RandomPosterize

class torchvision.transforms.v2.RandomPosterize(bits: int, p: float = 0.5)

[BETA] Posterize the image or video with a given probability by reducing the number of bits for each color channel.

Note

The RandomPosterize transform is in Beta stage, and while we do not expect disruptive breaking changes, some APIs may slightly change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753.

If the input is a torch.Tensor, it should be of type torch.uint8, and 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 “L” or “RGB”.

Parameters:

• bits (int) – number of bits to keep for each channel (0-8)

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

Examples using RandomPosterize:

Illustration of transforms

Illustration of transforms