code: def parse_args():
      parser = ArgsParser()
      parser.add_argument(
          "--output_eval",
          default=None,
          type=str,
          help="Evaluation directory, default is current directory.",
      )
  
      parser.add_argument(
          "--json_eval",
          action="store_true",
          default=False,
          help="Whether to re eval with already exists bbox.json or mask.json",
      )
  
      parser.add_argument(
          "--slim_config",
          default=None,
          type=str,
          help="Configuration file of slim method.",
      )
  
      # TODO: bias should be unified
      parser.add_argument(
          "--bias",
          action="store_true",
          help="whether add bias or not while getting w and h",
      )
  
      parser.add_argument(
          "--classwise",
          action="store_true",
          help="whether per-category AP and draw P-R Curve or not.",
      )
  
      parser.add_argument(
          "--save_prediction_only",
          action="store_true",
          default=False,
          help="Whether to save the evaluation results only",
      )
  
      parser.add_argument(
          "--amp",
          action="store_true",
          default=False,
          help="Enable auto mixed precision eval.",
      )
  
      # for smalldet slice_infer
      parser.add_argument(
          "--slice_infer",
          action="store_true",
          help="Whether to slice the image and merge the inference results for small object detection.",
      )
      parser.add_argument(
          "--slice_size",
          nargs="+",
          type=int,
          default=[640, 640],
          help="Height of the sliced image.",
      )
      parser.add_argument(
          "--overlap_ratio",
          nargs="+",
          type=float,
          default=[0.25, 0.25],
          help="Overlap height ratio of the sliced image.",
      )
      parser.add_argument(
          "--combine_method",
          type=str,
          default="nms",
          help="Combine method of the sliced images' detection results, choose in ['nms', 'nmm', 'concat'].",
      )
      parser.add_argument(
          "--match_threshold",
          type=float,
          default=0.6,
          help="Combine method matching threshold.",
      )
      parser.add_argument(
          "--match_metric",
          type=str,
          default="ios",
          help="Combine method matching metric, choose in ['iou', 'ios'].",
      )
      args = parser.parse_args()
      return args
  
file_path: PaddleDetection/tools/eval.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import sys
  import warnings
  import paddle
  from ppdet.core.workspace import create, load_config, merge_config
  from ppdet.utils.check import check_gpu, check_npu, check_xpu, check_mlu, check_version, check_config
  from ppdet.utils.cli import ArgsParser, merge_args
  from ppdet.engine import Trainer, Trainer_ARSL, init_parallel_env
  from ppdet.metrics.coco_utils import json_eval_results
  from ppdet.slim import build_slim_model
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args