def approximate(self, image):
resized = cap.doResize(image, 2, cv.CV_INTER_NN)
self.__init__(cv.GetSize(resized))
for x in xrange(self.steps):
if not self.push(resized): break
forLog = cv.CreateImage(cv.GetSize(resized), cv.IPL_DEPTH_8U, 3)
cv.CvtColor(resized, forLog, cv.CV_GRAY2BGR)
self.draw(forLog)
return self.alpha, forLog
def approximate(self, image):
resized = cap.doResize(image, 2, cv.CV_INTER_NN)
self.__init__(cv.GetSize(resized))
for x in xrange(self.steps):
if not self.push(resized): break
forLog = cv.CreateImage(cv.GetSize(resized), cv.IPL_DEPTH_8U, 3)
cv.CvtColor(resized, forLog, cv.CV_GRAY2BGR)
self.draw(forLog)
return self.alpha, forLog
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
image = cap.doResize(image, factor, cv.CV_INTER_CUBIC)
log.log(image)
image = undistort(image)
log.log(image)
cv.Threshold(image, image, 200, 255, cv.CV_THRESH_BINARY)
log.log(image)
image = cap.repaintCCs(image, doRepaint=lambda comp, col: comp[0] <= 10 and col <= 128)
log.log(image)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return image
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
image = cap.doResize(image, factor, cv.CV_INTER_CUBIC)
log.log(image)
image = undistort(image)
log.log(image)
cv.Threshold(image, image, 200, 255, cv.CV_THRESH_BINARY)
log.log(image)
image = cap.repaintCCs(
image, doRepaint=lambda comp, col: comp[0] <= 10 and col <= 128)
log.log(image)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return image
