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OpenCVstereomatching代码matlab实现视差显示

原作者: [db:作者] 来自: [db:来源] 收藏 邀请

之前在网上也没有现成的代码，现在把库中的sample拿出来，分享下

 

结合大牛的博客，好好学习下：

 

http://blog.csdn.net/chenyusiyuan/article/details/5967291

 

 

/*
 *  stereo_match.cpp
 *  calibration
 *
 *  Created by Victor  Eruhimov on 1/18/10.
 *  Copyright 2010 Argus Corp. All rights reserved.
 *
 */

#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/contrib/contrib.hpp"

#include <stdio.h>

using namespace cv;

static void print_help()
{
    printf("\nDemo stereo matching converting L and R images into disparity and point clouds\n");
    printf("\nUsage: stereo_match <left_image> <right_image> [--algorithm=bm|sgbm|hh|var] [--blocksize=<block_size>]\n"
           "[--max-disparity=<max_disparity>] [--scale=scale_factor>] [-i <intrinsic_filename>] [-e <extrinsic_filename>]\n"
           "[--no-display] [-o <disparity_image>] [-p <point_cloud_file>]\n");
}

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)
{
    const char* algorithm_opt = "--algorithm=";
    const char* maxdisp_opt = "--max-disparity=";
    const char* blocksize_opt = "--blocksize=";
    const char* nodisplay_opt = "--no-display";
    const char* scale_opt = "--scale=";

    if(argc < 3)
    {
        print_help();
        return 0;
    }
    const char* img1_filename = 0;
    const char* img2_filename = 0;
    const char* intrinsic_filename = 0;
    const char* extrinsic_filename = 0;
    const char* disparity_filename = 0;
    const char* point_cloud_filename = 0;

    enum { STEREO_BM=0, STEREO_SGBM=1, STEREO_HH=2, STEREO_VAR=3 };
    int alg = STEREO_SGBM;
    int SADWindowSize = 0, numberOfDisparities = 0;
    bool no_display = false;
    float scale = 1.f;

    StereoBM bm;
    StereoSGBM sgbm;
    StereoVar var;

    for( int i = 1; i < argc; i++ )
    {
        if( argv[i][0] != '-' )
        {
            if( !img1_filename )
                img1_filename = argv[i];
            else
                img2_filename = argv[i];
        }
        else if( strncmp(argv[i], algorithm_opt, strlen(algorithm_opt)) == 0 )
        {
            char* _alg = argv[i] + strlen(algorithm_opt);
            alg = strcmp(_alg, "bm") == 0 ? STEREO_BM :
                  strcmp(_alg, "sgbm") == 0 ? STEREO_SGBM :
                  strcmp(_alg, "hh") == 0 ? STEREO_HH :
                  strcmp(_alg, "var") == 0 ? STEREO_VAR : -1;
            if( alg < 0 )
            {
                printf("Command-line parameter error: Unknown stereo algorithm\n\n");
                print_help();
                return -1;
            }
        }
        else if( strncmp(argv[i], maxdisp_opt, strlen(maxdisp_opt)) == 0 )
        {
            if( sscanf( argv[i] + strlen(maxdisp_opt), "%d", &numberOfDisparities ) != 1 ||
                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();
                return -1;
            }
        }
        else if( strncmp(argv[i], blocksize_opt, strlen(blocksize_opt)) == 0 )
        {
            if( sscanf( argv[i] + strlen(blocksize_opt), "%d", &SADWindowSize ) != 1 ||
                SADWindowSize < 1 || SADWindowSize % 2 != 1 )
            {
                printf("Command-line parameter error: The block size (--blocksize=<...>) must be a positive odd number\n");
                return -1;
            }
        }
        else if( strncmp(argv[i], scale_opt, strlen(scale_opt)) == 0 )
        {
            if( sscanf( argv[i] + strlen(scale_opt), "%f", &scale ) != 1 || scale < 0 )
            {
                printf("Command-line parameter error: The scale factor (--scale=<...>) must be a positive floating-point number\n");
                return -1;
            }
        }
        else if( strcmp(argv[i], nodisplay_opt) == 0 )
            no_display = true;
        else if( strcmp(argv[i], "-i" ) == 0 )
            intrinsic_filename = argv[++i];
        else if( strcmp(argv[i], "-e" ) == 0 )
            extrinsic_filename = argv[++i];
        else if( strcmp(argv[i], "-o" ) == 0 )
            disparity_filename = argv[++i];
        else if( strcmp(argv[i], "-p" ) == 0 )
            point_cloud_filename = argv[++i];
        else
        {
            printf("Command-line parameter error: unknown option %s\n", argv[i]);
            return -1;
        }
    }

    if( !img1_filename || !img2_filename )
    {
        printf("Command-line parameter error: both left and right images must be specified\n");
        return -1;
    }

    if( (intrinsic_filename != 0) ^ (extrinsic_filename != 0) )
    {
        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 == 0 && point_cloud_filename )
    {
        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( 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 )
    {
        // reading intrinsic parameters
        FileStorage fs(intrinsic_filename, CV_STORAGE_READ);
        if(!fs.isOpened())
        {
            printf("Failed to open file %s\n", intrinsic_filename);
            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, CV_STORAGE_READ);
        if(!fs.isOpened())
        {
            printf("Failed to open file %s\n", extrinsic_filename);
            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.state->roi1 = roi1;
    bm.state->roi2 = roi2;
    bm.state->preFilterCap = 31;
    bm.state->SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 9;
    bm.state->minDisparity = 0;
    bm.state->numberOfDisparities = numberOfDisparities;
    bm.state->textureThreshold = 10;
    bm.state->uniquenessRatio = 15;
    bm.state->speckleWindowSize = 100;
    bm.state->speckleRange = 32;
    bm.state->disp12MaxDiff = 1;

    sgbm.preFilterCap = 63;
    sgbm.SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 3;

    int cn = img1.channels();

    sgbm.P1 = 8*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
    sgbm.P2 = 32*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
    sgbm.minDisparity = 0;
    sgbm.numberOfDisparities = numberOfDisparities;
    sgbm.uniquenessRatio = 10;
    sgbm.speckleWindowSize = bm.state->speckleWindowSize;
    sgbm.speckleRange = bm.state->speckleRange;
    sgbm.disp12MaxDiff = 1;
    sgbm.fullDP = alg == STEREO_HH;

    var.levels = 3;                                 // ignored with USE_AUTO_PARAMS
    var.pyrScale = 0.5;                             // ignored with USE_AUTO_PARAMS
    var.nIt = 25;
    var.minDisp = -numberOfDisparities;
    var.maxDisp = 0;
    var.poly_n = 3;
    var.poly_sigma = 0.0;
    var.fi = 15.0f;
    var.lambda = 0.03f;
    var.penalization = var.PENALIZATION_TICHONOV;   // ignored with USE_AUTO_PARAMS
    var.cycle = var.CYCLE_V;                        // ignored with USE_AUTO_PARAMS
    var.flags = var.USE_SMART_ID | var.USE_AUTO_PARAMS | var.USE_INITIAL_DISPARITY | var.USE_MEDIAN_FILTERING ;

    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();
    if( alg == STEREO_BM )
        bm(img1, img2, disp);
    else if( alg == STEREO_VAR ) {
        var(img1, img2, disp);
    }
    else if( alg == STEREO_SGBM || alg == STEREO_HH )
        sgbm(img1, img2, disp);
    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);
    if( !no_display )
    {
        namedWindow("left", 1);
        imshow("left", img1);
        namedWindow("right", 1);
        imshow("right", img2);
        namedWindow("disparity", 0);
        imshow("disparity", disp8);
        printf("press any key to continue...");
        fflush(stdout);
        waitKey();
        printf("\n");
    }

    if(disparity_filename)
        imwrite(disparity_filename, disp8);

    if(point_cloud_filename)
    {
        printf("storing the point cloud...");
        fflush(stdout);
        Mat xyz;
        reprojectImageTo3D(disp, xyz, Q, true);
        saveXYZ(point_cloud_filename, xyz);
        printf("\n");
    }

    return 0;
}


 

 调试参数：

 

view_l.png view_r.png --algorithm=bm --blocksize=5 --max-disparity=256  --scale=1.0 --no-display -o disparity.bmp

立体匹配效果：

 

 

根据大牛的代码增加一个函数：实现视差数据保存成txt又matlab显示

 

void saveDisp(const char* filename, const Mat& mat)		
{
	FILE* fp = fopen(filename, "wt");
	fprintf(fp, "%02d\n", mat.rows);
	fprintf(fp, "%02d\n", mat.cols);
	for(int y = 0; y < mat.rows; y++)
	{
		for(int x = 0; x < mat.cols; x++)
		{
			int disp = (int)mat.at<float>(y, x);	// 这里视差矩阵是CV_16S 格式的，故用 short 类型读取
			fprintf(fp, "%d\n", disp);			// 若视差矩阵是 CV_32F 格式，则用 float 类型读取
		}
		//fprintf(fp, "\n");
	}
	fclose(fp);
}

 

matlab代码：

 

function img = txt2img(filename)
data = importdata(filename);
r = data(1);    % 行数
c = data(2);    % 列数
disp = data(3:end); % 视差
vmin = min(disp);
vmax = max(disp);
disp = reshape(disp, [c,r])'; % 将列向量形式的 disp 重构为 矩阵形式
%  OpenCV 是行扫描存储图像，Matlab 是列扫描存储图像
%  故对 disp 的重新排列是首先变成 c 行 r 列的矩阵，然后再转置回 r 行 c 列
img = uint8( 255 * ( disp - vmin ) / ( vmax - vmin ) );
mesh(disp);
set(gca,'YDir','reverse');  % 通过 mesh 方式绘图时，需倒置 Y 轴方向
axis tight; % 使坐标轴显示范围与数据范围相贴合，去除空白显示区


 

实现效果：

 

 


 

 

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