Undo commenting out remaining tests
This commit is contained in:
parent
87238705dd
commit
ea77a7c25d
|
@ -125,8 +125,7 @@ class ImageEmbedderTest(parameterized.TestCase):
|
|||
(-0.2101883, -0.193027)),
|
||||
(True, False, False, ModelFileType.FILE_NAME, 0.925519, 1024,
|
||||
(-0.0142344, -0.0131606)),
|
||||
(False, True, False, ModelFileType.FILE_NAME,
|
||||
0.906201, 1024, (229, 231)),
|
||||
(False, True, False, ModelFileType.FILE_NAME, 0.906201, 1024, (229, 231)),
|
||||
(False, False, True, ModelFileType.FILE_CONTENT, 0.999931, 1024,
|
||||
(-0.195062, -0.193027)))
|
||||
def test_embed(self, l2_normalize, quantize, with_roi, model_file_type,
|
||||
|
@ -169,231 +168,231 @@ class ImageEmbedderTest(parameterized.TestCase):
|
|||
# Closes the embedder explicitly when the embedder is not used in
|
||||
# a context.
|
||||
embedder.close()
|
||||
#
|
||||
# @parameterized.parameters(
|
||||
# (False, False, ModelFileType.FILE_NAME, 0.925519),
|
||||
# (False, False, ModelFileType.FILE_CONTENT, 0.925519))
|
||||
# def test_embed_in_context(self, l2_normalize, quantize, model_file_type,
|
||||
# expected_similarity):
|
||||
# # Creates embedder.
|
||||
# if model_file_type is ModelFileType.FILE_NAME:
|
||||
# base_options = _BaseOptions(model_asset_path=self.model_path)
|
||||
# elif model_file_type is ModelFileType.FILE_CONTENT:
|
||||
# with open(self.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.')
|
||||
#
|
||||
# embedder_options = _EmbedderOptions(
|
||||
# l2_normalize=l2_normalize, quantize=quantize)
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=base_options, embedder_options=embedder_options)
|
||||
#
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# # Extracts both embeddings.
|
||||
# image_result = embedder.embed(self.test_image)
|
||||
# crop_result = embedder.embed(self.test_cropped_image)
|
||||
#
|
||||
# # Checks cosine similarity.
|
||||
# self._check_cosine_similarity(image_result, crop_result,
|
||||
# expected_similarity)
|
||||
#
|
||||
# def test_missing_result_callback(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.LIVE_STREAM)
|
||||
# with self.assertRaisesRegex(ValueError,
|
||||
# r'result callback must be provided'):
|
||||
# with _ImageEmbedder.create_from_options(options) as unused_embedder:
|
||||
# pass
|
||||
#
|
||||
# @parameterized.parameters((_RUNNING_MODE.IMAGE), (_RUNNING_MODE.VIDEO))
|
||||
# def test_illegal_result_callback(self, running_mode):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=running_mode,
|
||||
# result_callback=mock.MagicMock())
|
||||
# with self.assertRaisesRegex(ValueError,
|
||||
# r'result callback should not be provided'):
|
||||
# with _ImageEmbedder.create_from_options(options) as unused_embedder:
|
||||
# pass
|
||||
#
|
||||
# def test_calling_embed_for_video_in_image_mode(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.IMAGE)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# with self.assertRaisesRegex(ValueError,
|
||||
# r'not initialized with the video mode'):
|
||||
# embedder.embed_for_video(self.test_image, 0)
|
||||
#
|
||||
# def test_calling_embed_async_in_image_mode(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.IMAGE)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# with self.assertRaisesRegex(ValueError,
|
||||
# r'not initialized with the live stream mode'):
|
||||
# embedder.embed_async(self.test_image, 0)
|
||||
#
|
||||
# def test_calling_embed_in_video_mode(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.VIDEO)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# with self.assertRaisesRegex(ValueError,
|
||||
# r'not initialized with the image mode'):
|
||||
# embedder.embed(self.test_image)
|
||||
#
|
||||
# def test_calling_embed_async_in_video_mode(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.VIDEO)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# with self.assertRaisesRegex(ValueError,
|
||||
# r'not initialized with the live stream mode'):
|
||||
# embedder.embed_async(self.test_image, 0)
|
||||
#
|
||||
# def test_embed_for_video_with_out_of_order_timestamp(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.VIDEO)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# unused_result = embedder.embed_for_video(self.test_image, 1)
|
||||
# with self.assertRaisesRegex(
|
||||
# ValueError, r'Input timestamp must be monotonically increasing'):
|
||||
# embedder.embed_for_video(self.test_image, 0)
|
||||
#
|
||||
# def test_embed_for_video(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.VIDEO)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder0, \
|
||||
# _ImageEmbedder.create_from_options(options) as embedder1:
|
||||
# for timestamp in range(0, 300, 30):
|
||||
# # Extracts both embeddings.
|
||||
# image_result = embedder0.embed_for_video(self.test_image, timestamp)
|
||||
# crop_result = embedder1.embed_for_video(self.test_cropped_image,
|
||||
# timestamp)
|
||||
# # Checks cosine similarity.
|
||||
# self._check_cosine_similarity(
|
||||
# image_result, crop_result, expected_similarity=0.925519)
|
||||
#
|
||||
# def test_embed_for_video_succeeds_with_region_of_interest(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.VIDEO)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder0, \
|
||||
# _ImageEmbedder.create_from_options(options) as embedder1:
|
||||
# # Region-of-interest in "burger.jpg" corresponding to "burger_crop.jpg".
|
||||
# roi = _Rect(left=0, top=0, right=0.833333, bottom=1)
|
||||
# image_processing_options = _ImageProcessingOptions(roi)
|
||||
#
|
||||
# for timestamp in range(0, 300, 30):
|
||||
# # Extracts both embeddings.
|
||||
# image_result = embedder0.embed_for_video(self.test_image, timestamp,
|
||||
# image_processing_options)
|
||||
# crop_result = embedder1.embed_for_video(self.test_cropped_image,
|
||||
# timestamp)
|
||||
#
|
||||
# # Checks cosine similarity.
|
||||
# self._check_cosine_similarity(
|
||||
# image_result, crop_result, expected_similarity=0.999931)
|
||||
#
|
||||
# def test_calling_embed_in_live_stream_mode(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
# result_callback=mock.MagicMock())
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# with self.assertRaisesRegex(ValueError,
|
||||
# r'not initialized with the image mode'):
|
||||
# embedder.embed(self.test_image)
|
||||
#
|
||||
# def test_calling_embed_for_video_in_live_stream_mode(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
# result_callback=mock.MagicMock())
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# with self.assertRaisesRegex(ValueError,
|
||||
# r'not initialized with the video mode'):
|
||||
# embedder.embed_for_video(self.test_image, 0)
|
||||
#
|
||||
# def test_embed_async_calls_with_illegal_timestamp(self):
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
# result_callback=mock.MagicMock())
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# embedder.embed_async(self.test_image, 100)
|
||||
# with self.assertRaisesRegex(
|
||||
# ValueError, r'Input timestamp must be monotonically increasing'):
|
||||
# embedder.embed_async(self.test_image, 0)
|
||||
#
|
||||
# def test_embed_async_calls(self):
|
||||
# # Get the embedding result for the cropped image.
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.IMAGE)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# crop_result = embedder.embed(self.test_cropped_image)
|
||||
#
|
||||
# observed_timestamp_ms = -1
|
||||
#
|
||||
# def check_result(result: _ImageEmbedderResult, output_image: _Image,
|
||||
# timestamp_ms: int):
|
||||
# # Checks cosine similarity.
|
||||
# self._check_cosine_similarity(
|
||||
# result, crop_result, expected_similarity=0.925519)
|
||||
# self.assertTrue(
|
||||
# np.array_equal(output_image.numpy_view(),
|
||||
# self.test_image.numpy_view()))
|
||||
# self.assertLess(observed_timestamp_ms, timestamp_ms)
|
||||
# self.observed_timestamp_ms = timestamp_ms
|
||||
#
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
# result_callback=check_result)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# for timestamp in range(0, 300, 30):
|
||||
# embedder.embed_async(self.test_image, timestamp)
|
||||
#
|
||||
# def test_embed_async_succeeds_with_region_of_interest(self):
|
||||
# # Get the embedding result for the cropped image.
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.IMAGE)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# crop_result = embedder.embed(self.test_cropped_image)
|
||||
#
|
||||
# # Region-of-interest in "burger.jpg" corresponding to "burger_crop.jpg".
|
||||
# roi = _Rect(left=0, top=0, right=0.833333, bottom=1)
|
||||
# image_processing_options = _ImageProcessingOptions(roi)
|
||||
# observed_timestamp_ms = -1
|
||||
#
|
||||
# def check_result(result: _ImageEmbedderResult, output_image: _Image,
|
||||
# timestamp_ms: int):
|
||||
# # Checks cosine similarity.
|
||||
# self._check_cosine_similarity(
|
||||
# result, crop_result, expected_similarity=0.999931)
|
||||
# self.assertTrue(
|
||||
# np.array_equal(output_image.numpy_view(),
|
||||
# self.test_image.numpy_view()))
|
||||
# self.assertLess(observed_timestamp_ms, timestamp_ms)
|
||||
# self.observed_timestamp_ms = timestamp_ms
|
||||
#
|
||||
# options = _ImageEmbedderOptions(
|
||||
# base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
# running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
# result_callback=check_result)
|
||||
# with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# for timestamp in range(0, 300, 30):
|
||||
# embedder.embed_async(self.test_image, timestamp,
|
||||
# image_processing_options)
|
||||
|
||||
@parameterized.parameters(
|
||||
(False, False, ModelFileType.FILE_NAME, 0.925519),
|
||||
(False, False, ModelFileType.FILE_CONTENT, 0.925519))
|
||||
def test_embed_in_context(self, l2_normalize, quantize, model_file_type,
|
||||
expected_similarity):
|
||||
# Creates embedder.
|
||||
if model_file_type is ModelFileType.FILE_NAME:
|
||||
base_options = _BaseOptions(model_asset_path=self.model_path)
|
||||
elif model_file_type is ModelFileType.FILE_CONTENT:
|
||||
with open(self.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.')
|
||||
|
||||
embedder_options = _EmbedderOptions(
|
||||
l2_normalize=l2_normalize, quantize=quantize)
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=base_options, embedder_options=embedder_options)
|
||||
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
# Extracts both embeddings.
|
||||
image_result = embedder.embed(self.test_image)
|
||||
crop_result = embedder.embed(self.test_cropped_image)
|
||||
|
||||
# Checks cosine similarity.
|
||||
self._check_cosine_similarity(image_result, crop_result,
|
||||
expected_similarity)
|
||||
|
||||
def test_missing_result_callback(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM)
|
||||
with self.assertRaisesRegex(ValueError,
|
||||
r'result callback must be provided'):
|
||||
with _ImageEmbedder.create_from_options(options) as unused_embedder:
|
||||
pass
|
||||
|
||||
@parameterized.parameters((_RUNNING_MODE.IMAGE), (_RUNNING_MODE.VIDEO))
|
||||
def test_illegal_result_callback(self, running_mode):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=running_mode,
|
||||
result_callback=mock.MagicMock())
|
||||
with self.assertRaisesRegex(ValueError,
|
||||
r'result callback should not be provided'):
|
||||
with _ImageEmbedder.create_from_options(options) as unused_embedder:
|
||||
pass
|
||||
|
||||
def test_calling_embed_for_video_in_image_mode(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.IMAGE)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
with self.assertRaisesRegex(ValueError,
|
||||
r'not initialized with the video mode'):
|
||||
embedder.embed_for_video(self.test_image, 0)
|
||||
|
||||
def test_calling_embed_async_in_image_mode(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.IMAGE)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
with self.assertRaisesRegex(ValueError,
|
||||
r'not initialized with the live stream mode'):
|
||||
embedder.embed_async(self.test_image, 0)
|
||||
|
||||
def test_calling_embed_in_video_mode(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.VIDEO)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
with self.assertRaisesRegex(ValueError,
|
||||
r'not initialized with the image mode'):
|
||||
embedder.embed(self.test_image)
|
||||
|
||||
def test_calling_embed_async_in_video_mode(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.VIDEO)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
with self.assertRaisesRegex(ValueError,
|
||||
r'not initialized with the live stream mode'):
|
||||
embedder.embed_async(self.test_image, 0)
|
||||
|
||||
def test_embed_for_video_with_out_of_order_timestamp(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.VIDEO)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
unused_result = embedder.embed_for_video(self.test_image, 1)
|
||||
with self.assertRaisesRegex(
|
||||
ValueError, r'Input timestamp must be monotonically increasing'):
|
||||
embedder.embed_for_video(self.test_image, 0)
|
||||
|
||||
def test_embed_for_video(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.VIDEO)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder0, \
|
||||
_ImageEmbedder.create_from_options(options) as embedder1:
|
||||
for timestamp in range(0, 300, 30):
|
||||
# Extracts both embeddings.
|
||||
image_result = embedder0.embed_for_video(self.test_image, timestamp)
|
||||
crop_result = embedder1.embed_for_video(self.test_cropped_image,
|
||||
timestamp)
|
||||
# Checks cosine similarity.
|
||||
self._check_cosine_similarity(
|
||||
image_result, crop_result, expected_similarity=0.925519)
|
||||
|
||||
def test_embed_for_video_succeeds_with_region_of_interest(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.VIDEO)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder0, \
|
||||
_ImageEmbedder.create_from_options(options) as embedder1:
|
||||
# Region-of-interest in "burger.jpg" corresponding to "burger_crop.jpg".
|
||||
roi = _Rect(left=0, top=0, right=0.833333, bottom=1)
|
||||
image_processing_options = _ImageProcessingOptions(roi)
|
||||
|
||||
for timestamp in range(0, 300, 30):
|
||||
# Extracts both embeddings.
|
||||
image_result = embedder0.embed_for_video(self.test_image, timestamp,
|
||||
image_processing_options)
|
||||
crop_result = embedder1.embed_for_video(self.test_cropped_image,
|
||||
timestamp)
|
||||
|
||||
# Checks cosine similarity.
|
||||
self._check_cosine_similarity(
|
||||
image_result, crop_result, expected_similarity=0.999931)
|
||||
|
||||
def test_calling_embed_in_live_stream_mode(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
result_callback=mock.MagicMock())
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
with self.assertRaisesRegex(ValueError,
|
||||
r'not initialized with the image mode'):
|
||||
embedder.embed(self.test_image)
|
||||
|
||||
def test_calling_embed_for_video_in_live_stream_mode(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
result_callback=mock.MagicMock())
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
with self.assertRaisesRegex(ValueError,
|
||||
r'not initialized with the video mode'):
|
||||
embedder.embed_for_video(self.test_image, 0)
|
||||
|
||||
def test_embed_async_calls_with_illegal_timestamp(self):
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
result_callback=mock.MagicMock())
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
embedder.embed_async(self.test_image, 100)
|
||||
with self.assertRaisesRegex(
|
||||
ValueError, r'Input timestamp must be monotonically increasing'):
|
||||
embedder.embed_async(self.test_image, 0)
|
||||
|
||||
def test_embed_async_calls(self):
|
||||
# Get the embedding result for the cropped image.
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.IMAGE)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
crop_result = embedder.embed(self.test_cropped_image)
|
||||
|
||||
observed_timestamp_ms = -1
|
||||
|
||||
def check_result(result: _ImageEmbedderResult, output_image: _Image,
|
||||
timestamp_ms: int):
|
||||
# Checks cosine similarity.
|
||||
self._check_cosine_similarity(
|
||||
result, crop_result, expected_similarity=0.925519)
|
||||
self.assertTrue(
|
||||
np.array_equal(output_image.numpy_view(),
|
||||
self.test_image.numpy_view()))
|
||||
self.assertLess(observed_timestamp_ms, timestamp_ms)
|
||||
self.observed_timestamp_ms = timestamp_ms
|
||||
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
result_callback=check_result)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
for timestamp in range(0, 300, 30):
|
||||
embedder.embed_async(self.test_image, timestamp)
|
||||
|
||||
def test_embed_async_succeeds_with_region_of_interest(self):
|
||||
# Get the embedding result for the cropped image.
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.IMAGE)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
crop_result = embedder.embed(self.test_cropped_image)
|
||||
|
||||
# Region-of-interest in "burger.jpg" corresponding to "burger_crop.jpg".
|
||||
roi = _Rect(left=0, top=0, right=0.833333, bottom=1)
|
||||
image_processing_options = _ImageProcessingOptions(roi)
|
||||
observed_timestamp_ms = -1
|
||||
|
||||
def check_result(result: _ImageEmbedderResult, output_image: _Image,
|
||||
timestamp_ms: int):
|
||||
# Checks cosine similarity.
|
||||
self._check_cosine_similarity(
|
||||
result, crop_result, expected_similarity=0.999931)
|
||||
self.assertTrue(
|
||||
np.array_equal(output_image.numpy_view(),
|
||||
self.test_image.numpy_view()))
|
||||
self.assertLess(observed_timestamp_ms, timestamp_ms)
|
||||
self.observed_timestamp_ms = timestamp_ms
|
||||
|
||||
options = _ImageEmbedderOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
result_callback=check_result)
|
||||
with _ImageEmbedder.create_from_options(options) as embedder:
|
||||
for timestamp in range(0, 300, 30):
|
||||
embedder.embed_async(self.test_image, timestamp,
|
||||
image_processing_options)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
|
Loading…
Reference in New Issue
Block a user