def __getitem__(self, idx: int) -> Dict[str, Any]:
        """
        Gets selected images from the list

        Args:
            idx (int): video index in the video list file
        Returns:
            A dictionary containing two keys:
                images (torch.Tensor): tensor of size [N, 3, H, W] (N = 1, or 0 for _EMPTY_IMAGE)
                categories (List[str]): categories of the frames
        """
        categories = [self.category_list[idx]]
        fpath = self.image_list[idx]
        transform = self.transform

        try:
            image = torch.from_numpy(np.ascontiguousarray(read_image(fpath, format="BGR")))
            image = image.permute(2, 0, 1).unsqueeze(0).float()  # HWC -> NCHW
            if transform is not None:
                image = transform(image)
            return {"images": image, "categories": categories}
        except (OSError, RuntimeError) as e:
            logger = logging.getLogger(__name__)
            logger.warning(f"Error opening image file container {fpath}: {e}")

        return {"images": self._EMPTY_IMAGE, "categories": []}

        Gets selected images from the list

        Args:
            idx (int): video index in the video list file
        Returns:
            A dictionary containing two keys:
                images (torch.Tensor): tensor of size [N, 3, H, W] (N = 1, or 0 for _EMPTY_IMAGE)
                categories (List[str]): categories of the frames
        
EVA-02/det/projects/DensePose/densepose/data/image_list_dataset.py