code: def readGTImage(
      image_file: Union[str, Path], backend_args: Optional[dict] = None
  ) -> np.ndarray:
      """Read an image from path.
  
      Same as obj:``cityscapesscripts.evaluation.
      evalInstanceLevelSemanticLabeling.readGTImage``, but support loading
      groundtruth image from file backend.
      Args:
          image_file (str or Path): Either a str or pathlib.Path.
          backend_args (dict, optional): Instantiates the corresponding file
              backend. It may contain `backend` key to specify the file
              backend. If it contains, the file backend corresponding to this
              value will be used and initialized with the remaining values,
              otherwise the corresponding file backend will be selected
              based on the prefix of the file path. Defaults to None.
      Returns:
          np.ndarray: The groundtruth image.
      """
      img_bytes = get(image_file, backend_args=backend_args)
      img = mmcv.imfrombytes(
          img_bytes, flag="unchanged", backend="pillow"
      )
      return img
  
file_path: mmdetection/mmdet/evaluation/functional/cityscapes_utils.py
imports: import json
  import os
  import sys
  from pathlib import Path
  from typing import Optional, Union
  import mmcv
  import numpy
  from mmengine.fileio import get
label_desc: Use image node_id 3 for calling a global function with example usage: readGTImage(image_file, backend_args) and returns: img