code: def detect(self, image_path, path=None):
      self.yolo_parameter = self.MainModel.yolo_parameter()
      # yolov3 80 classes
      assert self.yolo_parameter[1] == 80
      self.anchors = []
      for i in range(len(self.yolo_parameter[0])):
          if i % 2:
              tmp = [
                  self.yolo_parameter[0][i - 1],
                  self.yolo_parameter[0][i],
              ]
              self.anchors.append(tmp)
      self.anchors = np.array(self.anchors)
      self.score_threshold = self.yolo_parameter[2]
      self.iou_threshold = self.yolo_parameter[3]
  
      self.preprocess(image_path)
  
      self.yolo_result(path)
  
      print(
          "Keras yolo model result file is saved as [{}.jpg], generated by [{}.py] and [{}].".format(
              path, self.args.n, self.args.w
          )
      )
  
file_path: MMdnn/mmdnn/conversion/examples/keras/imagenet_test.py
imports: import argparse
  import numpy
  import sys
  import os
  from mmdnn.conversion.examples.imagenet_test import TestKit
  import colorsys
  from keras import backend
  from PIL import Image, ImageFont, ImageDraw
  from mmdnn.conversion.examples.keras.utils import yolo_eval
label_desc: Use image node_id 9 for calling the TestKeras obj's underlying member method code with example usage: obj.detect(image_path, path) without return types