” (x2), and “tench”.  Real images. Now that the images are loaded, let’s apply some lightweight pre-processing on them to use them for FID calculation.   Copied from torchvision.transforms import functional as F


def preprocess_image(image):
    image = torch.tensor(image).unsqueeze(0)
    image = image.permute(0, 3, 1, 2) / 255.0
    return F.center_crop(image, (256, 256))

real_images = torch.cat([preprocess_image(image) for image in real_im