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,