Fixed some typos and revised image embedder tests
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kinaryml
parent
7ec0d8cf3b
commit
0e9b925726
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@ -100,28 +100,22 @@ class ImageEmbedderTest(parameterized.TestCase):
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embedder = _ImageEmbedder.create_from_options(options)
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self.assertIsInstance(embedder, _ImageEmbedder)
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def _check_cosine_similarity(self, result0, result1, quantize,
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expected_similarity):
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# Checks head_index and head_name.
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self.assertEqual(result0.embeddings[0].head_index, 0)
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self.assertEqual(result1.embeddings[0].head_index, 0)
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self.assertEqual(result0.embeddings[0].head_name, 'feature')
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self.assertEqual(result1.embeddings[0].head_name, 'feature')
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def _check_embedding_value(self, result, expected_first_value):
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# Check embedding first value.
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self.assertAlmostEqual(result.embeddings[0].embedding[0],
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expected_first_value, delta=_EPSILON)
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# Check embedding sizes.
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def _check_embedding_size(result):
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self.assertLen(result.embeddings, 1)
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embedding_result = result.embeddings[0]
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self.assertLen(embedding_result.embedding, 1024)
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if quantize:
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self.assertEqual(embedding_result.embedding.dtype, np.uint8)
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else:
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self.assertEqual(embedding_result.embedding.dtype, float)
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# Checks results sizes.
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_check_embedding_size(result0)
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_check_embedding_size(result1)
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def _check_embedding_size(self, result, quantize, expected_embedding_size):
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# Check embedding size.
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self.assertLen(result.embeddings, 1)
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embedding_result = result.embeddings[0]
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self.assertLen(embedding_result.embedding, expected_embedding_size)
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if quantize:
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self.assertEqual(embedding_result.embedding.dtype, np.uint8)
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else:
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self.assertEqual(embedding_result.embedding.dtype, float)
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def _check_cosine_similarity(self, result0, result1, expected_similarity):
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# Checks cosine similarity.
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similarity = _ImageEmbedder.cosine_similarity(
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result0.embeddings[0], result1.embeddings[0])
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@ -129,13 +123,17 @@ class ImageEmbedderTest(parameterized.TestCase):
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delta=_SIMILARITY_TOLERANCE)
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@parameterized.parameters(
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(False, False, False, ModelFileType.FILE_NAME, 0.925519, -0.2101883),
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(True, False, False, ModelFileType.FILE_NAME, 0.925519, -0.0142344),
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# (False, True, False, ModelFileType.FILE_NAME, 0.926791, 229),
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(False, False, True, ModelFileType.FILE_CONTENT, 0.999931, -0.195062)
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(False, False, False, ModelFileType.FILE_NAME,
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0.925519, 1024, (-0.2101883, -0.193027)),
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(True, False, False, ModelFileType.FILE_NAME,
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0.925519, 1024, (-0.0142344, -0.0131606)),
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# (False, True, False, ModelFileType.FILE_NAME,
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# 0.926791, 1024, (229, 231)),
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(False, False, True, ModelFileType.FILE_CONTENT,
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0.999931, 1024, (-0.195062, -0.193027))
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)
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def test_embed(self, l2_normalize, quantize, with_roi, model_file_type,
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expected_similarity, expected_first_value):
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expected_similarity, expected_size, expected_first_values):
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# Creates embedder.
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if model_file_type is ModelFileType.FILE_NAME:
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base_options = _BaseOptions(model_asset_path=self.model_path)
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@ -163,12 +161,13 @@ class ImageEmbedderTest(parameterized.TestCase):
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image_result = embedder.embed(self.test_image, image_processing_options)
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crop_result = embedder.embed(self.test_cropped_image)
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# Check embedding value.
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self.assertAlmostEqual(image_result.embeddings[0].embedding[0],
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expected_first_value, delta=_EPSILON)
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# Checks cosine similarity.
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self._check_cosine_similarity(image_result, crop_result, quantize,
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# Checks embeddings and cosine similarity.
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expected_result0_value, expected_result1_value = expected_first_values
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self._check_embedding_size(image_result, quantize, expected_size)
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self._check_embedding_size(crop_result, quantize, expected_size)
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self._check_embedding_value(image_result, expected_result0_value)
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self._check_embedding_value(crop_result, expected_result1_value)
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self._check_cosine_similarity(image_result, crop_result,
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expected_similarity)
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# Closes the embedder explicitly when the embedder is not used in
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# a context.
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@ -201,7 +200,7 @@ class ImageEmbedderTest(parameterized.TestCase):
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crop_result = embedder.embed(self.test_cropped_image)
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# Checks cosine similarity.
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self._check_cosine_similarity(image_result, crop_result, quantize,
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self._check_cosine_similarity(image_result, crop_result,
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expected_similarity)
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def test_missing_result_callback(self):
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@ -283,8 +282,7 @@ class ImageEmbedderTest(parameterized.TestCase):
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timestamp)
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# Checks cosine similarity.
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self._check_cosine_similarity(
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image_result, crop_result, quantize=False,
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expected_similarity=0.925519)
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image_result, crop_result, expected_similarity=0.925519)
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def test_embed_for_video_succeeds_with_region_of_interest(self):
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options = _ImageEmbedderOptions(
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@ -305,8 +303,7 @@ class ImageEmbedderTest(parameterized.TestCase):
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# Checks cosine similarity.
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self._check_cosine_similarity(
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image_result, crop_result, quantize=False,
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expected_similarity=0.999931)
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image_result, crop_result, expected_similarity=0.999931)
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def test_calling_embed_in_live_stream_mode(self):
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options = _ImageEmbedderOptions(
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@ -352,8 +349,8 @@ class ImageEmbedderTest(parameterized.TestCase):
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def check_result(result: ImageEmbedderResult, output_image: _Image,
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timestamp_ms: int):
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# Checks cosine similarity.
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self._check_cosine_similarity(result, crop_result, quantize=False,
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expected_similarity=0.925519)
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self._check_cosine_similarity(result, crop_result,
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expected_similarity=0.925519)
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self.assertTrue(
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np.array_equal(output_image.numpy_view(),
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self.test_image.numpy_view()))
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@ -384,7 +381,7 @@ class ImageEmbedderTest(parameterized.TestCase):
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def check_result(result: ImageEmbedderResult, output_image: _Image,
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timestamp_ms: int):
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# Checks cosine similarity.
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self._check_cosine_similarity(result, crop_result, quantize=False,
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self._check_cosine_similarity(result, crop_result,
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expected_similarity=0.999931)
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self.assertTrue(
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np.array_equal(output_image.numpy_view(),
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@ -20,7 +20,6 @@ from mediapipe.python import packet_creator
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from mediapipe.python import packet_getter
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from mediapipe.python._framework_bindings import image as image_module
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from mediapipe.python._framework_bindings import packet as packet_module
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from mediapipe.python._framework_bindings import task_runner as task_runner_module
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from mediapipe.tasks.cc.vision.image_embedder.proto import image_embedder_graph_options_pb2
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from mediapipe.tasks.cc.components.containers.proto import embeddings_pb2
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from mediapipe.tasks.python.components.processors import embedder_options
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@ -40,7 +39,6 @@ _EmbedderOptions = embedder_options.EmbedderOptions
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_RunningMode = running_mode_module.VisionTaskRunningMode
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_TaskInfo = task_info_module.TaskInfo
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_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions
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_TaskRunner = task_runner_module.TaskRunner
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_EMBEDDINGS_OUT_STREAM_NAME = 'embeddings_out'
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_EMBEDDINGS_TAG = 'EMBEDDINGS'
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@ -112,7 +110,7 @@ class ImageEmbedder(base_vision_task_api.BaseVisionTaskApi):
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`ImageEmbedderOptions`.
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Raises:
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ValueError: If failed to create `ImageClassifier` object from the provided
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ValueError: If failed to create `ImageEmbedder` object from the provided
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file such as invalid file path.
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RuntimeError: If other types of error occurred.
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"""
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@ -185,7 +183,7 @@ class ImageEmbedder(base_vision_task_api.BaseVisionTaskApi):
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image_processing_options: Options for image processing.
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Returns:
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A embedding result object that contains a list of embeddings.
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An embedding result object that contains a list of embeddings.
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Raises:
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ValueError: If any of the input arguments is invalid.
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@ -223,7 +221,7 @@ class ImageEmbedder(base_vision_task_api.BaseVisionTaskApi):
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image_processing_options: Options for image processing.
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Returns:
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A embedding result object that contains a list of embeddings.
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An embedding result object that contains a list of embeddings.
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Raises:
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ValueError: If any of the input arguments is invalid.
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@ -265,7 +263,7 @@ class ImageEmbedder(base_vision_task_api.BaseVisionTaskApi):
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per input image.
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The `result_callback` provides:
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- A embedding result object that contains a list of embeddings.
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- An embedding result object that contains a list of embeddings.
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- The input image that the image embedder runs on.
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- The input timestamp in milliseconds.
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