text: #!/usr/bin/env python
  
  '''
  face detection using haar cascades
  
  USAGE:
      facedetect.py [--cascade <cascade_fn>] [--nested-cascade <cascade_fn>] [<video_source>]
  '''
  
  # Python 2/3 compatibility
  from __future__ import print_function
  
  import numpy as np
  import cv2 as cv
  
  # local modules
  from video import create_capture
  from common import clock, draw_str
  
  
  def detect(img, cascade):
      rects = cascade.detectMultiScale(img, scaleFactor=1.3, minNeighbors=4, minSize=(30, 30),
                                       flags=cv.CASCADE_SCALE_IMAGE)
      if len(rects) == 0:
          return []
      rects[:,2:] += rects[:,:2]
      return rects
  
  def draw_rects(img, rects, color):
      for x1, y1, x2, y2 in rects:
          cv.rectangle(img, (x1, y1), (x2, y2), color, 2)
  
  if __name__ == '__main__':
      import sys, getopt
      print(__doc__)
  
      args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade='])
      try:
          video_src = video_src[0]
      except:
          video_src = 0
      args = dict(args)
      cascade_fn = args.get('--cascade', "../../data/haarcascades/haarcascade_frontalface_alt.xml")
      nested_fn  = args.get('--nested-cascade', "../../data/haarcascades/haarcascade_eye.xml")
  
      cascade = cv.CascadeClassifier(cascade_fn)
      nested = cv.CascadeClassifier(nested_fn)
  
      cam = create_capture(video_src, fallback='synth:bg=../data/lena.jpg:noise=0.05')
  
      while True:
          ret, img = cam.read()
          gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
          gray = cv.equalizeHist(gray)
  
          t = clock()
          rects = detect(gray, cascade)
          vis = img.copy()
          draw_rects(vis, rects, (0, 255, 0))
          if not nested.empty():
              for x1, y1, x2, y2 in rects:
                  roi = gray[y1:y2, x1:x2]
                  vis_roi = vis[y1:y2, x1:x2]
                  subrects = detect(roi.copy(), nested)
                  draw_rects(vis_roi, subrects, (255, 0, 0))
          dt = clock() - t
  
          draw_str(vis, (20, 20), 'time: %.1f ms' % (dt*1000))
          cv.imshow('facedetect', vis)
  
          if cv.waitKey(5) == 27:
              break
      cv.destroyAllWindows()
  