from PIL import Image

from torch.utils.data import Dataset,DataLoader
from torchvision.datasets import MNIST
from torchvision import transforms

class MNISTImageDataset_train(Dataset):
    def __init__(self) -> None:
        super().__init__()
        self.trainData = MNIST('./Data/ImageData', train=True, download=True,transform=transforms.ToTensor())
        
    def __len__(self) -> int:
        return len(self.trainData)

    def __getitem__(self, index):
        return self.trainData[index][0],self.trainData[index][1]


class MNISTImageDataset_test(Dataset):
    def __init__(self) -> None:
        super().__init__()
        self.testData = MNIST('./Data/ImageData', train=False, download=True,transform=transforms.ToTensor())
        
    def __len__(self) -> int:
        return len(self.testData)

    def __getitem__(self, index):
        return self.testData[index][0],self.testData[index][1]

if __name__ == "__main__":
    print(len(MNISTImageDataset_train()))
    print(len(MNISTImageDataset_test()))