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import numpy as np
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import cv2
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def angle_cos(p0, p1, p2):
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d1, d2 = p0-p1, p2-p1
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return abs( np.dot(d1, d2) / np.sqrt( np.dot(d1, d1)*np.dot(d2, d2) ) )
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def find_squares(img):
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img = cv2.GaussianBlur(img, (5, 5), 0)
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squares = []
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for gray in cv2.split(img):
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for thrs in xrange(0, 255, 26):
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if thrs == 0:
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bin = cv2.Canny(gray, 0, 50, apertureSize=5)
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bin = cv2.dilate(bin, None)
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else:
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retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY)
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contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
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for cnt in contours:
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cnt_len = cv2.arcLength(cnt, True)
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cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True)
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if len(cnt) == 4 and cv2.contourArea(cnt) > 1000 and cv2.isContourConvex(cnt):
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cnt = cnt.reshape(-1, 2)
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max_cos = np.max([angle_cos( cnt[i], cnt[(i+1) % 4], cnt[(i+2) % 4] ) for i in xrange(4)])
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if max_cos < 0.1:
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squares.append(cnt)
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return squares
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if __name__ == '__main__':
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from glob import glob
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for fn in glob('../cpp/pic*.png'):
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img = cv2.imread(fn)
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squares = find_squares(img)
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cv2.drawContours( img, squares, -1, (0, 255, 0), 3 )
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cv2.imshow('squares', img)
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ch = cv2.waitKey()
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if ch == 27:
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break
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