class_docstr: Image with additional label metadata.
  
  This feature connector is similar to `tfds.features.Image`, but expose
  additional attributes from `tfds.features.ClassLabel` to access label
  metadata.
  
  This can be used for segmentation tasks were each pixel is labeled.
  
  ```python
  builder = tfds.builder('my_dataset')
  builder.info.features['label_image'].names == ['background', 'car', ...]
  ```
class_docstr_tok: ["Image","with","additional","label","metadata",".","This","feature","connector","is","similar","to","`","tfds.features.Image","`",",","but","expose","additional","attributes","from","`","tfds.features.ClassLabel","`","to","access","label","metadata",".","This","can","be","used","for","segmentation","tasks","were","each","pixel","is","labeled",".","``","`","python","builder","=","tfds.builder","(","'my_dataset","'",")","builder.info.features","[","'label_image","'","]",".names","==","[","'background","'",",","'car","'",",","...","]","``","`"]
code: def _additional_repr_info(self):
      return {"num_classes": self.num_classes}
  
file_path: datasets/tensorflow_datasets/core/features/labeled_image.py
imports: from __future__ import annotations
  from typing import Optional, Union
  from etils import epath
  from tensorflow_datasets.core.features import class_label_feature
  from tensorflow_datasets.core.features import feature
  from tensorflow_datasets.core.features import image_feature
  from tensorflow_datasets.core.proto import feature_pb2
  from tensorflow_datasets.core.utils import type_utils
label_desc: Use image node_id 6 for calling the LabeledImage obj's underlying member method code with example usage: obj._additional_repr_info() and returns: dict