code: def get_parser(self):
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--model_name",
          default="FRCNN",
          type=str,
          help="Model to use for detection",
      )
      parser.add_argument(
          "--model_file",
          default=None,
          type=str,
          help="Huggingface model file. This overrides the model_name param.",
      )
      parser.add_argument(
          "--config_name",
          default="FRCNN",
          type=str,
          help="Config to use for detection",
      )
      parser.add_argument(
          "--config_file",
          default=None,
          type=str,
          help="Huggingface config file",
      )
      parser.add_argument(
          "--start_index",
          default=0,
          type=int,
          help="Index to start from ",
      )
      parser.add_argument(
          "--end_index", default=None, type=int, help=""
      )
      parser.add_argument(
          "--batch_size", type=int, default=1, help="Batch size"
      )
      parser.add_argument(
          "--num_features",
          type=int,
          default=100,
          help="Number of features to extract.",
      )
      parser.add_argument(
          "--output_folder",
          type=str,
          default="./output",
          help="Output folder",
      )
      parser.add_argument(
          "--image_dir", type=str, help="Image directory or file"
      )
      # TODO add functionality for this flag
      parser.add_argument(
          "--feature_name",
          type=str,
          help="The name of the feature to extract",
          default="fc6",
      )
      parser.add_argument(
          "--exclude_list",
          type=str,
          help="List of images to be excluded from feature conversion. "
          + "Each image on a new line",
          default="./list",
      )
      parser.add_argument(
          "--confidence_threshold",
          type=float,
          default=0,
          help="Threshold of detection confidence above which boxes will be selected",
      )
      # TODO finish background flag
      parser.add_argument(
          "--background",
          action="store_true",
          help="The model will output predictions for the background class when set",
      )
      parser.add_argument(
          "--padding",
          type=str,
          default=None,
          help="You can set your padding, i.e. 'max_detections'",
      )
      parser.add_argument(
          "--visualize",
          type=bool,
          default=False,
          help="Add this flag to save the extra file used for visualization",
      )
      parser.add_argument(
          "--partition",
          type=int,
          default=None,
          help="Add this flag to save the extra file used for visualization",
      )
      parser.add_argument(
          "--max_partition",
          type=int,
          default=None,
          help="Add this flag to save the extra file used for visualization",
      )
      return parser
  
file_path: mmf/tools/scripts/features/frcnn/extract_features_frcnn.py
imports: import argparse
  import copy
  import logging
  import os
  import numpy
  import torch
  from tools.scripts.features.extraction_utils import chunks, get_image_files
  from tools.scripts.features.frcnn.frcnn_utils import Config
  from tools.scripts.features.frcnn.modeling_frcnn import GeneralizedRCNN
  from tools.scripts.features.frcnn.processing_image import Preprocess
label_desc: Use image node_id 2 for calling the FeatureExtractor obj's underlying member method code with example usage: obj.get_parser() and returns: parser