I’m using the patchify pypi module to first patchify images and save them as a new dataset and then load them back as individual images in a pytorch dataset.
It’s just:
`patches_img = patchify(image, (patch_size, patch_size, 3), step=patch_size)`

for all images and then I’ll load the individual patches in just like any images.
What I’d like to do is something like this
    class Dataset(object):
        #images are the full pre patchified images
        def __init__(self, images: List[str]):
            self.images = images 
            self.transformer = Transform()
            
        
        def __getitem__(self, idx: int):
            image = self.images[idx]
            #IMPORTANT switch to color later
            patches = patchify(image, (patch_size, patch_size, 3), step=patch_size)
    
            image_patches_tensor = self.transformer(patches)
            return image_patches tensor
        
        def __len__(self):
            return len(self.files)

how would I do that?
Thanks in advance!