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RandomPerspective

class torchvision.transforms.RandomPerspective(distortion_scale=0.5, p=0.5, interpolation=<InterpolationMode.BILINEAR: 'bilinear'>, fill=0)[source]

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. For backward compatibility integer values (e.g. PIL.Image.NEAREST) are still acceptable.

  • 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.

Examples using RandomPerspective:

forward(img)[source]
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]]][source]

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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