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Fix donut image processor (#20625)

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* fix donut image processor

* Update test values

* Apply lower bound on resizing size

* Add in missing size param

* Resolve resize channel_dimension bug

* Update src/transformers/image_transforms.py
This commit is contained in:
amyeroberts
2022-12-08 19:10:40 +00:00
committed by GitHub
parent e3cc4487fe
commit cf1b8c34cc
4 changed files with 58 additions and 14 deletions
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19
tests/test_image_transforms.py
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@@ -184,6 +184,25 @@ class ImageTransformsTester(unittest.TestCase):
image = np.random.randint(0, 256, (3, 50, 40))
self.assertEqual(get_resize_output_image_size(image, 20, default_to_square=False, max_size=22), (22, 17))
# Test correct channel dimension is returned if output size if height == 3
# Defaults to input format - channels first
image = np.random.randint(0, 256, (3, 18, 97))
resized_image = resize(image, (3, 20))
self.assertEqual(resized_image.shape, (3, 3, 20))
# Defaults to input format - channels last
image = np.random.randint(0, 256, (18, 97, 3))
resized_image = resize(image, (3, 20))
self.assertEqual(resized_image.shape, (3, 20, 3))
image = np.random.randint(0, 256, (3, 18, 97))
resized_image = resize(image, (3, 20), data_format="channels_last")
self.assertEqual(resized_image.shape, (3, 20, 3))
image = np.random.randint(0, 256, (18, 97, 3))
resized_image = resize(image, (3, 20), data_format="channels_first")
self.assertEqual(resized_image.shape, (3, 3, 20))
def test_resize(self):
image = np.random.randint(0, 256, (3, 224, 224))