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