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Add fix for albu channel order #9981

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Add fix for albu channel order #9981

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6 changes: 6 additions & 0 deletions mmdet/datasets/pipelines/transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1484,8 +1484,14 @@ def __call__(self, results):
else:
results['masks'] = [mask for mask in results['masks'].masks]

# Convert to RGB since Albumentations works with RGB images
results['image'] = cv2.cvtColor(results['image'], cv2.COLOR_BGR2RGB)
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@BIGWangYuDong BIGWangYuDong Mar 18, 2023 •
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This fixing may have some potential errors.

As show in Loading Image:

mmdetection/mmdet/datasets/pipelines/loading.py

Line 40 in e9cae2d

channel_order='bgr',

The image may be rgb, and this option may convert the image to BGR?

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@mmeendez8 mmeendez8 Mar 18, 2023

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Should I add a channel_order parameter as in the loading init?

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@mmeendez8 mmeendez8 Mar 27, 2023

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@BIGWangYuDong ?

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@BIGWangYuDong BIGWangYuDong Mar 29, 2023

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sorry for the late reply, we need to discuss it. Kindly ping @RangiLyu and @hhaAndroid have a look

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@mmeendez8 mmeendez8 Apr 12, 2023

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@RangiLyu @hhaAndroid @BIGWangYuDong any new?


results = self.aug(**results)

# Convert back to BGR
results['image'] = cv2.cvtColor(results['image'], cv2.COLOR_RGB2BGR)

if 'bboxes' in results:
if isinstance(results['bboxes'], list):
results['bboxes'] = np.array(
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36 changes: 36 additions & 0 deletions tests/test_data/test_pipelines/test_transform/test_transform.py
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Expand Up @@ -496,6 +496,42 @@ def test_albu_transform():
assert results['img'].dtype == np.float32


def test_albu_channel_order():
results = dict(
img_prefix=osp.join(osp.dirname(__file__), '../../../data'),
img_info=dict(filename='color.jpg'))

# Define simple pipeline
load = dict(type='LoadImageFromFile')
load = build_from_cfg(load, PIPELINES)

# Transform is modifying B channel
albu_transform = dict(
type='Albu',
transforms=[
dict(
type='RGBShift',
r_shift_limit=0,
g_shift_limit=0,
b_shift_limit=200,
p=1)
])
albu_transform = build_from_cfg(albu_transform, PIPELINES)

# Execute transforms
results_load = load(results)
results_albu = albu_transform(results_load)

# assert only Green and Red channel are not modified
np.testing.assert_array_equal(results_albu['img'][..., 1:],
results_load['img'][..., 1:])

# assert Blue channel is modified
with pytest.raises(AssertionError):
np.testing.assert_array_equal(results_albu['img'][..., 0],
results_load['img'][..., 0])


def test_random_center_crop_pad():
# test assertion for invalid crop_size while test_mode=False
with pytest.raises(AssertionError):
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