minc.py 文件源码

def __init__(self, args):
        normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                         std=[0.229, 0.224, 0.225])
        transform_train = transforms.Compose([
            transforms.Resize(256),
            transforms.RandomResizedCrop(224),
            transforms.RandomHorizontalFlip(),
            transforms.ColorJitter(0.4,0.4,0.4),
            transforms.ToTensor(),
            Lighting(0.1, _imagenet_pca['eigval'], _imagenet_pca['eigvec']),
            normalize,
        ])
        transform_test = transforms.Compose([
            transforms.Resize(256),
            transforms.CenterCrop(224),
            transforms.ToTensor(),
            normalize,
        ])

        trainset = MINCDataloder(root=os.path.expanduser('~/data/minc-2500/'), 
            train=True, transform=transform_train)
        testset = MINCDataloder(root=os.path.expanduser('~/data/minc-2500/'), 
            train=False, transform=transform_test)

        kwargs = {'num_workers': 8, 'pin_memory': True} if args.cuda else {}
        trainloader = torch.utils.data.DataLoader(trainset, batch_size=
            args.batch_size, shuffle=True, **kwargs)
        testloader = torch.utils.data.DataLoader(testset, batch_size=
            args.test_batch_size, shuffle=False, **kwargs)
        self.trainloader = trainloader 
        self.testloader = testloader