- Marker检测采用小觅相机，可以实时检测Marker的位置和姿态，效果如下：
参考代码如下：
1 #include "pch.h"
2
3 #include <Eigen/Dense>
4 #include <opencv2/core.hpp>
5 #include <opencv2\highgui.hpp>
6 #include <opencv2\aruco.hpp>
7 #include <opencv2\aruco\dictionary.hpp>
8 #include <opencv2/calib3d.hpp>
9 #include <opencv2/core/eigen.hpp>
10 #include <opencv2/opencv.hpp>
11
12 #include <mynteyed/camera.h>
13 #include <mynteyed/utils.h>
14
15 #include <vector>
16 #include <iostream>
17 #include <Windows.h>
18 #include <fstream>
19
20 using namespace std;
21 using namespace cv;
22 using namespace Eigen;
23 using namespace aruco;
24
25
26 int main(int argc, char *argv[]) {
27 mynteyed::Camera cam;
28 mynteyed::DeviceInfo dev_info;
29 if (!mynteyed::util::select(cam, &dev_info)) {
30 return 1;
31 }
32 mynteyed::util::print_stream_infos(cam, dev_info.index);
33
34 std::cout << "Open device: " << dev_info.index << ", "
35 << dev_info.name << std::endl << std::endl;
36 //设置相机的参数
37 mynteyed::OpenParams params(dev_info.index);
38 //params.depth_mode = mynteyed::DepthMode::DEPTH_GRAY;
39 //params.stream_mode = mynteyed::StreamMode::
40 params.stream_mode = mynteyed::StreamMode::STREAM_2560x720;
41 params.color_mode = mynteyed::ColorMode::COLOR_RECTIFIED;
42 //params.ir_intensity = 4;
43 params.framerate = 30;
44
45 cam.Open(params);
46
47
48
49 Ptr<aruco::Dictionary> dictionary = aruco::getPredefinedDictionary(aruco::DICT_6X6_250);
50 Mat out;
51 dictionary->drawMarker(100, 600, out, 5);
52
53 Ptr<aruco::DetectorParameters> detectorParams = aruco::DetectorParameters::create();
54
55
56 for (;;) {
57 auto Left_color = cam.GetStreamData(mynteyed::ImageType::IMAGE_LEFT_COLOR);
58 if (Left_color.img)
59 {
60 Mat image = Left_color.img->To(mynteyed::ImageFormat::COLOR_BGR)->ToMat();
61 Mat imageCopy;
62 //相机内参矩阵
63 const Mat intrinsic_matrix = (Mat_<float>(3, 3)
64 << 713.12554931640625000, 0.0, 634.99163818359375000, 0.0,
65 714.41278076171875000, 363.88098144531250000, 0.0, 0.0, 1.0);
66
67 //畸变校正
68 const Mat arucodistCoeffs = (Mat_<float>(1, 5) << -0.29668807983398438, 0.07767868041992188,
69 0.00000000000000000, -0.00012969970703125,
70 0.00000000000000000);
71 vector< int > ids;
72 vector< vector< Point2f > > corners, rejected;
73 vector< Vec3d > rvecs, tvecs;
74 Mat R;
75 MatrixXd M(4, 4);
76 // detect markers and estimate pose
77 detectMarkers(image, dictionary, corners, ids, detectorParams, rejected);//rejected拒绝的矩形区域
78 image.copyTo(imageCopy);
79 if (ids.size() > 0)
80 {
81 drawDetectedMarkers(imageCopy, corners, ids);
82 std::vector <cv::Vec3d> rvecs，tvecs;
83 estimatePoseSingleMarkers(corners,0.05, intrinsic_matrix, arucodistCoeffs, rvecs, tvecs);
84 //0.05为Marker的大小
85 Rodrigues(rvecs[0], R, noArray());//罗德里格斯变换将旋转矩阵变为旋转向量
86 MatrixXd r(3, 3);
87 VectorXd t(3);
88 VectorXd T_mm(3);
89 cv2eigen(R, r);
90 cv2eigen(tvecs[0], t);
91 cv2eigen(tvecs[0], T_mm);
92 T_mm = T_mm * 1000;
93 M(0, 0) = r(0, 0); M(0, 1) = r(0, 1); M(0, 2) = r(0, 2); M(0, 3) = t(0, 0);
94 M(1, 0) = r(1, 0); M(1, 1) = r(1, 1); M(1, 2) = r(1, 2); M(1, 3) = t(1, 0);
95 M(2, 0) = r(2, 0); M(0, 1) = r(2, 1); M(2, 2) = r(2, 2); M(2, 3) = t(2, 0);
96 M(3, 0) = 0; M(3, 1) = 0; M(3, 2) = 0; M(3, 3) = 1;
97
98 cout << "R :" << r << endl;
99 cout << "T :" << T_mm << endl;
100
101 for (int i = 0; i < ids.size(); i++)
102 {
103 cv::aruco::drawAxis(imageCopy, intrinsic_matrix, arucodistCoeffs, rvecs[i], tvecs[i], 0.05);
104 }
105
106 }
107
108 imshow("out", imageCopy);
109 char key = (char)waitKey(1);
110 if (key == 27) break;
111 }
112
113 }
114 return 0;
115 }
116
117
