[torch, dataset] Image dataloader with path

class RawDataset(Dataset):
    def __init__(self, root):
        self.rgb = True
        self.image_path_list = []
        for dirpath, dirnames, filenames in os.walk(root, followlinks=True):
            for name in filenames:
                _, ext = os.path.splitext(name)
                ext = ext.lower()
                if ext == ".jpg" or ext == ".jpeg" or ext == ".png":
                    self.image_path_list.append(os.path.join(dirpath, name))

        self.image_path_list = natsorted(self.image_path_list)
        self.nSamples = len(self.image_path_list)

    def __len__(self):
        return self.nSamples

    def __getitem__(self, index):
        img = np.array(Image.open(self.image_path_list[index]).convert("RGB"))  # for color image
        img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        img_gray = np.dstack([img_gray,img_gray,img_gray])
        pil_image = Image.fromarray(img_gray)

        return (pil_image, self.image_path_list[index])