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[原创] 【Khadas VIM试用】双目视觉运行能力测试2

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    [LV.6]常住居民II

    发表于 2018-2-8 21:57:03 |显示全部楼层
    (一)
    根据上一张帖子标定的结果:
    1. Mat cameraMatrixL = (Mat_<double>(3, 3) << 274.07311, 0, 334.46683,
    2.                      0, 273.77609, 230.80436,
    3.                      0, 0, 1);
    4. Mat distCoeffL = (Mat_<double>(5, 1) << -0.21470, 0.03484, -0.00121, -0.00279, 0.00000);

    5. Mat cameraMatrixR = (Mat_<double>(3, 3) << 284.34939, 0, 283.30332,
    6.                      0, 285.84734, 243.33090,
    7.                      0, 0, 1);
    8. Mat distCoeffR = (Mat_<double>(5, 1) << -0.21396, 0.03400, -0.00154, 0.00204, 0.00000);

    9. Mat T = (Mat_<double>(3, 1) << -90.67152, -2.93721, 16.09332);//T平移向量
    10. Mat rec = (Mat_<double>(3, 1) << 0.02428, 0.15673, -0.00825);//rec旋转向量
    11. Mat R;//R 旋转矩阵
    复制代码
    带入双目测距程序里面:
    1. /******************************/
    2. /*        立体匹配和测距        */
    3. /******************************/

    4. #include <opencv2/opencv.hpp>
    5. #include <imgproc.hpp>
    6. #include <iostream>
    7. #include <time.h>

    8. using namespace std;
    9. using namespace cv;

    10. const int imageWidth = 640;                             //摄像头的分辨率
    11. const int imageHeight = 480;
    12. Size imageSize = Size(imageWidth, imageHeight);

    13. Mat rgbImageL, grayImageL;
    14. Mat rgbImageR, grayImageR;
    15. Mat rectifyImageL, rectifyImageR;

    16. Rect validROIL;//图像校正之后,会对图像进行裁剪,这里的validROI就是指裁剪之后的区域
    17. Rect validROIR;

    18. Mat mapLx, mapLy, mapRx, mapRy;     //映射表
    19. Mat Rl, Rr, Pl, Pr, Q;              //校正旋转矩阵R,投影矩阵P 重投影矩阵Q
    20. Mat xyz;              //三维坐标

    21. Point origin;         //鼠标按下的起始点
    22. Rect selection;      //定义矩形选框
    23. bool selectObject = false;    //是否选择对象

    24. int blockSize = 0, uniquenessRatio =0, numDisparities=0;
    25. Ptr<StereoBM> bm = StereoBM::create(16, 9);

    26. /*
    27. 事先标定好的相机的参数
    28. fx 0 cx
    29. 0 fy cy
    30. 0 0  1
    31. */
    32. Mat cameraMatrixL = (Mat_<double>(3, 3) << 274.07311, 0, 334.46683,
    33.                      0, 273.77609, 230.80436,
    34.                      0, 0, 1);
    35. Mat distCoeffL = (Mat_<double>(5, 1) << -0.21470, 0.03484, -0.00121, -0.00279, 0.00000);

    36. Mat cameraMatrixR = (Mat_<double>(3, 3) << 284.34939, 0, 283.30332,
    37.                      0, 285.84734, 243.33090,
    38.                      0, 0, 1);
    39. Mat distCoeffR = (Mat_<double>(5, 1) << -0.21396, 0.03400, -0.00154, 0.00204, 0.00000);

    40. Mat T = (Mat_<double>(3, 1) << -90.67152, -2.93721, 16.09332);//T平移向量
    41. Mat rec = (Mat_<double>(3, 1) << 0.02428, 0.15673, -0.00825);//rec旋转向量
    42. Mat R;//R 旋转矩阵


    43. /*Mat cameraMatrixL = (Mat_<double>(3, 3) << 268.0870787552206, 0, 335.7271612649919,
    44.                      0, 268.0500620563969, 228.181598739472,
    45.                      0, 0, 1);
    46. Mat distCoeffL = (Mat_<double>(5, 1) << -0.2320648740970932, 0.04510313360911739, -9.418532128676933e-05, -0.0008271590194063145, 0);

    47. Mat cameraMatrixR = (Mat_<double>(3, 3) << 268.0746191870755, 0, 313.554845275748,
    48.                      0, 267.8032936757982, 237.0287771634367,
    49.                      0, 0, 1);
    50. Mat distCoeffR = (Mat_<double>(5, 1) << -0.2391280628833069, 0.04899490848168394, 7.734678017422217e-05, 7.975132256511924e-05, 0);

    51. Mat T = (Mat_<double>(3, 1) << -90.67152, -2.93721, 16.09332);//T平移向量
    52. Mat rec = (Mat_<double>(3, 1) << 0.02428, 0.15673, -0.00825);//rec旋转向量
    53. Mat R;//R 旋转矩阵*/

    54. /*****立体匹配*****/
    55. void stereo_match(int,void*)
    56. {
    57.     bm->setBlockSize(2*blockSize+5);     //SAD窗口大小,5~21之间为宜
    58.     bm->setROI1(validROIL);
    59.     bm->setROI2(validROIR);
    60.     bm->setPreFilterCap(31);
    61.     bm->setMinDisparity(0);  //最小视差,默认值为0, 可以是负值,int型
    62.     bm->setNumDisparities(numDisparities*16+16);//视差窗口,即最大视差值与最小视差值之差,窗口大小必须是16的整数倍,int型
    63.     bm->setTextureThreshold(10);
    64.     bm->setUniquenessRatio(uniquenessRatio);//uniquenessRatio主要可以防止误匹配
    65.     bm->setSpeckleWindowSize(100);
    66.     bm->setSpeckleRange(32);
    67.     bm->setDisp12MaxDiff(-1);
    68.     Mat disp, disp8;
    69.     bm->compute(rectifyImageL, rectifyImageR, disp);//输入图像必须为灰度图
    70.     disp.convertTo(disp8, CV_8U, 255 / ((numDisparities * 16 + 16)*16.));//计算出的视差是CV_16S格式
    71.     reprojectImageTo3D(disp, xyz, Q, true); //在实际求距离时,ReprojectTo3D出来的X / W, Y / W, Z / W都要乘以16(也就是W除以16),才能得到正确的三维坐标信息。
    72.     xyz = xyz * 16;

    73.     Point p;
    74.     p.x = 400; p.y = 300;
    75.     cout << "in world coordinate: " << xyz.at<Vec3f>(p) << endl;

    76.     imshow("disparity", disp8);
    77. }

    78. /*****描述:鼠标操作回调*****/
    79. static void onMouse(int event, int x, int y, int, void*)
    80. {
    81.     if (selectObject)
    82.     {
    83.         selection.x = MIN(x, origin.x);
    84.         selection.y = MIN(y, origin.y);
    85.         selection.width = std::abs(x - origin.x);
    86.         selection.height = std::abs(y - origin.y);
    87.     }

    88.     switch (event)
    89.     {
    90.     case EVENT_LBUTTONDOWN:   //鼠标左按钮按下的事件
    91.         origin = Point(x, y);
    92.         selection = Rect(x, y, 0, 0);
    93.         selectObject = true;
    94.         cout << origin <<"in world coordinate is: " << xyz.at<Vec3f>(origin) << endl;
    95.         break;
    96.     case EVENT_LBUTTONUP:    //鼠标左按钮释放的事件
    97.         selectObject = false;
    98.         if (selection.width > 0 && selection.height > 0)
    99.         break;
    100.     }
    101. }


    102. /*****主函数*****/
    103. int main()
    104. {
    105.     int counter_frame = 0;

    106.     /*
    107.     立体校正
    108.     */
    109.     Rodrigues(rec, R); //Rodrigues变换
    110.     stereoRectify(cameraMatrixL, distCoeffL, cameraMatrixR, distCoeffR, imageSize, R, T, Rl, Rr, Pl, Pr, Q, CALIB_ZERO_DISPARITY,
    111.         0, imageSize, &validROIL, &validROIR);
    112.     initUndistortRectifyMap(cameraMatrixL, distCoeffL, Rl, Pr, imageSize, CV_32FC1, mapLx, mapLy);
    113.     initUndistortRectifyMap(cameraMatrixR, distCoeffR, Rr, Pr, imageSize, CV_32FC1, mapRx, mapRy);

    114.     VideoCapture left("Left.avi");
    115.     VideoCapture right("Right.avi");

    116.     Mat left_frame,right_frame;

    117.     if(!left.isOpened() || !right.isOpened())
    118.     {
    119.     cout<<"open error"<<endl;
    120.     return -1;
    121.     }

    122.     clock_t start_clock,end_clock;
    123.     start_clock = clock();


    124.     while(1)
    125.     {

    126.         if(counter_frame++ >= 30)
    127.         {
    128.             counter_frame = 0;
    129.             end_clock = clock();
    130.             std::cout << end_clock - start_clock << std::endl;
    131.             start_clock = clock();
    132.         }
    133.         /*
    134.         读取图片
    135.         */
    136.         left >> rgbImageL;
    137.         right >> rgbImageR;

    138.         cvtColor(rgbImageL, grayImageL, CV_BGR2GRAY);
    139.         cvtColor(rgbImageR, grayImageR, CV_BGR2GRAY);

    140.         imshow("ImageL Before Rectify", grayImageL);
    141.         imshow("ImageR Before Rectify", grayImageR);

    142.         /*
    143.         经过remap之后,左右相机的图像已经共面并且行对准了
    144.         */
    145.         remap(grayImageL, rectifyImageL, mapLx, mapLy, INTER_LINEAR);
    146.         remap(grayImageR, rectifyImageR, mapRx, mapRy, INTER_LINEAR);

    147.         /*
    148.         把校正结果显示出来
    149.         */
    150.         Mat rgbRectifyImageL, rgbRectifyImageR;
    151.         cvtColor(rectifyImageL, rgbRectifyImageL, CV_GRAY2BGR);  //伪彩色图
    152.         cvtColor(rectifyImageR, rgbRectifyImageR, CV_GRAY2BGR);

    153.         //单独显示
    154.         //rectangle(rgbRectifyImageL, validROIL, Scalar(0, 0, 255), 3, 8);
    155.         //rectangle(rgbRectifyImageR, validROIR, Scalar(0, 0, 255), 3, 8);
    156.         imshow("ImageL After Rectify", rgbRectifyImageL);
    157.         imshow("ImageR After Rectify", rgbRectifyImageR);

    158.         //显示在同一张图上
    159.         Mat canvas;
    160.         double sf;
    161.         int w, h;
    162.         sf = 600. / MAX(imageSize.width, imageSize.height);
    163.         w = cvRound(imageSize.width * sf);
    164.         h = cvRound(imageSize.height * sf);
    165.         canvas.create(h, w * 2, CV_8UC3);   //注意通道

    166.         //左图像画到画布上
    167.         Mat canvasPart = canvas(Rect(w * 0, 0, w, h));                                //得到画布的一部分
    168.         resize(rgbRectifyImageL, canvasPart, canvasPart.size(), 0, 0, INTER_AREA);     //把图像缩放到跟canvasPart一样大小
    169.         Rect vroiL(cvRound(validROIL.x*sf), cvRound(validROIL.y*sf),                //获得被截取的区域
    170.             cvRound(validROIL.width*sf), cvRound(validROIL.height*sf));
    171.         //rectangle(canvasPart, vroiL, Scalar(0, 0, 255), 3, 8);                      //画上一个矩形
    172.         cout << "Painted ImageL" << endl;

    173.         //右图像画到画布上
    174.         canvasPart = canvas(Rect(w, 0, w, h));                                      //获得画布的另一部分
    175.         resize(rgbRectifyImageR, canvasPart, canvasPart.size(), 0, 0, INTER_LINEAR);
    176.         Rect vroiR(cvRound(validROIR.x * sf), cvRound(validROIR.y*sf),
    177.             cvRound(validROIR.width * sf), cvRound(validROIR.height * sf));
    178.         //rectangle(canvasPart, vroiR, Scalar(0, 0, 255), 3, 8);
    179.         cout << "Painted ImageR" << endl;

    180.         //画上对应的线条
    181.         for (int i = 0; i < canvas.rows; i += 16)
    182.             line(canvas, Point(0, i), Point(canvas.cols, i), Scalar(0, 255, 0), 1, 8);
    183.         imshow("rectified", canvas);

    184.         /*
    185.         立体匹配
    186.         */
    187.         namedWindow("disparity", CV_WINDOW_AUTOSIZE);
    188.         // 创建SAD窗口 Trackbar
    189.         createTrackbar("BlockSize:\n", "disparity",&blockSize, 8, stereo_match);
    190.         // 创建视差唯一性百分比窗口 Trackbar
    191.         createTrackbar("UniquenessRatio:\n", "disparity", &uniquenessRatio, 50, stereo_match);
    192.         // 创建视差窗口 Trackbar
    193.         createTrackbar("NumDisparities:\n", "disparity", &numDisparities, 16, stereo_match);
    194.         //鼠标响应函数setMouseCallback(窗口名称, 鼠标回调函数, 传给回调函数的参数,一般取0)
    195.         setMouseCallback("disparity", onMouse, 0);
    196.         stereo_match(0,0);

    197.         waitKey(30);
    198.     }

    199.     return 0;
    200. }
    复制代码
    (二)双目视频获取
    由于Khadas的usb线宽不足以采集手头两个usb摄像头1280*720的分辨率图片,春节将至,快递都停了,一时间又不好再买新的摄像头,只好用pc采集视频流做成avi再拷贝到开发板代替双目摄像头:
    IMG_20180208_214518.jpg

    代码:
    1. #include <opencv2/core/core.hpp>
    2. #include <opencv2/highgui/highgui.hpp>

    3. using namespace cv;

    4. int main()
    5. {
    6.     int counter;

    7.     VideoCapture capture_left(0);//如果是笔记本,0打开的是自带的摄像头,1 打开外接的相机
    8.     VideoCapture capture_right(1);

    9.     double rate = 25.0;//视频的帧率
    10.     Size videoSize(640,480);

    11.     VideoWriter writer_left("Left2.avi", CV_FOURCC('M', 'J', 'P', 'G'), rate, videoSize);
    12.     VideoWriter writer_right("Right2.avi", CV_FOURCC('M', 'J', 'P', 'G'), rate, videoSize);

    13.     Mat left,right;

    14.     while (capture_left.isOpened() || capture_right.isOpened())
    15.     {
    16.         capture_left >> left;
    17.         capture_right >> right;

    18.         writer_left << left;
    19.         writer_right << right;

    20.         imshow("video_left2", left);
    21.         imshow("video_right2", right);

    22.         if (waitKey(20) == 27)//27是键盘摁下esc时,计算机接收到的ascii码值
    23.         {
    24.             break;
    25.         }

    26.         if(counter++ >=200)
    27.             break;
    28.     }

    29.     capture_left.release();
    30.     capture_right.release();

    31.     return 0;
    32. }
    复制代码
    (三)效果
    1.jpg


    2.jpg

    部分结构的log:
    1. in world coordinate: [306.073, 641.233, 2638.34]
    2. Painted ImageL
    3. Painted ImageR
    4. in world coordinate: [215.967, 452.458, 1861.64]
    5. Painted ImageL
    6. Painted ImageR
    7. in world coordinate: [-2888.56, -6051.63, 160000]
    8. Painted ImageL
    9. Painted ImageR
    10. in world coordinate: [-2888.56, -6051.63, 160000]
    11. Painted ImageL
    12. Painted ImageR
    13. in world coordinate: [385.141, 806.884, 3319.92]
    14. Painted ImageL
    15. Painted ImageR
    16. in world coordinate: [-2888.56, -6051.63, 160000]
    17. Painted ImageL
    18. Painted ImageR
    19. in world coordinate: [-2888.56, -6051.63, 160000]
    20. Painted ImageL
    21. Painted ImageR
    22. in world coordinate: [491.67, 1030.07, 4238.19]
    23. Painted ImageL
    24. Painted ImageR
    25. in world coordinate: [248.478, 520.57, 2141.88]
    26. Painted ImageL
    27. Painted ImageR
    28. in world coordinate: [320.951, 672.404, 2766.6]
    29. Painted ImageL
    30. Painted ImageR
    31. in world coordinate: [332.496, 696.591, 2866.11]
    32. Painted ImageL
    33. Painted ImageR
    34. in world coordinate: [378.828, 793.657, 3265.49]
    35. Painted ImageL
    36. Painted ImageR
    37. in world coordinate: [192.571, 403.442, 1659.96]
    38. Painted ImageL
    39. Painted ImageR
    40. in world coordinate: [212.981, 446.203, 1835.9]
    41. Painted ImageL
    42. Painted ImageR
    43. in world coordinate: [249.821, 523.384, 2153.46]
    44. Painted ImageL
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    46. in world coordinate: [316.555, 663.193, 2728.7]
    47. Painted ImageL
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    50. Painted ImageL
    51. Painted ImageR
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    54. Painted ImageR
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    76. in world coordinate: [inf, inf, inf]
    77. Painted ImageL
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    80. 9302492
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    84. Painted ImageL
    85. Painted ImageR
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    103. Painted ImageR
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    105. Painted ImageL
    106. Painted ImageR
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    108. Painted ImageL
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    141. Painted ImageL
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    163. Painted ImageR
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    170. in world coordinate: [-2888.56, -6051.63, 160000]
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    复制代码
    大部分结构都落在9s左右(30帧9s),而这个在i5 12g 2400ddr配置的pc机上成绩在2s左右。稍后会推出在树莓派上运行的结果,对比pc机肯定是被虐,那么khadas又能不能虐树莓派呢?有点小期待。本来也想在banana pi berry上试一下的,可惜捣鼓了一个星期,系统刷锅好几遍都没能给banana pi装上opencv3.4,大概是因为系统依赖有点问题,只能作罢。
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    发表于 2018-2-9 09:46:39 |显示全部楼层
    你这俩个usb摄像头咋固定在硬纸板上的
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    [LV.7]常住居民III

    发表于 2018-2-9 21:07:32 |显示全部楼层
    本帖最后由 robe.zhang 于 2018-2-9 21:10 编辑

    banana pi 是啥系统,能不能用源在线安装,他自己会处理依赖关系
    继续加油啊,双目是可以还原出来3D空间的,期待着看树莓派 和 banana pi,
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    [LV.6]常住居民II

    发表于 2018-2-18 21:26:35 |显示全部楼层
    噗噗熊 发表于 2018-2-9 09:46
    你这俩个usb摄像头咋固定在硬纸板上的

    就是用m2的螺丝。孔是用笔芯捅出来的,标定的时候还发现标定板打印的尺寸有点问题,最后的噪声超级大。
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    [LV.6]常住居民II

    发表于 2018-2-18 21:28:55 |显示全部楼层
    robe.zhang 发表于 2018-2-9 21:07
    banana pi 是啥系统,能不能用源在线安装,他自己会处理依赖关系
    继续加油啊,双目是可以还原出来3D空间的 ...

    是用ubuntu mate的,总是感觉那个镜像有点问题,他的依赖感觉有点问题,png和jpg的处理库总是莫名其妙找不到,已经努力很久了……把各种库删了又安,重刷啦好多次都不行……
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