class_docstr: Kitti dataset.
class_docstr_tok: ["Kitti","dataset","."]
code: def _info(self):
      # Annotation descriptions are in the object development kit.
      annotations = {
          "type": tfds.features.ClassLabel(
              names=_OBJECT_LABELS,
              doc="The type of object, e.g. 'Car' or 'Van'",
          ),
          "truncated": tfds.features.Tensor(
              shape=(),
              dtype=np.float32,
              doc=(
                  "Float from 0 (non-truncated) to 1 (truncated), where"
                  "truncated refers to the object leaving image boundaries"
              ),
          ),
          "occluded": tfds.features.ClassLabel(
              names=_OCCLUDED_LABELS,
              doc=(
                  "Integer (0,1,2,3) indicating occlusion state: "
                  "0 = fully visible, 1 = partly occluded"
                  "2 = largely occluded, 3 = unknown"
              ),
          ),
          "alpha": tfds.features.Tensor(
              shape=(),
              dtype=np.float32,
              doc="Observation angle of object, ranging [-pi..pi]",
          ),
          "bbox": tfds.features.BBoxFeature(
              doc="2D bounding box of object in the image"
          ),
          "dimensions": tfds.features.Tensor(
              shape=(3,),
              dtype=np.float32,
              doc="3D object dimensions: height, width, length (in meters)",
          ),
          "location": tfds.features.Tensor(
              shape=(3,),
              dtype=np.float32,
              doc="3D object location x,y,z in camera coordinates (in meters)",
          ),
          "rotation_y": tfds.features.Tensor(
              shape=(),
              dtype=np.float32,
              doc="Rotation ry around Y-axis in camera coordinates [-pi..pi]",
          ),
      }
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "image": tfds.features.Image(),
                  "image/file_name": tfds.features.Text(),  # E.g. "000001.png".
                  "objects": tfds.features.Sequence(annotations),
              }
          ),
          homepage=_HOMEPAGE_URL,
      )
  
file_path: datasets/tensorflow_datasets/datasets/kitti/kitti_dataset_builder.py
imports: import collections
  import csv
  import os
  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