code: def parse_args():
      parser = ArgumentParser()
      parser.add_argument(
          "inputs", type=str, help="Input image file or folder path."
      )
      parser.add_argument(
          "--out-dir",
          type=str,
          default="results/",
          help="Output directory of results.",
      )
      parser.add_argument(
          "--det",
          type=str,
          default=None,
          help="Pretrained text detection algorithm. It's the path to the "
          "config file or the model name defined in metafile.",
      )
      parser.add_argument(
          "--det-weights",
          type=str,
          default=None,
          help="Path to the custom checkpoint file of the selected det model. "
          'If it is not specified and "det" is a model name of metafile, the '
          "weights will be loaded from metafile.",
      )
      parser.add_argument(
          "--rec",
          type=str,
          default=None,
          help="Pretrained text recognition algorithm. It's the path to the "
          "config file or the model name defined in metafile.",
      )
      parser.add_argument(
          "--rec-weights",
          type=str,
          default=None,
          help="Path to the custom checkpoint file of the selected recog model. "
          'If it is not specified and "rec" is a model name of metafile, the '
          "weights will be loaded from metafile.",
      )
      parser.add_argument(
          "--kie",
          type=str,
          default=None,
          help="Pretrained key information extraction algorithm. It's the path"
          "to the config file or the model name defined in metafile.",
      )
      parser.add_argument(
          "--kie-weights",
          type=str,
          default=None,
          help="Path to the custom checkpoint file of the selected kie model. "
          'If it is not specified and "kie" is a model name of metafile, the '
          "weights will be loaded from metafile.",
      )
      parser.add_argument(
          "--device",
          type=str,
          default=None,
          help="Device used for inference. "
          "If not specified, the available device will be automatically used.",
      )
      parser.add_argument(
          "--batch-size",
          type=int,
          default=1,
          help="Inference batch size.",
      )
      parser.add_argument(
          "--show",
          action="store_true",
          help="Display the image in a popup window.",
      )
      parser.add_argument(
          "--print-result",
          action="store_true",
          help="Whether to print the results.",
      )
      parser.add_argument(
          "--save_pred",
          action="store_true",
          help="Save the inference results to out_dir.",
      )
      parser.add_argument(
          "--save_vis",
          action="store_true",
          help="Save the visualization results to out_dir.",
      )
  
      call_args = vars(parser.parse_args())
  
      init_kws = [
          "det",
          "det_weights",
          "rec",
          "rec_weights",
          "kie",
          "kie_weights",
          "device",
      ]
      init_args = {}
      for init_kw in init_kws:
          init_args[init_kw] = call_args.pop(init_kw)
  
      return init_args, call_args
  
imports: from argparse import ArgumentParser
  from mmocr.apis.inferencers import MMOCRInferencer
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: init_args,  call_args