code: def create_class_names(class_dict: dict):
      keys = class_dict.keys()
      with open("./data/my_data_label.names", "w") as w:
          for index, k in enumerate(keys):
              if index + 1 == len(keys):
                  w.write(k)
              else:
                  w.write(k + "\n")
  
file_path: deep-learning-for-image-processing/pytorch_object_detection/yolov3_spp/trans_voc2yolo.py
imports: import os
  from tqdm import tqdm
  from lxml import etree
  import json
  import shutil
label_desc: Use image node_id 3 for calling a global function with example usage: create_class_names(class_dict) without return types