Code cleanup

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()

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)
-    })