RandomEqualize

class torchvision.transforms.v2.RandomEqualize(p: float = 0.5)

Equalize the histogram of the given image or video with a given probability.

If the input is a torch.Tensor, it is expected to have […, 1 or 3, H, W] shape, where … means an arbitrary number of leading dimensions. If img is PIL Image, it is expected to be in mode “P”, “L” or “RGB”.

Parameters:

p (float) – probability of the image being equalized. Default value is 0.5

Examples using RandomEqualize:

Illustration of transforms

Illustration of transforms

transform(inpt: Any, params: dict[str, Any]) → Any

Method to override for custom transforms.

See How to write your own v2 transforms