code: def parse_args():
      """Training Options for Depth Prediction Experiments"""
      parser = argparse.ArgumentParser(
          description="MXNet Gluon Monodepth2 Demo"
      )
  
      # model and dataset
      parser.add_argument(
          "--model_zoo",
          type=str,
          choices=[
              "monodepth2_resnet18_kitti_stereo_640x192",
              "monodepth2_resnet18_kitti_mono_640x192",
              "monodepth2_resnet18_kitti_mono_stereo_640x192",
          ],
          default="monodepth2_resnet18_kitti_mono_stereo_640x192",
          help="choose depth model from model zoo model",
      )
  
      parser.add_argument(
          "--input_format",
          type=str,
          choices=["image", "video"],
          default="image",
          help="choose the format of input data",
      )
      parser.add_argument(
          "--data_path", type=str, help="path to the data"
      )
      parser.add_argument(
          "--height", type=int, help="input image height", default=192
      )
      parser.add_argument(
          "--width", type=int, help="input image width", default=640
      )
  
      parser.add_argument(
          "--prediction_only",
          action="store_true",
          help="if true, just store pure prediction results",
      )
      parser.add_argument(
          "--use_depth",
          action="store_true",
          help="use depth map as prediction results",
      )
      parser.add_argument(
          "--output_format",
          type=str,
          choices=["image", "video"],
          default="video",
          help="choose the format of output",
      )
      parser.add_argument(
          "--output_path",
          type=str,
          help="path to store the results",
          default=os.path.join(os.path.expanduser("."), "tmp"),
      )
  
      # the parser
      args = parser.parse_args()
  
      return args
  
file_path: gluon-cv/scripts/depth/demo.py
imports: import os
  import argparse
  import time
  import PIL.Image
  import numpy
  import mxnet
  from mxnet.gluon.data.vision import transforms
  import gluoncv
  from gluoncv.model_zoo.monodepthv2.layers import disp_to_depth
  import matplotlib
  import matplotlib.cm
  import cv2
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args