code: def convert_to_cityscape_format(img: Tensor) -> Tensor:
      """Utility to map predicted segmentation labels to cityscapes format"""
      img[img == 19] = 255
      img[img == 18] = 33
      img[img == 17] = 32
      img[img == 16] = 31
      img[img == 15] = 28
      img[img == 14] = 27
      img[img == 13] = 26
      img[img == 12] = 25
      img[img == 11] = 24
      img[img == 10] = 23
      img[img == 9] = 22
      img[img == 8] = 21
      img[img == 7] = 20
      img[img == 6] = 19
      img[img == 5] = 17
      img[img == 4] = 13
      img[img == 3] = 12
      img[img == 2] = 11
      img[img == 1] = 8
      img[img == 0] = 7
      img[img == 255] = 0
      return img
  
file_path: ml-cvnets/utils/visualization_utils.py
imports: import copy
  import random
  import sys
  from typing import List, Optional
  from torch import Tensor
  import numpy
  from matplotlib.colors import hsv_to_rgb
  from torch import Tensor
  from utils import logger
  from utils.color_map import Colormap
label_desc: Use image node_id 4 for calling a global function with example usage: convert_to_cityscape_format(img) and returns: img