def findcontours(iplimage, threshold=100):
srcimage = opencv.cvCloneImage(iplimage)
# create the storage area and bw image
grayscale = opencv.cvCreateImage(opencv.cvGetSize(srcimage), 8, 1)
opencv.cvCvtColor(srcimage, grayscale, opencv.CV_BGR2GRAY)
#threshold
opencv.cvThreshold(grayscale, grayscale, threshold, 255, opencv.CV_THRESH_BINARY)
storage = opencv.cvCreateMemStorage(0)
opencv.cvClearMemStorage(storage)
# find the contours
nb_contours, contours = opencv.cvFindContours (grayscale, storage)
# comment this out if you do not want approximation
contours = opencv.cvApproxPoly (contours, opencv.sizeof_CvContour, storage, opencv.CV_POLY_APPROX_DP, 3, 1)
# next line is for ctypes-opencv
#contours = opencv.cvApproxPoly (contours, opencv.sizeof(opencv.CvContour), storage, opencv.CV_POLY_APPROX_DP, 3, 1)
conts = []
for cont in contours.hrange():
points=[]
for pt in cont:
points.append((pt.x,pt.y))
conts.append(points)
opencv.cvReleaseMemStorage(storage)
opencv.cvReleaseImage(srcimage)
opencv.cvReleaseImage(grayscale)
return (nb_contours, conts)
def findcontours(iplimage, threshold=100):
srcimage = opencv.cvCloneImage(iplimage)
# create the storage area and bw image
grayscale = opencv.cvCreateImage(opencv.cvGetSize(srcimage), 8, 1)
opencv.cvCvtColor(srcimage, grayscale, opencv.CV_BGR2GRAY)
# threshold
opencv.cvThreshold(grayscale, grayscale, threshold, 255, opencv.CV_THRESH_BINARY)
storage = opencv.cvCreateMemStorage(0)
opencv.cvClearMemStorage(storage)
# find the contours
nb_contours, contours = opencv.cvFindContours(grayscale, storage)
# comment this out if you do not want approximation
contours = opencv.cvApproxPoly(contours, opencv.sizeof_CvContour, storage, opencv.CV_POLY_APPROX_DP, 3, 1)
# next line is for ctypes-opencv
# contours = opencv.cvApproxPoly (contours, opencv.sizeof(opencv.CvContour), storage, opencv.CV_POLY_APPROX_DP, 3, 1)
conts = []
for cont in contours.hrange():
points = []
for pt in cont:
points.append((pt.x, pt.y))
conts.append(points)
opencv.cvReleaseMemStorage(storage)
opencv.cvReleaseImage(srcimage)
opencv.cvReleaseImage(grayscale)
return (nb_contours, conts)
if time.time() > timer + 0.5:
switchMode(MODE_DETECT_OBSTACLES2)
elif mode == MODE_DETECT_OBSTACLES3:
screen.fill(white)
queryWebcam()
if time.time() > timer + 0.5:
action = ""
switchMode(MODE_READY)
elif mode == MODE_DETECT_OBSTACLES2:
before = time.time()
screen.fill(white)
im = queryWebcam()
opencv.cvCvtColor (im, igray, opencv.CV_BGR2GRAY)
opencv.cvSmooth(igray, igray, opencv.CV_GAUSSIAN, 3, 3)
opencv.cvAdaptiveThreshold(igray, iwhite, 255, opencv.CV_ADAPTIVE_THRESH_GAUSSIAN_C)
num, contours = opencv.cvFindContours (iwhite, stor, opencv.sizeof_CvContour, opencv.CV_RETR_LIST)
opencv.cvCvtColor(iwhite, im, opencv.CV_GRAY2BGR)
staticImage = im
retrieveObstacles(contours)
switchMode(MODE_DETECT_OBSTACLES3)
action = "Detection took: %.2f" % (time.time()-before)
elif mode == MODE_READY:
screen.fill(lgray)
im = queryWebcam()
opencv.cvCvtColor(im, igray, opencv.CV_BGR2GRAY)
opencv.cvSmooth(igray, igray, opencv.CV_GAUSSIAN, 5, 5)
circles = opencv.cvHoughCircles(igray, stor, opencv.CV_HOUGH_GRADIENT, 2, height/4, 200, 150)
