| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280 | /*M///////////////////////////////////////////////////////////////////////////////////////////  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.////  By downloading, copying, installing or using the software you agree to this license.//  If you do not agree to this license, do not download, install,//  copy or use the software.//////                          License Agreement//                For Open Source Computer Vision Library//// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.// Copyright (C) 2009, Willow Garage Inc., all rights reserved.// Copyright (C) 2013, OpenCV Foundation, all rights reserved.// Third party copyrights are property of their respective owners.//// Redistribution and use in source and binary forms, with or without modification,// are permitted provided that the following conditions are met:////   * Redistribution's of source code must retain the above copyright notice,//     this list of conditions and the following disclaimer.////   * Redistribution's in binary form must reproduce the above copyright notice,//     this list of conditions and the following disclaimer in the documentation//     and/or other materials provided with the distribution.////   * The name of the copyright holders may not be used to endorse or promote products//     derived from this software without specific prior written permission.//// This software is provided by the copyright holders and contributors "as is" and// any express or implied warranties, including, but not limited to, the implied// warranties of merchantability and fitness for a particular purpose are disclaimed.// In no event shall the Intel Corporation or contributors be liable for any direct,// indirect, incidental, special, exemplary, or consequential damages// (including, but not limited to, procurement of substitute goods or services;// loss of use, data, or profits; or business interruption) however caused// and on any theory of liability, whether in contract, strict liability,// or tort (including negligence or otherwise) arising in any way out of// the use of this software, even if advised of the possibility of such damage.////M*/#ifndef OPENCV_CORE_EIGEN_HPP#define OPENCV_CORE_EIGEN_HPP#include "opencv2/core.hpp"#if defined _MSC_VER && _MSC_VER >= 1200#pragma warning( disable: 4714 ) //__forceinline is not inlined#pragma warning( disable: 4127 ) //conditional expression is constant#pragma warning( disable: 4244 ) //conversion from '__int64' to 'int', possible loss of data#endifnamespace cv{//! @addtogroup core_eigen//! @{template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inlinevoid eigen2cv( const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& src, Mat& dst ){    if( !(src.Flags & Eigen::RowMajorBit) )    {        Mat _src(src.cols(), src.rows(), traits::Type<_Tp>::value,              (void*)src.data(), src.stride()*sizeof(_Tp));        transpose(_src, dst);    }    else    {        Mat _src(src.rows(), src.cols(), traits::Type<_Tp>::value,                 (void*)src.data(), src.stride()*sizeof(_Tp));        _src.copyTo(dst);    }}// Matx casetemplate<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inlinevoid eigen2cv( const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& src,               Matx<_Tp, _rows, _cols>& dst ){    if( !(src.Flags & Eigen::RowMajorBit) )    {        dst = Matx<_Tp, _cols, _rows>(static_cast<const _Tp*>(src.data())).t();    }    else    {        dst = Matx<_Tp, _rows, _cols>(static_cast<const _Tp*>(src.data()));    }}template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inlinevoid cv2eigen( const Mat& src,               Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& dst ){    CV_DbgAssert(src.rows == _rows && src.cols == _cols);    if( !(dst.Flags & Eigen::RowMajorBit) )    {        const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        if( src.type() == _dst.type() )            transpose(src, _dst);        else if( src.cols == src.rows )        {            src.convertTo(_dst, _dst.type());            transpose(_dst, _dst);        }        else            Mat(src.t()).convertTo(_dst, _dst.type());    }    else    {        const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        src.convertTo(_dst, _dst.type());    }}// Matx casetemplate<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inlinevoid cv2eigen( const Matx<_Tp, _rows, _cols>& src,               Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& dst ){    if( !(dst.Flags & Eigen::RowMajorBit) )    {        const Mat _dst(_cols, _rows, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        transpose(src, _dst);    }    else    {        const Mat _dst(_rows, _cols, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        Mat(src).copyTo(_dst);    }}template<typename _Tp>  static inlinevoid cv2eigen( const Mat& src,               Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic>& dst ){    dst.resize(src.rows, src.cols);    if( !(dst.Flags & Eigen::RowMajorBit) )    {        const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value,             dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        if( src.type() == _dst.type() )            transpose(src, _dst);        else if( src.cols == src.rows )        {            src.convertTo(_dst, _dst.type());            transpose(_dst, _dst);        }        else            Mat(src.t()).convertTo(_dst, _dst.type());    }    else    {        const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        src.convertTo(_dst, _dst.type());    }}// Matx casetemplate<typename _Tp, int _rows, int _cols> static inlinevoid cv2eigen( const Matx<_Tp, _rows, _cols>& src,               Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic>& dst ){    dst.resize(_rows, _cols);    if( !(dst.Flags & Eigen::RowMajorBit) )    {        const Mat _dst(_cols, _rows, traits::Type<_Tp>::value,             dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        transpose(src, _dst);    }    else    {        const Mat _dst(_rows, _cols, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        Mat(src).copyTo(_dst);    }}template<typename _Tp> static inlinevoid cv2eigen( const Mat& src,               Eigen::Matrix<_Tp, Eigen::Dynamic, 1>& dst ){    CV_Assert(src.cols == 1);    dst.resize(src.rows);    if( !(dst.Flags & Eigen::RowMajorBit) )    {        const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        if( src.type() == _dst.type() )            transpose(src, _dst);        else            Mat(src.t()).convertTo(_dst, _dst.type());    }    else    {        const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        src.convertTo(_dst, _dst.type());    }}// Matx casetemplate<typename _Tp, int _rows> static inlinevoid cv2eigen( const Matx<_Tp, _rows, 1>& src,               Eigen::Matrix<_Tp, Eigen::Dynamic, 1>& dst ){    dst.resize(_rows);    if( !(dst.Flags & Eigen::RowMajorBit) )    {        const Mat _dst(1, _rows, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        transpose(src, _dst);    }    else    {        const Mat _dst(_rows, 1, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        src.copyTo(_dst);    }}template<typename _Tp> static inlinevoid cv2eigen( const Mat& src,               Eigen::Matrix<_Tp, 1, Eigen::Dynamic>& dst ){    CV_Assert(src.rows == 1);    dst.resize(src.cols);    if( !(dst.Flags & Eigen::RowMajorBit) )    {        const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        if( src.type() == _dst.type() )            transpose(src, _dst);        else            Mat(src.t()).convertTo(_dst, _dst.type());    }    else    {        const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        src.convertTo(_dst, _dst.type());    }}//Matxtemplate<typename _Tp, int _cols> static inlinevoid cv2eigen( const Matx<_Tp, 1, _cols>& src,               Eigen::Matrix<_Tp, 1, Eigen::Dynamic>& dst ){    dst.resize(_cols);    if( !(dst.Flags & Eigen::RowMajorBit) )    {        const Mat _dst(_cols, 1, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        transpose(src, _dst);    }    else    {        const Mat _dst(1, _cols, traits::Type<_Tp>::value,                 dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));        Mat(src).copyTo(_dst);    }}//! @}} // cv#endif
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