Moved ClassifierOptions to mediapipe/tasks/python/components to align with the C++ API

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",
+    ],
+)

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())

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),
+        base_options=_BaseOptions(file_name=self.model_path),
-      category_denylist=_DENY_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)
@@ -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'],
+          classifier_options=classifier_options)
-          category_denylist=['bar'])
       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)

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",

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
+  classifier_options: _ClassifierOptions = _ClassifierOptions()
-  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
@@ -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 = self.classifier_options.to_pb2()
-    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,