python+opencv实现高斯平滑滤波

# -*- coding: utf-8 -*- 

import cv2

#两个回调函数
def GaussianBlurSize(GaussianBlur_size):
 global KSIZE 
 KSIZE = GaussianBlur_size * 2 +3
 print KSIZE, SIGMA
 dst = cv2.GaussianBlur(scr, (KSIZE,KSIZE), SIGMA, KSIZE) 
 cv2.imshow(window_name,dst)

def GaussianBlurSigma(GaussianBlur_sigma):
 global SIGMA
 SIGMA = GaussianBlur_sigma/10.0
 print KSIZE, SIGMA
 dst = cv2.GaussianBlur(scr, (KSIZE,KSIZE), SIGMA, KSIZE) 
 cv2.imshow(window_name,dst)

#全局变量
GaussianBlur_size = 1
GaussianBlur_sigma = 15

KSIZE = 1
SIGMA = 15
max_value = 300
max_type = 6
window_name = "GaussianBlurS Demo"
trackbar_size = "Size*2+3"
trackbar_sigema = "Sigma/10"

#读入图片，模式为灰度图，创建窗口
scr = cv2.imread("G:\homework\lena.bmp",0)
cv2.namedWindow(window_name)

#创建滑动条
cv2.createTrackbar( trackbar_size, window_name, \
   GaussianBlur_size, max_type, GaussianBlurSize )
cv2.createTrackbar( trackbar_sigema, window_name, \
   GaussianBlur_sigma, max_value, GaussianBlurSigma )
#初始化
GaussianBlurSize(1)
GaussianBlurSigma(15)

if cv2.waitKey(0) == 27: 
 cv2.destroyAllWindows()

>>> import os
>>> os.chdir("g:\homework")
>>> import GaussianBlur
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