GaussianBlur

class torchvision.transforms.GaussianBlur(kernel_size, sigma=(0.1, 2.0))

Blurs image with randomly chosen Gaussian blur. If the image is torch Tensor, it is expected to have […, C, H, W] shape, where … means an arbitrary number of leading dimensions.

Parameters

• 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.

Returns

Gaussian blurred version of the input image.

Return type

PIL Image or Tensor

Examples using GaussianBlur:

Illustration of transforms

forward(img: torch.Tensor) → torch.Tensor

Parameters

img (PIL Image or Tensor) – image to be blurred.

Returns

Gaussian blurred image

Return type

PIL Image or Tensor

static get_params(sigma_min: float, sigma_max: float) → float

Choose sigma for random gaussian blurring.

Parameters

• sigma_min (float) – Minimum standard deviation that can be chosen for blurring kernel.

• sigma_max (float) – Maximum standard deviation that can be chosen for blurring kernel.

Returns

Standard deviation to be passed to calculate kernel for gaussian blurring.

Return type

float