code: def parse_args():
      parser = argparse.ArgumentParser(description="Model prediction")
  
      # params of prediction
      parser.add_argument(
          "--config",
          dest="cfg",
          help="The config file.",
          default=None,
          type=str,
      )
      parser.add_argument(
          "--model_path",
          dest="model_path",
          help="The path of model for prediction",
          type=str,
          default=None,
      )
      parser.add_argument(
          "--image_path",
          dest="image_path",
          help="The image to predict, which can be a path of image, or a file list containing image paths, or a directory including images",
          type=str,
          default=None,
      )
      parser.add_argument(
          "--save_dir",
          dest="save_dir",
          help="The directory for saving the predicted results",
          type=str,
          default="./output/result",
      )
  
      # augment for prediction
      parser.add_argument(
          "--aug_pred",
          dest="aug_pred",
          help="Whether to use mulit-scales and flip augment for prediction",
          action="store_true",
      )
      parser.add_argument(
          "--scales",
          dest="scales",
          nargs="+",
          help="Scales for augment",
          type=float,
          default=1.0,
      )
      parser.add_argument(
          "--flip_horizontal",
          dest="flip_horizontal",
          help="Whether to use flip horizontally augment",
          action="store_true",
      )
      parser.add_argument(
          "--flip_vertical",
          dest="flip_vertical",
          help="Whether to use flip vertically augment",
          action="store_true",
      )
  
      # sliding window prediction
      parser.add_argument(
          "--is_slide",
          dest="is_slide",
          help="Whether to prediction by sliding window",
          action="store_true",
      )
      parser.add_argument(
          "--crop_size",
          dest="crop_size",
          nargs=2,
          help="The crop size of sliding window, the first is width and the second is height.",
          type=int,
          default=None,
      )
      parser.add_argument(
          "--stride",
          dest="stride",
          nargs=2,
          help="The stride of sliding window, the first is width and the second is height.",
          type=int,
          default=None,
      )
  
      # custom color map
      parser.add_argument(
          "--custom_color",
          dest="custom_color",
          nargs="+",
          help="Save images with a custom color map. Default: None, use paddleseg's default color map.",
          type=int,
          default=None,
      )
  
      # set device
      parser.add_argument(
          "--device",
          dest="device",
          help="Device place to be set, which can be GPU, XPU, NPU, MLU, CPU",
          default="gpu",
          type=str,
      )
  
      return parser.parse_args()
  
file_path: PaddleSeg/contrib/RSSegBenchmark/predict.py
imports: import argparse
  import os
  import paddle
  import backbones
  from paddleseg.cvlibs import manager, Config
  from paddleseg.utils import get_sys_env, logger, get_image_list
  from paddleseg.core import predict
  from paddleseg.transforms import Compose
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: parser