Added text classifier implementation and tests
This commit is contained in:
parent
ddf37d014e
commit
6e9a070dd1
|
@ -90,6 +90,7 @@ cc_library(
|
|||
"//mediapipe/tasks/cc/vision/image_classifier:image_classifier_graph",
|
||||
"//mediapipe/tasks/cc/vision/image_segmenter:image_segmenter_graph",
|
||||
"//mediapipe/tasks/cc/vision/object_detector:object_detector_graph",
|
||||
"//mediapipe/tasks/cc/text/text_classifier:text_classifier_graph",
|
||||
],
|
||||
)
|
||||
|
||||
|
|
37
mediapipe/tasks/python/test/text/BUILD
Normal file
37
mediapipe/tasks/python/test/text/BUILD
Normal file
|
@ -0,0 +1,37 @@
|
|||
# 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 test compatibility macro.
|
||||
|
||||
package(default_visibility = ["//mediapipe/tasks:internal"])
|
||||
|
||||
licenses(["notice"])
|
||||
|
||||
py_test(
|
||||
name = "text_classifier_test",
|
||||
srcs = ["text_classifier_test.py"],
|
||||
data = [
|
||||
"//mediapipe/tasks/testdata/text:bert_text_classifier_models",
|
||||
"//mediapipe/tasks/testdata/text:text_classifier_models",
|
||||
],
|
||||
deps = [
|
||||
"//mediapipe/python:_framework_bindings",
|
||||
"//mediapipe/tasks/python/components/containers:category",
|
||||
"//mediapipe/tasks/python/components/containers:classifications",
|
||||
"//mediapipe/tasks/python/components/processors:classifier_options",
|
||||
"//mediapipe/tasks/python/core:base_options",
|
||||
"//mediapipe/tasks/python/test:test_utils",
|
||||
"//mediapipe/tasks/python/text:text_classifier",
|
||||
],
|
||||
)
|
13
mediapipe/tasks/python/test/text/__init__.py
Normal file
13
mediapipe/tasks/python/test/text/__init__.py
Normal file
|
@ -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.
|
246
mediapipe/tasks/python/test/text/text_classifier_test.py
Normal file
246
mediapipe/tasks/python/test/text/text_classifier_test.py
Normal file
|
@ -0,0 +1,246 @@
|
|||
# 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 text classifier."""
|
||||
|
||||
import enum
|
||||
import os
|
||||
|
||||
from absl.testing import absltest
|
||||
from absl.testing import parameterized
|
||||
|
||||
|
||||
from mediapipe.tasks.python.components.containers import category
|
||||
from mediapipe.tasks.python.components.containers import classifications as classifications_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.test import test_utils
|
||||
from mediapipe.tasks.python.text import text_classifier
|
||||
|
||||
_BaseOptions = base_options_module.BaseOptions
|
||||
_ClassifierOptions = classifier_options.ClassifierOptions
|
||||
_Category = category.Category
|
||||
_ClassificationEntry = classifications_module.ClassificationEntry
|
||||
_Classifications = classifications_module.Classifications
|
||||
_ClassificationResult = classifications_module.ClassificationResult
|
||||
_TextClassifier = text_classifier.TextClassifier
|
||||
_TextClassifierOptions = text_classifier.TextClassifierOptions
|
||||
|
||||
_BERT_MODEL_FILE = 'bert_text_classifier.tflite'
|
||||
_REGEX_MODEL_FILE = 'test_model_text_classifier_with_regex_tokenizer.tflite'
|
||||
_TEST_DATA_DIR = 'mediapipe/tasks/testdata/text'
|
||||
|
||||
_NEGATIVE_TEXT = "What a waste of my time."
|
||||
_POSITIVE_TEXT = ("This is the best movie I’ve seen in recent years."
|
||||
"Strongly recommend it!")
|
||||
|
||||
_BERT_NEGATIVE_RESULTS = _ClassificationResult(
|
||||
classifications=[
|
||||
_Classifications(
|
||||
entries=[
|
||||
_ClassificationEntry(
|
||||
categories=[
|
||||
_Category(
|
||||
index=0, score=0.999479, display_name='',
|
||||
category_name='negative'),
|
||||
_Category(
|
||||
index=1, score=0.00052154, display_name='',
|
||||
category_name='positive')
|
||||
],
|
||||
timestamp_ms=0
|
||||
)
|
||||
],
|
||||
head_index=0,
|
||||
head_name='probability')
|
||||
])
|
||||
_BERT_POSITIVE_RESULTS = _ClassificationResult(
|
||||
classifications=[
|
||||
_Classifications(
|
||||
entries=[
|
||||
_ClassificationEntry(
|
||||
categories=[
|
||||
_Category(
|
||||
index=1, score=0.999466, display_name='',
|
||||
category_name='positive'),
|
||||
_Category(
|
||||
index=0, score=0.000533596, display_name='',
|
||||
category_name='negative')
|
||||
],
|
||||
timestamp_ms=0
|
||||
)
|
||||
],
|
||||
head_index=0,
|
||||
head_name='probability')
|
||||
])
|
||||
_REGEX_NEGATIVE_RESULTS = _ClassificationResult(
|
||||
classifications=[
|
||||
_Classifications(
|
||||
entries=[
|
||||
_ClassificationEntry(
|
||||
categories=[
|
||||
_Category(
|
||||
index=0, score=0.81313, display_name='',
|
||||
category_name='Negative'),
|
||||
_Category(
|
||||
index=1, score=0.1868704, display_name='',
|
||||
category_name='Positive')
|
||||
],
|
||||
timestamp_ms=0
|
||||
)
|
||||
],
|
||||
head_index=0,
|
||||
head_name='probability')
|
||||
])
|
||||
_REGEX_POSITIVE_RESULTS = _ClassificationResult(
|
||||
classifications=[
|
||||
_Classifications(
|
||||
entries=[
|
||||
_ClassificationEntry(
|
||||
categories=[
|
||||
_Category(
|
||||
index=1, score=0.5134273, display_name='',
|
||||
category_name='Positive'),
|
||||
_Category(
|
||||
index=0, score=0.486573, display_name='',
|
||||
category_name='Negative')
|
||||
],
|
||||
timestamp_ms=0
|
||||
)
|
||||
],
|
||||
head_index=0,
|
||||
head_name='probability')
|
||||
])
|
||||
|
||||
|
||||
class ModelFileType(enum.Enum):
|
||||
FILE_CONTENT = 1
|
||||
FILE_NAME = 2
|
||||
|
||||
|
||||
class ImageClassifierTest(parameterized.TestCase):
|
||||
|
||||
def setUp(self):
|
||||
super().setUp()
|
||||
self.model_path = test_utils.get_test_data_path(
|
||||
os.path.join(_TEST_DATA_DIR, _BERT_MODEL_FILE))
|
||||
|
||||
def test_create_from_file_succeeds_with_valid_model_path(self):
|
||||
# Creates with default option and valid model file successfully.
|
||||
with _TextClassifier.create_from_model_path(self.model_path) as classifier:
|
||||
self.assertIsInstance(classifier, _TextClassifier)
|
||||
|
||||
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 = _TextClassifierOptions(base_options=base_options)
|
||||
with _TextClassifier.create_from_options(options) as classifier:
|
||||
self.assertIsInstance(classifier, _TextClassifier)
|
||||
|
||||
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 = _TextClassifierOptions(base_options=base_options)
|
||||
_TextClassifier.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 = _TextClassifierOptions(base_options=base_options)
|
||||
classifier = _TextClassifier.create_from_options(options)
|
||||
self.assertIsInstance(classifier, _TextClassifier)
|
||||
|
||||
@parameterized.parameters(
|
||||
(ModelFileType.FILE_NAME, _BERT_MODEL_FILE, _NEGATIVE_TEXT,
|
||||
_BERT_NEGATIVE_RESULTS),
|
||||
(ModelFileType.FILE_CONTENT, _BERT_MODEL_FILE, _NEGATIVE_TEXT,
|
||||
_BERT_NEGATIVE_RESULTS),
|
||||
(ModelFileType.FILE_NAME, _BERT_MODEL_FILE, _POSITIVE_TEXT,
|
||||
_BERT_POSITIVE_RESULTS),
|
||||
(ModelFileType.FILE_CONTENT, _BERT_MODEL_FILE, _POSITIVE_TEXT,
|
||||
_BERT_POSITIVE_RESULTS),
|
||||
(ModelFileType.FILE_NAME, _REGEX_MODEL_FILE, _NEGATIVE_TEXT,
|
||||
_REGEX_NEGATIVE_RESULTS),
|
||||
(ModelFileType.FILE_CONTENT, _REGEX_MODEL_FILE, _NEGATIVE_TEXT,
|
||||
_REGEX_NEGATIVE_RESULTS),
|
||||
(ModelFileType.FILE_NAME, _REGEX_MODEL_FILE, _POSITIVE_TEXT,
|
||||
_REGEX_POSITIVE_RESULTS),
|
||||
(ModelFileType.FILE_CONTENT, _REGEX_MODEL_FILE, _POSITIVE_TEXT,
|
||||
_REGEX_POSITIVE_RESULTS))
|
||||
def test_classify(self, model_file_type, model_name, text,
|
||||
expected_classification_result):
|
||||
# Creates classifier.
|
||||
model_path = test_utils.get_test_data_path(
|
||||
os.path.join(_TEST_DATA_DIR, model_name))
|
||||
if model_file_type is ModelFileType.FILE_NAME:
|
||||
base_options = _BaseOptions(model_asset_path=model_path)
|
||||
elif model_file_type is ModelFileType.FILE_CONTENT:
|
||||
with open(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.')
|
||||
|
||||
custom_classifier_options = _ClassifierOptions()
|
||||
options = _TextClassifierOptions(
|
||||
base_options=base_options, classifier_options=custom_classifier_options)
|
||||
classifier = _TextClassifier.create_from_options(options)
|
||||
|
||||
# Performs text classification on the input.
|
||||
text_result = classifier.classify(text)
|
||||
# Comparing results.
|
||||
test_utils.assert_proto_equals(self, text_result.to_pb2(),
|
||||
expected_classification_result.to_pb2())
|
||||
# Closes the classifier explicitly when the classifier is not used in
|
||||
# a context.
|
||||
classifier.close()
|
||||
|
||||
@parameterized.parameters(
|
||||
(ModelFileType.FILE_NAME, _BERT_MODEL_FILE, _NEGATIVE_TEXT,
|
||||
_BERT_NEGATIVE_RESULTS),
|
||||
(ModelFileType.FILE_CONTENT, _BERT_MODEL_FILE, _NEGATIVE_TEXT,
|
||||
_BERT_NEGATIVE_RESULTS))
|
||||
def test_classify_in_context(self, model_file_type, model_name, text,
|
||||
expected_classification_result):
|
||||
# Creates classifier.
|
||||
model_path = test_utils.get_test_data_path(
|
||||
os.path.join(_TEST_DATA_DIR, model_name))
|
||||
if model_file_type is ModelFileType.FILE_NAME:
|
||||
base_options = _BaseOptions(model_asset_path=model_path)
|
||||
elif model_file_type is ModelFileType.FILE_CONTENT:
|
||||
with open(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.')
|
||||
|
||||
custom_classifier_options = _ClassifierOptions()
|
||||
options = _TextClassifierOptions(
|
||||
base_options=base_options, classifier_options=custom_classifier_options)
|
||||
|
||||
with _TextClassifier.create_from_options(options) as classifier:
|
||||
# Performs text classification on the input.
|
||||
text_result = classifier.classify(text)
|
||||
# Comparing results.
|
||||
test_utils.assert_proto_equals(self, text_result.to_pb2(),
|
||||
expected_classification_result.to_pb2())
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
absltest.main()
|
39
mediapipe/tasks/python/text/BUILD
Normal file
39
mediapipe/tasks/python/text/BUILD
Normal file
|
@ -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.
|
||||
|
||||
# Placeholder for internal Python strict library and test compatibility macro.
|
||||
|
||||
package(default_visibility = ["//mediapipe/tasks:internal"])
|
||||
|
||||
licenses(["notice"])
|
||||
|
||||
py_library(
|
||||
name = "text_classifier",
|
||||
srcs = [
|
||||
"text_classifier.py",
|
||||
],
|
||||
deps = [
|
||||
"//mediapipe/python:_framework_bindings",
|
||||
"//mediapipe/python:packet_creator",
|
||||
"//mediapipe/python:packet_getter",
|
||||
"//mediapipe/tasks/cc/components/containers/proto:classifications_py_pb2",
|
||||
"//mediapipe/tasks/cc/text/text_classifier/proto:text_classifier_graph_options_py_pb2",
|
||||
"//mediapipe/tasks/python/components/containers:classifications",
|
||||
"//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/text/core:base_text_task_api",
|
||||
],
|
||||
)
|
31
mediapipe/tasks/python/text/__init__.py
Normal file
31
mediapipe/tasks/python/text/__init__.py
Normal file
|
@ -0,0 +1,31 @@
|
|||
# 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 Tasks Vision API."""
|
||||
|
||||
import mediapipe.tasks.python.vision.core
|
||||
import mediapipe.tasks.python.vision.image_classifier
|
||||
import mediapipe.tasks.python.vision.object_detector
|
||||
|
||||
ImageClassifier = image_classifier.ImageClassifier
|
||||
ImageClassifierOptions = image_classifier.ImageClassifierOptions
|
||||
ObjectDetector = object_detector.ObjectDetector
|
||||
ObjectDetectorOptions = object_detector.ObjectDetectorOptions
|
||||
RunningMode = core.vision_task_running_mode.VisionTaskRunningMode
|
||||
|
||||
# Remove unnecessary modules to avoid duplication in API docs.
|
||||
del core
|
||||
del image_classifier
|
||||
del object_detector
|
||||
del mediapipe
|
31
mediapipe/tasks/python/text/core/BUILD
Normal file
31
mediapipe/tasks/python/text/core/BUILD
Normal file
|
@ -0,0 +1,31 @@
|
|||
# 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 and test compatibility macro.
|
||||
|
||||
package(default_visibility = ["//mediapipe/tasks:internal"])
|
||||
|
||||
licenses(["notice"])
|
||||
|
||||
py_library(
|
||||
name = "base_text_task_api",
|
||||
srcs = [
|
||||
"base_text_task_api.py",
|
||||
],
|
||||
deps = [
|
||||
"//mediapipe/framework:calculator_py_pb2",
|
||||
"//mediapipe/python:_framework_bindings",
|
||||
"//mediapipe/tasks/python/core:optional_dependencies",
|
||||
],
|
||||
)
|
14
mediapipe/tasks/python/text/core/__init__.py
Normal file
14
mediapipe/tasks/python/text/core/__init__.py
Normal file
|
@ -0,0 +1,14 @@
|
|||
"""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.
|
||||
"""
|
57
mediapipe/tasks/python/text/core/base_text_task_api.py
Normal file
57
mediapipe/tasks/python/text/core/base_text_task_api.py
Normal file
|
@ -0,0 +1,57 @@
|
|||
# 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 text task base api."""
|
||||
|
||||
from mediapipe.framework import calculator_pb2
|
||||
from mediapipe.python._framework_bindings import task_runner
|
||||
from mediapipe.tasks.python.core.optional_dependencies import doc_controls
|
||||
|
||||
_TaskRunner = task_runner.TaskRunner
|
||||
|
||||
|
||||
class BaseTextTaskApi(object):
|
||||
"""The base class of the user-facing mediapipe text task api classes."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
graph_config: calculator_pb2.CalculatorGraphConfig
|
||||
) -> None:
|
||||
"""Initializes the `BaseVisionTaskApi` object.
|
||||
|
||||
Args:
|
||||
graph_config: The mediapipe text task graph config proto.
|
||||
"""
|
||||
self._runner = _TaskRunner.create(graph_config)
|
||||
|
||||
def close(self) -> None:
|
||||
"""Shuts down the mediapipe text task instance.
|
||||
|
||||
Raises:
|
||||
RuntimeError: If the mediapipe text task failed to close.
|
||||
"""
|
||||
self._runner.close()
|
||||
|
||||
@doc_controls.do_not_generate_docs
|
||||
def __enter__(self):
|
||||
"""Return `self` upon entering the runtime context."""
|
||||
return self
|
||||
|
||||
@doc_controls.do_not_generate_docs
|
||||
def __exit__(self, unused_exc_type, unused_exc_value, unused_traceback):
|
||||
"""Shuts down the mediapipe text task instance on exit of the context manager.
|
||||
|
||||
Raises:
|
||||
RuntimeError: If the mediapipe text task failed to close.
|
||||
"""
|
||||
self.close()
|
146
mediapipe/tasks/python/text/text_classifier.py
Normal file
146
mediapipe/tasks/python/text/text_classifier.py
Normal file
|
@ -0,0 +1,146 @@
|
|||
# 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 text classifier task."""
|
||||
|
||||
import dataclasses
|
||||
|
||||
from mediapipe.python import packet_creator
|
||||
from mediapipe.python import packet_getter
|
||||
# TODO: Import MPImage directly one we have an alias
|
||||
from mediapipe.tasks.cc.components.containers.proto import classifications_pb2
|
||||
from mediapipe.tasks.cc.text.text_classifier.proto import text_classifier_graph_options_pb2
|
||||
from mediapipe.tasks.python.components.containers import classifications
|
||||
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.text.core import base_text_task_api
|
||||
|
||||
_BaseOptions = base_options_module.BaseOptions
|
||||
_TextClassifierGraphOptionsProto = text_classifier_graph_options_pb2.TextClassifierGraphOptions
|
||||
_ClassifierOptions = classifier_options.ClassifierOptions
|
||||
_TaskInfo = task_info_module.TaskInfo
|
||||
|
||||
_CLASSIFICATION_RESULT_OUT_STREAM_NAME = 'classification_result_out'
|
||||
_CLASSIFICATION_RESULT_TAG = 'CLASSIFICATION_RESULT'
|
||||
_TEXT_IN_STREAM_NAME = 'text_in'
|
||||
_TEXT_TAG = 'TEXT'
|
||||
_TASK_GRAPH_NAME = 'mediapipe.tasks.text.text_classifier.TextClassifierGraph'
|
||||
_MICRO_SECONDS_PER_MILLISECOND = 1000
|
||||
|
||||
|
||||
@dataclasses.dataclass
|
||||
class TextClassifierOptions:
|
||||
"""Options for the text classifier task.
|
||||
|
||||
Attributes:
|
||||
base_options: Base options for the text classifier task.
|
||||
classifier_options: Options for the text classification task.
|
||||
"""
|
||||
base_options: _BaseOptions
|
||||
classifier_options: _ClassifierOptions = _ClassifierOptions()
|
||||
|
||||
@doc_controls.do_not_generate_docs
|
||||
def to_pb2(self) -> _TextClassifierGraphOptionsProto:
|
||||
"""Generates an TextClassifierOptions protobuf object."""
|
||||
base_options_proto = self.base_options.to_pb2()
|
||||
classifier_options_proto = self.classifier_options.to_pb2()
|
||||
|
||||
return _TextClassifierGraphOptionsProto(
|
||||
base_options=base_options_proto,
|
||||
classifier_options=classifier_options_proto)
|
||||
|
||||
|
||||
class TextClassifier(base_text_task_api.BaseTextTaskApi):
|
||||
"""Class that performs classification on text."""
|
||||
|
||||
@classmethod
|
||||
def create_from_model_path(cls, model_path: str) -> 'TextClassifier':
|
||||
"""Creates an `TextClassifier` object from a TensorFlow Lite model and the default `TextClassifierOptions`.
|
||||
|
||||
Args:
|
||||
model_path: Path to the model.
|
||||
|
||||
Returns:
|
||||
`TextClassifier` object that's created from the model file and the
|
||||
default `TextClassifierOptions`.
|
||||
|
||||
Raises:
|
||||
ValueError: If failed to create `TextClassifier` 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 = TextClassifierOptions(base_options=base_options)
|
||||
return cls.create_from_options(options)
|
||||
|
||||
@classmethod
|
||||
def create_from_options(cls,
|
||||
options: TextClassifierOptions) -> 'TextClassifier':
|
||||
"""Creates the `TextClassifier` object from text classifier options.
|
||||
|
||||
Args:
|
||||
options: Options for the text classifier task.
|
||||
|
||||
Returns:
|
||||
`TextClassifier` object that's created from `options`.
|
||||
|
||||
Raises:
|
||||
ValueError: If failed to create `TextClassifier` object from
|
||||
`TextClassifierOptions` such as missing the model.
|
||||
RuntimeError: If other types of error occurred.
|
||||
"""
|
||||
task_info = _TaskInfo(
|
||||
task_graph=_TASK_GRAPH_NAME,
|
||||
input_streams=[
|
||||
':'.join([_TEXT_TAG, _TEXT_IN_STREAM_NAME])
|
||||
],
|
||||
output_streams=[
|
||||
':'.join([
|
||||
_CLASSIFICATION_RESULT_TAG,
|
||||
_CLASSIFICATION_RESULT_OUT_STREAM_NAME
|
||||
])
|
||||
],
|
||||
task_options=options)
|
||||
return cls(task_info.generate_graph_config())
|
||||
|
||||
def classify(
|
||||
self,
|
||||
text: str,
|
||||
) -> classifications.ClassificationResult:
|
||||
"""Performs classification on the input `text`.
|
||||
|
||||
Args:
|
||||
text: The input text.
|
||||
|
||||
Returns:
|
||||
A classification result object that contains a list of classifications.
|
||||
|
||||
Raises:
|
||||
ValueError: If any of the input arguments is invalid.
|
||||
RuntimeError: If text classification failed to run.
|
||||
"""
|
||||
output_packets = self._runner.process({
|
||||
_TEXT_IN_STREAM_NAME: packet_creator.create_string(text)
|
||||
})
|
||||
|
||||
classification_result_proto = classifications_pb2.ClassificationResult()
|
||||
classification_result_proto.CopyFrom(
|
||||
packet_getter.get_proto(
|
||||
output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]))
|
||||
|
||||
return classifications.ClassificationResult([
|
||||
classifications.Classifications.create_from_pb2(classification)
|
||||
for classification in classification_result_proto.classifications
|
||||
])
|
Loading…
Reference in New Issue
Block a user