Explicitly state the modes in the tests for ImageSegmenterOptions and InteractiveSegmenterOptions
This commit is contained in:
parent
3f68f90238
commit
a03fa448dc
|
@ -157,7 +157,9 @@ class ImageSegmenterTest(parameterized.TestCase):
|
|||
raise ValueError('model_file_type is invalid.')
|
||||
|
||||
options = _ImageSegmenterOptions(
|
||||
base_options=base_options, output_category_mask=True)
|
||||
base_options=base_options, output_category_mask=True,
|
||||
output_confidence_masks=False
|
||||
)
|
||||
segmenter = _ImageSegmenter.create_from_options(options)
|
||||
|
||||
# Performs image segmentation on the input.
|
||||
|
@ -188,8 +190,9 @@ class ImageSegmenterTest(parameterized.TestCase):
|
|||
|
||||
# Run segmentation on the model in CONFIDENCE_MASK mode.
|
||||
options = _ImageSegmenterOptions(
|
||||
base_options=base_options,
|
||||
activation=_Activation.SOFTMAX)
|
||||
base_options=base_options, output_category_mask=False,
|
||||
output_confidence_masks=True, activation=_Activation.SOFTMAX
|
||||
)
|
||||
|
||||
with _ImageSegmenter.create_from_options(options) as segmenter:
|
||||
segmentation_result = segmenter.segment(test_image)
|
||||
|
@ -279,7 +282,9 @@ class ImageSegmenterTest(parameterized.TestCase):
|
|||
options = _ImageSegmenterOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
output_category_mask=True,
|
||||
running_mode=_RUNNING_MODE.VIDEO)
|
||||
output_confidence_masks=False,
|
||||
running_mode=_RUNNING_MODE.VIDEO
|
||||
)
|
||||
with _ImageSegmenter.create_from_options(options) as segmenter:
|
||||
for timestamp in range(0, 300, 30):
|
||||
segmentation_result = segmenter.segment_for_video(
|
||||
|
@ -297,8 +302,10 @@ class ImageSegmenterTest(parameterized.TestCase):
|
|||
os.path.join(_TEST_DATA_DIR, _CAT_IMAGE)))
|
||||
|
||||
options = _ImageSegmenterOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.VIDEO)
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.VIDEO, output_category_mask=False,
|
||||
output_confidence_masks=True
|
||||
)
|
||||
with _ImageSegmenter.create_from_options(options) as segmenter:
|
||||
for timestamp in range(0, 300, 30):
|
||||
segmentation_result = segmenter.segment_for_video(
|
||||
|
@ -370,8 +377,10 @@ class ImageSegmenterTest(parameterized.TestCase):
|
|||
options = _ImageSegmenterOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
output_category_mask=True,
|
||||
output_confidence_masks=False,
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
result_callback=check_result)
|
||||
result_callback=check_result
|
||||
)
|
||||
with _ImageSegmenter.create_from_options(options) as segmenter:
|
||||
for timestamp in range(0, 300, 30):
|
||||
segmenter.segment_async(self.test_image, timestamp)
|
||||
|
@ -405,9 +414,12 @@ class ImageSegmenterTest(parameterized.TestCase):
|
|||
self.observed_timestamp_ms = timestamp_ms
|
||||
|
||||
options = _ImageSegmenterOptions(
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
result_callback=check_result)
|
||||
base_options=_BaseOptions(model_asset_path=self.model_path),
|
||||
running_mode=_RUNNING_MODE.LIVE_STREAM,
|
||||
output_category_mask=False,
|
||||
output_confidence_masks=True,
|
||||
result_callback=check_result
|
||||
)
|
||||
with _ImageSegmenter.create_from_options(options) as segmenter:
|
||||
for timestamp in range(0, 300, 30):
|
||||
segmenter.segment_async(test_image, timestamp)
|
||||
|
|
|
@ -200,7 +200,8 @@ class InteractiveSegmenterTest(parameterized.TestCase):
|
|||
raise ValueError('model_file_type is invalid.')
|
||||
|
||||
options = _InteractiveSegmenterOptions(
|
||||
base_options=base_options, output_category_mask=True
|
||||
base_options=base_options, output_category_mask=True,
|
||||
output_confidence_masks=False
|
||||
)
|
||||
segmenter = _InteractiveSegmenter.create_from_options(options)
|
||||
|
||||
|
@ -252,7 +253,10 @@ class InteractiveSegmenterTest(parameterized.TestCase):
|
|||
roi = _RegionOfInterest(format=roi_format, keypoint=keypoint)
|
||||
|
||||
# Run segmentation on the model in CONFIDENCE_MASK mode.
|
||||
options = _InteractiveSegmenterOptions(base_options=base_options)
|
||||
options = _InteractiveSegmenterOptions(
|
||||
base_options=base_options, output_category_mask=False,
|
||||
output_confidence_masks=True
|
||||
)
|
||||
|
||||
with _InteractiveSegmenter.create_from_options(options) as segmenter:
|
||||
# Perform segmentation
|
||||
|
@ -284,7 +288,10 @@ class InteractiveSegmenterTest(parameterized.TestCase):
|
|||
)
|
||||
|
||||
# Run segmentation on the model in CONFIDENCE_MASK mode.
|
||||
options = _InteractiveSegmenterOptions(base_options=base_options)
|
||||
options = _InteractiveSegmenterOptions(
|
||||
base_options=base_options, output_category_mask=False,
|
||||
output_confidence_masks=True
|
||||
)
|
||||
|
||||
with _InteractiveSegmenter.create_from_options(options) as segmenter:
|
||||
# Perform segmentation
|
||||
|
@ -310,7 +317,10 @@ class InteractiveSegmenterTest(parameterized.TestCase):
|
|||
)
|
||||
|
||||
# Run segmentation on the model in CONFIDENCE_MASK mode.
|
||||
options = _InteractiveSegmenterOptions(base_options=base_options)
|
||||
options = _InteractiveSegmenterOptions(
|
||||
base_options=base_options, output_category_mask=False,
|
||||
output_confidence_masks=True
|
||||
)
|
||||
|
||||
with self.assertRaisesRegex(
|
||||
ValueError, "This task doesn't support region-of-interest."
|
||||
|
|
Loading…
Reference in New Issue
Block a user