code: def get_label_map_coco(data_dir: str):
      """Gets the label map from a COCO formatted dataset directory.
  
      Note that id 0 is reserved for the background class. If id=0 is set, it needs
      to be set to "background". It is optional to include id=0 if it is unused, and
      it will be automatically added by this method.
  
      Args:
        data_dir: Path of the dataset directory
  
      Returns:
        label_map dictionary of the format {<id>:<label_name>}
  
      Raises:
        ValueError: If the label_name for id 0 is set to something other than
        the "background" class.
      """
      data_dir = os.path.abspath(data_dir)
      # Process labels.json file
      label_file = os.path.join(data_dir, "labels.json")
      with open(label_file, "r") as f:
          data = json.load(f)
  
      # Categories
      label_map = {}
      for category in data["categories"]:
          label_map[int(category["id"])] = category["name"]
  
      if 0 in label_map and label_map[0] != "background":
          raise ValueError(
              (
                  "Label index 0 is reserved for the background class, but "
                  f"it was found to be {label_map[0]}"
              ),
          )
      if 0 not in label_map:
          label_map[0] = "background"
  
      return label_map
  
imports: import abc
  import collections
  import hashlib
  import json
  import math
  import os
  import tempfile
  from typing import Any, Dict, List, Mapping, Optional
  import xml.etree.ElementTree
  import tensorflow
  from mediapipe.model_maker.python.core.data import cache_files
  from official.vision.data import tfrecord_lib
label_desc: Use image node_id 7 for calling a global function with example usage: get_label_map_coco(data_dir) and returns: label_map