data.py

import torchvision.transforms as transforms

# once the images are loaded, how do we pre-process them before being passed into the network
# by default, we resize the images to 64 x 64 in size
# and normalize them to mean = 0 and standard-deviation = 1 based on statistics collected from
# the training set


data_transforms = {
    'train_images': transforms.Compose([
        transforms.Resize(256),
        transforms.CenterCrop(224),
        transforms.ToTensor(),
        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
    ]),
    'val_images': transforms.Compose([
        transforms.Resize(256),
        transforms.CenterCrop(224),
        transforms.ToTensor(),
        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
    ]),
}