def cannyThresholding(self, contour_retrieval_mode = cv2.RETR_LIST):
'''
contour_retrieval_mode is passed through as second argument to cv2.findContours
'''
# Attempt to match edges found in blue, green or red channels : collect all
channel = 0
for gray in cv2.split(self.img):
channel += 1
print('channel %d ' % channel)
title = self.tgen.next('channel-%d' % channel)
if self.show: ImageViewer(gray).show(window = title, destroy = self.destroy, info = self.info, thumbnailfn = title)
found = {}
for thrs in xrange(0, 255, 26):
print('Using threshold %d' % thrs)
if thrs == 0:
print('First step')
bin = cv2.Canny(gray, 0, 50, apertureSize=5)
title = self.tgen.next('canny-%d' % channel)
if self.show: ImageViewer(bin).show(window = title, destroy = self.destroy, info = self.info, thumbnailfn = title)
bin = cv2.dilate(bin, None)
title = self.tgen.next('canny-dilate-%d' % channel)
if self.show: ImageViewer(bin).show(window = title, destroy = self.destroy, info = self.info, thumbnailfn = title)
else:
retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY)
title = self.tgen.next('channel-%d-threshold-%d' % (channel, thrs))
if self.show: ImageViewer(bin).show(window='Next threshold (n to continue)', destroy = self.destroy, info = self.info, thumbnailfn = title)
bin, contours, hierarchy = cv2.findContours(bin, contour_retrieval_mode, cv2.CHAIN_APPROX_SIMPLE)
title = self.tgen.next('channel-%d-threshold-%d-contours' % (channel, thrs))
if self.show: ImageViewer(bin).show(window = title, destroy = self.destroy, info = self.info, thumbnailfn = title)
if contour_retrieval_mode == cv2.RETR_LIST or contour_retrieval_mode == cv2.RETR_EXTERNAL:
filteredContours = contours
else:
filteredContours = []
h = hierarchy[0]
for component in zip(contours, h):
currentContour = component[0]
currentHierarchy = component[1]
if currentHierarchy[3] < 0:
# Found the outermost parent component
filteredContours.append(currentContour)
print('Contours filtered. Input %d Output %d' % (len(contours), len(filteredContours)))
time.sleep(5)
for cnt in filteredContours:
cnt_len = cv2.arcLength(cnt, True)
cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True)
cnt_len = len(cnt)
cnt_area = cv2.contourArea(cnt)
cnt_isConvex = cv2.isContourConvex(cnt)
if cnt_len == 4 and (cnt_area > self.area_min and cnt_area < self.area_max) and cnt_isConvex:
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 < self.cos_limit :
sq = Square(cnt, cnt_area, cnt_isConvex, max_cos)
self.squares.append(sq)
else:
#print('dropped a square with max_cos %f' % max_cos)
pass
found[thrs] = len(self.squares)
print('Found %d quadrilaterals with threshold %d' % (len(self.squares), thrs))
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