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# RandomPerspective

class torchvision.transforms.RandomPerspective(distortion_scale=0.5, p=0.5, interpolation=InterpolationMode.BILINEAR, fill=0)

  Performs a random perspective transformation of the given image with a given probability. If the image is torch Tensor, it is expected to have […, H, W] shape, where … means an arbitrary number of leading dimensions.

  Parameters:

    - distortion_scale (float) – argument to control the degree of distortion and ranges from 0 to 1. Default is 0.5.

    - p (float) – probability of the image being transformed. Default is 0.5.

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

    - fill (sequence or number) – Pixel fill value for the area outside the transformed image. Default is `0`. If given a number, the value is used for all bands respectively.

  forward(img)
    Parameters:

      img (PIL Image or Tensor) – Image to be Perspectively transformed.

    Returns:

      Randomly transformed image.

    Return type:

      PIL Image or Tensor

  static get_params(width: int, height: int, distortion_scale: float) → Tuple[List[List[int]], List[List[int]]]

    Get parameters for `perspective` for a random perspective transform.

    Parameters:

      - width (int) – width of the image.

      - height (int) – height of the image.

      - distortion_scale (float) – argument to control the degree of distortion and ranges from 0 to 1.

    Returns:

      List containing [top-left, top-right, bottom-right, bottom-left] of the original image, List containing [top-left, top-right, bottom-right, bottom-left] of the transformed image.

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