code: def draw_face(path, face_list=[], p=0.2):
      deepfakes_num = 0
  
      # img = cv2.cvtColor(cv2.imread(path), cv2.COLOR_BGR2RGB)
      img = cv2.imread(path)
  
      for i in range(len(face_list)):
          score = face_list[i]["score"]
  
          # print(score)
  
          if float(score) <= p:
              left = int(face_list[i]["location"]["left"])
              top = int(face_list[i]["location"]["top"])
              width = int(face_list[i]["location"]["width"])
              height = int(face_list[i]["location"]["height"])
  
              cv2.rectangle(
                  img,
                  (left, top),
                  (left + width, top + height),
                  (0, 255, 0),
                  4,
              )
              cv2.putText(
                  img,
                  "score={}".format(score),
                  (int(left), int(top - height / 5)),
                  cv2.FONT_HERSHEY_PLAIN,
                  2.0,
                  (255, 255, 255),
                  2,
                  1,
              )
  
              deepfakes_num += 1
  
      cv2.imwrite(path, img)
  
file_path: AdvBox/applications/fake_face_detect/benchmarking.py
imports: import requests
  import cv2
  import os
  import shutil
  import glob
  import argparse
  import time
label_desc: Use image node_id 1 for calling a global function with example usage: draw_face(path, face_list, p) without return types