class_docstr: Open Images v4.
class_docstr_tok: ["Open","Images","v4","."]
code: def _info(self):
      source_class_label = tfds.features.ClassLabel(
          names=IMAGE_LEVEL_SOURCES + BBOX_SOURCES
      )
      all_class_label = tfds.features.ClassLabel(
          names_file=tfds.core.tfds_path(
              os.path.join(
                  "object_detection", "open_images_classes_all.txt"
              )
          )
      )
      trainable_class_label = tfds.features.ClassLabel(
          names_file=tfds.core.tfds_path(
              os.path.join(
                  "object_detection",
                  "open_images_classes_trainable.txt",
              )
          )
      )
      boxable_class_label = tfds.features.ClassLabel(
          names_file=tfds.core.tfds_path(
              os.path.join(
                  "object_detection", "open_images_classes_boxable.txt"
              )
          )
      )
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "image": tfds.features.Image(),
                  "image/filename": tfds.features.Text(),  # eg '226f0a1873b9bf8e.jpg'
                  "objects": tfds.features.Sequence(
                      {
                          "label": all_class_label,
                          # Original data is 0, .1, ..., 1. We use 0, 1, 2, ..., 10.
                          "confidence": np.int32,
                          "source": source_class_label,
                      }
                  ),
                  "objects_trainable": tfds.features.Sequence(
                      {
                          "label": trainable_class_label,
                          # Original data is 0, .1, ..., 1. We use 0, 1, 2, ..., 10.
                          "confidence": np.int32,
                          "source": source_class_label,
                      }
                  ),
                  "bobjects": tfds.features.Sequence(
                      {
                          "label": boxable_class_label,
                          "source": source_class_label,
                          "bbox": tfds.features.BBoxFeature(),
                          # Following values can be:
                          # 1 (true), 0 (false) and -1 (unknown).
                          "is_occluded": np.int8,
                          "is_truncated": np.int8,
                          "is_group_of": np.int8,
                          "is_depiction": np.int8,
                          "is_inside": np.int8,
                      }
                  ),
              }
          ),
          homepage="https://storage.googleapis.com/openimages/web/index.html",
      )
  
imports: from __future__ import annotations
  import collections
  import csv
  import functools
  import io
  import os
  from typing import List
  from absl import logging
  from etils import epath
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the Builder obj's underlying member method code with example usage: obj._info() and returns: self