- class torchvision.transforms.v2.GaussianBlur(kernel_size: Union[int, Sequence[int]], sigma: Union[int, float, Sequence[float]] = (0.1, 2.0))¶
[BETA] Blurs image with randomly chosen Gaussian blur.
The GausssianBlur 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 Tensor, it is expected to have […, C, H, W] shape, where … means an arbitrary number of leading dimensions.
kernel_size (int or sequence) – Size of the Gaussian kernel.
sigma (float or tuple of python:float (min, max)) – Standard deviation to be used for creating kernel to perform blurring. If float, sigma is fixed. If it is tuple of float (min, max), sigma is chosen uniformly at random to lie in the given range.
GaussianBlur:Illustration of transforms
- static get_params(sigma_min: float, sigma_max: float) float ¶
Choose sigma for random gaussian blurring.