torchvision.datasets.datasetfolder example
def load_data(data_folder, batch_size, train, kwargs): transform = { 'train': transforms.Compose( [transforms.Resize([256, 256]), transforms.RandomCrop(224), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])]), 'test': transforms.Compose( [transforms.Resize([224, 224]), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])]) } data = datasets.ImageFolder(root = data_folder, transform=transform['train' if train else 'test']) data_loader = torch.utils.data.DataLoader(data, batch_size=batch_size, shuffle=True, **kwargs, drop_last = True if train else False) return data_loader
