_module.Landmark -_LandmarkList = landmark_module.LandmarkList _NormalizedLandmark = landmark_module.NormalizedLandmark -_NormalizedLandmarkList = landmark_module.NormalizedLandmarkList _LandmarksDetectionResult = landmark_detection_result_module.LandmarksDetectionResult _Image = image_module.Image _GestureRecognizer = gesture_recognizer.GestureRecognizer @@ -76,14 +73,11 @@ def _get_expected_gesture_recognition_result( text_format.Parse(f.read(), landmarks_detection_result_proto) landmarks_detection_result = _LandmarksDetectionResult.create_from_pb2( landmarks_detection_result_proto) - gesture = _ClassificationList( - classifications=[ - _Classification(label=gesture_label, index=gesture_index, - display_name='') - ]) + gesture = _Category(category_name=gesture_label, index=gesture_index, + display_name='') return _GestureRecognitionResult( - gestures=[gesture], - handedness=[landmarks_detection_result.classifications], + gestures=[[gesture]], + handedness=[landmarks_detection_result.categories], hand_landmarks=[landmarks_detection_result.landmarks], hand_world_landmarks=[landmarks_detection_result.world_landmarks]) @@ -115,25 +109,27 @@ class GestureRecognizerTest(parameterized.TestCase): self.assertLen(actual_result.handedness, len(expected_result.handedness)) self.assertLen(actual_result.gestures, len(expected_result.gestures)) # Actual landmarks match expected landmarks. - self.assertLen(actual_result.hand_landmarks[0].landmarks, - len(expected_result.hand_landmarks[0].landmarks)) - actual_landmarks = actual_result.hand_landmarks[0].landmarks - expected_landmarks = expected_result.hand_landmarks[0].landmarks + self.assertLen(actual_result.hand_landmarks[0], + len(expected_result.hand_landmarks[0])) + actual_landmarks = actual_result.hand_landmarks[0] + expected_landmarks = expected_result.hand_landmarks[0] for i in range(len(actual_landmarks)): self.assertAlmostEqual(actual_landmarks[i].x, expected_landmarks[i].x, delta=_LANDMARKS_ERROR_TOLERANCE) self.assertAlmostEqual(actual_landmarks[i].y, expected_landmarks[i].y, delta=_LANDMARKS_ERROR_TOLERANCE) # Actual handedness matches expected handedness. - actual_top_handedness = actual_result.handedness[0].classifications[0] - expected_top_handedness = expected_result.handedness[0].classifications[0] + actual_top_handedness = actual_result.handedness[0][0] + expected_top_handedness = expected_result.handedness[0][0] self.assertEqual(actual_top_handedness.index, expected_top_handedness.index) - self.assertEqual(actual_top_handedness.label, expected_top_handedness.label) + self.assertEqual(actual_top_handedness.category_name, + expected_top_handedness.category_name) # Actual gesture with top score matches expected gesture. - actual_top_gesture = actual_result.gestures[0].classifications[0] - expected_top_gesture = expected_result.gestures[0].classifications[0] + actual_top_gesture = actual_result.gestures[0][0] + expected_top_gesture = expected_result.gestures[0][0] self.assertEqual(actual_top_gesture.index, expected_top_gesture.index) - self.assertEqual(actual_top_gesture.label, expected_top_gesture.label) + self.assertEqual(actual_top_gesture.category_name, + expected_top_gesture.category_name) def test_create_from_file_succeeds_with_valid_model_path(self): # Creates with default option and valid model file successfully. @@ -235,12 +231,13 @@ class GestureRecognizerTest(parameterized.TestCase): expected_result = _get_expected_gesture_recognition_result( _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX) # Only contains one top scoring gesture. - self.assertLen(recognition_result.gestures[0].classifications, 1) + self.assertLen(recognition_result.gestures[0], 1) # Actual gesture with top score matches expected gesture. - actual_top_gesture = recognition_result.gestures[0].classifications[0] - expected_top_gesture = expected_result.gestures[0].classifications[0] + actual_top_gesture = recognition_result.gestures[0][0] + expected_top_gesture = expected_result.gestures[0][0] self.assertEqual(actual_top_gesture.index, expected_top_gesture.index) - self.assertEqual(actual_top_gesture.label, expected_top_gesture.label) + self.assertEqual(actual_top_gesture.category_name, + expected_top_gesture.category_name) def test_recognize_succeeds_with_num_hands(self): # Creates gesture recognizer. diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index fc74911ea..f0b3c9f53 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -74,7 +74,7 @@ py_library( "//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_py_pb2", "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_py_pb2", "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_py_pb2", - "//mediapipe/tasks/python/components/containers:classification", + "//mediapipe/tasks/python/components/containers:category", "//mediapipe/tasks/python/components/containers:landmark", "//mediapipe/tasks/python/components/processors:classifier_options", "//mediapipe/tasks/python/core:base_options", diff --git a/mediapipe/tasks/python/vision/gesture_recognizer.py b/mediapipe/tasks/python/vision/gesture_recognizer.py index 11cb5c7b2..142eb1dc6 100644 --- a/mediapipe/tasks/python/vision/gesture_recognizer.py +++ b/mediapipe/tasks/python/vision/gesture_recognizer.py @@ -27,7 +27,7 @@ from mediapipe.tasks.cc.vision.gesture_recognizer.proto import hand_gesture_reco from mediapipe.tasks.cc.vision.hand_detector.proto import hand_detector_graph_options_pb2 from mediapipe.tasks.cc.vision.hand_landmarker.proto import hand_landmarker_graph_options_pb2 from mediapipe.tasks.cc.vision.hand_landmarker.proto import hand_landmarks_detector_graph_options_pb2 -from mediapipe.tasks.python.components.containers import classification as classification_module +from mediapipe.tasks.python.components.containers import category as category_module from mediapipe.tasks.python.components.containers import landmark as landmark_module from mediapipe.tasks.python.components.processors import classifier_options from mediapipe.tasks.python.core import base_options as base_options_module @@ -80,10 +80,10 @@ class GestureRecognitionResult: hand_world_landmarks: Detected hand landmarks in world coordinates. """ - gestures: List[classification_module.ClassificationList] - handedness: List[classification_module.ClassificationList] - hand_landmarks: List[landmark_module.NormalizedLandmarkList] - hand_world_landmarks: List[landmark_module.LandmarkList] + gestures: List[List[category_module.Category]] + handedness: List[List[category_module.Category]] + hand_landmarks: List[List[landmark_module.NormalizedLandmark]] + hand_world_landmarks: List[List[landmark_module.Landmark]] @dataclasses.dataclass @@ -231,16 +231,26 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): gesture_recognition_result = GestureRecognitionResult( [ - classification_module.ClassificationList.create_from_pb2(gestures) - for gestures in gestures_proto_list + [ + category_module.Category( + index=gesture.index, score=gesture.score, + display_name=gesture.display_name, category_name=gesture.label) + for gesture in gesture_classifications.classification] + for gesture_classifications in gestures_proto_list ], [ - classification_module.ClassificationList.create_from_pb2(handedness) - for handedness in handedness_proto_list + [ + category_module.Category( + index=gesture.index, score=gesture.score, + display_name=gesture.display_name, category_name=gesture.label) + for gesture in handedness_classifications.classification] + for handedness_classifications in handedness_proto_list ], [ - landmark_module.NormalizedLandmarkList.create_from_pb2(hand_landmarks) + [landmark_module.NormalizedLandmark.create_from_pb2(hand_landmark) + for hand_landmark in hand_landmarks.landmark] for hand_landmarks in hand_landmarks_proto_list ], [ - landmark_module.LandmarkList.create_from_pb2(hand_world_landmarks) + [landmark_module.Landmark.create_from_pb2(hand_world_landmark) + for hand_world_landmark in hand_world_landmarks.landmark] for hand_world_landmarks in hand_world_landmarks_proto_list ] ) @@ -314,16 +324,26 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): return GestureRecognitionResult( [ - classification_module.ClassificationList.create_from_pb2(gestures) - for gestures in gestures_proto_list + [ + category_module.Category( + index=gesture.index, score=gesture.score, + display_name=gesture.display_name, category_name=gesture.label) + for gesture in gesture_classifications.classification] + for gesture_classifications in gestures_proto_list ], [ - classification_module.ClassificationList.create_from_pb2(handedness) - for handedness in handedness_proto_list + [ + category_module.Category( + index=gesture.index, score=gesture.score, + display_name=gesture.display_name, category_name=gesture.label) + for gesture in handedness_classifications.classification] + for handedness_classifications in handedness_proto_list ], [ - landmark_module.NormalizedLandmarkList.create_from_pb2(hand_landmarks) + [landmark_module.NormalizedLandmark.create_from_pb2(hand_landmark) + for hand_landmark in hand_landmarks.landmark] for hand_landmarks in hand_landmarks_proto_list ], [ - landmark_module.LandmarkList.create_from_pb2(hand_world_landmarks) + [landmark_module.Landmark.create_from_pb2(hand_world_landmark) + for hand_world_landmark in hand_world_landmarks.landmark] for hand_world_landmarks in hand_world_landmarks_proto_list ] ) @@ -377,16 +397,26 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): return GestureRecognitionResult( [ - classification_module.ClassificationList.create_from_pb2(gestures) - for gestures in gestures_proto_list + [ + category_module.Category( + index=gesture.index, score=gesture.score, + display_name=gesture.display_name, category_name=gesture.label) + for gesture in gesture_classifications.classification] + for gesture_classifications in gestures_proto_list ], [ - classification_module.ClassificationList.create_from_pb2(handedness) - for handedness in handedness_proto_list + [ + category_module.Category( + index=gesture.index, score=gesture.score, + display_name=gesture.display_name, category_name=gesture.label) + for gesture in handedness_classifications.classification] + for handedness_classifications in handedness_proto_list ], [ - landmark_module.NormalizedLandmarkList.create_from_pb2(hand_landmarks) + [landmark_module.NormalizedLandmark.create_from_pb2(hand_landmark) + for hand_landmark in hand_landmarks.landmark] for hand_landmarks in hand_landmarks_proto_list ], [ - landmark_module.LandmarkList.create_from_pb2(hand_world_landmarks) + [landmark_module.Landmark.create_from_pb2(hand_world_landmark) + for hand_world_landmark in hand_world_landmarks.landmark] for hand_world_landmarks in hand_world_landmarks_proto_list ] ) From 4b66599419bd7ffe8bb90db7c7a5533a43004801 Mon Sep 17 00:00:00 2001 From: kinaryml Date: Sun, 30 Oct 2022 09:10:15 -0700 Subject: [PATCH 095/125] Updated docstring in gesture_recognizer --- mediapipe/tasks/python/vision/gesture_recognizer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mediapipe/tasks/python/vision/gesture_recognizer.py b/mediapipe/tasks/python/vision/gesture_recognizer.py index 142eb1dc6..e8d9ef342 100644 --- a/mediapipe/tasks/python/vision/gesture_recognizer.py +++ b/mediapipe/tasks/python/vision/gesture_recognizer.py @@ -444,7 +444,7 @@ class GestureRecognizer(base_vision_task_api.BaseVisionTaskApi): The `result_callback` provides: - The hand gesture recognition results. - - The input image that the image classifier runs on. + - The input image that the gesture recognizer runs on. - The input timestamp in milliseconds. Args: From be13a76928d4d281fcabc6d94b008fcca18c2066 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Sun, 30 Oct 2022 15:34:14 -0700 Subject: [PATCH 096/125] Integrate canned and custom gesture classifier. PiperOrigin-RevId: 484914164 --- .../tasks/cc/vision/gesture_recognizer/BUILD | 6 +- .../combined_prediction_calculator.cc | 7 +- .../gesture_recognizer/gesture_recognizer.cc | 4 + .../hand_gesture_recognizer_graph.cc | 192 ++++++++++----- .../GestureRecognitionResult.java | 12 +- .../GestureRecognizerTest.java | 75 ++++-- mediapipe/tasks/testdata/vision/BUILD | 6 + .../testdata/vision/fist_landmarks.pbtxt | 223 ++++++++++++++++++ ...ure_recognizer_with_custom_classifier.task | Bin 0 -> 8379310 bytes ...ure_recognizer_with_custom_classifier.task | Bin 0 -> 560003 bytes .../testdata/vision/victory_landmarks.pbtxt | 223 ++++++++++++++++++ third_party/external_files.bzl | 24 ++ 12 files changed, 692 insertions(+), 80 deletions(-) create mode 100644 mediapipe/tasks/testdata/vision/fist_landmarks.pbtxt create mode 100644 mediapipe/tasks/testdata/vision/gesture_recognizer_with_custom_classifier.task create mode 100644 mediapipe/tasks/testdata/vision/hand_gesture_recognizer_with_custom_classifier.task create mode 100644 mediapipe/tasks/testdata/vision/victory_landmarks.pbtxt diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD b/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD index 6296017d4..a88d0d72c 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/BUILD @@ -62,14 +62,18 @@ cc_library( "//mediapipe/tasks/cc/components:image_preprocessing", "//mediapipe/tasks/cc/components/processors:classification_postprocessing_graph", "//mediapipe/tasks/cc/components/processors/proto:classification_postprocessing_graph_options_cc_proto", + "//mediapipe/tasks/cc/components/processors/proto:classifier_options_cc_proto", "//mediapipe/tasks/cc/core:model_asset_bundle_resources", "//mediapipe/tasks/cc/core:model_resources", "//mediapipe/tasks/cc/core:model_resources_cache", "//mediapipe/tasks/cc/core:model_task_graph", "//mediapipe/tasks/cc/core:utils", + "//mediapipe/tasks/cc/core/proto:base_options_cc_proto", "//mediapipe/tasks/cc/core/proto:external_file_cc_proto", "//mediapipe/tasks/cc/core/proto:inference_subgraph_cc_proto", "//mediapipe/tasks/cc/metadata/utils:zip_utils", + "//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:combined_prediction_calculator", + "//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:combined_prediction_calculator_cc_proto", "//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:handedness_to_matrix_calculator", "//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:landmarks_to_matrix_calculator", "//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:landmarks_to_matrix_calculator_cc_proto", @@ -77,8 +81,6 @@ cc_library( "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_embedder_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_cc_proto", "//mediapipe/tasks/cc/vision/hand_landmarker:hand_landmarks_detector_graph", - "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_cc_proto", - "//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_cc_proto", "//mediapipe/tasks/metadata:metadata_schema_cc", "@com_google_absl//absl/status", "@com_google_absl//absl/status:statusor", diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.cc index c7147ea6e..cb95091d4 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.cc @@ -153,13 +153,12 @@ class CombinedPredictionCalculator : public Node { // After loop, if have winning prediction return. Otherwise empty packet. std::unique_ptr first_winning_prediction = nullptr; auto collection = kClassificationListIn(cc); - for (int idx = 0; idx < collection.Count(); ++idx) { - const auto& packet = collection[idx]; - if (packet.IsEmpty()) { + for (const auto& input : collection) { + if (input.IsEmpty() || input.Get().classification_size() == 0) { continue; } auto prediction = GetWinningPrediction( - packet.Get(), classwise_thresholds_, options_.background_label(), + input.Get(), classwise_thresholds_, options_.background_label(), options_.default_global_threshold()); if (prediction->classification(0).label() != options_.background_label()) { diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc index d4ab16ac8..fa1fc69ce 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/gesture_recognizer.cc @@ -146,6 +146,10 @@ ConvertGestureRecognizerGraphOptionsProto(GestureRecognizerOptions* options) { ->mutable_canned_gesture_classifier_graph_options() ->mutable_classifier_options() ->set_score_threshold(options->min_gesture_confidence); + hand_gesture_recognizer_graph_options + ->mutable_custom_gesture_classifier_graph_options() + ->mutable_classifier_options() + ->set_score_threshold(options->min_gesture_confidence); } return options_proto; } diff --git a/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc b/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc index 7b7746956..6e83f9eec 100644 --- a/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc +++ b/mediapipe/tasks/cc/vision/gesture_recognizer/hand_gesture_recognizer_graph.cc @@ -30,14 +30,17 @@ limitations under the License. #include "mediapipe/tasks/cc/common.h" #include "mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.h" #include "mediapipe/tasks/cc/components/processors/proto/classification_postprocessing_graph_options.pb.h" +#include "mediapipe/tasks/cc/components/processors/proto/classifier_options.pb.h" #include "mediapipe/tasks/cc/core/model_asset_bundle_resources.h" #include "mediapipe/tasks/cc/core/model_resources.h" #include "mediapipe/tasks/cc/core/model_resources_cache.h" #include "mediapipe/tasks/cc/core/model_task_graph.h" +#include "mediapipe/tasks/cc/core/proto/base_options.pb.h" #include "mediapipe/tasks/cc/core/proto/external_file.pb.h" #include "mediapipe/tasks/cc/core/proto/inference_subgraph.pb.h" #include "mediapipe/tasks/cc/core/utils.h" #include "mediapipe/tasks/cc/metadata/utils/zip_utils.h" +#include "mediapipe/tasks/cc/vision/gesture_recognizer/calculators/combined_prediction_calculator.pb.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/calculators/landmarks_to_matrix_calculator.pb.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_classifier_graph_options.pb.h" #include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_embedder_graph_options.pb.h" @@ -58,6 +61,7 @@ using ::mediapipe::api2::builder::Source; using ::mediapipe::tasks::components::processors:: ConfigureTensorsToClassificationCalculator; using ::mediapipe::tasks::core::ModelAssetBundleResources; +using ::mediapipe::tasks::core::proto::BaseOptions; using ::mediapipe::tasks::metadata::SetExternalFile; using ::mediapipe::tasks::vision::gesture_recognizer::proto:: HandGestureRecognizerGraphOptions; @@ -78,13 +82,20 @@ constexpr char kVectorTag[] = "VECTOR"; constexpr char kIndexTag[] = "INDEX"; constexpr char kIterableTag[] = "ITERABLE"; constexpr char kBatchEndTag[] = "BATCH_END"; +constexpr char kPredictionTag[] = "PREDICTION"; +constexpr char kBackgroundLabel[] = "None"; constexpr char kGestureEmbedderTFLiteName[] = "gesture_embedder.tflite"; constexpr char kCannedGestureClassifierTFLiteName[] = "canned_gesture_classifier.tflite"; +constexpr char kCustomGestureClassifierTFLiteName[] = + "custom_gesture_classifier.tflite"; struct SubTaskModelResources { - const core::ModelResources* gesture_embedder_model_resource; - const core::ModelResources* canned_gesture_classifier_model_resource; + const core::ModelResources* gesture_embedder_model_resource = nullptr; + const core::ModelResources* canned_gesture_classifier_model_resource = + nullptr; + const core::ModelResources* custom_gesture_classifier_model_resource = + nullptr; }; Source> ConvertMatrixToTensor(Source matrix, @@ -94,41 +105,21 @@ Source> ConvertMatrixToTensor(Source matrix, return node[Output>{"TENSORS"}]; } -// Sets the base options in the sub tasks. -absl::Status SetSubTaskBaseOptions(const ModelAssetBundleResources& resources, - HandGestureRecognizerGraphOptions* options, - bool is_copy) { - ASSIGN_OR_RETURN(const auto gesture_embedder_file, - resources.GetModelFile(kGestureEmbedderTFLiteName)); - auto* gesture_embedder_graph_options = - options->mutable_gesture_embedder_graph_options(); - SetExternalFile(gesture_embedder_file, - gesture_embedder_graph_options->mutable_base_options() - ->mutable_model_asset(), - is_copy); - gesture_embedder_graph_options->mutable_base_options() - ->mutable_acceleration() - ->CopyFrom(options->base_options().acceleration()); - gesture_embedder_graph_options->mutable_base_options()->set_use_stream_mode( - options->base_options().use_stream_mode()); - - ASSIGN_OR_RETURN(const auto canned_gesture_classifier_file, - resources.GetModelFile(kCannedGestureClassifierTFLiteName)); - auto* canned_gesture_classifier_graph_options = - options->mutable_canned_gesture_classifier_graph_options(); - SetExternalFile( - canned_gesture_classifier_file, - canned_gesture_classifier_graph_options->mutable_base_options() - ->mutable_model_asset(), - is_copy); - canned_gesture_classifier_graph_options->mutable_base_options() - ->mutable_acceleration() - ->CopyFrom(options->base_options().acceleration()); - canned_gesture_classifier_graph_options->mutable_base_options() - ->set_use_stream_mode(options->base_options().use_stream_mode()); +absl::Status ConfigureCombinedPredictionCalculator( + CombinedPredictionCalculatorOptions* options) { + options->set_background_label(kBackgroundLabel); return absl::OkStatus(); } +void PopulateAccelerationAndUseStreamMode( + const BaseOptions& parent_base_options, + BaseOptions* sub_task_base_options) { + sub_task_base_options->mutable_acceleration()->CopyFrom( + parent_base_options.acceleration()); + sub_task_base_options->set_use_stream_mode( + parent_base_options.use_stream_mode()); +} + } // namespace // A @@ -212,6 +203,56 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { } private: + // Sets the base options in the sub tasks. + absl::Status SetSubTaskBaseOptions(const ModelAssetBundleResources& resources, + HandGestureRecognizerGraphOptions* options, + bool is_copy) { + ASSIGN_OR_RETURN(const auto gesture_embedder_file, + resources.GetModelFile(kGestureEmbedderTFLiteName)); + auto* gesture_embedder_graph_options = + options->mutable_gesture_embedder_graph_options(); + SetExternalFile(gesture_embedder_file, + gesture_embedder_graph_options->mutable_base_options() + ->mutable_model_asset(), + is_copy); + PopulateAccelerationAndUseStreamMode( + options->base_options(), + gesture_embedder_graph_options->mutable_base_options()); + + ASSIGN_OR_RETURN( + const auto canned_gesture_classifier_file, + resources.GetModelFile(kCannedGestureClassifierTFLiteName)); + auto* canned_gesture_classifier_graph_options = + options->mutable_canned_gesture_classifier_graph_options(); + SetExternalFile( + canned_gesture_classifier_file, + canned_gesture_classifier_graph_options->mutable_base_options() + ->mutable_model_asset(), + is_copy); + PopulateAccelerationAndUseStreamMode( + options->base_options(), + canned_gesture_classifier_graph_options->mutable_base_options()); + + const auto custom_gesture_classifier_file = + resources.GetModelFile(kCustomGestureClassifierTFLiteName); + if (custom_gesture_classifier_file.ok()) { + has_custom_gesture_classifier = true; + auto* custom_gesture_classifier_graph_options = + options->mutable_custom_gesture_classifier_graph_options(); + SetExternalFile( + custom_gesture_classifier_file.value(), + custom_gesture_classifier_graph_options->mutable_base_options() + ->mutable_model_asset(), + is_copy); + PopulateAccelerationAndUseStreamMode( + options->base_options(), + custom_gesture_classifier_graph_options->mutable_base_options()); + } else { + LOG(INFO) << "Custom gesture classifier is not defined."; + } + return absl::OkStatus(); + } + absl::StatusOr CreateSubTaskModelResources( SubgraphContext* sc) { auto* options = sc->MutableOptions(); @@ -237,6 +278,19 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { std::make_unique( std::move(canned_gesture_classifier_model_asset)), "_canned_gesture_classifier")); + if (has_custom_gesture_classifier) { + auto& custom_gesture_classifier_model_asset = + *options->mutable_custom_gesture_classifier_graph_options() + ->mutable_base_options() + ->mutable_model_asset(); + ASSIGN_OR_RETURN( + sub_task_model_resources.custom_gesture_classifier_model_resource, + CreateModelResources( + sc, + std::make_unique( + std::move(custom_gesture_classifier_model_asset)), + "_custom_gesture_classifier")); + } return sub_task_model_resources; } @@ -302,7 +356,7 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { hand_world_landmarks_tensor >> concatenate_tensor_vector.In(2); auto concatenated_tensors = concatenate_tensor_vector.Out(""); - // Inference for static hand gesture recognition. + // Inference for gesture embedder. auto& gesture_embedder_inference = AddInference(*sub_task_model_resources.gesture_embedder_model_resource, graph_options.gesture_embedder_graph_options() @@ -310,34 +364,64 @@ class SingleHandGestureRecognizerGraph : public core::ModelTaskGraph { .acceleration(), graph); concatenated_tensors >> gesture_embedder_inference.In(kTensorsTag); - auto embedding_tensors = gesture_embedder_inference.Out(kTensorsTag); + auto embedding_tensors = + gesture_embedder_inference.Out(kTensorsTag).Cast(); - auto& canned_gesture_classifier_inference = AddInference( - *sub_task_model_resources.canned_gesture_classifier_model_resource, - graph_options.canned_gesture_classifier_graph_options() - .base_options() - .acceleration(), - graph); - embedding_tensors >> canned_gesture_classifier_inference.In(kTensorsTag); - auto inference_output_tensors = - canned_gesture_classifier_inference.Out(kTensorsTag); + auto& combine_predictions = graph.AddNode("CombinedPredictionCalculator"); + MP_RETURN_IF_ERROR(ConfigureCombinedPredictionCalculator( + &combine_predictions + .GetOptions())); + int classifier_nums = 0; + // Inference for custom gesture classifier if it exists. + if (has_custom_gesture_classifier) { + ASSIGN_OR_RETURN( + auto gesture_clasification_list, + GetGestureClassificationList( + sub_task_model_resources.custom_gesture_classifier_model_resource, + graph_options.custom_gesture_classifier_graph_options(), + embedding_tensors, graph)); + gesture_clasification_list >> combine_predictions.In(classifier_nums++); + } + + // Inference for canned gesture classifier. + ASSIGN_OR_RETURN( + auto gesture_clasification_list, + GetGestureClassificationList( + sub_task_model_resources.canned_gesture_classifier_model_resource, + graph_options.canned_gesture_classifier_graph_options(), + embedding_tensors, graph)); + gesture_clasification_list >> combine_predictions.In(classifier_nums++); + + auto combined_classification_list = + combine_predictions.Out(kPredictionTag).Cast(); + + return combined_classification_list; + } + + absl::StatusOr> GetGestureClassificationList( + const core::ModelResources* model_resources, + const proto::GestureClassifierGraphOptions& options, + Source& embedding_tensors, Graph& graph) { + auto& custom_gesture_classifier_inference = AddInference( + *model_resources, options.base_options().acceleration(), graph); + embedding_tensors >> custom_gesture_classifier_inference.In(kTensorsTag); + auto custom_gesture_inference_out_tensors = + custom_gesture_classifier_inference.Out(kTensorsTag); auto& tensors_to_classification = graph.AddNode("TensorsToClassificationCalculator"); MP_RETURN_IF_ERROR(ConfigureTensorsToClassificationCalculator( - graph_options.canned_gesture_classifier_graph_options() - .classifier_options(), - *sub_task_model_resources.canned_gesture_classifier_model_resource - ->GetMetadataExtractor(), + options.classifier_options(), *model_resources->GetMetadataExtractor(), 0, &tensors_to_classification.GetOptions< mediapipe::TensorsToClassificationCalculatorOptions>())); - inference_output_tensors >> tensors_to_classification.In(kTensorsTag); - auto classification_list = - tensors_to_classification[Output( - "CLASSIFICATIONS")]; - return classification_list; + custom_gesture_inference_out_tensors >> + tensors_to_classification.In(kTensorsTag); + return tensors_to_classification.Out("CLASSIFICATIONS") + .Cast(); } + + bool has_custom_gesture_classifier = false; }; // clang-format off diff --git a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognitionResult.java b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognitionResult.java index fd764cb18..e9e1ebe8a 100644 --- a/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognitionResult.java +++ b/mediapipe/tasks/java/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognitionResult.java @@ -31,6 +31,8 @@ import java.util.List; @AutoValue public abstract class GestureRecognitionResult implements TaskResult { + private static final int kGestureDefaultIndex = -1; + /** * Creates a {@link GestureRecognitionResult} instance from the lists of landmarks, handedness, * and gestures protobuf messages. @@ -97,7 +99,9 @@ public abstract class GestureRecognitionResult implements TaskResult { gestures.add( Category.create( classification.getScore(), - classification.getIndex(), + // Gesture index is not used, because the final gesture result comes from multiple + // classifiers. + kGestureDefaultIndex, classification.getLabel(), classification.getDisplayName())); } @@ -123,6 +127,10 @@ public abstract class GestureRecognitionResult implements TaskResult { /** Handedness of detected hands. */ public abstract List> handednesses(); - /** Recognized hand gestures of detected hands */ + /** + * Recognized hand gestures of detected hands. Note that the index of the gesture is always -1, + * because the raw indices from multiple gesture classifiers cannot consolidate to a meaningful + * index. + */ public abstract List> gestures(); } diff --git a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java index eca5d35c2..2d4b3a50d 100644 --- a/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java +++ b/mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/gesturerecognizer/GestureRecognizerTest.java @@ -46,19 +46,24 @@ import org.junit.runners.Suite.SuiteClasses; @SuiteClasses({GestureRecognizerTest.General.class, GestureRecognizerTest.RunningModeTest.class}) public class GestureRecognizerTest { private static final String GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE = "gesture_recognizer.task"; + private static final String GESTURE_RECOGNIZER_WITH_CUSTOM_CLASSIFIER_BUNDLE_ASSET_FILE = + "gesture_recognizer_with_custom_classifier.task"; private static final String TWO_HANDS_IMAGE = "right_hands.jpg"; private static final String THUMB_UP_IMAGE = "thumb_up.jpg"; private static final String POINTING_UP_ROTATED_IMAGE = "pointing_up_rotated.jpg"; private static final String NO_HANDS_IMAGE = "cats_and_dogs.jpg"; + private static final String FIST_IMAGE = "fist.jpg"; private static final String THUMB_UP_LANDMARKS = "thumb_up_landmarks.pb"; + private static final String FIST_LANDMARKS = "fist_landmarks.pb"; private static final String TAG = "Gesture Recognizer Test"; private static final String THUMB_UP_LABEL = "Thumb_Up"; - private static final int THUMB_UP_INDEX = 5; private static final String POINTING_UP_LABEL = "Pointing_Up"; - private static final int POINTING_UP_INDEX = 3; + private static final String FIST_LABEL = "Closed_Fist"; + private static final String ROCK_LABEL = "Rock"; private static final float LANDMARKS_ERROR_TOLERANCE = 0.03f; private static final int IMAGE_WIDTH = 382; private static final int IMAGE_HEIGHT = 406; + private static final int GESTURE_EXPECTED_INDEX = -1; @RunWith(AndroidJUnit4.class) public static final class General extends GestureRecognizerTest { @@ -77,7 +82,7 @@ public class GestureRecognizerTest { GestureRecognitionResult actualResult = gestureRecognizer.recognize(getImageFromAsset(THUMB_UP_IMAGE)); GestureRecognitionResult expectedResult = - getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); + getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL); assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult); } @@ -108,16 +113,14 @@ public class GestureRecognizerTest { BaseOptions.builder() .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) .build()) - // TODO update the confidence to be in range [0,1] after embedding model - // and scoring calculator is integrated. - .setMinGestureConfidence(2.0f) + .setMinGestureConfidence(0.5f) .build(); GestureRecognizer gestureRecognizer = GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); GestureRecognitionResult actualResult = gestureRecognizer.recognize(getImageFromAsset(THUMB_UP_IMAGE)); GestureRecognitionResult expectedResult = - getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); + getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL); // Only contains one top scoring gesture. assertThat(actualResult.gestures().get(0)).hasSize(1); assertActualGestureEqualExpectedGesture( @@ -159,10 +162,48 @@ public class GestureRecognizerTest { gestureRecognizer.recognize( getImageFromAsset(POINTING_UP_ROTATED_IMAGE), imageProcessingOptions); assertThat(actualResult.gestures()).hasSize(1); - assertThat(actualResult.gestures().get(0).get(0).index()).isEqualTo(POINTING_UP_INDEX); assertThat(actualResult.gestures().get(0).get(0).categoryName()).isEqualTo(POINTING_UP_LABEL); } + @Test + public void recognize_successWithCannedGestureFist() throws Exception { + GestureRecognizerOptions options = + GestureRecognizerOptions.builder() + .setBaseOptions( + BaseOptions.builder() + .setModelAssetPath(GESTURE_RECOGNIZER_BUNDLE_ASSET_FILE) + .build()) + .setNumHands(1) + .build(); + GestureRecognizer gestureRecognizer = + GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); + GestureRecognitionResult actualResult = + gestureRecognizer.recognize(getImageFromAsset(FIST_IMAGE)); + GestureRecognitionResult expectedResult = + getExpectedGestureRecognitionResult(FIST_LANDMARKS, FIST_LABEL); + assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult); + } + + @Test + public void recognize_successWithCustomGestureRock() throws Exception { + GestureRecognizerOptions options = + GestureRecognizerOptions.builder() + .setBaseOptions( + BaseOptions.builder() + .setModelAssetPath( + GESTURE_RECOGNIZER_WITH_CUSTOM_CLASSIFIER_BUNDLE_ASSET_FILE) + .build()) + .setNumHands(1) + .build(); + GestureRecognizer gestureRecognizer = + GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); + GestureRecognitionResult actualResult = + gestureRecognizer.recognize(getImageFromAsset(FIST_IMAGE)); + GestureRecognitionResult expectedResult = + getExpectedGestureRecognitionResult(FIST_LANDMARKS, ROCK_LABEL); + assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult); + } + @Test public void recognize_failsWithRegionOfInterest() throws Exception { GestureRecognizerOptions options = @@ -331,7 +372,7 @@ public class GestureRecognizerTest { GestureRecognitionResult actualResult = gestureRecognizer.recognize(getImageFromAsset(THUMB_UP_IMAGE)); GestureRecognitionResult expectedResult = - getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); + getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL); assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult); } @@ -348,7 +389,7 @@ public class GestureRecognizerTest { GestureRecognizer gestureRecognizer = GestureRecognizer.createFromOptions(ApplicationProvider.getApplicationContext(), options); GestureRecognitionResult expectedResult = - getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); + getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL); for (int i = 0; i < 3; i++) { GestureRecognitionResult actualResult = gestureRecognizer.recognizeForVideo( @@ -361,7 +402,7 @@ public class GestureRecognizerTest { public void recognize_failsWithOutOfOrderInputTimestamps() throws Exception { MPImage image = getImageFromAsset(THUMB_UP_IMAGE); GestureRecognitionResult expectedResult = - getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); + getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL); GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( @@ -393,7 +434,7 @@ public class GestureRecognizerTest { public void recognize_successWithLiveSteamMode() throws Exception { MPImage image = getImageFromAsset(THUMB_UP_IMAGE); GestureRecognitionResult expectedResult = - getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL, THUMB_UP_INDEX); + getExpectedGestureRecognitionResult(THUMB_UP_LANDMARKS, THUMB_UP_LABEL); GestureRecognizerOptions options = GestureRecognizerOptions.builder() .setBaseOptions( @@ -423,7 +464,7 @@ public class GestureRecognizerTest { } private static GestureRecognitionResult getExpectedGestureRecognitionResult( - String filePath, String gestureLabel, int gestureIndex) throws Exception { + String filePath, String gestureLabel) throws Exception { AssetManager assetManager = ApplicationProvider.getApplicationContext().getAssets(); InputStream istr = assetManager.open(filePath); LandmarksDetectionResult landmarksDetectionResultProto = @@ -431,9 +472,7 @@ public class GestureRecognizerTest { ClassificationProto.ClassificationList gesturesProto = ClassificationProto.ClassificationList.newBuilder() .addClassification( - ClassificationProto.Classification.newBuilder() - .setLabel(gestureLabel) - .setIndex(gestureIndex)) + ClassificationProto.Classification.newBuilder().setLabel(gestureLabel)) .build(); return GestureRecognitionResult.create( Arrays.asList(landmarksDetectionResultProto.getLandmarks()), @@ -479,8 +518,8 @@ public class GestureRecognizerTest { private static void assertActualGestureEqualExpectedGesture( Category actualGesture, Category expectedGesture) { - assertThat(actualGesture.index()).isEqualTo(actualGesture.index()); - assertThat(expectedGesture.categoryName()).isEqualTo(expectedGesture.categoryName()); + assertThat(actualGesture.categoryName()).isEqualTo(expectedGesture.categoryName()); + assertThat(actualGesture.index()).isEqualTo(GESTURE_EXPECTED_INDEX); } private static void assertImageSizeIsExpected(MPImage inputImage) { diff --git a/mediapipe/tasks/testdata/vision/BUILD b/mediapipe/tasks/testdata/vision/BUILD index c45cc6e69..ad8072b87 100644 --- a/mediapipe/tasks/testdata/vision/BUILD +++ b/mediapipe/tasks/testdata/vision/BUILD @@ -37,6 +37,7 @@ mediapipe_files(srcs = [ "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite", "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_with_dummy_score_calibration.tflite", "deeplabv3.tflite", + "fist.jpg", "hand_landmark_full.tflite", "hand_landmark_lite.tflite", "left_hands.jpg", @@ -64,6 +65,7 @@ mediapipe_files(srcs = [ "selfie_segm_144_256_3.tflite", "selfie_segm_144_256_3_expected_mask.jpg", "thumb_up.jpg", + "victory.jpg", ]) exports_files( @@ -91,6 +93,7 @@ filegroup( "cats_and_dogs.jpg", "cats_and_dogs_no_resizing.jpg", "cats_and_dogs_rotated.jpg", + "fist.jpg", "hand_landmark_full.tflite", "hand_landmark_lite.tflite", "left_hands.jpg", @@ -107,6 +110,7 @@ filegroup( "selfie_segm_128_128_3_expected_mask.jpg", "selfie_segm_144_256_3_expected_mask.jpg", "thumb_up.jpg", + "victory.jpg", ], visibility = [ "//mediapipe/python:__subpackages__", @@ -148,6 +152,7 @@ filegroup( "expected_left_up_hand_rotated_landmarks.prototxt", "expected_right_down_hand_landmarks.prototxt", "expected_right_up_hand_landmarks.prototxt", + "fist_landmarks.pbtxt", "hand_detector_result_one_hand.pbtxt", "hand_detector_result_one_hand_rotated.pbtxt", "hand_detector_result_two_hands.pbtxt", @@ -155,5 +160,6 @@ filegroup( "pointing_up_rotated_landmarks.pbtxt", "thumb_up_landmarks.pbtxt", "thumb_up_rotated_landmarks.pbtxt", + "victory_landmarks.pbtxt", ], ) diff --git a/mediapipe/tasks/testdata/vision/fist_landmarks.pbtxt b/mediapipe/tasks/testdata/vision/fist_landmarks.pbtxt new file mode 100644 index 000000000..a24358c3c --- /dev/null +++ b/mediapipe/tasks/testdata/vision/fist_landmarks.pbtxt @@ -0,0 +1,223 @@ +classifications { + classification { + score: 1.0 + label: "Left" + display_name: "Left" + } +} + +landmarks { + landmark { + x: 0.47709703 + y: 0.66129065 + z: -3.3540672e-07 + } + landmark { + x: 0.6125982 + y: 0.5578249 + z: -0.041392017 + } + landmark { + x: 0.71123487 + y: 0.4316616 + z: -0.064544134 + } + landmark { + x: 0.6836403 + y: 0.3199585 + z: -0.08752567 + } + landmark { + x: 0.5593274 + y: 0.3206453 + z: -0.09880819 + } + landmark { + x: 0.60828537 + y: 0.3068749 + z: -0.014799656 + } + landmark { + x: 0.62940764 + y: 0.21414441 + z: -0.06007311 + } + landmark { + x: 0.6244353 + y: 0.32872596 + z: -0.08326768 + } + landmark { + x: 0.60784453 + y: 0.3684796 + z: -0.09658983 + } + landmark { + x: 0.5156504 + y: 0.32194698 + z: -0.021699267 + } + landmark { + x: 0.52931 + y: 0.24767634 + z: -0.062571 + } + landmark { + x: 0.5484773 + y: 0.3805329 + z: -0.07028895 + } + landmark { + x: 0.54428184 + y: 0.3881125 + z: -0.07458326 + } + landmark { + x: 0.43159598 + y: 0.34918433 + z: -0.037482508 + } + landmark { + x: 0.4486106 + y: 0.27649382 + z: -0.08174769 + } + landmark { + x: 0.47723144 + y: 0.3964985 + z: -0.06496752 + } + landmark { + x: 0.46794242 + y: 0.4082967 + z: -0.04897496 + } + landmark { + x: 0.34826216 + y: 0.37813392 + z: -0.057438444 + } + landmark { + x: 0.3861837 + y: 0.32820183 + z: -0.07282783 + } + landmark { + x: 0.41143674 + y: 0.39734486 + z: -0.047633167 + } + landmark { + x: 0.39401984 + y: 0.41149133 + z: -0.029640475 + } +} + +world_landmarks { + landmark { + x: -0.008604452 + y: 0.08165767 + z: 0.0061365655 + } + landmark { + x: 0.027301773 + y: 0.061905317 + z: -0.00872007 + } + landmark { + x: 0.049898714 + y: 0.035359327 + z: -0.016682662 + } + landmark { + x: 0.050297678 + y: 0.005200807 + z: -0.028928496 + } + landmark { + x: 0.015639625 + y: -0.0063155442 + z: -0.03174634 + } + landmark { + x: 0.029161729 + y: -0.0024596984 + z: 0.0011553494 + } + landmark { + x: 0.034491 + y: -0.017581237 + z: -0.020781275 + } + landmark { + x: 0.034020264 + y: -0.0059247985 + z: -0.02573838 + } + landmark { + x: 0.02867364 + y: 0.011137734 + z: -0.009430941 + } + landmark { + x: 0.0015385814 + y: -0.004778851 + z: 0.0056454404 + } + landmark { + x: 0.010490709 + y: -0.019680617 + z: -0.027034117 + } + landmark { + x: 0.0132071925 + y: 0.0071370844 + z: -0.034802448 + } + landmark { + x: 0.0139978565 + y: 0.011672501 + z: -0.0040006908 + } + landmark { + x: -0.019919239 + y: -0.0006897822 + z: -0.0003317799 + } + landmark { + x: -0.01088193 + y: -0.008502296 + z: -0.02873486 + } + landmark { + x: -0.005327127 + y: 0.012745364 + z: -0.034153957 + } + landmark { + x: -0.0027040644 + y: 0.02167169 + z: -0.011669062 + } + landmark { + x: -0.038813893 + y: 0.011925209 + z: -0.0076287366 + } + landmark { + x: -0.030842202 + y: 0.0010964936 + z: -0.022697516 + } + landmark { + x: -0.01829514 + y: 0.013929318 + z: -0.032819964 + } + landmark { + x: -0.024175374 + y: 0.022456694 + z: -0.02357186 + } +} diff --git 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