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Allow 2D numpy arrays as inputs for to_image #8256

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merged 3 commits into from
Feb 6, 2024
Merged

Allow 2D numpy arrays as inputs for to_image #8256

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be2bebe
Allow 2D numpy arrays as inputs for to_image
mantasu Feb 5, 2024
b8f5610
Merge branch 'main' into to-image-fix
mantasu Feb 6, 2024
3100374
Add non-regression test
NicolasHug Feb 6, 2024
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5 changes: 5 additions & 0 deletions test/test_transforms_v2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5182,6 +5182,11 @@ def test_functional_and_transform(self, make_input, fn):
if isinstance(input, torch.Tensor):
assert output.data_ptr() == input.data_ptr()

def test_2d_np_array(self):
# Non-regression test for https://github.com/pytorch/vision/issues/8255
input = np.random.rand(10, 10)
assert F.to_image(input).shape == (1, 10, 10)

def test_functional_error(self):
with pytest.raises(TypeError, match="Input can either be a pure Tensor, a numpy array, or a PIL image"):
F.to_image(object())
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2 changes: 1 addition & 1 deletion torchvision/transforms/v2/functional/_type_conversion.py
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Expand Up @@ -11,7 +11,7 @@
def to_image(inpt: Union[torch.Tensor, PIL.Image.Image, np.ndarray]) -> tv_tensors.Image:
"""See :class:`~torchvision.transforms.v2.ToImage` for details."""
if isinstance(inpt, np.ndarray):
output = torch.from_numpy(inpt).permute((2, 0, 1)).contiguous()
output = torch.from_numpy(np.atleast_3d(inpt)).permute((2, 0, 1)).contiguous()
elif isinstance(inpt, PIL.Image.Image):
output = pil_to_tensor(inpt)
elif isinstance(inpt, torch.Tensor):
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