code: def get_coco_format_classes(sample_data_path: str):
      """
      The all class names for COCO format data.
  
      Parameters
      ----------
      sample_data_path
          The path to COCO format json annotation file. Could be any split, e.g. train/val/test/....
  
      Returns
      -------
          All the class names.
      """
      try:
          with open(sample_data_path, "r") as f:
              annotation = json.load(f)
      except:
          raise ValueError(
              f"Failed to load json from provided json file: {sample_data_path}."
          )
      return [cat["name"] for cat in annotation["categories"]]
  
imports: import json
  import logging
  import os
  import warnings
  from pathlib import Path
  from typing import Dict, Iterable, List, Optional, Union
  import defusedxml.ElementTree
  import numpy
  import pandas
  import PIL
  from torchmetrics.detection.mean_ap import MeanAveragePrecision
  from ..constants import BBOX, LABEL, MAP, MAP_50, MAP_75, MAP_LARGE, MAP_MEDIUM, MAP_SMALL, MAR_1, MAR_10, MAR_100, MAR_LARGE, MAR_MEDIUM, MAR_SMALL, MEAN_AVERAGE_PRECISION
  from .download import download, is_url
label_desc: Use image node_id 27 for calling a global function with example usage: get_coco_format_classes(sample_data_path) and returns: unknown