torchvision.datasets.ImageFolder

torchvision.datasets.ImageFolder is a PyTorch dataset class that represents a generic image folder dataset. It assumes that the images are organized in subfolders under a root folder, where each subfolder represents a label/class. For example, the root folder may contain subfolders "cat", "dog", "bird", etc., where each subfolder contains images of the corresponding label/class.

The ImageFolder class takes two arguments: the path to the root folder and an optional transform function. The transform function is applied to each image before it is returned. The class also provides a default transformation that resizes the image to 256x256 and applies a center crop to obtain a 224x224 image.

The ImageFolder dataset can be used as input to a DataLoader to create a batched data loader for training or testing a neural network.