text: # coding=utf-8
  """Performs face detection in realtime.
  
  Based on code from https://github.com/shanren7/real_time_face_recognition
  """
  # MIT License
  #
  # Copyright (c) 2017 François Gervais
  #
  # Permission is hereby granted, free of charge, to any person obtaining a copy
  # of this software and associated documentation files (the "Software"), to deal
  # in the Software without restriction, including without limitation the rights
  # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  # copies of the Software, and to permit persons to whom the Software is
  # furnished to do so, subject to the following conditions:
  #
  # The above copyright notice and this permission notice shall be included in all
  # copies or substantial portions of the Software.
  #
  # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  # SOFTWARE.
  import argparse
  import sys
  import time
  
  import cv2
  
  import face # Original
  # import contributed.face # Modified
  
  def add_overlays(frame, faces, frame_rate):
      if faces is not None:
          for face in faces:
              print("111")
              face_bb = face.bounding_box.astype(int)
              cv2.rectangle(frame,
                            (face_bb[0], face_bb[1]), (face_bb[2], face_bb[3]),
                            (0, 255, 0), 2)
              print("222")
              if face.name is not None:
                  cv2.putText(frame, face.name, (face_bb[0], face_bb[3]),
                              cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0),
                              thickness=2, lineType=2)
                  print("Accuracy")
                  print("333")
      cv2.putText(frame, str(frame_rate) + " fps", (10, 30),
                  cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0),
                  thickness=2, lineType=2)
      print("444")
  
  def main(args):
      frame_interval = 3  # Number of frames after which to run face detection
      fps_display_interval = 20  # seconds
      # fps_display_interval = 5  # seconds
      frame_rate = 0
      frame_count = 0
      
      video_capture = cv2.VideoCapture(0) # Original
      face_recognition = face.Recognition()
      start_time = time.time()
      if args.debug:
          print("Debug enabled")
          face.debug = True
  
      while True:
          # Capture frame-by-frame
          ret, frame = video_capture.read()
      
          # print('While2') # Modified
          # print("frame : ", frame) # Modified
          # print("frame.shape : ", frame.shape) # Modified
          if (frame_count % frame_interval) == 0:
  
              faces = face_recognition.identify(frame)
              # print("faces : ", faces) # Modified
  
              # Check our current fps
              end_time = time.time()
              if (end_time - start_time) > fps_display_interval:
                  frame_rate = int(frame_count / (end_time - start_time))
                  start_time = time.time()
                  frame_count = 0
          add_overlays(frame, faces, frame_rate)
          frame_count += 1
          cv2.imshow('Video', frame)
          # break # Modified
          if cv2.waitKey(1) & 0xFF == ord('q'):
              break
  
      # When everything is done, release the capture
      video_capture.release()
      cv2.destroyAllWindows()
  
  
  def parse_arguments(argv):
      parser = argparse.ArgumentParser()
  
      parser.add_argument('--debug', action='store_true',
                          help='Enable some debug outputs.')
      return parser.parse_args(argv)
  
  
  if __name__ == '__main__':
      main(parse_arguments(sys.argv[1:]))
  