old_contents: # Simle detection using Haar Cascade + CNN.
  import sensor, time, image, os, nn
  
  sensor.reset()                          # Reset and initialize the sensor.
  sensor.set_contrast(2)
  sensor.set_pixformat(sensor.GRAYSCALE)  # Set pixel format to RGB565
  sensor.set_framesize(sensor.QQVGA)      # Set frame size to QVGA (320x240)
  sensor.skip_frames(time=2000)
  sensor.set_auto_gain(False)
  
  # Load smile detection network
  net = nn.load('/smile.network')
  
  # Load Face Haar Cascade
  face_cascade = image.HaarCascade("frontalface", stages=25)
  print(face_cascade)
  
  # FPS clock
  clock = time.clock()
  while (True):
      clock.tick()
  
      # Capture snapshot
      img = sensor.snapshot()
  
      # Find faces.
      objects = img.find_features(face_cascade, threshold=0.75, scale_factor=1.25)
  
      # Detect smiles
      for r in objects:
          img.draw_rectangle(r)
          out = net.forward(img, roi=r, softmax=True)
          img.draw_string(r[0], r[1], ':)' if (out[0]/127 > 0.8) else ':(', color=(255), scale=2)
  
      print(clock.fps())
  
new_contents: # Simle detection using Haar Cascade + CNN.
  import sensor, time, image, os, nn
  
  sensor.reset()                          # Reset and initialize the sensor.
  sensor.set_contrast(2)
  sensor.set_pixformat(sensor.GRAYSCALE)  # Set pixel format to RGB565
  sensor.set_framesize(sensor.QQVGA)      # Set frame size to QVGA (320x240)
  sensor.skip_frames(time=2000)
  sensor.set_auto_gain(False)
  
  # Load smile detection network
  net = nn.load('/smile.network')
  
  # Load Face Haar Cascade
  face_cascade = image.HaarCascade("frontalface", stages=25)
  print(face_cascade)
  
  # FPS clock
  clock = time.clock()
  while (True):
      clock.tick()
  
      # Capture snapshot
      img = sensor.snapshot()
  
      # Find faces.
      objects = img.find_features(face_cascade, threshold=0.75, scale_factor=1.25)
  
      # Detect smiles
      for r in objects:
          # Resize and center detection area
          r = [r[0], r[1]+10, int(r[2]*1.1), int(r[2]*1.1)]
          img.draw_rectangle(r)
          out = net.forward(img, roi=r, softmax=True)
          img.draw_string(r[0], r[1], ':)' if (out[0]/127 > 0.8) else ':(', color=(255), scale=2)
  
      print(clock.fps())
  
subject: Update smile detection example.