Resize

class torchvision.transforms.Resize(size, interpolation=<InterpolationMode.BILINEAR: 'bilinear'>, max_size=None, antialias=None)

Resize the input image to the given size. 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. See also below the antialias parameter, which can help making the output of PIL images and tensors closer.

Parameters

• 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, smaller edge of the image will be matched to this number. i.e, if height > width, then image will be rescaled to (size * height / width, size).

  Note

  In torchscript mode size as single int is not supported, use a sequence of length 1: [size, ].

• interpolation (InterpolationMode) – Desired interpolation enum defined by torchvision.transforms.InterpolationMode. Default is InterpolationMode.BILINEAR. If input is Tensor, only InterpolationMode.NEAREST, InterpolationMode.BILINEAR and InterpolationMode.BICUBIC are supported. For backward compatibility integer values (e.g. PIL.Image.NEAREST) are still acceptable.

• max_size (int, optional) – The maximum allowed for the longer edge of the resized image: if the longer edge of the image is greater than max_size after being resized according to size, then the image is resized again so that the longer edge is equal to max_size. As a result, size might be overruled, i.e the smaller edge may be shorter than size. This is only supported if size is an int (or a sequence of length 1 in torchscript mode).

• antialias (bool, optional) –

  antialias flag. If img is PIL Image, the flag is ignored and anti-alias is always used. If img is Tensor, the flag is False by default and can be set to True for InterpolationMode.BILINEAR only mode. This can help making the output for PIL images and tensors closer.

  Warning

  There is no autodiff support for antialias=True option with input img as Tensor.

Examples using Resize:

Tensor transforms and JIT

Optical Flow: Predicting movement with the RAFT model

Illustration of transforms

Video API

forward(img)

Parameters

img (PIL Image or Tensor) – Image to be scaled.

Returns

Rescaled image.

Return type

PIL Image or Tensor