参考 opencv aruco 实现对二维码(QR码)的检测与定位

参考 opencv aruco 实现对单个QR码的检测与定位

aruco是opencv_contrib的一个模块,实现了对AR码的检测/姿态估计
使用aruco需要安装opencv_contrib,本文将aruco中姿态估计用到的函数提取出来,结合zbar对QR码识别定位.

效果如下图

安装zbar

# ubuntu  apt install
sudo apt install libzbar-dev

将aruco中姿态估计用到的函数提取出来

estimate_marker_pose.h

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/opencv.hpp>  
using namespace std;           
using namespace cv;     
//绘制坐标轴
void myDrawFrameAxes(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs,
                   InputArray rvec, InputArray tvec, float length, int thickness);
//绘制边框以及id
void myDrawDetectedMarkers(InputOutputArray _image, InputArrayOfArrays _corners,
                         InputArray _ids, Scalar borderColor);
//生成实际四个定点的坐标
void myGetSingleMarkerObjectPoints(float markerLength, OutputArray _objPoints); 
//解PnP获得旋转向量和平移向量
void myEstimatePoseSingleMarkers(InputArrayOfArrays _corners, float markerLength,
                               InputArray _cameraMatrix, InputArray _distCoeffs,
                               OutputArray _rvecs, OutputArray _tvecs); 

estimate_marker_pose.cpp

#include <estimate_marker_pose.h>
using namespace std;        
using namespace cv;     

void myDrawFrameAxes(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs,
                   InputArray rvec, InputArray tvec, float length, int thickness)
{

    CV_Assert(image.getMat().total() > 0);
    CV_Assert(length > 0);

    // project axes points
    vector<Point3f> axesPoints;
    axesPoints.push_back(Point3f(0, 0, 0));
    axesPoints.push_back(Point3f(length, 0, 0));
    axesPoints.push_back(Point3f(0, length, 0));
    axesPoints.push_back(Point3f(0, 0, length));
    vector<Point2f> imagePoints;
    projectPoints(axesPoints, rvec, tvec, cameraMatrix, distCoeffs, imagePoints);

    // draw axes lines
    line(image, imagePoints[0], imagePoints[1], Scalar(0, 0, 255), thickness);
    line(image, imagePoints[0], imagePoints[2], Scalar(0, 255, 0), thickness);
    line(image, imagePoints[0], imagePoints[3], Scalar(255, 0, 0), thickness);
}

void myDrawDetectedMarkers(InputOutputArray _image, InputArrayOfArrays _corners,
                         InputArray _ids, Scalar borderColor) 
    {
    CV_Assert(_image.getMat().total() != 0 &&
              (_image.getMat().channels() == 1 || _image.getMat().channels() == 3));
    CV_Assert((_corners.total() == _ids.total()) || _ids.total() == 0);

    // calculate colors
    Scalar textColor, cornerColor;
    textColor = cornerColor = borderColor;
    swap(textColor.val[0], textColor.val[1]);     // text color just sawp G and R
    swap(cornerColor.val[1], cornerColor.val[2]); // corner color just sawp G and B

    int nMarkers = (int)_corners.total();
    for(int i = 0; i < nMarkers; i++) {
        Mat currentMarker = _corners.getMat(i);
        CV_Assert(currentMarker.total() == 4 && currentMarker.type() == CV_32FC2);

        // draw marker sides
        for(int j = 0; j < 4; j++) {
            Point2f p0, p1;
            p0 = currentMarker.ptr< Point2f >(0)[j];
            p1 = currentMarker.ptr< Point2f >(0)[(j + 1) % 4];
            line(_image, p0, p1, borderColor, 1);
        }
        // draw first corner mark
        rectangle(_image, currentMarker.ptr< Point2f >(0)[0] - Point2f(3, 3),
                  currentMarker.ptr< Point2f >(0)[0] + Point2f(3, 3), cornerColor, 1, LINE_AA);

        // draw ID
        if(_ids.total() != 0) {
            Point2f cent(0, 0);
            for(int p = 0; p < 4; p++)
                cent += currentMarker.ptr< Point2f >(0)[p];
            cent = cent / 4.;
            stringstream s;
            s << "id=" << _ids.getMat().ptr< int >(0)[i];
            putText(_image, s.str(), cent, FONT_HERSHEY_SIMPLEX, 0.5, textColor, 2);
        }
    }
}

void myGetSingleMarkerObjectPoints(float markerLength, OutputArray _objPoints) {


    _objPoints.create(4, 1, CV_32FC3);
    Mat objPoints = _objPoints.getMat();
    // set coordinate system in the middle of the marker, with Z pointing out
    objPoints.ptr< Vec3f >(0)[0] = Vec3f(-markerLength / 2.f, markerLength / 2.f, 0);
    objPoints.ptr< Vec3f >(0)[1] = Vec3f(markerLength / 2.f, markerLength / 2.f, 0);
    objPoints.ptr< Vec3f >(0)[2] = Vec3f(markerLength / 2.f, -markerLength / 2.f, 0);
    objPoints.ptr< Vec3f >(0)[3] = Vec3f(-markerLength / 2.f, -markerLength / 2.f, 0);
}


void myEstimatePoseSingleMarkers(InputArrayOfArrays _corners, float markerLength,
                               InputArray _cameraMatrix, InputArray _distCoeffs,
                               OutputArray _rvecs, OutputArray _tvecs) {


    Mat markerObjPoints;
    myGetSingleMarkerObjectPoints(markerLength, markerObjPoints);
    int nMarkers = (int)_corners.total();
    _rvecs.create(nMarkers, 1, CV_64FC3);
    _tvecs.create(nMarkers, 1, CV_64FC3);

    Mat rvecs = _rvecs.getMat(), tvecs = _tvecs.getMat();

     for each marker, calculate its pose
    parallel_for_(Range(0, nMarkers), [&](const Range& range) {
        const int begin = range.start;
        const int end = range.end;

        for (int i = begin; i < end; i++) {
            solvePnP(markerObjPoints, _corners.getMat(i), _cameraMatrix, _distCoeffs, rvecs.at<Vec3d>(i),
                     tvecs.at<Vec3d>(i));
        }
    });

}

main.cpp

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/opencv.hpp>     
#include <iostream>        
#include <zbar.h>
#include <estimate_marker_pose.h>
#include <opencv2/imgproc/types_c.h>

using namespace std;        
using namespace zbar;  //添加zbar名称空间      
using namespace cv;     

    
int main(int argc,char*argv[])      
{        
    cout<< "CV_VERSION: " << CV_VERSION << endl;
    //相机标定的参数-------
    double fx = 412.433229;
	double cx = 318.310004;
	double fy = 414.182775;
	double cy = 236.769192;
	double k1 = -0.320394;
	double k2 =  0.108028;
	double p1 = -0.000993;
	double p2 =  0.001297;
	double k3 =  0;
    Mat cameraMatrix = (cv::Mat_<float>(3, 3) <<
        fx, 0.0, cx,
        0.0, fy, cy,
        0.0, 0.0, 1.0);
    Mat distCoeffs = (cv::Mat_<float>(5, 1) << k1, k2, p1, p2, k3);
    //相机标定的参数-------
    //二维码的边长
	double marker_size = 5.0; //单位  cm
    //zbar::ImageScanner
    ImageScanner scanner;        
    scanner.set_config(ZBAR_NONE, ZBAR_CFG_ENABLE, 1);      
    
    cv::VideoCapture inputVideo;
    inputVideo.open(0);
	inputVideo.set(cv::CAP_PROP_FRAME_WIDTH,1280);
	inputVideo.set(cv::CAP_PROP_FRAME_HEIGHT,720);

    while (inputVideo.grab()) 
    {
        cv::Mat image;
		inputVideo.retrieve(image);//抓取视频中的一张照片
		flip(image,image,1);//  水平方向镜像
        Mat imageGray;        
        cvtColor(image,imageGray,CV_RGB2GRAY);   
        int width = imageGray.cols;        
        int height = imageGray.rows;        
        uchar *raw = (uchar *)imageGray.data;           
        Image imageZbar(width, height, "Y800", raw, width * height);          
        scanner.scan(imageZbar); //扫描条码      
        Image::SymbolIterator symbol = imageZbar.symbol_begin();    
        if(imageZbar.symbol_begin()==imageZbar.symbol_end())    
        {    
            cout<<"can't detect QR code！"<<endl;    
        }    
        std::vector<int> ids;
        std::vector<std::vector<cv::Point2f> > corners;
        std::vector<cv::Vec3d> rvecs, tvecs;
        for(int i = 0;symbol != imageZbar.symbol_end();++symbol)      
        {        
            cout<<"type："<<endl<<symbol->get_type_name()<<endl<<endl;      
            cout<<"data："<<endl<<symbol->get_data()<<endl<<endl; 
            cout<<"data_length："<<endl<<symbol->get_data_length()<<endl<<endl; 
            cout<<"location_size："<<endl<<symbol->get_location_size()<<endl<<endl; 
             
            std::vector<cv::Point2f> corner;
            corner.push_back(cv::Point2f(symbol->get_location_x(0),symbol->get_location_y(0)));
            corner.push_back(cv::Point2f(symbol->get_location_x(3),symbol->get_location_y(3)));
            corner.push_back(cv::Point2f(symbol->get_location_x(2),symbol->get_location_y(2)));
            corner.push_back(cv::Point2f(symbol->get_location_x(1),symbol->get_location_y(1)));
            corners.push_back(corner);
            ids.push_back(i);
            i++; 
        }        

        //求解旋转向量rvecs和平移向量tvecs
        myEstimatePoseSingleMarkers(corners, marker_size, cameraMatrix, distCoeffs, rvecs, tvecs);
        for (int i = 0; i < ids.size(); i ++)
        {
            // cv::aruco::drawDetectedMarkers(image, corners, ids);//绘制检测到的靶标的框
            myDrawDetectedMarkers(image, corners, ids,Scalar(100, 0, 255));//绘制检测到的靶标的框
            // cv::aruco::drawAxis(image, cameraMatrix, distCoeffs, rvecs[i], tvecs[i], 5);
            myDrawFrameAxes(image, cameraMatrix, distCoeffs, rvecs[i], tvecs[i], 5, 3);
            // drawFrameAxes(image, cameraMatrix, distCoeffs, rvecs[i], tvecs[i], 5, 3);//opencv 3.3.1 没有 4.2.1有
            cout<<"  T :"<<tvecs[i]<<endl;
            cout<<"  R :"<<rvecs[i]<<endl;
        }
        imshow("Source Image",image);    
        waitKey(1);      
    }

    return 0;    
}     

CMakeLists.txt

# estimate_marker_pose
add_library( estimate_marker_pose src/estimate_marker_pose.cpp)
target_link_libraries(estimate_marker_pose ${OpenCV_LIBS} )
# main
add_executable(main src/main.cpp)
target_link_libraries(main zbar estimate_marker_pose ${OpenCV_LIBS} )

打印

type：
QR-Code

data：
1

data_length：
1

location_size：
4

  T :[2.16432, -0.594964, 15.9725]
  R :[2.47789, -0.487188, -0.156933]