def METHOD_NAME(
    image: str,
    ds: Dataset,
    tensors: Dict[str, Tensor],
):
    images_tensor_name = self._images_tensor_name
    full_sample: Dict[str, List] = {key: [] for key in self._structure.all_keys}
    full_sample[images_tensor_name] = self.images.get_image(
        image,
        tensors[images_tensor_name].is_link,
        creds_key=self._image_creds_key,
    )
    for coco_file in self.annotation_files:
        file_name = coco_file.file_name
        id_to_label = coco_file.id_to_label_mapping
        matching_annotations = coco_file.get_annotations_for_image(image)
        group_prefix = self.file_to_group.get(file_name, file_name)
        for annotation in matching_annotations:
            for tensor_name in self.tensor_to_key:
                full_name = self._get_full_tensor_name(
                    group_prefix, tensor_name
                )
                coco_key = self.tensor_to_key.get(tensor_name, tensor_name)
                value = coco_to_deeplake(
                    coco_key,
                    annotation[coco_key],
                    tensors[full_name],
                    category_lookup=id_to_label,
                )
                full_sample[full_name].append(value)
    ds.append(full_sample)