class_docstr: Dataset for the Detection Track.
class_docstr_tok: ["Dataset","for","the","Detection","Track","."]
code: def _info(self):
      label = tfds.features.ClassLabel(num_classes=_NUM_CLASSES)
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "id": tfds.features.Text(),
                  "image": tfds.features.Image(),
                  # A sequence of image-level labels.
                  "objects": tfds.features.Sequence(
                      {
                          "label": label,
                          # All labels have been verified by humans.
                          #  - If confidence is 1.0, the object IS in the image.
                          #  - If confidence is 0.0, the object is NOT in the image.
                          "confidence": np.float32,
                          "source": tfds.features.Text(),
                      }
                  ),
                  # A sequence of bounding boxes.
                  "bobjects": tfds.features.Sequence(
                      {
                          "label": label,
                          "bbox": tfds.features.BBoxFeature(),
                          "is_group_of": np.bool_,
                      }
                  ),
              }
          ),
          homepage=_URL,
      )
  
file_path: datasets/tensorflow_datasets/datasets/open_images_challenge2019_detection/open_images_challenge2019_detection_dataset_builder.py
imports: from __future__ import annotations
  import abc
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the Builder obj's underlying member method code with example usage: obj._info() and returns: self