augsegdataset.py

transform = transforms.Compose([
    transforms.RandomHorizontalFlip(),
    transforms.RandomVerticalFlip(),
    transforms.RandomRotation(90),
    transforms.RandomAffine(degrees=15, translate=(0.1, 0.1), scale=(0.8, 0.8))
])

augmented_mri_dataset = Brain_MRI_Segmentation_Dataset(positive_diagnoses, transform=transform)

validation_size = int(0.3 * len(mri_dataset))
atrain_set, aval_set = data.random_split(mri_dataset, [len(mri_dataset)-validation_size, validation_size])

aug_train_loader = data.DataLoader(dataset=atrain_set, batch_size=2, shuffle=True)
aug_val_loader = data.DataLoader(dataset=aval_set, batch_size=2, shuffle=False)