Returns splits.

def _split_generators(self, dl_manager):
    """Returns splits."""
    # 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]