contours = cv.FindContours(marker_mask, storage, cv.CV_RETR_CCOMP,
cv.CV_CHAIN_APPROX_SIMPLE)
def contour_iterator(contour):
while contour:
yield contour
contour = contour.h_next()
cv.Zero(markers)
comp_count = 0
for c in contour_iterator(contours):
cv.DrawContours(markers, c, cv.ScalarAll(comp_count + 1),
cv.ScalarAll(comp_count + 1), -1, -1, 8)
comp_count += 1
cv.Watershed(img0, markers)
cv.Set(wshed, cv.ScalarAll(255))
# paint the watershed image
color_tab = [
(cv.RandInt(rng) % 180 + 50, cv.RandInt(rng) % 180 + 50,
cv.RandInt(rng) % 180 + 50) for i in range(comp_count)
]
for j in range(markers.height):
for i in range(markers.width):
idx = markers[j, i]
if idx != -1:
wshed[j, i] = color_tab[int(idx - 1)]
cv.AddWeighted(wshed, 0.5, img_gray, 0.5, 0, wshed)
# markers are differentiated by colour
# background marker, identified by colour (80, 80, 80)
cv.Circle(imgMarkers, (60, 60), 3, (80, 80, 80), -1)
# upper circle marker, identified by colour (160, 160, 160)
cv.Circle(imgMarkers, (180, 180), 3, (160, 160, 160), -1)
# lower circle marker, identified by colour (240, 240, 240)
cv.Circle(imgMarkers, (320, 320), 3, (240, 240, 240), -1)
# seed imgWatershed with the markers for the background, upper circle, and lower circle
cv.ConvertScale(imgMarkers, imgWatershed, 1)
# this is where the magic happens...
cv.Watershed(imgOriginal, imgWatershed)
cv.ShowImage("imgOriginal", imgOriginal)
cv.ShowImage("imgMarkers", imgMarkers)
# cv.IPL_DEPTH_32S images are divided by 256 on display so scale accordingly
cv.ConvertScale(imgWatershed, imgWatershed, 256)
cv.ShowImage("imgWatershed", imgWatershed)
Esc = 27
while True:
keyPressed = cv.WaitKey(0) % 0x100
if ((keyPressed == Esc) or (keyPressed == ord('q'))):