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# resized_crop

torchvision.transforms.functional.resized_crop(img: Tensor, top: int, left: int, height: int, width: int, size: List[int], interpolation: InterpolationMode = InterpolationMode.BILINEAR, antialias: Optional[Union[str, bool]] = 'warn') → Tensor

  Crop the given image and resize it to desired size. If the image is torch Tensor, it is expected to have […, H, W] shape, where … means an arbitrary number of leading dimensions

  Notably used in `RandomResizedCrop`.

  Parameters:

    - img (PIL Image or Tensor) – Image to be cropped. (0,0) denotes the top left corner of the image.

    - top (int) – Vertical component of the top left corner of the crop box.

    - left (int) – Horizontal component of the top left corner of the crop box.

    - height (int) – Height of the crop box.

    - width (int) – Width of the crop box.

    - size (sequence or int) – Desired output size. Same semantics as `resize`.

    - interpolation (InterpolationMode) – Desired interpolation enum defined by `torchvision.transforms.InterpolationMode`. Default is `InterpolationMode.BILINEAR`. If input is Tensor, only `InterpolationMode.NEAREST`, `InterpolationMode.NEAREST_EXACT`, `InterpolationMode.BILINEAR` and `InterpolationMode.BICUBIC` are supported. The corresponding Pillow integer constants, e.g. `PIL.Image.BILINEAR` are accepted as well.

    - antialias (bool, optional) –

      Whether to apply antialiasing. It only affects tensors with bilinear or bicubic modes and it is ignored otherwise: on PIL images, antialiasing is always applied on bilinear or bicubic modes; on other modes (for PIL images and tensors), antialiasing makes no sense and this parameter is ignored. Possible values are:

      - `True`: will apply antialiasing for bilinear or bicubic modes. Other mode aren’t affected. This is probably what you want to use.

      - `False`: will not apply antialiasing for tensors on any mode. PIL images are still antialiased on bilinear or bicubic modes, because PIL doesn’t support no antialias.

      - `None`: equivalent to `False` for tensors and `True` for PIL images. This value exists for legacy reasons and you probably don’t want to use it unless you really know what you are doing.

      The current default is `None` but will change to `True` in v0.17 for the PIL and Tensor backends to be consistent.

  Returns:

    Cropped image.

  Return type:

    PIL Image or Tensor

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