code: def argsparser():
      parser = argparse.ArgumentParser(description=__doc__)
      parser.add_argument(
          "--model_dir",
          type=str,
          default=None,
          help=(
              "Directory include:'model.pdiparams', 'model.pdmodel', "
              "'infer_cfg.yml', created by tools/export_model.py."
          ),
          required=True,
      )
      parser.add_argument(
          "--image_file",
          type=str,
          default=None,
          help="Path of image file.",
      )
      parser.add_argument(
          "--image_dir",
          type=str,
          default=None,
          help="Dir of image file, `image_file` has a higher priority.",
      )
      parser.add_argument(
          "--batch_size",
          type=int,
          default=1,
          help="batch_size for inference.",
      )
      parser.add_argument(
          "--video_file",
          type=str,
          default=None,
          help="Path of video file, `video_file` or `camera_id` has a highest priority.",
      )
      parser.add_argument(
          "--camera_id",
          type=int,
          default=-1,
          help="device id of camera to predict.",
      )
      parser.add_argument(
          "--threshold",
          type=float,
          default=0.5,
          help="Threshold of score.",
      )
      parser.add_argument(
          "--output_dir",
          type=str,
          default="output",
          help="Directory of output visualization files.",
      )
      parser.add_argument(
          "--run_mode",
          type=str,
          default="paddle",
          help="mode of running(paddle/trt_fp32/trt_fp16/trt_int8)",
      )
      parser.add_argument(
          "--device",
          type=str,
          default="cpu",
          help="Choose the device you want to run, it can be: CPU/GPU/XPU/NPU, default is CPU.",
      )
      parser.add_argument(
          "--use_gpu",
          type=ast.literal_eval,
          default=False,
          help="Deprecated, please use `--device`.",
      )
      parser.add_argument(
          "--run_benchmark",
          type=ast.literal_eval,
          default=False,
          help="Whether to predict a image_file repeatedly for benchmark",
      )
      parser.add_argument(
          "--enable_mkldnn",
          type=ast.literal_eval,
          default=False,
          help="Whether use mkldnn with CPU.",
      )
      parser.add_argument(
          "--cpu_threads",
          type=int,
          default=1,
          help="Num of threads with CPU.",
      )
      parser.add_argument(
          "--trt_min_shape",
          type=int,
          default=1,
          help="min_shape for TensorRT.",
      )
      parser.add_argument(
          "--trt_max_shape",
          type=int,
          default=1280,
          help="max_shape for TensorRT.",
      )
      parser.add_argument(
          "--trt_opt_shape",
          type=int,
          default=640,
          help="opt_shape for TensorRT.",
      )
      parser.add_argument(
          "--trt_calib_mode",
          type=bool,
          default=False,
          help="If the model is produced by TRT offline quantitative "
          "calibration, trt_calib_mode need to set True.",
      )
      parser.add_argument(
          "--save_images",
          action="store_true",
          help="Save visualization image results.",
      )
      parser.add_argument(
          "--save_mot_txts",
          action="store_true",
          help="Save tracking results (txt).",
      )
      parser.add_argument(
          "--save_mot_txt_per_img",
          action="store_true",
          help="Save tracking results (txt) for each image.",
      )
      parser.add_argument(
          "--scaled",
          type=bool,
          default=False,
          help="Whether coords after detector outputs are scaled, False in JDE YOLOv3 "
          "True in general detector.",
      )
      parser.add_argument(
          "--tracker_config",
          type=str,
          default=None,
          help=("tracker donfig"),
      )
      parser.add_argument(
          "--reid_model_dir",
          type=str,
          default=None,
          help=(
              "Directory include:'model.pdiparams', 'model.pdmodel', "
              "'infer_cfg.yml', created by tools/export_model.py."
          ),
      )
      parser.add_argument(
          "--reid_batch_size",
          type=int,
          default=50,
          help="max batch_size for reid model inference.",
      )
      parser.add_argument(
          "--use_dark",
          type=ast.literal_eval,
          default=True,
          help="whether to use darkpose to get better keypoint position predict ",
      )
      parser.add_argument(
          "--skip_frame_num",
          type=int,
          default=-1,
          help="Skip frames to speed up the process of getting mot results.",
      )
      parser.add_argument(
          "--warmup_frame",
          type=int,
          default=50,
          help="Warmup frames to test speed of the process of getting mot results.",
      )
      parser.add_argument(
          "--do_entrance_counting",
          action="store_true",
          help="Whether counting the numbers of identifiers entering "
          "or getting out from the entrance. Note that only support single-class MOT.",
      )
      parser.add_argument(
          "--do_break_in_counting",
          action="store_true",
          help="Whether counting the numbers of identifiers break in "
          "the area. Note that only support single-class MOT and "
          "the video should be taken by a static camera.",
      )
      parser.add_argument(
          "--region_type",
          type=str,
          default="horizontal",
          help="Area type for entrance counting or break in counting, 'horizontal' and "
          "'vertical' used when do entrance counting. 'custom' used when do break in counting. "
          "Note that only support single-class MOT, and the video should be taken by a static camera.",
      )
      parser.add_argument(
          "--region_polygon",
          nargs="+",
          type=int,
          default=[],
          help="Clockwise point coords (x0,y0,x1,y1...) of polygon of area when "
          "do_break_in_counting. Note that only support single-class MOT and "
          "the video should be taken by a static camera.",
      )
      parser.add_argument(
          "--secs_interval",
          type=int,
          default=2,
          help="The seconds interval to count after tracking",
      )
      parser.add_argument(
          "--draw_center_traj",
          action="store_true",
          help="Whether drawing the trajectory of center",
      )
      parser.add_argument(
          "--mtmct_dir",
          type=str,
          default=None,
          help="The MTMCT scene video folder.",
      )
      parser.add_argument(
          "--mtmct_cfg",
          type=str,
          default=None,
          help="The MTMCT config.",
      )
      return parser
  
imports: import time
  import os
  import sys
  import ast
  import argparse
label_desc: Use image node_id 1 for calling a global function with example usage: argsparser() and returns: parser