f4334277
 Hu Chunming
提交3rdparty
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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 as cv
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 = cv.GaussianBlur(img, (5, 5), 0)
squares = []
for gray in cv.split(img):
for thrs in xrange(0, 255, 26):
if thrs == 0:
bin = cv.Canny(gray, 0, 50, apertureSize=5)
bin = cv.dilate(bin, None)
else:
_retval, bin = cv.threshold(gray, thrs, 255, cv.THRESH_BINARY)
contours, _hierarchy = cv.findContours(bin, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
for cnt in contours:
cnt_len = cv.arcLength(cnt, True)
cnt = cv.approxPolyDP(cnt, 0.02*cnt_len, True)
if len(cnt) == 4 and cv.contourArea(cnt) > 1000 and cv.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 and filterSquares(squares, cnt):
squares.append(cnt)
return squares
def intersectionRate(s1, s2):
area, _intersection = cv.intersectConvexConvex(np.array(s1), np.array(s2))
return 2 * area / (cv.contourArea(np.array(s1)) + cv.contourArea(np.array(s2)))
def filterSquares(squares, square):
for i in range(len(squares)):
if intersectionRate(squares[i], square) > 0.95:
return False
return True
from tests_common import NewOpenCVTests
class squares_test(NewOpenCVTests):
def test_squares(self):
img = self.get_sample('samples/data/pic1.png')
squares = find_squares(img)
testSquares = [
[[43, 25],
[43, 129],
[232, 129],
[232, 25]],
[[252, 87],
[324, 40],
[387, 137],
[315, 184]],
[[154, 178],
[196, 180],
[198, 278],
[154, 278]],
[[0, 0],
[400, 0],
[400, 300],
[0, 300]]
]
matches_counter = 0
for i in range(len(squares)):
for j in range(len(testSquares)):
if intersectionRate(squares[i], testSquares[j]) > 0.9:
matches_counter += 1
self.assertGreater(matches_counter / len(testSquares), 0.9)
self.assertLess( (len(squares) - matches_counter) / len(squares), 0.2)
if __name__ == '__main__':
NewOpenCVTests.bootstrap()
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