#!/usr/bin/env python ''' Simple "Square Detector" program. Loads several images sequentially and tries to find squares in each image. ''' # Python 2/3 compatibility import sys PY3 = sys.version_info[0] == 3 if PY3: xrange = range import numpy as np import cv2 def angle_cos(p0, p1, p2): d1, d2 = (p0-p1).astype('float'), (p2-p1).astype('float') return abs( np.dot(d1, d2) / np.sqrt( np.dot(d1, d1)*np.dot(d2, d2) ) ) def find_squares(img): img = cv2.GaussianBlur(img, (5, 5), 0) squares = [] for gray in cv2.split(img): for thrs in xrange(0, 255, 26): if thrs == 0: bin = cv2.Canny(gray, 0, 50, apertureSize=5) bin = cv2.dilate(bin, None) else: retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY) bin, contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) for cnt in contours: cnt_len = cv2.arcLength(cnt, True) cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True) if len(cnt) == 4 and cv2.contourArea(cnt) > 1000 and cv2.isContourConvex(cnt): cnt = cnt.reshape(-1, 2) max_cos = np.max([angle_cos( cnt[i], cnt[(i+1) % 4], cnt[(i+2) % 4] ) for i in xrange(4)]) if max_cos < 0.1: squares.append(cnt) return squares if __name__ == '__main__': from glob import glob for fn in glob('../data/pic*.png'): img = cv2.imread(fn) squares = find_squares(img) cv2.drawContours( img, squares, -1, (0, 255, 0), 3 ) cv2.imshow('squares', img) ch = cv2.waitKey() if ch == 27: break cv2.destroyAllWindows()
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