code: def get_frcnn_features(self, image_paths):
      image_preprocess = Preprocess(self.frcnn_cfg)
  
      images, sizes, scales_yx = image_preprocess(image_paths)
  
      output_dict = self.frcnn(
          images,
          sizes,
          scales_yx=scales_yx,
          padding=None,
          max_detections=self.frcnn_cfg.max_detections,
          return_tensors="pt",
      )
  
      return output_dict
  
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 4 for calling the FeatureExtractor obj's underlying member method code with example usage: obj.get_frcnn_features(image_paths) and returns: output_dict