facedetect.py sample works

samples/python2/facedetect.py

@@ -1,22 +1,52 @@
 import numpy as np
-import cv2
+import cv2, cv
 from video import create_capture
 
+help_message = '''
+USAGE: facedetect.py [--cascade <cascade_fn>] [--nested-cascade <cascade_fn>] [<video_source>]
+'''
+
+def detect(img, cascade):
+    rects = cascade.detectMultiScale(img, scaleFactor=1.3, minNeighbors=4, minSize=(30, 30))
+    if len(rects) == 0:
+        return []
+    rects[:,2:] += rects[:,:2]
+    return rects
+
+def draw_rects(img, rects, color):
+    for x1, y1, x2, y2 in rects:
+        cv2.rectangle(img, (x1, y1), (x2, y2), color)
+
 if __name__ == '__main__':
     import sys, getopt
+    print help_message
     
     args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade='])
     try: video_src = video_src[0]
-    except: video_src = '0'
+    except: video_src = 'synth:bg=../cpp/lena.jpg:noise=0.05'
+    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.xml")
+    nested_fn  = args.get('--nested-cascade', "../../data/haarcascades/haarcascade_eye.xml")
 
+    cascade = cv2.CascadeClassifier(cascade_fn)
+    nested = cv2.CascadeClassifier(nested_fn)
 
     cam = create_capture(video_src)
 
     while True:
         ret, img = cam.read()
-        cv2.imshow('facedetect', img)
+        gray = cv2.cvtColor(img, cv.CV_BGR2GRAY)
+        gray = cv2.equalizeHist(gray)
+        rects = detect(gray, cascade)
+        vis = cv2.cvtColor(gray, cv.CV_GRAY2BGR)
+        draw_rects(vis, rects, (0, 255, 0))
+        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))
+
+        cv2.imshow('facedetect', vis)
 
         if cv2.waitKey(5) == 27:
             break