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bugfix: reshape array to singular dimension for opencv #18

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Merged
erjel merged 3 commits into from
Mar 21, 2025
Merged

bugfix: reshape array to singular dimension for opencv #18

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e41ea04
bugfix: reshape array to singular dimension for opencv
erjel Mar 21, 2025
ac5e07c
bugfix: Make arithmetic add more robust on windows
erjel Mar 21, 2025
ddb6017
doc: Updated changelog to account for actual fix
erjel Mar 21, 2025
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12 changes: 12 additions & 0 deletions changelogs/master/fixed/20250321_fix_cv_shape_error.md
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Original file line number Diff line number Diff line change
@@ -0,0 +1,12 @@
# Fix error in `arithmetic._add_scalar_to_uint8_` on Windows

On Python 3.8 tests for `_add_scalar_to_uint8_` fail for
windows due to dimension and dtype-specific behavior
in `cv2.add`.

The fix the errors by directly adding scalar values
if the input image is 2D or 3D with a singular channel
dimension.

If channel-dependent is required, broadcast the values
to full image shape and add it via `cv2.add`.
19 changes: 6 additions & 13 deletions imgaug/augmenters/arithmetic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -166,25 +166,18 @@ def _add_scalar_to_uint8_(image, value):
value = round(value)
elif ia.is_np_scalar(value) or ia.is_np_array(value):
is_single_value = (value.size == 1)
value = np.round(value) if value.dtype.kind == "f" else value
value = np.round(value).astype(int) if value.dtype.kind == "f" else value
else:
is_single_value = False
is_channelwise = not is_single_value

if image.ndim == 2 and is_single_value:
return cv2.add(image, value, dst=image, dtype=cv2.CV_8U)

input_shape = image.shape
image = image.reshape(-1, 1)
values = np.array(value)
if not is_channelwise:
values = np.broadcast_to(values, image.shape)
else:
values = np.tile(values, image.size // len(values))

image_add = cv2.add(image, values, dst=image, dtype=cv2.CV_8U)
if is_single_value and (image.ndim == 2 or (image.ndim == 3 and image.shape[-1] == 1)):
values = value
else:
values = np.broadcast_to(value, input_shape)

return image_add.reshape(input_shape)
return cv2.add(image, values, dtype=cv2.CV_8U).reshape(input_shape)


def _add_scalar_to_non_uint8(image, value):
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