StereoSGBM图像分割

import cv2
import numpy as np
def update():
#定义compute计算视差图函数
    stereo.setBlockSize(cv2.getTrackbarPos('window_size','disparity'))
    stereo.setUniquenessRatio(cv2.getTrackbarPos('uniquenessRatio','disparity'))
    stereo.setSpeckleWindowSize(cv2.getTrackbarPos('speckleWindowSize','disparity'))
    stereo.setSpeckleRange(cv2.getTrackbarPos('speckleRange','disparity'))
    stereo.setDisp12MaxDiff(cv2.getTrackbarPos('disp12MaxDiff','disparity'))
    print('computing disparity...')
    disp=stereo.compute(imgL, imgR).astype(np.float32)/16.0
    cv2.imshow('left',imgL)
    cv2.imshow('right',imgR)
    cv2.imshow('disp',disp)  
    cv2.imshow('disp',(disp-min_disp)/num_disp)
    cv2.imshow('disparity',(disp-min_disp)/num_disp)
if __name__=="__main__":
    window_size=3
    min_disp=16
    num_disp=192-min_disp
    blockSize=window_size
    uniquenessRatio=1
    speckleRange=12
    speckleWindowSize=3
    disp12MaxDiff=200
    P1=600
    P2=2400
    imgL=cv2.imread('C:/Users/xpp/Desktop/Lena.png')#原始图像
    imgR=cv2.imread('C:/Users/xpp/Desktop/Lena.png')#原始图像
    imgL=cv2.resize(imgL,(800,450))
    imgR=cv2.resize(imgR,(800,450))
    print(imgL.shape)
    print(imgR.shape)
    cv2.namedWindow('disparity')
    cv2.createTrackbar('speckleRange','disparity',speckleRange,50,update)
    cv2.createTrackbar('window_size','disparity',window_size,10,update)
    cv2.createTrackbar('speckleWindowSize','disparity',speckleWindowSize,200,update)
    cv2.createTrackbar('uniquenessRatio','disparity',uniquenessRatio,50,update)
    cv2.createTrackbar('disp12MaxDiff','disparity',disp12MaxDiff,250,update)
    stereo=cv2.StereoSGBM_create(
        minDisparity=min_disp,
        numDisparities=num_disp,
        blockSize=window_size,
        uniquenessRatio=uniquenessRatio,
        speckleRange=speckleRange,
        speckleWindowSize=speckleWindowSize,
        disp12MaxDiff=disp12MaxDiff,
        P1=P1,
        P2=P2
    )
    update()
    cv2.waitKey(0)
    cv2.destroyAllWindows()