class_docstr: DatasetBuilder for tao dataset.
class_docstr_tok: ["DatasetBuilder","for","tao","dataset","."]
docstr: Returns the dataset metadata.
docstr_tok: ["Returns","the","dataset","metadata","."]
code: def _info(self) -> tfds.core.DatasetInfo:
      """Returns the dataset metadata."""
      names_file = tfds.core.tfds_path("video/tao/labels.txt")
      video_shape = (
          None,
          self.builder_config.height,
          self.builder_config.width,
          3,
      )
      all_features = {
          "video": tfds.features.Video(
              video_shape
          ),  # pytype: disable=wrong-arg-types  # gen-stub-imports
          "metadata": {
              "height": np.int32,
              "width": np.int32,
              "num_frames": np.int32,
              "video_name": np.str_,
              "neg_category_ids": tfds.features.Tensor(
                  shape=(None,), dtype=np.int32
              ),
              "not_exhaustive_category_ids": tfds.features.Tensor(
                  shape=(None,), dtype=np.int32
              ),
              "dataset": np.str_,
          },
          "tracks": tfds.features.Sequence(
              {
                  "bboxes": tfds.features.Sequence(
                      tfds.features.BBoxFeature()
                  ),
                  "category": tfds.features.ClassLabel(
                      names_file=names_file
                  ),
                  "is_crowd": np.bool_,
                  "track_id": np.int32,
                  "scale_category": np.str_,
                  # Labels do not occur for all frames. This indicates the
                  # indices of the frames that have labels.
                  "frames": tfds.features.Sequence(np.int32),
              }
          ),
      }
  
      return tfds.core.DatasetInfo(
          builder=self,
          description=_DESCRIPTION,
          features=tfds.features.FeaturesDict(all_features),
          supervised_keys=None,
          homepage="https://taodataset.org/",
          citation=_CITATION,
      )
  
imports: from __future__ import annotations
  import collections
  import json
  import os
  from typing import Any, Dict, Optional, Tuple
  from etils import epath
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the Tao obj's underlying member method code with example usage: obj._info() and returns: tfds