Open Source Computer Vision Library https://opencv.org/
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'''
Coherence-enhancing filtering example
inspired by
Joachim Weickert "Coherence-Enhancing Shock Filters"
http://www.mia.uni-saarland.de/Publications/weickert-dagm03.pdf
'''
import numpy as np
import cv2, cv
def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
h, w = img.shape[:2]
for i in xrange(iter_n):
print i,
gray = cv2.cvtColor(img, cv.CV_BGR2GRAY)
eigen = cv2.cornerEigenValsAndVecs(gray, str_sigma, 3)
eigen = eigen.reshape(h, w, 3, 2) # [[e1, e2], v1, v2]
x, y = eigen[:,:,1,0], eigen[:,:,1,1]
14 years ago
gxx = cv2.Sobel(gray, cv2.CV_32F, 2, 0, ksize=sigma)
gxy = cv2.Sobel(gray, cv2.CV_32F, 1, 1, ksize=sigma)
gyy = cv2.Sobel(gray, cv2.CV_32F, 0, 2, ksize=sigma)
gvv = x*x*gxx + 2*x*y*gxy + y*y*gyy
m = gvv < 0
ero = cv2.erode(img, None)
dil = cv2.dilate(img, None)
img1 = ero
img1[m] = dil[m]
img = np.uint8(img*(1.0 - blend) + img1*blend)
print 'done'
return img
if __name__ == '__main__':
import sys
try: fn = sys.argv[1]
except: fn = '../cpp/baboon.jpg'
src = cv2.imread(fn)
def nothing(*argv):
pass
def update():
sigma = cv2.getTrackbarPos('sigma', 'control')*2+1
str_sigma = cv2.getTrackbarPos('str_sigma', 'control')*2+1
blend = cv2.getTrackbarPos('blend', 'control') / 10.0
print 'sigma: %d str_sigma: %d blend_coef: %f' % (sigma, str_sigma, blend)
dst = coherence_filter(src, sigma=sigma, str_sigma = str_sigma, blend = blend)
cv2.imshow('dst', dst)
cv2.namedWindow('control', 0)
cv2.createTrackbar('sigma', 'control', 9, 15, nothing)
cv2.createTrackbar('blend', 'control', 7, 10, nothing)
cv2.createTrackbar('str_sigma', 'control', 9, 15, nothing)
print 'Press SPACE to update the image\n'
cv2.imshow('src', src)
update()
while True:
ch = cv2.waitKey()
if ch == ord(' '):
update()
if ch == 27:
break