faster detection and timing in facedetect.py

This commit is contained in:
Alexander Mordvintsev 2011-07-11 09:21:27 +00:00
parent b5d864f579
commit 0217ae3a70

View File

@ -1,13 +1,14 @@
import numpy as np
import cv2, cv
from video import create_capture
from common import clock, draw_str
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))
rects = cascade.detectMultiScale(img, scaleFactor=1.3, minNeighbors=4, minSize=(30, 30), flags = cv.CV_HAAR_SCALE_IMAGE)
if len(rects) == 0:
return []
rects[:,2:] += rects[:,:2]
@ -37,6 +38,8 @@ if __name__ == '__main__':
ret, img = cam.read()
gray = cv2.cvtColor(img, cv.CV_BGR2GRAY)
gray = cv2.equalizeHist(gray)
t = clock()
rects = detect(gray, cascade)
vis = img.copy()
draw_rects(vis, rects, (0, 255, 0))
@ -45,7 +48,9 @@ if __name__ == '__main__':
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))
cv2.imshow('facedetect', vis)
if cv2.waitKey(5) == 27: