code: def argsparser():
      """
      argsparser func
      """
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--model_path", type=str, help="inference model filepath"
      )
      parser.add_argument(
          "--image_file",
          type=str,
          default=None,
          help="image path, if set image_file, it will not eval coco.",
      )
      parser.add_argument(
          "--reader_config",
          type=str,
          default=None,
          help="path of datset and reader config.",
      )
      parser.add_argument(
          "--benchmark",
          type=bool,
          default=False,
          help="Whether run benchmark or not.",
      )
      parser.add_argument(
          "--use_trt",
          type=bool,
          default=False,
          help="Whether use TensorRT or not.",
      )
      parser.add_argument(
          "--precision",
          type=str,
          default="paddle",
          help="mode of running(fp32/fp16/int8)",
      )
      parser.add_argument(
          "--device",
          type=str,
          default="GPU",
          help="Choose the device you want to run, it can be: CPU/GPU/XPU, default is GPU",
      )
      parser.add_argument(
          "--use_dynamic_shape",
          type=bool,
          default=True,
          help="Whether use dynamic shape or not.",
      )
      parser.add_argument(
          "--use_mkldnn",
          type=bool,
          default=False,
          help="Whether use mkldnn or not.",
      )
      parser.add_argument(
          "--cpu_threads",
          type=int,
          default=10,
          help="Num of cpu threads.",
      )
      parser.add_argument(
          "--img_shape", type=int, default=640, help="input_size"
      )
      parser.add_argument(
          "--include_nms",
          type=bool,
          default=True,
          help="Whether include nms or not.",
      )
  
      return parser
  
imports: import os
  import argparse
  import time
  import sys
  import cv2
  import numpy
  import paddle
  from paddle.inference import Config
  from paddle.inference import create_predictor
  from ppdet.core.workspace import load_config, create
  from ppdet.metrics import COCOMetric
  from post_process import PPYOLOEPostProcess
label_desc: Use image node_id 1 for calling a global function with example usage: argsparser() and returns: parser