code: def parse_args():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "-l",
          "--lang_list",
          nargs="+",
          type=str,
          default=["en"],
          help="-l en ch_sim ... (language lists for easyocr)",
      )
      parser.add_argument(
          "-s",
          "--detector_onnx_save_path",
          type=str,
          default="detector_craft.onnx",
          help="export detector onnx file path ending in .onnx"
          + "Do not pass in this flag to avoid exporting detector",
      )
      parser.add_argument(
          "-d",
          "--dynamic",
          action="store_true",
          help="Dynamic  input output shapes for detector",
      )
      parser.add_argument(
          "-is",
          "--in_shape",
          nargs="+",
          type=int,
          default=[1, 3, 608, 800],
          help="-is 1 3 608 800 (bsize, channel, height, width)",
      )
      parser.add_argument(
          "-m",
          "--model_storage_directory",
          type=str,
          help="model storage directory for craft model",
      )
      parser.add_argument(
          "-u",
          "--user_network_directory",
          type=str,
          help="user model storage directory",
      )
      args = parser.parse_args()
      dpath = args.detector_onnx_save_path
      args.detector_onnx_save_path = None if dpath == "None" else dpath
      if len(args.in_shape) != 4:
          raise ValueError(
              f"Input shape must have four values (bsize, channel, height, width) eg. 1 3 608 800"
          )
      return args
  
imports: import argparse
  import onnx
  import torch
  import easyocr
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: parse_args() and returns: args