code: def main(args=None):
      # parse arguments
      if args is None:
          args = sys.argv[1:]
      args = parse_args(args)
  
      # make sure tensorflow is the minimum required version
      check_tf_version()
  
      # create the generator
      generator = create_generator(args)
  
      # optionally load config parameters
      if args.config:
          args.config = read_config_file(args.config)
  
      # optionally load anchor parameters
      anchor_params = None
      if args.config and "anchor_parameters" in args.config:
          anchor_params = parse_anchor_parameters(args.config)
  
      pyramid_levels = None
      if args.config and "pyramid_levels" in args.config:
          pyramid_levels = parse_pyramid_levels(args.config)
      # create the display window if necessary
      if not args.no_gui:
          cv2.namedWindow("Image", cv2.WINDOW_NORMAL)
  
      run(
          generator,
          args,
          anchor_params=anchor_params,
          pyramid_levels=pyramid_levels,
      )
  
file_path: ImageAI/imageai_tf_deprecated/Detection/keras_retinanet/bin/debug.py
imports: import argparse
  import os
  import sys
  import cv2
  from ..preprocessing.pascal_voc import PascalVocGenerator
  from ..preprocessing.csv_generator import CSVGenerator
  from ..preprocessing.kitti import KittiGenerator
  from ..preprocessing.open_images import OpenImagesGenerator
  from ..utils.anchors import anchors_for_shape, compute_gt_annotations
  from ..utils.config import read_config_file, parse_anchor_parameters, parse_pyramid_levels
  from ..utils.image import random_visual_effect_generator
  from ..utils.tf_version import check_tf_version
  from ..utils.transform import random_transform_generator
  from ..utils.visualization import draw_annotations, draw_boxes, draw_caption
label_desc: Use image node_id 5 for calling a global function with example usage: main(args) without return types