code: def _split_generators(self, dl_manager):
      
      # Download images and annotations that come in separate archives.
      # Note, that the extension of archives is .tar.gz even though the actual
      # archives format is uncompressed tar.
      dl_paths = dl_manager.download_and_extract({
          "images": tfds.download.Resource(
              url=os.path.join(_BASE_URL, "images.tar.gz"),
              extract_method=tfds.download.ExtractMethod.TAR),
          "annotations": tfds.download.Resource(
              url=os.path.join(_BASE_URL, "annotations.tar.gz"),
              extract_method=tfds.download.ExtractMethod.TAR)
      })
  
      images_path_dir = os.path.join(dl_paths["images"], "images")
      annotations_path_dir = os.path.join(dl_paths["annotations"], "annotations")
  
      # Setup train and test splits
      train_split = tfds.core.SplitGenerator(
          name="train",
          num_shards=_NUM_SHARDS,
          gen_kwargs={
              "images_dir_path": images_path_dir,
              "images_list_file": os.path.join(annotations_path_dir,
                                               "trainval.txt"),
              },
          )
      test_split = tfds.core.SplitGenerator(
          name="test",
          num_shards=_NUM_SHARDS,
          gen_kwargs={
              "images_dir_path": images_path_dir,
              "images_list_file": os.path.join(annotations_path_dir,
                                               "test.txt")
              },
          )
  
      return [train_split, test_split]
docs: Returns splits.