【Khadas VIM试用】双目视觉运行能力测试2

day_day

（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. 
   
6. Mat cameraMatrixR = (Mat_<double>(3, 3) << 284.34939, 0, 283.30332,
   
7.                      0, 285.84734, 243.33090,
   
8.                      0, 0, 1);
   
9. Mat distCoeffR = (Mat_<double>(5, 1) << -0.21396, 0.03400, -0.00154, 0.00204, 0.00000);
   
10. 
    
11. Mat T = (Mat_<double>(3, 1) << -90.67152, -2.93721, 16.09332);//T平移向量
    
12. Mat rec = (Mat_<double>(3, 1) << 0.02428, 0.15673, -0.00825);//rec旋转向量
    
13. Mat R;//R 旋转矩阵

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带入双目测距程序里面：

1. /******************************/
   
2. /*        立体匹配和测距        */
   
3. /******************************/
   
4. 
   
5. #include <opencv2/opencv.hpp>
   
6. #include <imgproc.hpp>
   
7. #include <iostream>
   
8. #include <time.h>
   
9. 
   
10. using namespace std;
    
11. using namespace cv;
    
12. 
    
13. const int imageWidth = 640;                             //摄像头的分辨率
    
14. const int imageHeight = 480;
    
15. Size imageSize = Size(imageWidth, imageHeight);
    
16. 
    
17. Mat rgbImageL, grayImageL;
    
18. Mat rgbImageR, grayImageR;
    
19. Mat rectifyImageL, rectifyImageR;
    
20. 
    
21. 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
    
22. Rect validROIR;
    
23. 
    
24. Mat mapLx, mapLy, mapRx, mapRy;     //映射表
    
25. Mat Rl, Rr, Pl, Pr, Q;              //校正旋转矩阵R，投影矩阵P 重投影矩阵Q
    
26. Mat xyz;              //三维坐标
    
27. 
    
28. Point origin;         //鼠标按下的起始点
    
29. Rect selection;      //定义矩形选框
    
30. bool selectObject = false;    //是否选择对象
    
31. 
    
32. int blockSize = 0, uniquenessRatio =0, numDisparities=0;
    
33. Ptr<StereoBM> bm = StereoBM::create(16, 9);
    
34. 
    
35. /*
    
36. 事先标定好的相机的参数
    
37. fx 0 cx
    
38. 0 fy cy
    
39. 0 0  1
    
40. */
    
41. Mat cameraMatrixL = (Mat_<double>(3, 3) << 274.07311, 0, 334.46683,
    
42.                      0, 273.77609, 230.80436,
    
43.                      0, 0, 1);
    
44. Mat distCoeffL = (Mat_<double>(5, 1) << -0.21470, 0.03484, -0.00121, -0.00279, 0.00000);
    
45. 
    
46. Mat cameraMatrixR = (Mat_<double>(3, 3) << 284.34939, 0, 283.30332,
    
47.                      0, 285.84734, 243.33090,
    
48.                      0, 0, 1);
    
49. Mat distCoeffR = (Mat_<double>(5, 1) << -0.21396, 0.03400, -0.00154, 0.00204, 0.00000);
    
50. 
    
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. 
    
55. 
    
56. /*Mat cameraMatrixL = (Mat_<double>(3, 3) << 268.0870787552206, 0, 335.7271612649919,
    
57.                      0, 268.0500620563969, 228.181598739472,
    
58.                      0, 0, 1);
    
59. Mat distCoeffL = (Mat_<double>(5, 1) << -0.2320648740970932, 0.04510313360911739, -9.418532128676933e-05, -0.0008271590194063145, 0);
    
60. 
    
61. Mat cameraMatrixR = (Mat_<double>(3, 3) << 268.0746191870755, 0, 313.554845275748,
    
62.                      0, 267.8032936757982, 237.0287771634367,
    
63.                      0, 0, 1);
    
64. Mat distCoeffR = (Mat_<double>(5, 1) << -0.2391280628833069, 0.04899490848168394, 7.734678017422217e-05, 7.975132256511924e-05, 0);
    
65. 
    
66. Mat T = (Mat_<double>(3, 1) << -90.67152, -2.93721, 16.09332);//T平移向量
    
67. Mat rec = (Mat_<double>(3, 1) << 0.02428, 0.15673, -0.00825);//rec旋转向量
    
68. Mat R;//R 旋转矩阵*/
    
69. 
    
70. /*****立体匹配*****/
    
71. void stereo_match(int,void*)
    
72. {
    
73.     bm->setBlockSize(2*blockSize+5);     //SAD窗口大小，5~21之间为宜
    
74.     bm->setROI1(validROIL);
    
75.     bm->setROI2(validROIR);
    
76.     bm->setPreFilterCap(31);
    
77.     bm->setMinDisparity(0);  //最小视差，默认值为0, 可以是负值，int型
    
78.     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
    
79.     bm->setTextureThreshold(10);
    
80.     bm->setUniquenessRatio(uniquenessRatio);//uniquenessRatio主要可以防止误匹配
    
81.     bm->setSpeckleWindowSize(100);
    
82.     bm->setSpeckleRange(32);
    
83.     bm->setDisp12MaxDiff(-1);
    
84.     Mat disp, disp8;
    
85.     bm->compute(rectifyImageL, rectifyImageR, disp);//输入图像必须为灰度图
    
86.     disp.convertTo(disp8, CV_8U, 255 / ((numDisparities * 16 + 16)*16.));//计算出的视差是CV_16S格式
    
87.     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。
    
88.     xyz = xyz * 16;
    
89. 
    
90.     Point p;
    
91.     p.x = 400; p.y = 300;
    
92.     cout << "in world coordinate: " << xyz.at<Vec3f>(p) << endl;
    
93. 
    
94.     imshow("disparity", disp8);
    
95. }
    
96. 
    
97. /*****描述：鼠标操作回调*****/
    
98. static void onMouse(int event, int x, int y, int, void*)
    
99. {
    
100.     if (selectObject)
     
101.     {
     
102.         selection.x = MIN(x, origin.x);
     
103.         selection.y = MIN(y, origin.y);
     
104.         selection.width = std::abs(x - origin.x);
     
105.         selection.height = std::abs(y - origin.y);
     
106.     }
     
107. 
     
108.     switch (event)
     
109.     {
     
110.     case EVENT_LBUTTONDOWN:   //鼠标左按钮按下的事件
     
111.         origin = Point(x, y);
     
112.         selection = Rect(x, y, 0, 0);
     
113.         selectObject = true;
     
114.         cout << origin <<"in world coordinate is: " << xyz.at<Vec3f>(origin) << endl;
     
115.         break;
     
116.     case EVENT_LBUTTONUP:    //鼠标左按钮释放的事件
     
117.         selectObject = false;
     
118.         if (selection.width > 0 && selection.height > 0)
     
119.         break;
     
120.     }
     
121. }
     
122. 
     
123. 
     
124. /*****主函数*****/
     
125. int main()
     
126. {
     
127.     int counter_frame = 0;
     
128. 
     
129.     /*
     
130.     立体校正
     
131.     */
     
132.     Rodrigues(rec, R); //Rodrigues变换
     
133.     stereoRectify(cameraMatrixL, distCoeffL, cameraMatrixR, distCoeffR, imageSize, R, T, Rl, Rr, Pl, Pr, Q, CALIB_ZERO_DISPARITY,
     
134.         0, imageSize, &validROIL, &validROIR);
     
135.     initUndistortRectifyMap(cameraMatrixL, distCoeffL, Rl, Pr, imageSize, CV_32FC1, mapLx, mapLy);
     
136.     initUndistortRectifyMap(cameraMatrixR, distCoeffR, Rr, Pr, imageSize, CV_32FC1, mapRx, mapRy);
     
137. 
     
138.     VideoCapture left("Left.avi");
     
139.     VideoCapture right("Right.avi");
     
140. 
     
141.     Mat left_frame,right_frame;
     
142. 
     
143.     if(!left.isOpened() || !right.isOpened())
     
144.     {
     
145.     cout<<"open error"<<endl;
     
146.     return -1;
     
147.     }
     
148. 
     
149.     clock_t start_clock,end_clock;
     
150.     start_clock = clock();
     
151. 
     
152. 
     
153.     while(1)
     
154.     {
     
155. 
     
156.         if(counter_frame++ >= 30)
     
157.         {
     
158.             counter_frame = 0;
     
159.             end_clock = clock();
     
160.             std::cout << end_clock - start_clock << std::endl;
     
161.             start_clock = clock();
     
162.         }
     
163.         /*
     
164.         读取图片
     
165.         */
     
166.         left >> rgbImageL;
     
167.         right >> rgbImageR;
     
168. 
     
169.         cvtColor(rgbImageL, grayImageL, CV_BGR2GRAY);
     
170.         cvtColor(rgbImageR, grayImageR, CV_BGR2GRAY);
     
171. 
     
172.         imshow("ImageL Before Rectify", grayImageL);
     
173.         imshow("ImageR Before Rectify", grayImageR);
     
174. 
     
175.         /*
     
176.         经过remap之后，左右相机的图像已经共面并且行对准了
     
177.         */
     
178.         remap(grayImageL, rectifyImageL, mapLx, mapLy, INTER_LINEAR);
     
179.         remap(grayImageR, rectifyImageR, mapRx, mapRy, INTER_LINEAR);
     
180. 
     
181.         /*
     
182.         把校正结果显示出来
     
183.         */
     
184.         Mat rgbRectifyImageL, rgbRectifyImageR;
     
185.         cvtColor(rectifyImageL, rgbRectifyImageL, CV_GRAY2BGR);  //伪彩色图
     
186.         cvtColor(rectifyImageR, rgbRectifyImageR, CV_GRAY2BGR);
     
187. 
     
188.         //单独显示
     
189.         //rectangle(rgbRectifyImageL, validROIL, Scalar(0, 0, 255), 3, 8);
     
190.         //rectangle(rgbRectifyImageR, validROIR, Scalar(0, 0, 255), 3, 8);
     
191.         imshow("ImageL After Rectify", rgbRectifyImageL);
     
192.         imshow("ImageR After Rectify", rgbRectifyImageR);
     
193. 
     
194.         //显示在同一张图上
     
195.         Mat canvas;
     
196.         double sf;
     
197.         int w, h;
     
198.         sf = 600. / MAX(imageSize.width, imageSize.height);
     
199.         w = cvRound(imageSize.width * sf);
     
200.         h = cvRound(imageSize.height * sf);
     
201.         canvas.create(h, w * 2, CV_8UC3);   //注意通道
     
202. 
     
203.         //左图像画到画布上
     
204.         Mat canvasPart = canvas(Rect(w * 0, 0, w, h));                                //得到画布的一部分
     
205.         resize(rgbRectifyImageL, canvasPart, canvasPart.size(), 0, 0, INTER_AREA);     //把图像缩放到跟canvasPart一样大小
     
206.         Rect vroiL(cvRound(validROIL.x*sf), cvRound(validROIL.y*sf),                //获得被截取的区域
     
207.             cvRound(validROIL.width*sf), cvRound(validROIL.height*sf));
     
208.         //rectangle(canvasPart, vroiL, Scalar(0, 0, 255), 3, 8);                      //画上一个矩形
     
209.         cout << "Painted ImageL" << endl;
     
210. 
     
211.         //右图像画到画布上
     
212.         canvasPart = canvas(Rect(w, 0, w, h));                                      //获得画布的另一部分
     
213.         resize(rgbRectifyImageR, canvasPart, canvasPart.size(), 0, 0, INTER_LINEAR);
     
214.         Rect vroiR(cvRound(validROIR.x * sf), cvRound(validROIR.y*sf),
     
215.             cvRound(validROIR.width * sf), cvRound(validROIR.height * sf));
     
216.         //rectangle(canvasPart, vroiR, Scalar(0, 0, 255), 3, 8);
     
217.         cout << "Painted ImageR" << endl;
     
218. 
     
219.         //画上对应的线条
     
220.         for (int i = 0; i < canvas.rows; i += 16)
     
221.             line(canvas, Point(0, i), Point(canvas.cols, i), Scalar(0, 255, 0), 1, 8);
     
222.         imshow("rectified", canvas);
     
223. 
     
224.         /*
     
225.         立体匹配
     
226.         */
     
227.         namedWindow("disparity", CV_WINDOW_AUTOSIZE);
     
228.         // 创建SAD窗口 Trackbar
     
229.         createTrackbar("BlockSize:\n", "disparity",&blockSize, 8, stereo_match);
     
230.         // 创建视差唯一性百分比窗口 Trackbar
     
231.         createTrackbar("UniquenessRatio:\n", "disparity", &uniquenessRatio, 50, stereo_match);
     
232.         // 创建视差窗口 Trackbar
     
233.         createTrackbar("NumDisparities:\n", "disparity", &numDisparities, 16, stereo_match);
     
234.         //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)
     
235.         setMouseCallback("disparity", onMouse, 0);
     
236.         stereo_match(0,0);
     
237. 
     
238.         waitKey(30);
     
239.     }
     
240. 
     
241.     return 0;
     
242. }
     

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（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：

代码：

1. #include <opencv2/core/core.hpp>
   
2. #include <opencv2/highgui/highgui.hpp>
   
3. 
   
4. using namespace cv;
   
5. 
   
6. int main()
   
7. {
   
8.     int counter;
   
9. 
   
10.     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
    
11.     VideoCapture capture_right(1);
    
12. 
    
13.     double rate = 25.0;//视频的帧率
    
14.     Size videoSize(640,480);
    
15. 
    
16.     VideoWriter writer_left("Left2.avi", CV_FOURCC('M', 'J', 'P', 'G'), rate, videoSize);
    
17.     VideoWriter writer_right("Right2.avi", CV_FOURCC('M', 'J', 'P', 'G'), rate, videoSize);
    
18. 
    
19.     Mat left,right;
    
20. 
    
21.     while (capture_left.isOpened() || capture_right.isOpened())
    
22.     {
    
23.         capture_left >> left;
    
24.         capture_right >> right;
    
25. 
    
26.         writer_left << left;
    
27.         writer_right << right;
    
28. 
    
29.         imshow("video_left2", left);
    
30.         imshow("video_right2", right);
    
31. 
    
32.         if (waitKey(20) == 27)//27是键盘摁下esc时，计算机接收到的ascii码值
    
33.         {
    
34.             break;
    
35.         }
    
36. 
    
37.         if(counter++ >=200)
    
38.             break;
    
39.     }
    
40. 
    
41.     capture_left.release();
    
42.     capture_right.release();
    
43. 
    
44.     return 0;
    
45. }
    

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（三）效果



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
    
45. Painted ImageR
    
46. in world coordinate: [316.555, 663.193, 2728.7]
    
47. Painted ImageL
    
48. Painted ImageR
    
49. in world coordinate: [-2888.56, -6051.63, 160000]
    
50. Painted ImageL
    
51. Painted ImageR
    
52. in world coordinate: [2310.85, 4841.31, 19919.5]
    
53. Painted ImageL
    
54. Painted ImageR
    
55. in world coordinate: [-2888.56, -6051.63, 160000]
    
56. Painted ImageL
    
57. Painted ImageR
    
58. in world coordinate: [-2888.56, -6051.63, 160000]
    
59. Painted ImageL
    
60. Painted ImageR
    
61. in world coordinate: [385.141, 806.884, 3319.92]
    
62. Painted ImageL
    
63. Painted ImageR
    
64. in world coordinate: [-2888.56, -6051.63, 160000]
    
65. Painted ImageL
    
66. Painted ImageR
    
67. in world coordinate: [2567.61, 5379.23, 22132.8]
    
68. Painted ImageL
    
69. Painted ImageR
    
70. in world coordinate: [-2888.56, -6051.63, 160000]
    
71. Painted ImageL
    
72. Painted ImageR
    
73. in world coordinate: [-2888.56, -6051.63, 160000]
    
74. Painted ImageL
    
75. Painted ImageR
    
76. in world coordinate: [inf, inf, inf]
    
77. Painted ImageL
    
78. Painted ImageR
    
79. in world coordinate: [-2888.56, -6051.63, 160000]
    
80. 9302492
    
81. Painted ImageL
    
82. Painted ImageR
    
83. in world coordinate: [-2888.56, -6051.63, 160000]
    
84. Painted ImageL
    
85. Painted ImageR
    
86. in world coordinate: [-2888.56, -6051.63, 160000]
    
87. Painted ImageL
    
88. Painted ImageR
    
89. in world coordinate: [2432.47, 5096.11, 20967.9]
    
90. Painted ImageL
    
91. Painted ImageR
    
92. in world coordinate: [249.821, 523.384, 2153.46]
    
93. Painted ImageL
    
94. Painted ImageR
    
95. in world coordinate: [192.571, 403.442, 1659.96]
    
96. Painted ImageL
    
97. Painted ImageR
    
98. in world coordinate: [-2888.56, -6051.63, 160000]
    
99. Painted ImageL
    
100. Painted ImageR
     
101. in world coordinate: [-2888.56, -6051.63, 160000]
     
102. Painted ImageL
     
103. Painted ImageR
     
104. in world coordinate: [253.939, 532.012, 2188.96]
     
105. Painted ImageL
     
106. Painted ImageR
     
107. in world coordinate: [inf, inf, inf]
     
108. Painted ImageL
     
109. Painted ImageR
     
110. in world coordinate: [inf, inf, inf]
     
111. Painted ImageL
     
112. Painted ImageR
     
113. in world coordinate: [711.03, 1489.63, 6129.08]
     
114. Painted ImageL
     
115. Painted ImageR
     
116. in world coordinate: [-2888.56, -6051.63, 160000]
     
117. Painted ImageL
     
118. Painted ImageR
     
119. in world coordinate: [1711.74, 3586.15, 14755.2]
     
120. Painted ImageL
     
121. Painted ImageR
     
122. in world coordinate: [-2888.56, -6051.63, 160000]
     
123. Painted ImageL
     
124. Painted ImageR
     
125. in world coordinate: [872.018, 1826.91, 7516.79]
     
126. Painted ImageL
     
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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。

噗噗熊

你这俩个usb摄像头咋固定在硬纸板上的

robe.zhang

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，

day_day

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。

day_day

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……