Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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// License Agreement
// For Open Source Computer Vision Library
//
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#include "precomp.hpp"
#include "upnp.h"
#include "dls.h"
#include "epnp.h"
#include "p3p.h"
#include "ap3p.h"
#include "calib3d_c_api.h"
#include <iostream>
namespace cv
{
void drawFrameAxes(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs,
InputArray rvec, InputArray tvec, float length, int thickness)
{
CV_INSTRUMENT_REGION();
int type = image.type();
int cn = CV_MAT_CN(type);
CV_CheckType(type, cn == 1 || cn == 3 || cn == 4,
"Number of channels must be 1, 3 or 4" );
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);
}
bool solvePnP( InputArray _opoints, InputArray _ipoints,
InputArray _cameraMatrix, InputArray _distCoeffs,
OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int flags )
{
CV_INSTRUMENT_REGION();
Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
CV_Assert( ( (npoints >= 4) || (npoints == 3 && flags == SOLVEPNP_ITERATIVE && useExtrinsicGuess) )
&& npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) );
Mat rvec, tvec;
if( flags != SOLVEPNP_ITERATIVE )
useExtrinsicGuess = false;
if( useExtrinsicGuess )
{
int rtype = _rvec.type(), ttype = _tvec.type();
Size rsize = _rvec.size(), tsize = _tvec.size();
CV_Assert( (rtype == CV_32F || rtype == CV_64F) &&
(ttype == CV_32F || ttype == CV_64F) );
CV_Assert( (rsize == Size(1, 3) || rsize == Size(3, 1)) &&
(tsize == Size(1, 3) || tsize == Size(3, 1)) );
}
else
{
int mtype = CV_64F;
// use CV_32F if all PnP inputs are CV_32F and outputs are empty
if (_ipoints.depth() == _cameraMatrix.depth() && _ipoints.depth() == _opoints.depth() &&
_rvec.empty() && _tvec.empty())
mtype = _opoints.depth();
_rvec.create(3, 1, mtype);
_tvec.create(3, 1, mtype);
}
rvec = _rvec.getMat();
tvec = _tvec.getMat();
Mat cameraMatrix0 = _cameraMatrix.getMat();
Mat distCoeffs0 = _distCoeffs.getMat();
Mat cameraMatrix = Mat_<double>(cameraMatrix0);
Mat distCoeffs = Mat_<double>(distCoeffs0);
bool result = false;
if (flags == SOLVEPNP_EPNP || flags == SOLVEPNP_DLS || flags == SOLVEPNP_UPNP)
{
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
epnp PnP(cameraMatrix, opoints, undistortedPoints);
Mat R;
PnP.compute_pose(R, tvec);
Rodrigues(R, rvec);
result = true;
}
else if (flags == SOLVEPNP_P3P)
{
CV_Assert( npoints == 4);
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
p3p P3Psolver(cameraMatrix);
Mat R;
result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
if (result)
Rodrigues(R, rvec);
}
else if (flags == SOLVEPNP_AP3P)
{
CV_Assert( npoints == 4);
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
ap3p P3Psolver(cameraMatrix);
Mat R;
result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
if (result)
Rodrigues(R, rvec);
}
else if (flags == SOLVEPNP_ITERATIVE)
{
CvMat c_objectPoints = cvMat(opoints), c_imagePoints = cvMat(ipoints);
CvMat c_cameraMatrix = cvMat(cameraMatrix), c_distCoeffs = cvMat(distCoeffs);
CvMat c_rvec = cvMat(rvec), c_tvec = cvMat(tvec);
cvFindExtrinsicCameraParams2(&c_objectPoints, &c_imagePoints, &c_cameraMatrix,
(c_distCoeffs.rows && c_distCoeffs.cols) ? &c_distCoeffs : 0,
&c_rvec, &c_tvec, useExtrinsicGuess );
result = true;
}
/*else if (flags == SOLVEPNP_DLS)
{
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
dls PnP(opoints, undistortedPoints);
Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
bool result = PnP.compute_pose(R, tvec);
if (result)
Rodrigues(R, rvec);
return result;
}
else if (flags == SOLVEPNP_UPNP)
{
upnp PnP(cameraMatrix, opoints, ipoints);
Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
PnP.compute_pose(R, tvec);
Rodrigues(R, rvec);
return true;
}*/
else
CV_Error(CV_StsBadArg, "The flags argument must be one of SOLVEPNP_ITERATIVE, SOLVEPNP_P3P, SOLVEPNP_EPNP or SOLVEPNP_DLS");
return result;
}
class PnPRansacCallback CV_FINAL : public PointSetRegistrator::Callback
{
public:
PnPRansacCallback(Mat _cameraMatrix=Mat(3,3,CV_64F), Mat _distCoeffs=Mat(4,1,CV_64F), int _flags=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 and return number of found models */
int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
{
Mat opoints = _m1.getMat(), ipoints = _m2.getMat();
bool correspondence = solvePnP( _m1, _m2, cameraMatrix, distCoeffs,
rvec, tvec, useExtrinsicGuess, flags );
Mat _local_model;
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 CV_OVERRIDE
{
Mat opoints = _m1.getMat(), ipoints = _m2.getMat(), model = _model.getMat();
int i, count = opoints.checkVector(3);
Mat _rvec = model.col(0);
Mat _tvec = model.col(1);
Mat projpoints(count, 2, CV_32FC1);
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)norm( Matx21f(ipoints_ptr[i] - projpoints_ptr[i]), NORM_L2SQR );
}
Mat cameraMatrix;
Mat distCoeffs;
int flags;
bool useExtrinsicGuess;
Mat rvec;
Mat tvec;
};
bool 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)
{
CV_INSTRUMENT_REGION();
Mat opoints0 = _opoints.getMat(), ipoints0 = _ipoints.getMat();
Mat opoints, ipoints;
if( opoints0.depth() == CV_64F || !opoints0.isContinuous() )
opoints0.convertTo(opoints, CV_32F);
else
opoints = opoints0;
if( ipoints0.depth() == CV_64F || !ipoints0.isContinuous() )
ipoints0.convertTo(ipoints, CV_32F);
else
ipoints = ipoints0;
int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
CV_Assert( npoints >= 4 && 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();
int model_points = 5;
int ransac_kernel_method = SOLVEPNP_EPNP;
if( flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P)
{
model_points = 4;
ransac_kernel_method = flags;
}
else if( npoints == 4 )
{
model_points = 4;
ransac_kernel_method = SOLVEPNP_P3P;
}
if( model_points == npoints )
{
bool result = solvePnP(opoints, ipoints, cameraMatrix, distCoeffs, _rvec, _tvec, useExtrinsicGuess, ransac_kernel_method);
if(!result)
{
if( _inliers.needed() )
_inliers.release();
return false;
}
if(_inliers.needed())
{
_inliers.create(npoints, 1, CV_32S);
Mat _local_inliers = _inliers.getMat();
for(int i = 0; i < npoints; i++)
{
_local_inliers.at<int>(i) = i;
}
}
return true;
}
Ptr<PointSetRegistrator::Callback> cb; // pointer to callback
cb = makePtr<PnPRansacCallback>( cameraMatrix, distCoeffs, ransac_kernel_method, useExtrinsicGuess, rvec, tvec);
double param1 = reprojectionError; // reprojection error
double param2 = confidence; // confidence
int param3 = iterationsCount; // number maximum iterations
Mat _local_model(3, 2, CV_64FC1);
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;
}
vector<Point3d> opoints_inliers;
vector<Point2d> ipoints_inliers;
opoints = opoints.reshape(3);
ipoints = ipoints.reshape(2);
opoints.convertTo(opoints_inliers, CV_64F);
ipoints.convertTo(ipoints_inliers, CV_64F);
const uchar* mask = _mask_local_inliers.ptr<uchar>();
int npoints1 = compressElems(&opoints_inliers[0], mask, 1, npoints);
compressElems(&ipoints_inliers[0], mask, 1, npoints);
opoints_inliers.resize(npoints1);
ipoints_inliers.resize(npoints1);
result = solvePnP(opoints_inliers, ipoints_inliers, cameraMatrix,
distCoeffs, rvec, tvec, useExtrinsicGuess,
(flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P) ? SOLVEPNP_EPNP : flags) ? 1 : -1;
if( result <= 0 )
{
_rvec.assign(_local_model.col(0)); // output rotation vector
_tvec.assign(_local_model.col(1)); // output translation vector
if( _inliers.needed() )
_inliers.release();
return false;
}
else
{
_rvec.assign(rvec); // output rotation vector
_tvec.assign(tvec); // output translation vector
}
if(_inliers.needed())
{
Mat _local_inliers;
for (int i = 0; i < npoints; ++i)
{
if((int)_mask_local_inliers.at<uchar>(i) != 0) // inliers mask
_local_inliers.push_back(i); // output inliers vector
}
_local_inliers.copyTo(_inliers);
}
return true;
}
int solveP3P( InputArray _opoints, InputArray _ipoints,
InputArray _cameraMatrix, InputArray _distCoeffs,
OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, int flags) {
CV_INSTRUMENT_REGION();
Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
CV_Assert( npoints == 3 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) );
CV_Assert( flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P );
Mat cameraMatrix0 = _cameraMatrix.getMat();
Mat distCoeffs0 = _distCoeffs.getMat();
Mat cameraMatrix = Mat_<double>(cameraMatrix0);
Mat distCoeffs = Mat_<double>(distCoeffs0);
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
std::vector<Mat> Rs, ts;
int solutions = 0;
if (flags == SOLVEPNP_P3P)
{
p3p P3Psolver(cameraMatrix);
solutions = P3Psolver.solve(Rs, ts, opoints, undistortedPoints);
}
else if (flags == SOLVEPNP_AP3P)
{
ap3p P3Psolver(cameraMatrix);
solutions = P3Psolver.solve(Rs, ts, opoints, undistortedPoints);
}
if (solutions == 0) {
return 0;
}
if (_rvecs.needed()) {
_rvecs.create(solutions, 1, CV_64F);
}
if (_tvecs.needed()) {
_tvecs.create(solutions, 1, CV_64F);
}
for (int i = 0; i < solutions; i++) {
Mat rvec;
Rodrigues(Rs[i], rvec);
_tvecs.getMatRef(i) = ts[i];
_rvecs.getMatRef(i) = rvec;
}
return solutions;
}
}