What are the image processing modules in Torch?

The image processing module in Torch mainly includes the following components:

1. torchvision.transforms: Common transformations and preprocessing operations for images, such as scaling, cropping, rotating, flipping, and more.
2. torch.nn.functional contains functions related to image processing, such as convolution operations, pooling operations, and activation functions.
3. torchvision.datasets includes commonly used image datasets such as MNIST and CIFAR.
4. torch.utils.data.DataLoader: designed for loading and processing image data, it supports functions such as batch loading and data augmentation.
5. torch.optim: includes various optimization algorithms for training image processing models.
6. torchvision.models: contains some commonly used image processing models, such as ResNet, VGG, and more.
7. torchvision.utils: includes some helper functions for visualizing image data.