text: import cv2
  import numpy as np
  from mtcnn import mtcnn
  
  img = cv2.imread('img/1.jpg')
  
  model = mtcnn()
  threshold = [0.5,0.6,0.7]
  rectangles = model.detectFace(img, threshold)
  draw = img.copy()
  
  for rectangle in rectangles:
      if rectangle is not None:
          W = -int(rectangle[0]) + int(rectangle[2])
          H = -int(rectangle[1]) + int(rectangle[3])
          paddingH = 0.01 * W
          paddingW = 0.02 * H
  
          crop_img = img[int(rectangle[1]+paddingH):int(rectangle[3]-paddingH), int(rectangle[0]-paddingW):int(rectangle[2]+paddingW)]
          if crop_img is None:
              continue
          if crop_img.shape[0] < 0 or crop_img.shape[1] < 0:
              continue
          cv2.rectangle(draw, (int(rectangle[0]), int(rectangle[1])), (int(rectangle[2]), int(rectangle[3])), (255, 0, 0), 2)
  
          for i in range(5, 15, 2):
              cv2.circle(draw, (int(rectangle[i + 0]), int(rectangle[i + 1])), 2, (0, 0, 255),-1)
  
  cv2.imwrite("img/output.jpg",draw)
  
  cv2.imshow("output", draw)
  c = cv2.waitKey(0)