def __init__(self, dataset_name):
        """
        Args:
            dataset_name (str): name of the dataset, e.g., "voc_2007_test"
        """
        self._dataset_name = dataset_name
        meta = MetadataCatalog.get(dataset_name)

        # Too many tiny files, download all to local for speed.
        annotation_dir_local = PathManager.get_local_path(
            os.path.join(meta.dirname, "Annotations/")
        )
        self._anno_file_template = os.path.join(annotation_dir_local, "{}.xml")
        self._image_set_path = os.path.join(meta.dirname, "ImageSets", "Main", meta.split + ".txt")
        self._class_names = meta.thing_classes
        assert meta.year in [2007, 2012], meta.year
        self._is_2007 = meta.year == 2007
        self._cpu_device = torch.device("cpu")
        self._logger = logging.getLogger(__name__)

        Args:
            dataset_name (str): name of the dataset, e.g., "voc_2007_test"
        
iGPT/models/grit_src/third_party/CenterNet2/detectron2/evaluation/pascal_voc_evaluation.py