openCV library for Renesas RZ/A
Dependents: RZ_A2M_Mbed_samples
include/opencv2/core/affine.hpp
- Committer:
- RyoheiHagimoto
- Date:
- 2021-01-29
- Revision:
- 0:0e0631af0305
File content as of revision 0:0e0631af0305:
/*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_AFFINE3_HPP #define OPENCV_CORE_AFFINE3_HPP #ifdef __cplusplus #include <opencv2/core.hpp> namespace cv { //! @addtogroup core //! @{ /** @brief Affine transform @todo document */ template<typename T> class Affine3 { public: typedef T float_type; typedef Matx<float_type, 3, 3> Mat3; typedef Matx<float_type, 4, 4> Mat4; typedef Vec<float_type, 3> Vec3; Affine3(); //! Augmented affine matrix Affine3(const Mat4& affine); //! Rotation matrix Affine3(const Mat3& R, const Vec3& t = Vec3::all(0)); //! Rodrigues vector Affine3(const Vec3& rvec, const Vec3& t = Vec3::all(0)); //! Combines all contructors above. Supports 4x4, 4x3, 3x3, 1x3, 3x1 sizes of data matrix explicit Affine3(const Mat& data, const Vec3& t = Vec3::all(0)); //! From 16th element array explicit Affine3(const float_type* vals); //! Create identity transform static Affine3 Identity(); //! Rotation matrix void rotation(const Mat3& R); //! Rodrigues vector void rotation(const Vec3& rvec); //! Combines rotation methods above. Suports 3x3, 1x3, 3x1 sizes of data matrix; void rotation(const Mat& data); void linear(const Mat3& L); void translation(const Vec3& t); Mat3 rotation() const; Mat3 linear() const; Vec3 translation() const; //! Rodrigues vector Vec3 rvec() const; Affine3 inv(int method = cv::DECOMP_SVD) const; //! a.rotate(R) is equivalent to Affine(R, 0) * a; Affine3 rotate(const Mat3& R) const; //! a.rotate(rvec) is equivalent to Affine(rvec, 0) * a; Affine3 rotate(const Vec3& rvec) const; //! a.translate(t) is equivalent to Affine(E, t) * a; Affine3 translate(const Vec3& t) const; //! a.concatenate(affine) is equivalent to affine * a; Affine3 concatenate(const Affine3& affine) const; template <typename Y> operator Affine3<Y>() const; template <typename Y> Affine3<Y> cast() const; Mat4 matrix; #if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H Affine3(const Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>& affine); Affine3(const Eigen::Transform<T, 3, Eigen::Affine>& affine); operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>() const; operator Eigen::Transform<T, 3, Eigen::Affine>() const; #endif }; template<typename T> static Affine3<T> operator*(const Affine3<T>& affine1, const Affine3<T>& affine2); template<typename T, typename V> static V operator*(const Affine3<T>& affine, const V& vector); typedef Affine3<float> Affine3f; typedef Affine3<double> Affine3d; static Vec3f operator*(const Affine3f& affine, const Vec3f& vector); static Vec3d operator*(const Affine3d& affine, const Vec3d& vector); template<typename _Tp> class DataType< Affine3<_Tp> > { public: typedef Affine3<_Tp> value_type; typedef Affine3<typename DataType<_Tp>::work_type> work_type; typedef _Tp channel_type; enum { generic_type = 0, depth = DataType<channel_type>::depth, channels = 16, fmt = DataType<channel_type>::fmt + ((channels - 1) << 8), type = CV_MAKETYPE(depth, channels) }; typedef Vec<channel_type, channels> vec_type; }; //! @} core } //! @cond IGNORED /////////////////////////////////////////////////////////////////////////////////// // Implementaiton template<typename T> inline cv::Affine3<T>::Affine3() : matrix(Mat4::eye()) {} template<typename T> inline cv::Affine3<T>::Affine3(const Mat4& affine) : matrix(affine) {} template<typename T> inline cv::Affine3<T>::Affine3(const Mat3& R, const Vec3& t) { rotation(R); translation(t); matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; matrix.val[15] = 1; } template<typename T> inline cv::Affine3<T>::Affine3(const Vec3& _rvec, const Vec3& t) { rotation(_rvec); translation(t); matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; matrix.val[15] = 1; } template<typename T> inline cv::Affine3<T>::Affine3(const cv::Mat& data, const Vec3& t) { CV_Assert(data.type() == cv::DataType<T>::type); if (data.cols == 4 && data.rows == 4) { data.copyTo(matrix); return; } else if (data.cols == 4 && data.rows == 3) { rotation(data(Rect(0, 0, 3, 3))); translation(data(Rect(3, 0, 1, 3))); return; } rotation(data); translation(t); matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; matrix.val[15] = 1; } template<typename T> inline cv::Affine3<T>::Affine3(const float_type* vals) : matrix(vals) {} template<typename T> inline cv::Affine3<T> cv::Affine3<T>::Identity() { return Affine3<T>(cv::Affine3<T>::Mat4::eye()); } template<typename T> inline void cv::Affine3<T>::rotation(const Mat3& R) { linear(R); } template<typename T> inline void cv::Affine3<T>::rotation(const Vec3& _rvec) { double theta = norm(_rvec); if (theta < DBL_EPSILON) rotation(Mat3::eye()); else { double c = std::cos(theta); double s = std::sin(theta); double c1 = 1. - c; double itheta = (theta != 0) ? 1./theta : 0.; Point3_<T> r = _rvec*itheta; Mat3 rrt( r.x*r.x, r.x*r.y, r.x*r.z, r.x*r.y, r.y*r.y, r.y*r.z, r.x*r.z, r.y*r.z, r.z*r.z ); Mat3 r_x( 0, -r.z, r.y, r.z, 0, -r.x, -r.y, r.x, 0 ); // R = cos(theta)*I + (1 - cos(theta))*r*rT + sin(theta)*[r_x] // where [r_x] is [0 -rz ry; rz 0 -rx; -ry rx 0] Mat3 R = c*Mat3::eye() + c1*rrt + s*r_x; rotation(R); } } //Combines rotation methods above. Suports 3x3, 1x3, 3x1 sizes of data matrix; template<typename T> inline void cv::Affine3<T>::rotation(const cv::Mat& data) { CV_Assert(data.type() == cv::DataType<T>::type); if (data.cols == 3 && data.rows == 3) { Mat3 R; data.copyTo(R); rotation(R); } else if ((data.cols == 3 && data.rows == 1) || (data.cols == 1 && data.rows == 3)) { Vec3 _rvec; data.reshape(1, 3).copyTo(_rvec); rotation(_rvec); } else CV_Assert(!"Input marix can be 3x3, 1x3 or 3x1"); } template<typename T> inline void cv::Affine3<T>::linear(const Mat3& L) { matrix.val[0] = L.val[0]; matrix.val[1] = L.val[1]; matrix.val[ 2] = L.val[2]; matrix.val[4] = L.val[3]; matrix.val[5] = L.val[4]; matrix.val[ 6] = L.val[5]; matrix.val[8] = L.val[6]; matrix.val[9] = L.val[7]; matrix.val[10] = L.val[8]; } template<typename T> inline void cv::Affine3<T>::translation(const Vec3& t) { matrix.val[3] = t[0]; matrix.val[7] = t[1]; matrix.val[11] = t[2]; } template<typename T> inline typename cv::Affine3<T>::Mat3 cv::Affine3<T>::rotation() const { return linear(); } template<typename T> inline typename cv::Affine3<T>::Mat3 cv::Affine3<T>::linear() const { typename cv::Affine3<T>::Mat3 R; R.val[0] = matrix.val[0]; R.val[1] = matrix.val[1]; R.val[2] = matrix.val[ 2]; R.val[3] = matrix.val[4]; R.val[4] = matrix.val[5]; R.val[5] = matrix.val[ 6]; R.val[6] = matrix.val[8]; R.val[7] = matrix.val[9]; R.val[8] = matrix.val[10]; return R; } template<typename T> inline typename cv::Affine3<T>::Vec3 cv::Affine3<T>::translation() const { return Vec3(matrix.val[3], matrix.val[7], matrix.val[11]); } template<typename T> inline typename cv::Affine3<T>::Vec3 cv::Affine3<T>::rvec() const { cv::Vec3d w; cv::Matx33d u, vt, R = rotation(); cv::SVD::compute(R, w, u, vt, cv::SVD::FULL_UV + cv::SVD::MODIFY_A); R = u * vt; double rx = R.val[7] - R.val[5]; double ry = R.val[2] - R.val[6]; double rz = R.val[3] - R.val[1]; double s = std::sqrt((rx*rx + ry*ry + rz*rz)*0.25); double c = (R.val[0] + R.val[4] + R.val[8] - 1) * 0.5; c = c > 1.0 ? 1.0 : c < -1.0 ? -1.0 : c; double theta = acos(c); if( s < 1e-5 ) { if( c > 0 ) rx = ry = rz = 0; else { double t; t = (R.val[0] + 1) * 0.5; rx = std::sqrt(std::max(t, 0.0)); t = (R.val[4] + 1) * 0.5; ry = std::sqrt(std::max(t, 0.0)) * (R.val[1] < 0 ? -1.0 : 1.0); t = (R.val[8] + 1) * 0.5; rz = std::sqrt(std::max(t, 0.0)) * (R.val[2] < 0 ? -1.0 : 1.0); if( fabs(rx) < fabs(ry) && fabs(rx) < fabs(rz) && (R.val[5] > 0) != (ry*rz > 0) ) rz = -rz; theta /= std::sqrt(rx*rx + ry*ry + rz*rz); rx *= theta; ry *= theta; rz *= theta; } } else { double vth = 1/(2*s); vth *= theta; rx *= vth; ry *= vth; rz *= vth; } return cv::Vec3d(rx, ry, rz); } template<typename T> inline cv::Affine3<T> cv::Affine3<T>::inv(int method) const { return matrix.inv(method); } template<typename T> inline cv::Affine3<T> cv::Affine3<T>::rotate(const Mat3& R) const { Mat3 Lc = linear(); Vec3 tc = translation(); Mat4 result; result.val[12] = result.val[13] = result.val[14] = 0; result.val[15] = 1; for(int j = 0; j < 3; ++j) { for(int i = 0; i < 3; ++i) { float_type value = 0; for(int k = 0; k < 3; ++k) value += R(j, k) * Lc(k, i); result(j, i) = value; } result(j, 3) = R.row(j).dot(tc.t()); } return result; } template<typename T> inline cv::Affine3<T> cv::Affine3<T>::rotate(const Vec3& _rvec) const { return rotate(Affine3f(_rvec).rotation()); } template<typename T> inline cv::Affine3<T> cv::Affine3<T>::translate(const Vec3& t) const { Mat4 m = matrix; m.val[ 3] += t[0]; m.val[ 7] += t[1]; m.val[11] += t[2]; return m; } template<typename T> inline cv::Affine3<T> cv::Affine3<T>::concatenate(const Affine3<T>& affine) const { return (*this).rotate(affine.rotation()).translate(affine.translation()); } template<typename T> template <typename Y> inline cv::Affine3<T>::operator Affine3<Y>() const { return Affine3<Y>(matrix); } template<typename T> template <typename Y> inline cv::Affine3<Y> cv::Affine3<T>::cast() const { return Affine3<Y>(matrix); } template<typename T> inline cv::Affine3<T> cv::operator*(const cv::Affine3<T>& affine1, const cv::Affine3<T>& affine2) { return affine2.concatenate(affine1); } template<typename T, typename V> inline V cv::operator*(const cv::Affine3<T>& affine, const V& v) { const typename Affine3<T>::Mat4& m = affine.matrix; V r; r.x = m.val[0] * v.x + m.val[1] * v.y + m.val[ 2] * v.z + m.val[ 3]; r.y = m.val[4] * v.x + m.val[5] * v.y + m.val[ 6] * v.z + m.val[ 7]; r.z = m.val[8] * v.x + m.val[9] * v.y + m.val[10] * v.z + m.val[11]; return r; } static inline cv::Vec3f cv::operator*(const cv::Affine3f& affine, const cv::Vec3f& v) { const cv::Matx44f& m = affine.matrix; cv::Vec3f r; r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3]; r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7]; r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11]; return r; } static inline cv::Vec3d cv::operator*(const cv::Affine3d& affine, const cv::Vec3d& v) { const cv::Matx44d& m = affine.matrix; cv::Vec3d r; r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3]; r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7]; r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11]; return r; } #if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H template<typename T> inline cv::Affine3<T>::Affine3(const Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>& affine) { cv::Mat(4, 4, cv::DataType<T>::type, affine.matrix().data()).copyTo(matrix); } template<typename T> inline cv::Affine3<T>::Affine3(const Eigen::Transform<T, 3, Eigen::Affine>& affine) { Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)> a = affine; cv::Mat(4, 4, cv::DataType<T>::type, a.matrix().data()).copyTo(matrix); } template<typename T> inline cv::Affine3<T>::operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>() const { Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)> r; cv::Mat hdr(4, 4, cv::DataType<T>::type, r.matrix().data()); cv::Mat(matrix, false).copyTo(hdr); return r; } template<typename T> inline cv::Affine3<T>::operator Eigen::Transform<T, 3, Eigen::Affine>() const { return this->operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>(); } #endif /* defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H */ //! @endcond #endif /* __cplusplus */ #endif /* OPENCV_CORE_AFFINE3_HPP */