code: def parse_args(args):
      """Parse the arguments."""
      parser = argparse.ArgumentParser(
          description="Debug script for a RetinaNet network."
      )
      subparsers = parser.add_subparsers(
          help="Arguments for specific dataset types.",
          dest="dataset_type",
      )
      subparsers.required = True
  
      coco_parser = subparsers.add_parser("coco")
      coco_parser.add_argument(
          "coco_path", help="Path to dataset directory (ie. /tmp/COCO)."
      )
      coco_parser.add_argument(
          "--coco-set",
          help="Name of the set to show (defaults to val2017).",
          default="val2017",
      )
  
      pascal_parser = subparsers.add_parser("pascal")
      pascal_parser.add_argument(
          "pascal_path",
          help="Path to dataset directory (ie. /tmp/VOCdevkit).",
      )
      pascal_parser.add_argument(
          "--pascal-set",
          help="Name of the set to show (defaults to test).",
          default="test",
      )
      pascal_parser.add_argument(
          "--image-extension",
          help="Declares the dataset images' extension.",
          default=".jpg",
      )
  
      kitti_parser = subparsers.add_parser("kitti")
      kitti_parser.add_argument(
          "kitti_path",
          help="Path to dataset directory (ie. /tmp/kitti).",
      )
      kitti_parser.add_argument(
          "subset", help="Argument for loading a subset from train/val."
      )
  
      def csv_list(string):
          return string.split(",")
  
      oid_parser = subparsers.add_parser("oid")
      oid_parser.add_argument(
          "main_dir", help="Path to dataset directory."
      )
      oid_parser.add_argument(
          "subset",
          help="Argument for loading a subset from train/validation/test.",
      )
      oid_parser.add_argument(
          "--version",
          help="The current dataset version is v4.",
          default="v4",
      )
      oid_parser.add_argument(
          "--labels-filter",
          help="A list of labels to filter.",
          type=csv_list,
          default=None,
      )
      oid_parser.add_argument(
          "--annotation-cache-dir",
          help="Path to store annotation cache.",
          default=".",
      )
      oid_parser.add_argument(
          "--parent-label",
          help="Use the hierarchy children of this label.",
          default=None,
      )
  
      csv_parser = subparsers.add_parser("csv")
      csv_parser.add_argument(
          "annotations",
          help="Path to CSV file containing annotations for evaluation.",
      )
      csv_parser.add_argument(
          "classes",
          help="Path to a CSV file containing class label mapping.",
      )
  
      parser.add_argument(
          "--no-resize",
          help="Disable image resizing.",
          dest="resize",
          action="store_false",
      )
      parser.add_argument(
          "--anchors",
          help="Show positive anchors on the image.",
          action="store_true",
      )
      parser.add_argument(
          "--display-name",
          help="Display image name on the bottom left corner.",
          action="store_true",
      )
      parser.add_argument(
          "--show-annotations",
          help="Show annotations on the image. Green annotations have anchors, red annotations don't and therefore don't contribute to training.",
          action="store_true",
      )
      parser.add_argument(
          "--random-transform",
          help="Randomly transform image and annotations.",
          action="store_true",
      )
      parser.add_argument(
          "--image-min-side",
          help="Rescale the image so the smallest side is min_side.",
          type=int,
          default=800,
      )
      parser.add_argument(
          "--image-max-side",
          help="Rescale the image if the largest side is larger than max_side.",
          type=int,
          default=1333,
      )
      parser.add_argument(
          "--config",
          help="Path to a configuration parameters .ini file.",
      )
      parser.add_argument(
          "--no-gui",
          help="Do not open a GUI window. Save images to an output directory instead.",
          action="store_true",
      )
      parser.add_argument(
          "--output-dir",
          help="The output directory to save images to if --no-gui is specified.",
          default=".",
      )
      parser.add_argument(
          "--flatten-output",
          help="Flatten the folder structure of saved output images into a single folder.",
          action="store_true",
      )
      parser.add_argument(
          "--group-method",
          help="Determines how images are grouped together",
          type=str,
          default="ratio",
          choices=["none", "random", "ratio"],
      )
  
      return parser.parse_args(args)
  
file_path: ImageAI/imageai_tf_deprecated/Detection/keras_retinanet/bin/debug.py
imports: import argparse
  import os
  import sys
  import cv2
  from ..preprocessing.pascal_voc import PascalVocGenerator
  from ..preprocessing.csv_generator import CSVGenerator
  from ..preprocessing.kitti import KittiGenerator
  from ..preprocessing.open_images import OpenImagesGenerator
  from ..utils.anchors import anchors_for_shape, compute_gt_annotations
  from ..utils.config import read_config_file, parse_anchor_parameters, parse_pyramid_levels
  from ..utils.image import random_visual_effect_generator
  from ..utils.tf_version import check_tf_version
  from ..utils.transform import random_transform_generator
  from ..utils.visualization import draw_annotations, draw_boxes, draw_caption
label_desc: Use image node_id 2 for calling a global function with example usage: parse_args(args) and returns: parser, string