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Skip test_images for uint16 and multi-channel images #11176

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15 changes: 11 additions & 4 deletions tensorflow_datasets/core/features/image_feature_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,11 +67,18 @@ def make_none_fail():


def _unsupported_images_for_pil(
np_dtype: Type[np.generic], failing_lib: Optional[LibWithImportError]
np_dtype: Type[np.generic],
failing_lib: Optional[LibWithImportError],
channels: int,
) -> bool:
# PIL is used when OpenCV is not installed, but PIL doesn't support 16-bit
# images.
return np_dtype == np.uint16 and failing_lib == LibWithImportError.CV2
if np_dtype == np.uint16 and failing_lib == LibWithImportError.CV2:
return True
# PIL also doesn't support multi-channel 16-bit images for thumbnails.
if np_dtype == np.uint16 and channels > 1:
return True
return False


class ImageFeatureTest(
Expand All @@ -91,7 +98,7 @@ class ImageFeatureTest(
def test_images(self, make_lib_fail, dtypes, channels):
dtype, np_dtype = dtypes
with make_lib_fail() as failing_lib:
if _unsupported_images_for_pil(np_dtype, failing_lib):
if _unsupported_images_for_pil(np_dtype, failing_lib, channels):
return
img = randint(256, size=(128, 100, channels), dtype=np_dtype)
img_other_shape = randint(256, size=(64, 200, channels), dtype=np_dtype)
Expand Down Expand Up @@ -198,7 +205,7 @@ def test_images(self, make_lib_fail, dtypes, channels):
def test_images_with_invalid_shape(self, make_lib_fail, dtypes, channels):
dtype, np_dtype = dtypes
with make_lib_fail() as failing_lib:
if _unsupported_images_for_pil(np_dtype, failing_lib):
if _unsupported_images_for_pil(np_dtype, failing_lib, channels):
return
invalid_number_of_dimensions = testing.FeatureExpectationItem(
value=randint(256, size=(128, 128), dtype=np_dtype),
Expand Down
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