code: def parse_args():
      parser = argparse.ArgumentParser(description="Model prediction")
  
      # Common params
      parser.add_argument(
          "--config", help="The path of config file.", type=str
      )
      parser.add_argument(
          "--model_path",
          help="The path of trained weights for prediction.",
          type=str,
      )
      parser.add_argument(
          "--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,
      )
      parser.add_argument(
          "--dataset_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,
      )
  
      parser.add_argument(
          "--save_dir",
          help="The directory for saving the predicted results.",
          type=str,
          default="./output/result",
      )
      parser.add_argument(
          "--device",
          help="Set the device place for predicting model.",
          default="gpu",
          choices=["cpu", "gpu", "xpu", "npu", "mlu"],
          type=str,
      )
      parser.add_argument(
          "--device_id",
          help="Set the device id for predicting model.",
          default=0,
          type=int,
      )
  
      # Data augment params
      parser.add_argument(
          "--aug_pred",
          help="Whether to use mulit-scales and flip augment for prediction",
          action="store_true",
      )
      parser.add_argument(
          "--scales",
          nargs="+",
          help="Scales for augment, e.g., `--scales 0.75 1.0 1.25`.",
          type=float,
          default=1.0,
      )
      parser.add_argument(
          "--flip_horizontal",
          help="Whether to use flip horizontally augment",
          action="store_true",
      )
      parser.add_argument(
          "--flip_vertical",
          help="Whether to use flip vertically augment",
          action="store_true",
      )
  
      # Sliding window evaluation params
      parser.add_argument(
          "--is_slide",
          help="Whether to predict images in sliding window method",
          action="store_true",
      )
      parser.add_argument(
          "--crop_size",
          nargs=2,
          help="The crop size of sliding window, the first is width and the second is height."
          "For example, `--crop_size 512 512`",
          type=int,
      )
      parser.add_argument(
          "--stride",
          nargs=2,
          help="The stride of sliding window, the first is width and the second is height."
          "For example, `--stride 512 512`",
          type=int,
      )
  
      # Custom color map
      parser.add_argument(
          "--custom_color",
          nargs="+",
          help="Save images with a custom color map. Default: None, use paddleseg's default color map.",
          type=int,
      )
  
      parser.add_argument(
          "--opts",
          help="Update the key-value pairs of all options.",
          default=None,
          nargs="+",
      )
  
      return parser.parse_args()
  
file_path: PaddleSeg/tools/analyse.py
imports: import argparse
  from paddleseg.cvlibs import manager, Config, SegBuilder
  from paddleseg.utils import get_sys_env, logger, utils
  from paddleseg.core import analyse
  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