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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | from __future__ import print_function import numpy as np import cv2 as cv 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() | cs |