最新最靠谱-OpenCV双目摄像头例程使用教程-vs2022/opencv4.55

引言：

最近做双目测距项目，网上一大堆代码，放vs里各种错，仔细看下opencv官方自带双目标定与测距例程，还是官方的程序靠谱，在这里把使用方法记录下来，避免后人入坑，大家熟悉以后直接在例程基础上改就行，以免被网上的垃圾程序浪费时间！

1.开发环境：win10 / vs2022 / opencv4.5.5（vs-opencv自行百度，每个版本文件夹都有对应例程）
2.项目位置：opencv\sources\samples\cpp\stereo_calib.cpp||stereo_match.cpp
3.运行流程：复制到vs工程中直接在代码中修改CommandLineParser，在||之间填入参数后直接调试
关于：CommandLineParser 请自行百度，当初拿到例程不会用研究了半天，就是要通过这个函数把相应的参数传给程序才能启动，简略说明在开头注释中：
4.注意事项：全部为opencv原封代码，仅修改开头注释中，可直接去opencv官网下载，有不懂的地方欢迎留言

/* 
  cv::CommandLineParser parser(argc, argv, "{w|9|}{h|6|}{s|1.0|}{nr||}{help||}    {@input|stereo_calib.xml|}"); 
  w:棋盘横向交点个数
  h:棋盘纵向交点个数
  s:棋盘宽度，单位厘米
  input:图片路径存放位置
  注意：直接在||之间填入参数启动，例如：w为10，h为8，宽度为2.5cm则{w|10|}{h|8|}{s|2.5|}
  以此类推，弄清楚每个参数的意义，不填的直接空着
*/
#include "opencv2/calib3d.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"

#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 

using namespace cv;
using namespace std;

static int print_help(char** argv)
{
    cout <<
            " Given a list of chessboard images, the number of corners (nx, ny)\n"
            " on the chessboards, and a flag: useCalibrated for \n"
            "   calibrated (0) or\n"
            "   uncalibrated \n"
            "     (1: use stereoCalibrate(), 2: compute fundamental\n"
            "         matrix separately) stereo. \n"
            " Calibrate the cameras and display the\n"
            " rectified results along with the computed disparity images.   \n" << endl;
    cout << "Usage:\n " << argv[0] << " -w= -h= -s= \n" << endl;
    return 0;
}


static void
StereoCalib(const vector<string>& imagelist, Size boardSize, float squareSize, bool displayCorners = false, bool useCalibrated=true, bool showRectified=true)
{
    if( imagelist.size() % 2 != 0 )
    {
        cout << "Error: the image list contains odd (non-even) number of elements\n";
        return;
    }

    const int maxScale = 2;
    // ARRAY AND VECTOR STORAGE:

    vector<vector<Point2f> > imagePoints[2];
    vector<vector<Point3f> > objectPoints;
    Size imageSize;

    int i, j, k, nimages = (int)imagelist.size()/2;

    imagePoints[0].resize(nimages);
    imagePoints[1].resize(nimages);
    vector<string> goodImageList;

    for( i = j = 0; i < nimages; i++ )
    {
        for( k = 0; k < 2; k++ )
        {
            const string& filename = imagelist[i*2+k];
            Mat img = imread(filename, 0);
            if(img.empty())
                break;
            if( imageSize == Size() )
                imageSize = img.size();
            else if( img.size() != imageSize )
            {
                cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n";
                break;
            }
            bool found = false;
            vector<Point2f>& corners = imagePoints[k][j];
            for( int scale = 1; scale <= maxScale; scale++ )
            {
                Mat timg;
                if( scale == 1 )
                    timg = img;
                else
                    resize(img, timg, Size(), scale, scale, INTER_LINEAR_EXACT);
                found = findChessboardCorners(timg, boardSize, corners,
                    CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_NORMALIZE_IMAGE);
                if( found )
                {
                    if( scale > 1 )
                    {
                        Mat cornersMat(corners);
                        cornersMat *= 1./scale;
                    }
                    break;
                }
            }
            if( displayCorners )
            {
                cout << filename << endl;
                Mat cimg, cimg1;
                cvtColor(img, cimg, COLOR_GRAY2BGR);
                drawChessboardCorners(cimg, boardSize, corners, found);
                double sf = 640./MAX(img.rows, img.cols);
                resize(cimg, cimg1, Size(), sf, sf, INTER_LINEAR_EXACT);
                imshow("corners", cimg1);
                char c = (char)waitKey(500);
                if( c == 27 || c == 'q' || c == 'Q' ) //Allow ESC to quit
                    exit(-1);
            }
            else
                putchar('.');
            if( !found )
                break;
            cornerSubPix(img, corners, Size(11,11), Size(-1,-1),
                         TermCriteria(TermCriteria::COUNT+TermCriteria::EPS,
                                      30, 0.01));
        }
        if( k == 2 )
        {
            goodImageList.push_back(imagelist[i*2]);
            goodImageList.push_back(imagelist[i*2+1]);
            j++;
        }
    }
    cout << j << " pairs have been successfully detected.\n";
    nimages = j;
    if( nimages < 2 )
    {
        cout << "Error: too little pairs to run the calibration\n";
        return;
    }

    imagePoints[0].resize(nimages);
    imagePoints[1].resize(nimages);
    objectPoints.resize(nimages);

    for( i = 0; i < nimages; i++ )
    {
        for( j = 0; j < boardSize.height; j++ )
            for( k = 0; k < boardSize.width; k++ )
                objectPoints[i].push_back(Point3f(k*squareSize, j*squareSize, 0));
    }

    cout << "Running stereo calibration ...\n";

    Mat cameraMatrix[2], distCoeffs[2];
    cameraMatrix[0] = initCameraMatrix2D(objectPoints,imagePoints[0],imageSize,0);
    cameraMatrix[1] = initCameraMatrix2D(objectPoints,imagePoints[1],imageSize,0);
    Mat R, T, E, F;

    double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
                    cameraMatrix[0], distCoeffs[0],
                    cameraMatrix[1], distCoeffs[1],
                    imageSize, R, T, E, F,
                    CALIB_FIX_ASPECT_RATIO +
                    CALIB_ZERO_TANGENT_DIST +
                    CALIB_USE_INTRINSIC_GUESS +
                    CALIB_SAME_FOCAL_LENGTH +
                    CALIB_RATIONAL_MODEL +
                    CALIB_FIX_K3 + CALIB_FIX_K4 + CALIB_FIX_K5,
                    TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, 1e-5) );
    cout << "done with RMS error=" << rms << endl;

// CALIBRATION QUALITY CHECK
// because the output fundamental matrix implicitly
// includes all the output information,
// we can check the quality of calibration using the
// epipolar geometry constraint: m2^t*F*m1=0
    double err = 0;
    int npoints = 0;
    vector<Vec3f> lines[2];
    for( i = 0; i < nimages; i++ )
    {
        int npt = (int)imagePoints[0][i].size();
        Mat imgpt[2];
        for( k = 0; k < 2; k++ )
        {
            imgpt[k] = Mat(imagePoints[k][i]);
            undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]);
            computeCorrespondEpilines(imgpt[k], k+1, F, lines[k]);
        }
        for( j = 0; j < npt; j++ )
        {
            double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] +
                                imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) +
                           fabs(imagePoints[1][i][j].x*lines[0][j][0] +
                                imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]);
            err += errij;
        }
        npoints += npt;
    }
    cout << "average epipolar err = " <<  err/npoints << endl;

    // save intrinsic parameters
    FileStorage fs("intrinsics.yml", FileStorage::WRITE);
    if( fs.isOpened() )
    {
        fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0] <<
            "M2" << cameraMatrix[1] << "D2" << distCoeffs[1];
        fs.release();
    }
    else
        cout << "Error: can not save the intrinsic parameters\n";

    Mat R1, R2, P1, P2, Q;
    Rect validRoi[2];

    stereoRectify(cameraMatrix[0], distCoeffs[0],
                  cameraMatrix[1], distCoeffs[1],
                  imageSize, R, T, R1, R2, P1, P2, Q,
                  CALIB_ZERO_DISPARITY, 1, imageSize, &validRoi[0], &validRoi[1]);

    fs.open("extrinsics.yml", FileStorage::WRITE);
    if( fs.isOpened() )
    {
        fs << "R" << R << "T" << T << "R1" << R1 << "R2" << R2 << "P1" << P1 << "P2" << P2 << "Q" << Q;
        fs.release();
    }
    else
        cout << "Error: can not save the extrinsic parameters\n";

    // OpenCV can handle left-right
    // or up-down camera arrangements
    bool isVerticalStereo = fabs(P2.at<double>(1, 3)) > fabs(P2.at<double>(0, 3));

// COMPUTE AND DISPLAY RECTIFICATION
    if( !showRectified )
        return;

    Mat rmap[2][2];
// IF BY CALIBRATED (BOUGUET'S METHOD)
    if( useCalibrated )
    {
        // we already computed everything
    }
// OR ELSE HARTLEY'S METHOD
    else
 // use intrinsic parameters of each camera, but
 // compute the rectification transformation directly
 // from the fundamental matrix
    {
        vector<Point2f> allimgpt[2];
        for( k = 0; k < 2; k++ )
        {
            for( i = 0; i < nimages; i++ )
                std::copy(imagePoints[k][i].begin(), imagePoints[k][i].end(), back_inserter(allimgpt[k]));
        }
        F = findFundamentalMat(Mat(allimgpt[0]), Mat(allimgpt[1]), FM_8POINT, 0, 0);
        Mat H1, H2;
        stereoRectifyUncalibrated(Mat(allimgpt[0]), Mat(allimgpt[1]), F, imageSize, H1, H2, 3);

        R1 = cameraMatrix[0].inv()*H1*cameraMatrix[0];
        R2 = cameraMatrix[1].inv()*H2*cameraMatrix[1];
        P1 = cameraMatrix[0];
        P2 = cameraMatrix[1];
    }

    //Precompute maps for cv::remap()
    initUndistortRectifyMap(cameraMatrix[0], distCoeffs[0], R1, P1, imageSize, CV_16SC2, rmap[0][0], rmap[0][1]);
    initUndistortRectifyMap(cameraMatrix[1], distCoeffs[1], R2, P2, imageSize, CV_16SC2, rmap[1][0], rmap[1][1]);

    Mat canvas;
    double sf;
    int w, h;
    if( !isVerticalStereo )
    {
        sf = 600./MAX(imageSize.width, imageSize.height);
        w = cvRound(imageSize.width*sf);
        h = cvRound(imageSize.height*sf);
        canvas.create(h, w*2, CV_8UC3);
    }
    else
    {
        sf = 300./MAX(imageSize.width, imageSize.height);
        w = cvRound(imageSize.width*sf);
        h = cvRound(imageSize.height*sf);
        canvas.create(h*2, w, CV_8UC3);
    }

    for( i = 0; i < nimages; i++ )
    {
        for( k = 0; k < 2; k++ )
        {
            Mat img = imread(goodImageList[i*2+k], 0), rimg, cimg;
            remap(img, rimg, rmap[k][0], rmap[k][1], INTER_LINEAR);
            cvtColor(rimg, cimg, COLOR_GRAY2BGR);
            Mat canvasPart = !isVerticalStereo ? canvas(Rect(w*k, 0, w, h)) : canvas(Rect(0, h*k, w, h));
            resize(cimg, canvasPart, canvasPart.size(), 0, 0, INTER_AREA);
            if( useCalibrated )
            {
                Rect vroi(cvRound(validRoi[k].x*sf), cvRound(validRoi[k].y*sf),
                          cvRound(validRoi[k].width*sf), cvRound(validRoi[k].height*sf));
                rectangle(canvasPart, vroi, Scalar(0,0,255), 3, 8);
            }
        }

        if( !isVerticalStereo )
            for( j = 0; j < canvas.rows; j += 16 )
                line(canvas, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
        else
            for( j = 0; j < canvas.cols; j += 16 )
                line(canvas, Point(j, 0), Point(j, canvas.rows), Scalar(0, 255, 0), 1, 8);
        imshow("rectified", canvas);
        char c = (char)waitKey();
        if( c == 27 || c == 'q' || c == 'Q' )
            break;
    }
}


static bool readStringList( const string& filename, vector<string>& l )
{
    l.resize(0);
    FileStorage fs(filename, FileStorage::READ);
    if( !fs.isOpened() )
        return false;
    FileNode n = fs.getFirstTopLevelNode();
    if( n.type() != FileNode::SEQ )
        return false;
    FileNodeIterator it = n.begin(), it_end = n.end();
    for( ; it != it_end; ++it )
        l.push_back((string)*it);
    return true;
}

int main(int argc, char** argv)
{
    Size boardSize;
    string imagelistfn;
    bool showRectified;
    cv::CommandLineParser parser(argc, argv, "{w|9|}{h|6|}{s|1.0|}{nr||}{help||}{@input|stereo_calib.xml|}");
    if (parser.has("help"))
        return print_help(argv);
    showRectified = !parser.has("nr");
    imagelistfn = samples::findFile(parser.get<string>("@input"));
    boardSize.width = parser.get<int>("w");
    boardSize.height = parser.get<int>("h");
    float squareSize = parser.get<float>("s");
    if (!parser.check())
    {
        parser.printErrors();
        return 1;
    }
    vector<string> imagelist;
    bool ok = readStringList(imagelistfn, imagelist);
    if(!ok || imagelist.empty())
    {
        cout << "can not open " << imagelistfn << " or the string list is empty" << endl;
        return print_help(argv);
    }

    StereoCalib(imagelist, boardSize, squareSize, false, true, showRectified);
    return 0;
}

/*
  stereo_match.cpp 双目摄像头拍摄图片匹配
  cv::CommandLineParser parser(argc, argv,
  "{@arg1||}{@arg2||}{help h||}{algorithm||}{max-disparity|0|}{blocksize|0|}{no-display||}{color||}{scale|1|}{i||}{e||}{o||}{p||}");
  arg1:左摄像头图片位置
  arg1:左摄像头图片位置
  algorithm:匹配方法
  max-disparity:基本参数，必须是16的倍数，自己试效果
  blocksize:区块大小，奇数1~11，和分辨率有关，640*480实测5左右合适
  注意：直接在||之间填入参数启动，例如：arg1为left.jpg，arg1为right.jpg，方法为sgbm则
  {@arg1|left.jpg|}{@arg2|right.jpg|}{help h||}{algorithm|sgbm|}
  以此类推，弄清楚每个参数的意义，不填的直接空着
 */

#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/core/utility.hpp"

#include 
#include 

using namespace cv;

static void print_help(char** argv)
{
    printf("\nDemo stereo matching converting L and R images into disparity and point clouds\n");
    printf("\nUsage: %s   [--algorithm=bm|sgbm|hh|hh4|sgbm3way] [--blocksize=]\n"
           "[--max-disparity=] [--scale=scale_factor>] [-i=] [-e=]\n"
           "[--no-display] [--color] [-o=] [-p=]\n", argv[0]);
}

static void saveXYZ(const char* filename, const Mat& mat)
{
    const double max_z = 1.0e4;
    FILE* fp = fopen(filename, "wt");
    for(int y = 0; y < mat.rows; y++)
    {
        for(int x = 0; x < mat.cols; x++)
        {
            Vec3f point = mat.at<Vec3f>(y, x);
            if(fabs(point[2] - max_z) < FLT_EPSILON || fabs(point[2]) > max_z) continue;
            fprintf(fp, "%f %f %f\n", point[0], point[1], point[2]);
        }
    }
    fclose(fp);
}

int main(int argc, char** argv)
{
    std::string img1_filename = "";
    std::string img2_filename = "";
    std::string intrinsic_filename = "";
    std::string extrinsic_filename = "";
    std::string disparity_filename = "";
    std::string point_cloud_filename = "";

    enum { STEREO_BM=0, STEREO_SGBM=1, STEREO_HH=2, STEREO_VAR=3, STEREO_3WAY=4, STEREO_HH4=5 };
    int alg = STEREO_SGBM;
    int SADWindowSize, numberOfDisparities;
    bool no_display;
    bool color_display;
    float scale;

    Ptr<StereoBM> bm = StereoBM::create(16,9);
    Ptr<StereoSGBM> sgbm = StereoSGBM::create(0,16,3);
    cv::CommandLineParser parser(argc, argv,
        "{@arg1||}{@arg2||}{help h||}{algorithm||}{max-disparity|0|}{blocksize|0|}{no-display||}{color||}{scale|1|}{i||}{e||}{o||}{p||}");
    if(parser.has("help"))
    {
        print_help(argv);
        return 0;
    }
    img1_filename = samples::findFile(parser.get<std::string>(0));
    img2_filename = samples::findFile(parser.get<std::string>(1));
    if (parser.has("algorithm"))
    {
        std::string _alg = parser.get<std::string>("algorithm");
        alg = _alg == "bm" ? STEREO_BM :
            _alg == "sgbm" ? STEREO_SGBM :
            _alg == "hh" ? STEREO_HH :
            _alg == "var" ? STEREO_VAR :
            _alg == "hh4" ? STEREO_HH4 :
            _alg == "sgbm3way" ? STEREO_3WAY : -1;
    }
    numberOfDisparities = parser.get<int>("max-disparity");
    SADWindowSize = parser.get<int>("blocksize");
    scale = parser.get<float>("scale");
    no_display = parser.has("no-display");
    color_display = parser.has("color");
    if( parser.has("i") )
        intrinsic_filename = parser.get<std::string>("i");
    if( parser.has("e") )
        extrinsic_filename = parser.get<std::string>("e");
    if( parser.has("o") )
        disparity_filename = parser.get<std::string>("o");
    if( parser.has("p") )
        point_cloud_filename = parser.get<std::string>("p");
    if (!parser.check())
    {
        parser.printErrors();
        return 1;
    }
    if( alg < 0 )
    {
        printf("Command-line parameter error: Unknown stereo algorithm\n\n");
        print_help(argv);
        return -1;
    }
    if ( numberOfDisparities < 1 || numberOfDisparities % 16 != 0 )
    {
        printf("Command-line parameter error: The max disparity (--maxdisparity=<...>) must be a positive integer divisible by 16\n");
        print_help(argv);
        return -1;
    }
    if (scale < 0)
    {
        printf("Command-line parameter error: The scale factor (--scale=<...>) must be a positive floating-point number\n");
        return -1;
    }
    if (SADWindowSize < 1 || SADWindowSize % 2 != 1)
    {
        printf("Command-line parameter error: The block size (--blocksize=<...>) must be a positive odd number\n");
        return -1;
    }
    if( img1_filename.empty() || img2_filename.empty() )
    {
        printf("Command-line parameter error: both left and right images must be specified\n");
        return -1;
    }
    if( (!intrinsic_filename.empty()) ^ (!extrinsic_filename.empty()) )
    {
        printf("Command-line parameter error: either both intrinsic and extrinsic parameters must be specified, or none of them (when the stereo pair is already rectified)\n");
        return -1;
    }

    if( extrinsic_filename.empty() && !point_cloud_filename.empty() )
    {
        printf("Command-line parameter error: extrinsic and intrinsic parameters must be specified to compute the point cloud\n");
        return -1;
    }

    int color_mode = alg == STEREO_BM ? 0 : -1;
    Mat img1 = imread(img1_filename, color_mode);
    Mat img2 = imread(img2_filename, color_mode);

    if (img1.empty())
    {
        printf("Command-line parameter error: could not load the first input image file\n");
        return -1;
    }
    if (img2.empty())
    {
        printf("Command-line parameter error: could not load the second input image file\n");
        return -1;
    }

    if (scale != 1.f)
    {
        Mat temp1, temp2;
        int method = scale < 1 ? INTER_AREA : INTER_CUBIC;
        resize(img1, temp1, Size(), scale, scale, method);
        img1 = temp1;
        resize(img2, temp2, Size(), scale, scale, method);
        img2 = temp2;
    }

    Size img_size = img1.size();

    Rect roi1, roi2;
    Mat Q;

    if( !intrinsic_filename.empty() )
    {
        // reading intrinsic parameters
        FileStorage fs(intrinsic_filename, FileStorage::READ);
        if(!fs.isOpened())
        {
            printf("Failed to open file %s\n", intrinsic_filename.c_str());
            return -1;
        }

        Mat M1, D1, M2, D2;
        fs["M1"] >> M1;
        fs["D1"] >> D1;
        fs["M2"] >> M2;
        fs["D2"] >> D2;

        M1 *= scale;
        M2 *= scale;

        fs.open(extrinsic_filename, FileStorage::READ);
        if(!fs.isOpened())
        {
            printf("Failed to open file %s\n", extrinsic_filename.c_str());
            return -1;
        }

        Mat R, T, R1, P1, R2, P2;
        fs["R"] >> R;
        fs["T"] >> T;

        stereoRectify( M1, D1, M2, D2, img_size, R, T, R1, R2, P1, P2, Q, CALIB_ZERO_DISPARITY, -1, img_size, &roi1, &roi2 );

        Mat map11, map12, map21, map22;
        initUndistortRectifyMap(M1, D1, R1, P1, img_size, CV_16SC2, map11, map12);
        initUndistortRectifyMap(M2, D2, R2, P2, img_size, CV_16SC2, map21, map22);

        Mat img1r, img2r;
        remap(img1, img1r, map11, map12, INTER_LINEAR);
        remap(img2, img2r, map21, map22, INTER_LINEAR);

        img1 = img1r;
        img2 = img2r;
    }

    numberOfDisparities = numberOfDisparities > 0 ? numberOfDisparities : ((img_size.width/8) + 15) & -16;

    bm->setROI1(roi1);
    bm->setROI2(roi2);
    bm->setPreFilterCap(31);
    bm->setBlockSize(SADWindowSize > 0 ? SADWindowSize : 9);
    bm->setMinDisparity(0);
    bm->setNumDisparities(numberOfDisparities);
    bm->setTextureThreshold(10);
    bm->setUniquenessRatio(15);
    bm->setSpeckleWindowSize(100);
    bm->setSpeckleRange(32);
    bm->setDisp12MaxDiff(1);

    sgbm->setPreFilterCap(63);
    int sgbmWinSize = SADWindowSize > 0 ? SADWindowSize : 3;
    sgbm->setBlockSize(sgbmWinSize);

    int cn = img1.channels();

    sgbm->setP1(8*cn*sgbmWinSize*sgbmWinSize);
    sgbm->setP2(32*cn*sgbmWinSize*sgbmWinSize);
    sgbm->setMinDisparity(0);
    sgbm->setNumDisparities(numberOfDisparities);
    sgbm->setUniquenessRatio(10);
    sgbm->setSpeckleWindowSize(100);
    sgbm->setSpeckleRange(32);
    sgbm->setDisp12MaxDiff(1);
    if(alg==STEREO_HH)
        sgbm->setMode(StereoSGBM::MODE_HH);
    else if(alg==STEREO_SGBM)
        sgbm->setMode(StereoSGBM::MODE_SGBM);
    else if(alg==STEREO_HH4)
        sgbm->setMode(StereoSGBM::MODE_HH4);
    else if(alg==STEREO_3WAY)
        sgbm->setMode(StereoSGBM::MODE_SGBM_3WAY);

    Mat disp, disp8;
    //Mat img1p, img2p, dispp;
    //copyMakeBorder(img1, img1p, 0, 0, numberOfDisparities, 0, IPL_BORDER_REPLICATE);
    //copyMakeBorder(img2, img2p, 0, 0, numberOfDisparities, 0, IPL_BORDER_REPLICATE);

    int64 t = getTickCount();
    float disparity_multiplier = 1.0f;
    if( alg == STEREO_BM )
    {
        bm->compute(img1, img2, disp);
        if (disp.type() == CV_16S)
            disparity_multiplier = 16.0f;
    }
    else if( alg == STEREO_SGBM || alg == STEREO_HH || alg == STEREO_HH4 || alg == STEREO_3WAY )
    {
        sgbm->compute(img1, img2, disp);
        if (disp.type() == CV_16S)
            disparity_multiplier = 16.0f;
    }
    t = getTickCount() - t;
    printf("Time elapsed: %fms\n", t*1000/getTickFrequency());

    //disp = dispp.colRange(numberOfDisparities, img1p.cols);
    if( alg != STEREO_VAR )
        disp.convertTo(disp8, CV_8U, 255/(numberOfDisparities*16.));
    else
        disp.convertTo(disp8, CV_8U);

    Mat disp8_3c;
    if (color_display)
        cv::applyColorMap(disp8, disp8_3c, COLORMAP_TURBO);

    if(!disparity_filename.empty())
        imwrite(disparity_filename, color_display ? disp8_3c : disp8);

    if(!point_cloud_filename.empty())
    {
        printf("storing the point cloud...");
        fflush(stdout);
        Mat xyz;
        Mat floatDisp;
        disp.convertTo(floatDisp, CV_32F, 1.0f / disparity_multiplier);
        reprojectImageTo3D(floatDisp, xyz, Q, true);
        saveXYZ(point_cloud_filename.c_str(), xyz);
        printf("\n");
    }

    if( !no_display )
    {
        std::ostringstream oss;
        oss << "disparity  " << (alg==STEREO_BM ? "bm" :
                                 alg==STEREO_SGBM ? "sgbm" :
                                 alg==STEREO_HH ? "hh" :
                                 alg==STEREO_VAR ? "var" :
                                 alg==STEREO_HH4 ? "hh4" :
                                 alg==STEREO_3WAY ? "sgbm3way" : "");
        oss << "  blocksize:" << (alg==STEREO_BM ? SADWindowSize : sgbmWinSize);
        oss << "  max-disparity:" << numberOfDisparities;
        std::string disp_name = oss.str();

        namedWindow("left", cv::WINDOW_NORMAL);
        imshow("left", img1);
        namedWindow("right", cv::WINDOW_NORMAL);
        imshow("right", img2);
        namedWindow(disp_name, cv::WINDOW_AUTOSIZE);
        imshow(disp_name, color_display ? disp8_3c : disp8);

        printf("press ESC key or CTRL+C to close...");
        fflush(stdout);
        printf("\n");
        while(1)
        {
            if(waitKey() == 27) //ESC (prevents closing on actions like taking screenshots)
                break;
        }
    }

    return 0;
}