proData.py 文件源码

def CreateDataLoader(opt):
    random.seed(opt.manualSeed)

    # folder dataset
    CTrans = transforms.Compose([
        transforms.Scale(opt.imageSize, Image.BICUBIC),
        transforms.ToTensor(),
        transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
    ])

    VTrans = transforms.Compose([
        RandomSizedCrop(opt.imageSize // 4, Image.BICUBIC),
        transforms.ToTensor(),
        transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
    ])

    def jitter(x):
        ran = random.uniform(0.7, 1)
        return x * ran + 1 - ran

    STrans = transforms.Compose([
        transforms.Scale(opt.imageSize, Image.BICUBIC),
        transforms.ToTensor(),
        transforms.Lambda(jitter),
        transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
    ])

    dataset = ImageFolder(rootC=opt.datarootC,
                          rootS=opt.datarootS,
                          transform=CTrans,
                          vtransform=VTrans,
                          stransform=STrans
                          )

    assert dataset

    return data.DataLoader(dataset, batch_size=opt.batchSize,
                           shuffle=True, num_workers=int(opt.workers), drop_last=True)