Torchvision Transforms Noise. gaussian_blur(img: Tensor, kernel_size: list[int], sigma: Optio

gaussian_blur(img: Tensor, kernel_size: list[int], sigma: Optional[list[float]] = None) → Tensor [source] Performs Gaussian blurring on the image by given kernel The convolution will be using reflection padding corresponding to the kernel size, to maintain the input shape. Compose transforms # Now, we apply the transforms on a sample. There are several options for resizing your images so all of them have the same size, check documentation. e, we want to compose Rescale and RandomCrop transforms. Returns: The parameters used to apply the randomized transform along with their random order. nn as nn from torch. This layer implements optimized operations for co Augmentations for Neural Networks. PyTorch provides the torchvision library to perform different types of computer vision-related tasks. transforms as transforms from torchvision. v2 as T import torchvision.

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