opencv/modules/calib3d/src/solvepnp.cpp

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#include "precomp.hpp"
#include "dls.h"
#include "epnp.h"
#include "p3p.h"
#include "opencv2/calib3d/calib3d_c.h"

#include <iostream>
using namespace cv;

bool cv::solvePnP( InputArray _opoints, InputArray _ipoints,
                  InputArray _cameraMatrix, InputArray _distCoeffs,
                  OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int flags )
{
    Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
    int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
    CV_Assert( npoints >= 0 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) );
    _rvec.create(3, 1, CV_64F);
    _tvec.create(3, 1, CV_64F);
    Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();

    if (flags == SOLVEPNP_EPNP)
    {
        cv::Mat undistortedPoints;
        cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
        epnp PnP(cameraMatrix, opoints, undistortedPoints);

        cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
        PnP.compute_pose(R, tvec);
        cv::Rodrigues(R, rvec);
        return true;
    }
    else if (flags == SOLVEPNP_P3P)
    {
        CV_Assert( npoints == 4);
        cv::Mat undistortedPoints;
        cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
        p3p P3Psolver(cameraMatrix);

        cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
        bool result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
        if (result)
            cv::Rodrigues(R, rvec);
        return result;
    }
    else if (flags == SOLVEPNP_ITERATIVE)
    {
        CvMat c_objectPoints = opoints, c_imagePoints = ipoints;
        CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
        CvMat c_rvec = _rvec.getMat(), c_tvec = _tvec.getMat();
        cvFindExtrinsicCameraParams2(&c_objectPoints, &c_imagePoints, &c_cameraMatrix,
                                     c_distCoeffs.rows*c_distCoeffs.cols ? &c_distCoeffs : 0,
                                     &c_rvec, &c_tvec, useExtrinsicGuess );
        return true;
    }
    else if (flags == SOLVEPNP_DLS)
    {
        cv::Mat undistortedPoints;
        cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);

        dls PnP(opoints, undistortedPoints);

        cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
        bool result = PnP.compute_pose(R, tvec);
        if (result)
            cv::Rodrigues(R, rvec);
        return result;
    }
    else
        CV_Error(CV_StsBadArg, "The flags argument must be one of SOLVEPNP_ITERATIVE, SOLVEPNP_P3P, SOLVEPNP_EPNP or SOLVEPNP_DLS");
    return false;
}

class PnPRansacCallback : public PointSetRegistrator::Callback
{

public:

    PnPRansacCallback(Mat _cameraMatrix=Mat(3,3,CV_64F), Mat _distCoeffs=Mat(4,1,CV_64F), int _flags=cv::SOLVEPNP_ITERATIVE,
            bool _useExtrinsicGuess=false, Mat _rvec=Mat(), Mat _tvec=Mat() )
        : cameraMatrix(_cameraMatrix), distCoeffs(_distCoeffs), flags(_flags), useExtrinsicGuess(_useExtrinsicGuess),
          rvec(_rvec), tvec(_tvec) {}

    /* Pre: True */
    /* Post: compute _model with given points an return number of found models */
    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
    {
        Mat opoints = _m1.getMat(), ipoints = _m2.getMat();


        bool correspondence = cv::solvePnP( _m1, _m2, cameraMatrix, distCoeffs,
                                            rvec, tvec, useExtrinsicGuess, flags );

        Mat _local_model;
        cv::hconcat(rvec, tvec, _local_model);
        _local_model.copyTo(_model);

        return correspondence;
    }

    /* Pre: True */
    /* Post: fill _err with projection errors */
    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const
    {

        Mat opoints = _m1.getMat(), ipoints = _m2.getMat(), model = _model.getMat();

        int i, count = opoints.cols;
        Mat _rvec = model.col(0);
        Mat _tvec = model.col(1);


        Mat projpoints(count, 2, CV_32FC1);
        cv::projectPoints(opoints, _rvec, _tvec, cameraMatrix, distCoeffs, projpoints);

        const Point2f* ipoints_ptr = ipoints.ptr<Point2f>();
        const Point2f* projpoints_ptr = projpoints.ptr<Point2f>();

        _err.create(count, 1, CV_32FC1);
        float* err = _err.getMat().ptr<float>();

        for ( i = 0; i < count; ++i)
            err[i] = (float)cv::norm( ipoints_ptr[i] - projpoints_ptr[i] );

    }


    Mat cameraMatrix;
    Mat distCoeffs;
    int flags;
    bool useExtrinsicGuess;
    Mat rvec;
    Mat tvec;
};

bool cv::solvePnPRansac(InputArray _opoints, InputArray _ipoints,
                        InputArray _cameraMatrix, InputArray _distCoeffs,
                        OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess,
                        int iterationsCount, float reprojectionError, double confidence,
                        OutputArray _inliers, int flags)
{

    Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();

    int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
    CV_Assert( npoints >= 0 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) );

    CV_Assert(opoints.isContinuous());
    CV_Assert(opoints.depth() == CV_32F || opoints.depth() == CV_64F);
    CV_Assert((opoints.rows == 1 && opoints.channels() == 3) || opoints.cols*opoints.channels() == 3);
    CV_Assert(ipoints.isContinuous());
    CV_Assert(ipoints.depth() == CV_32F || ipoints.depth() == CV_64F);
    CV_Assert((ipoints.rows == 1 && ipoints.channels() == 2) || ipoints.cols*ipoints.channels() == 2);

    _rvec.create(3, 1, CV_64FC1);
    _tvec.create(3, 1, CV_64FC1);

    Mat rvec = useExtrinsicGuess ? _rvec.getMat() : Mat(3, 1, CV_64FC1);
    Mat tvec = useExtrinsicGuess ? _tvec.getMat() : Mat(3, 1, CV_64FC1);
    Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();

    Ptr<PointSetRegistrator::Callback> cb; // pointer to callback
    cb = makePtr<PnPRansacCallback>( cameraMatrix, distCoeffs, flags, useExtrinsicGuess, rvec, tvec);

    int model_points = flags == SOLVEPNP_P3P ? 4 : 6;          // minimum of number of model points
    double param1 = reprojectionError;                // reprojection error
    double param2 = confidence;                       // confidence
    int param3 = iterationsCount;                     // number maximum iterations

    cv::Mat _local_model(3, 2, CV_64FC1);
    cv::Mat _mask_local_inliers(1, opoints.rows, CV_8UC1);

    // call Ransac
    int result = createRANSACPointSetRegistrator(cb, model_points, param1, param2, param3)->run(opoints, ipoints, _local_model, _mask_local_inliers);

    if( result <= 0 || _local_model.rows <= 0)
    {
        _rvec.assign(rvec);    // output rotation vector
        _tvec.assign(tvec);    // output translation vector

        if( _inliers.needed() )
            _inliers.release();

        return false;
    }
    else
    {
        _rvec.assign(_local_model.col(0));    // output rotation vector
        _tvec.assign(_local_model.col(1));    // output translation vector
    }

    if(_inliers.needed())
    {
        Mat _local_inliers;
        int count = 0;
        for (int i = 0; i < _mask_local_inliers.rows; ++i)
        {
            if((int)_mask_local_inliers.at<uchar>(i) == 1) // inliers mask
            {
                _local_inliers.push_back(count);    // output inliers vector
                count++;
            }
        }
        _local_inliers.copyTo(_inliers);
    }
    return true;
}