def sobel():
cv.Smooth(src_image, dst_image, cv.CV_GAUSSIAN, 3, 3)
src_gray = cv.CreateImage((src_image.width, src_image.height), 8, 1)
dst_gray1 = cv.CreateImage((src_image.width, src_image.height), 8, 1)
dst_gray = cv.CreateImage((src_image.width, src_image.height), 8, 1)
cv.CvtColor(src_image, src_gray, cv.CV_BGR2GRAY)
cv.Sobel(src_gray, dst_gray1, 0, 1, 3)
cv.ConvertScaleAbs(dst_gray1, dst_gray1, 1, 0)
cv.Sobel(src_gray, dst_gray, 1, 0, 3)
cv.ConvertScaleAbs(dst_gray, dst_gray, 1, 0)
cv.AddWeighted(dst_gray, 0.5, dst_gray1, 0.5, 0, dst_gray)
cv.NamedWindow("Destination Image")
cv.ShowImage("Destination Image", dst_gray)
cv.WaitKey(0)
def get_gradient_img(self, input_img):
# Generate grad_x and grad_y to use Sobel
grad_x=cv.CreateMat(input_img.height, input_img.width, input_img.type)
grad_y=cv.CreateMat(input_img.height, input_img.width, input_img.type)
abs_grad_x=cv.CreateMat(input_img.height, input_img.width, input_img.type)
abs_grad_y=cv.CreateMat(input_img.height, input_img.width, input_img.type)
grad =cv.CreateMat(input_img.height, input_img.width, input_img.type)
#Gradient X
#Scharr( src_gray, grad_x, ddepth, 1, 0, scale, delta, BORDER_DEFAULT );#for small kernels use this instead of sobel
cv.Sobel( input_img, grad_x, 1, 0)
cv.Abs(grad_x, abs_grad_x )
#Gradient Y
#Scharr( src_gray, grad_y, ddepth, 0, 1, scale, delta, BORDER_DEFAULT );
cv.Sobel( input_img, grad_y, 0, 1)
cv.Abs( grad_y, abs_grad_y )
#/// Total Gradient (approximate)
cv.AddWeighted( abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad )
return grad
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)
cv.ShowImage("watershed transform", wshed)