Hi!
I know how to use ImageFolder to get my training batch from folders using this code
transform = transforms.Compose([
    transforms.Resize((224, 224), interpolation=3),
    transforms.RandomHorizontalFlip(),
    transforms.ToTensor()
])

image_dataset = datasets.ImageFolder(os.path.join(data_dir, 'train'), transform)
train_dataset = torch.utils.data.DataLoader(
        image_datasets, batch_size=32,
        shuffle=True, num_workers=16
    )

But I want to apply two transforms for the same image and get something like
for img1, img2, label in train_dataset:

Where img1 and img2 are same image with different size. An example below
im = cv2.imread('img.jpg').reshape((1, 1, 3))
im2 = cv2.resize(im, (448, 448))
im = im.transpose((1, 2, 0)).reshape((1, 3, 224, 224))
im2 = im2.transpose((1, 2, 0)).reshape((1, 3, 448, 448))

How Can I do this?
Thank you