code: def _build_detection_model(self):
      cfg.merge_from_file(self.args.config_file)
      cfg.freeze()
  
      model = build_detection_model(cfg)
      checkpoint = torch.load(
          self.args.model_file, map_location=torch.device("cpu")
      )
  
      load_state_dict(model, checkpoint.pop("model"))
  
      model.to("cuda")
      model.eval()
      return model
  
imports: import argparse
  import os
  import cv2
  import numpy
  import torch
  from maskrcnn_benchmark.config import cfg
  from maskrcnn_benchmark.layers import nms
  from maskrcnn_benchmark.modeling.detector import build_detection_model
  from maskrcnn_benchmark.structures.image_list import to_image_list
  from maskrcnn_benchmark.utils.model_serialization import load_state_dict
  from mmf.utils.download import download
  from PIL import Image
  from tools.scripts.features.extraction_utils import chunks, get_image_files
label_desc: Use image node_id 4 for calling the FeatureExtractor obj's underlying member method code with example usage: obj._build_detection_model() and returns: model