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Use Eigen::SelfAdjointEigenSolver in cv::eigen

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This commit is contained in:
woody.chow 2017-10-09 18:10:16 +09:00 committed by Alexander Alekhin
parent a3ec2ac3c5
commit 611cf8d86f
2 changed files with 52 additions and 4 deletions
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48
modules/core/src/lapack.cpp
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@ -43,6 +43,12 @@
#include "precomp.hpp" #include "precomp.hpp"
#include <limits> #include <limits>
#ifdef HAVE_EIGEN
#include <Eigen/Core>
#include <Eigen/Eigenvalues>
#include "opencv2/core/eigen.hpp"
#endif
#if defined _M_IX86 && defined _MSC_VER && _MSC_VER < 1700 #if defined _M_IX86 && defined _MSC_VER && _MSC_VER < 1700
#pragma float_control(precise, on) #pragma float_control(precise, on)
#endif #endif
@ -1396,6 +1402,47 @@ bool cv::eigen( InputArray _src, OutputArray _evals, OutputArray _evects )
v = _evects.getMat(); v = _evects.getMat();
} }
#ifdef HAVE_EIGEN
const bool evecNeeded = _evects.needed();
const int esOptions = evecNeeded ? Eigen::ComputeEigenvectors : Eigen::EigenvaluesOnly;
_evals.create(n, 1, type);
cv::Mat evals = _evals.getMat();
if ( type == CV_64F )
{
Eigen::MatrixXd src_eig, zeros_eig;
cv::cv2eigen(src, src_eig);
Eigen::SelfAdjointEigenSolver<Eigen::MatrixXd> es;
es.compute(src_eig, esOptions);
if ( es.info() == Eigen::Success )
{
cv::eigen2cv(es.eigenvalues().reverse().eval(), evals);
if ( evecNeeded )
{
cv::Mat evects = _evects.getMat();
cv::eigen2cv(es.eigenvectors().rowwise().reverse().transpose().eval(), v);
}
return true;
}
} else { // CV_32F
Eigen::MatrixXf src_eig, zeros_eig;
cv::cv2eigen(src, src_eig);
Eigen::SelfAdjointEigenSolver<Eigen::MatrixXf> es;
es.compute(src_eig, esOptions);
if ( es.info() == Eigen::Success )
{
cv::eigen2cv(es.eigenvalues().reverse().eval(), evals);
if ( evecNeeded )
{
cv::eigen2cv(es.eigenvectors().rowwise().reverse().transpose().eval(), v);
}
return true;
}
}
return false;
#else
size_t elemSize = src.elemSize(), astep = alignSize(n*elemSize, 16); size_t elemSize = src.elemSize(), astep = alignSize(n*elemSize, 16);
AutoBuffer<uchar> buf(n*astep + n*5*elemSize + 32); AutoBuffer<uchar> buf(n*astep + n*5*elemSize + 32);
uchar* ptr = alignPtr((uchar*)buf, 16); uchar* ptr = alignPtr((uchar*)buf, 16);
@ -1408,6 +1455,7 @@ bool cv::eigen( InputArray _src, OutputArray _evals, OutputArray _evects )
w.copyTo(_evals); w.copyTo(_evals);
return ok; return ok;
#endif
} }
namespace cv namespace cv

8
modules/core/test/test_eigen.cpp
View File

@ -59,7 +59,7 @@ using namespace std;
#define MESSAGE_ERROR_DIFF_1 "Accuracy of eigen values computing less than required." #define MESSAGE_ERROR_DIFF_1 "Accuracy of eigen values computing less than required."
#define MESSAGE_ERROR_DIFF_2 "Accuracy of eigen vectors computing less than required." #define MESSAGE_ERROR_DIFF_2 "Accuracy of eigen vectors computing less than required."
#define MESSAGE_ERROR_ORTHO "Matrix of eigen vectors is not orthogonal." #define MESSAGE_ERROR_ORTHO "Matrix of eigen vectors is not orthogonal."
#define MESSAGE_ERROR_ORDER "Eigen values are not sorted in ascending order." #define MESSAGE_ERROR_ORDER "Eigen values are not sorted in descending order."
const int COUNT_NORM_TYPES = 3; const int COUNT_NORM_TYPES = 3;
const int NORM_TYPE[COUNT_NORM_TYPES] = {cv::NORM_L1, cv::NORM_L2, cv::NORM_INF}; const int NORM_TYPE[COUNT_NORM_TYPES] = {cv::NORM_L1, cv::NORM_L2, cv::NORM_INF};
@ -257,7 +257,7 @@ bool Core_EigenTest::check_pairs_order(const cv::Mat& eigen_values)
if (!(eigen_values.at<float>(i, 0) > eigen_values.at<float>(i+1, 0))) if (!(eigen_values.at<float>(i, 0) > eigen_values.at<float>(i+1, 0)))
{ {
std::cout << endl; std::cout << "Checking order of eigen values vector " << eigen_values << "..." << endl; std::cout << endl; std::cout << "Checking order of eigen values vector " << eigen_values << "..." << endl;
std::cout << "Pair of indexes with non ascending of eigen values: (" << i << ", " << i+1 << ")." << endl; std::cout << "Pair of indexes with non descending of eigen values: (" << i << ", " << i+1 << ")." << endl;
std::cout << endl; std::cout << endl;
CV_Error(CORE_EIGEN_ERROR_ORDER, MESSAGE_ERROR_ORDER); CV_Error(CORE_EIGEN_ERROR_ORDER, MESSAGE_ERROR_ORDER);
return false; return false;
@ -272,9 +272,9 @@ bool Core_EigenTest::check_pairs_order(const cv::Mat& eigen_values)
if (!(eigen_values.at<double>(i, 0) > eigen_values.at<double>(i+1, 0))) if (!(eigen_values.at<double>(i, 0) > eigen_values.at<double>(i+1, 0)))
{ {
std::cout << endl; std::cout << "Checking order of eigen values vector " << eigen_values << "..." << endl; std::cout << endl; std::cout << "Checking order of eigen values vector " << eigen_values << "..." << endl;
std::cout << "Pair of indexes with non ascending of eigen values: (" << i << ", " << i+1 << ")." << endl; std::cout << "Pair of indexes with non descending of eigen values: (" << i << ", " << i+1 << ")." << endl;
std::cout << endl; std::cout << endl;
CV_Error(CORE_EIGEN_ERROR_ORDER, "Eigen values are not sorted in ascending order."); CV_Error(CORE_EIGEN_ERROR_ORDER, "Eigen values are not sorted in descending order.");
return false; return false;
} }