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- #!/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 = 0xFF & cv2.waitKey()
- if ch == 27:
- break
- cv2.destroyAllWindows()
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