自定义数据加载程序正在pytorch中返回列表

Question

我想从3个不同的文件夹中获得3批图像。我已经用pytorch编写了自定义数据加载器。但它返回的列表包含所有批次，而不是一次包含一个批次

#custom data loader
class set(Dataset):
    def __init__(self, dataset_input, dataset_expertA, dataset_expertB):
        self.dataset1 = dataset_input
        self.dataset2 = dataset_expertA
        self.dataset3 = dataset_expertB

    def __getitem__(self, index):
        x1 = self.dataset1[index]
        x2 = self.dataset2[index]
        x3 = self.dataset3[index]

        return x1, x2, x3

    def __len__(self):
        return len(self.dataset1)

input_path = "/content/gdrive/My Drive/project/input/"

dataset = datasets.ImageFolder(root= input_path, transform=transforms.Compose([
                               transforms.Resize([64,64]),
                               transforms.ToTensor(),
                               transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
                               ]))

expertA_path = "/content/gdrive/My Drive/project/expertA/"

datasetA = datasets.ImageFolder(root= expertA_path, transform=transforms.Compose([
                               transforms.Resize([64,64]),
                               transforms.ToTensor(),
                               transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
                               ]))


expertB_path = "/content/gdrive/My Drive/project/expertB/"

datasetB = datasets.ImageFolder(root= expertB_path, transform=transforms.Compose([
                               transforms.Resize([64,64]),
                               transforms.ToTensor(),
                               transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
                               ]))


data = set(dataset, datasetA, datasetB)
dataloader = torch.utils.data.DataLoader(data, batch_size=64,
                                         shuffle=True, num_workers=2)


for i, (inp, expA, expB) in enumerate(dataloader):

  print(inp.shape)
  break

这会打印错误，即inp是列表，当我打印（inp[0].shape）时，我得到了正确的形状，我认为inp包含所有批次，即inp[0]，inp[1]

我在数据加载程序代码中犯了什么错误

Answer 1

^{}返回（图像，标签）的元组，因此inp也是元组，其中inp[0]是图像，而inp[1]是它们对应的标签。这同样适用于expA和expB

如果您只想要没有标签的图像，可以忽略标签，在访问自定义数据集中的数据时只返回图像：

def __getitem__(self, index):
    image1, label1 = self.dataset1[index]
    image2, label2 = self.dataset2[index]
    image3, label3 = self.dataset3[index]

    return image1, image2, image3