def meanshiftUsingIntensityAndLocation(path):
im = cv2.LoadImageM(path, cv2.CV_LOAD_IMAGE_GRAYSCALE)
#creat a mat from the pixel intensity and its location
mat = cv2.LoadImageM(path)
for i in range(0, im.height):
for j in range(0, im.width):
value = (im[i, j], i, j)
mat[i, j] = value
#print mat[i,j]
(segmentedImage, labelsImage, numberRegions) = pms.segmentMeanShift(mat)
clusters = {}
for i in range(0, labelsImage.height):
for j in range(0, labelsImage.width):
v = labelsImage[i, j]
if v in clusters:
clusters[v].append(im[i, j])
else:
clusters[v] = [im[i, j]]
means = {}
for c in clusters:
means[c] = sum(clusters[c]) / len(clusters[c])
for i in range(0, im.height):
for j in range(0, im.width):
lbl = labelsImage[i, j]
im[i, j] = means[lbl]
print("number of region", numberRegions)
return im
def meanshiftUsingIntensityAndLocation(path):
im = cv.LoadImageM(path,cv.CV_LOAD_IMAGE_GRAYSCALE)
#creat a mat from the pixel intensity and its location
mat = cv.LoadImageM(path)
for i in xrange(0,im.height):
for j in xrange(0,im.width):
value = (im[i,j], i, j)
mat[i,j] = value
#print mat[i,j]
(segmentedImage, labelsImage, numberRegions) = pms.segmentMeanShift(mat)
clusters = {}
for i in xrange(0,labelsImage.height):
for j in xrange(0,labelsImage.width):
v = labelsImage[i,j]
if v in clusters:
clusters[v].append(im[i,j])
else:
clusters[v] = [im[i,j]]
means = {}
for c in clusters:
means[c] = sum(clusters[c])/len(clusters[c])
for i in xrange(0,im.height):
for j in xrange(0,im.width):
lbl = labelsImage[i,j]
im[i,j] = means[lbl]
print "number of region" , numberRegions
return im
def meanshiftUsingYUV(path):
im = cv2.LoadImageM(path)
cv2.CvtColor(im, im, cv2.CV_BGR2YCrCb)
(segmentedImage, labelsImage, numberRegions) = pms.segmentMeanShift(im)
print("number of region", numberRegions)
return segmentedImage
def meanshiftUsingRGB(path):
im = cv2.LoadImageM(path)
(segmentedImage, labelsImage, numberRegions) = pms.segmentMeanShift(im)
print("number of region", numberRegions)
return segmentedImage
def meanshiftUsingIntensity(path):
im = cv2.LoadImageM(path, cv2.CV_LOAD_IMAGE_GRAYSCALE)
(segmentedImage, labelsImage, numberRegions) = pms.segmentMeanShift(im)
print("number of region", numberRegions)
return segmentedImage
def meanshiftUsingYUV(path):
im = cv.LoadImageM(path)
cv.CvtColor(im,im,cv.CV_BGR2YCrCb)
(segmentedImage, labelsImage, numberRegions) = pms.segmentMeanShift(im)
print "number of region" , numberRegions
return segmentedImage
def meanshiftUsingRGB(path):
im = cv.LoadImageM(path)
(segmentedImage, labelsImage, numberRegions) = pms.segmentMeanShift(im)
print "number of region" , numberRegions
return segmentedImage
def meanshiftUsingIntensity(path): im = cv.LoadImageM(path,cv.CV_LOAD_IMAGE_GRAYSCALE) (segmentedImage, labelsImage, numberRegions) = pms.segmentMeanShift(im) print "number of region" , numberRegions return segmentedImage
