Deep Learning with PyTorch

Loading data into PyTorch tensors

The PyTorch torchvision.datasets package provides a utility class called ImageFolder that can be used to load images along with their associated labels when data is presented in the aforementioned format. It is a common practice to perform the following preprocessing steps:

1. Resize all the images to the same size. Most of the deep learning architectures expect the images to be of the same size.
2. Normalize the dataset with the mean and standard deviation of the dataset.
3. Convert the image dataset to a PyTorch tensor.

PyTorch makes a lot of these preprocessing steps easier by providing a lot of utility functions in the transforms module. For our example, let's apply three transformations:

• Scale to a 256 x 256 ...