code: def inference(cls, architecture, files, model_path, image_path):
      import numpy as np
  
      if cls.sanity_check(architecture):
          download_file(
              cls._base_model_url + "cfg/coco.data", directory="./"
          )
          download_file(
              cls._base_model_url + "data/coco.names",
              directory="./data/",
          )
  
          print(files)
          net = cdarknet.load_net(
              files[0].encode(), files[1].encode(), 0
          )
          meta = cdarknet.load_meta("coco.data".encode())
  
          r = cdarknet.detect(net, meta, image_path.encode())
          # print(r)
          return r
  
      else:
          return None
  
file_path: MMdnn/mmdnn/conversion/examples/darknet/extractor.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  import os
  from mmdnn.conversion.examples.darknet import darknet
  from mmdnn.conversion.examples.imagenet_test import TestKit
  from mmdnn.conversion.examples.extractor import base_extractor
  from mmdnn.conversion.common.utils import download_file
label_desc: Use image node_id 2 for calling the darknet_extractor obj's underlying member method code with example usage: obj.inference(cls, architecture, files, model_path, image_path) and returns: r, None