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Add warning in docs of Resize about different results for PIL and tensors #3615

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Merged
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Mar 31, 2021
Merged

Add warning in docs of Resize about different results for PIL and tensors #3615

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a56db8f
docs for resize
NicolasHug Mar 30, 2021
6928b0d
address comment: describe antialiasing
NicolasHug Mar 30, 2021
45b7b12
Merge branch 'master' into resize_doc
NicolasHug Mar 31, 2021
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6 changes: 6 additions & 0 deletions torchvision/transforms/functional.py
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Expand Up @@ -346,6 +346,12 @@ def resize(img: Tensor, size: List[int], interpolation: InterpolationMode = Inte
If the image is torch Tensor, it is expected
to have [..., H, W] shape, where ... means an arbitrary number of leading dimensions

.. warning::
The output image might be different depending on its type: when downsampling, the interpolation of PIL images
and tensors is slightly different, because PIL applies antialiasing. This may lead to significant differences
in the performance of a network. Therefore, it is preferable to train and serve a model with the same input
types.

Args:
img (PIL Image or Tensor): Image to be resized.
size (sequence or int): Desired output size. If size is a sequence like
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6 changes: 6 additions & 0 deletions torchvision/transforms/transforms.py
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Expand Up @@ -229,6 +229,12 @@ class Resize(torch.nn.Module):
If the image is torch Tensor, it is expected
to have [..., H, W] shape, where ... means an arbitrary number of leading dimensions

.. warning::
The output image might be different depending on its type: when downsampling, the interpolation of PIL images
and tensors is slightly different, because PIL applies antialiasing. This may lead to significant differences
in the performance of a network. Therefore, it is preferable to train and serve a model with the same input
types.

Args:
size (sequence or int): Desired output size. If size is a sequence like
(h, w), output size will be matched to this. If size is an int,
Expand Down