Joe Verbout
opencv on mbed
Diff: opencv2/core/operations.hpp
- Revision:
- 0:ea44dc9ed014
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/opencv2/core/operations.hpp Thu Mar 31 21:16:38 2016 +0000
@@ -0,0 +1,531 @@
+/*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.
+// Copyright (C) 2015, Itseez Inc., 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_OPERATIONS_HPP__
+#define __OPENCV_CORE_OPERATIONS_HPP__
+
+#ifndef __cplusplus
+# error operations.hpp header must be compiled as C++
+#endif
+
+#include <cstdio>
+
+//! @cond IGNORED
+
+namespace cv
+{
+
+////////////////////////////// Matx methods depending on core API /////////////////////////////
+
+namespace internal
+{
+
+template<typename _Tp, int m> struct Matx_FastInvOp
+{
+ bool operator()(const Matx<_Tp, m, m>& a, Matx<_Tp, m, m>& b, int method) const
+ {
+ Matx<_Tp, m, m> temp = a;
+
+ // assume that b is all 0's on input => make it a unity matrix
+ for( int i = 0; i < m; i++ )
+ b(i, i) = (_Tp)1;
+
+ if( method == DECOMP_CHOLESKY )
+ return Cholesky(temp.val, m*sizeof(_Tp), m, b.val, m*sizeof(_Tp), m);
+
+ return LU(temp.val, m*sizeof(_Tp), m, b.val, m*sizeof(_Tp), m) != 0;
+ }
+};
+
+template<typename _Tp> struct Matx_FastInvOp<_Tp, 2>
+{
+ bool operator()(const Matx<_Tp, 2, 2>& a, Matx<_Tp, 2, 2>& b, int) const
+ {
+ _Tp d = determinant(a);
+ if( d == 0 )
+ return false;
+ d = 1/d;
+ b(1,1) = a(0,0)*d;
+ b(0,0) = a(1,1)*d;
+ b(0,1) = -a(0,1)*d;
+ b(1,0) = -a(1,0)*d;
+ return true;
+ }
+};
+
+template<typename _Tp> struct Matx_FastInvOp<_Tp, 3>
+{
+ bool operator()(const Matx<_Tp, 3, 3>& a, Matx<_Tp, 3, 3>& b, int) const
+ {
+ _Tp d = (_Tp)determinant(a);
+ if( d == 0 )
+ return false;
+ d = 1/d;
+ b(0,0) = (a(1,1) * a(2,2) - a(1,2) * a(2,1)) * d;
+ b(0,1) = (a(0,2) * a(2,1) - a(0,1) * a(2,2)) * d;
+ b(0,2) = (a(0,1) * a(1,2) - a(0,2) * a(1,1)) * d;
+
+ b(1,0) = (a(1,2) * a(2,0) - a(1,0) * a(2,2)) * d;
+ b(1,1) = (a(0,0) * a(2,2) - a(0,2) * a(2,0)) * d;
+ b(1,2) = (a(0,2) * a(1,0) - a(0,0) * a(1,2)) * d;
+
+ b(2,0) = (a(1,0) * a(2,1) - a(1,1) * a(2,0)) * d;
+ b(2,1) = (a(0,1) * a(2,0) - a(0,0) * a(2,1)) * d;
+ b(2,2) = (a(0,0) * a(1,1) - a(0,1) * a(1,0)) * d;
+ return true;
+ }
+};
+
+
+template<typename _Tp, int m, int n> struct Matx_FastSolveOp
+{
+ bool operator()(const Matx<_Tp, m, m>& a, const Matx<_Tp, m, n>& b,
+ Matx<_Tp, m, n>& x, int method) const
+ {
+ Matx<_Tp, m, m> temp = a;
+ x = b;
+ if( method == DECOMP_CHOLESKY )
+ return Cholesky(temp.val, m*sizeof(_Tp), m, x.val, n*sizeof(_Tp), n);
+
+ return LU(temp.val, m*sizeof(_Tp), m, x.val, n*sizeof(_Tp), n) != 0;
+ }
+};
+
+template<typename _Tp> struct Matx_FastSolveOp<_Tp, 2, 1>
+{
+ bool operator()(const Matx<_Tp, 2, 2>& a, const Matx<_Tp, 2, 1>& b,
+ Matx<_Tp, 2, 1>& x, int) const
+ {
+ _Tp d = determinant(a);
+ if( d == 0 )
+ return false;
+ d = 1/d;
+ x(0) = (b(0)*a(1,1) - b(1)*a(0,1))*d;
+ x(1) = (b(1)*a(0,0) - b(0)*a(1,0))*d;
+ return true;
+ }
+};
+
+template<typename _Tp> struct Matx_FastSolveOp<_Tp, 3, 1>
+{
+ bool operator()(const Matx<_Tp, 3, 3>& a, const Matx<_Tp, 3, 1>& b,
+ Matx<_Tp, 3, 1>& x, int) const
+ {
+ _Tp d = (_Tp)determinant(a);
+ if( d == 0 )
+ return false;
+ d = 1/d;
+ x(0) = d*(b(0)*(a(1,1)*a(2,2) - a(1,2)*a(2,1)) -
+ a(0,1)*(b(1)*a(2,2) - a(1,2)*b(2)) +
+ a(0,2)*(b(1)*a(2,1) - a(1,1)*b(2)));
+
+ x(1) = d*(a(0,0)*(b(1)*a(2,2) - a(1,2)*b(2)) -
+ b(0)*(a(1,0)*a(2,2) - a(1,2)*a(2,0)) +
+ a(0,2)*(a(1,0)*b(2) - b(1)*a(2,0)));
+
+ x(2) = d*(a(0,0)*(a(1,1)*b(2) - b(1)*a(2,1)) -
+ a(0,1)*(a(1,0)*b(2) - b(1)*a(2,0)) +
+ b(0)*(a(1,0)*a(2,1) - a(1,1)*a(2,0)));
+ return true;
+ }
+};
+
+} // internal
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n> Matx<_Tp,m,n>::randu(_Tp a, _Tp b)
+{
+ Matx<_Tp,m,n> M;
+ cv::randu(M, Scalar(a), Scalar(b));
+ return M;
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n> Matx<_Tp,m,n>::randn(_Tp a, _Tp b)
+{
+ Matx<_Tp,m,n> M;
+ cv::randn(M, Scalar(a), Scalar(b));
+ return M;
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, n, m> Matx<_Tp, m, n>::inv(int method, bool *p_is_ok /*= NULL*/) const
+{
+ Matx<_Tp, n, m> b;
+ bool ok;
+ if( method == DECOMP_LU || method == DECOMP_CHOLESKY )
+ ok = cv::internal::Matx_FastInvOp<_Tp, m>()(*this, b, method);
+ else
+ {
+ Mat A(*this, false), B(b, false);
+ ok = (invert(A, B, method) != 0);
+ }
+ if( NULL != p_is_ok ) { *p_is_ok = ok; }
+ return ok ? b : Matx<_Tp, n, m>::zeros();
+}
+
+template<typename _Tp, int m, int n> template<int l> inline
+Matx<_Tp, n, l> Matx<_Tp, m, n>::solve(const Matx<_Tp, m, l>& rhs, int method) const
+{
+ Matx<_Tp, n, l> x;
+ bool ok;
+ if( method == DECOMP_LU || method == DECOMP_CHOLESKY )
+ ok = cv::internal::Matx_FastSolveOp<_Tp, m, l>()(*this, rhs, x, method);
+ else
+ {
+ Mat A(*this, false), B(rhs, false), X(x, false);
+ ok = cv::solve(A, B, X, method);
+ }
+
+ return ok ? x : Matx<_Tp, n, l>::zeros();
+}
+
+
+
+////////////////////////// Augmenting algebraic & logical operations //////////////////////////
+
+#define CV_MAT_AUG_OPERATOR1(op, cvop, A, B) \
+ static inline A& operator op (A& a, const B& b) { cvop; return a; }
+
+#define CV_MAT_AUG_OPERATOR(op, cvop, A, B) \
+ CV_MAT_AUG_OPERATOR1(op, cvop, A, B) \
+ CV_MAT_AUG_OPERATOR1(op, cvop, const A, B)
+
+#define CV_MAT_AUG_OPERATOR_T(op, cvop, A, B) \
+ template<typename _Tp> CV_MAT_AUG_OPERATOR1(op, cvop, A, B) \
+ template<typename _Tp> CV_MAT_AUG_OPERATOR1(op, cvop, const A, B)
+
+CV_MAT_AUG_OPERATOR (+=, cv::add(a,b,a), Mat, Mat)
+CV_MAT_AUG_OPERATOR (+=, cv::add(a,b,a), Mat, Scalar)
+CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Mat)
+CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Scalar)
+CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
+
+CV_MAT_AUG_OPERATOR (-=, cv::subtract(a,b,a), Mat, Mat)
+CV_MAT_AUG_OPERATOR (-=, cv::subtract(a,b,a), Mat, Scalar)
+CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Mat)
+CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Scalar)
+CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
+
+CV_MAT_AUG_OPERATOR (*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat, Mat)
+CV_MAT_AUG_OPERATOR_T(*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat_<_Tp>, Mat)
+CV_MAT_AUG_OPERATOR_T(*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat_<_Tp>, Mat_<_Tp>)
+CV_MAT_AUG_OPERATOR (*=, a.convertTo(a, -1, b), Mat, double)
+CV_MAT_AUG_OPERATOR_T(*=, a.convertTo(a, -1, b), Mat_<_Tp>, double)
+
+CV_MAT_AUG_OPERATOR (/=, cv::divide(a,b,a), Mat, Mat)
+CV_MAT_AUG_OPERATOR_T(/=, cv::divide(a,b,a), Mat_<_Tp>, Mat)
+CV_MAT_AUG_OPERATOR_T(/=, cv::divide(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
+CV_MAT_AUG_OPERATOR (/=, a.convertTo((Mat&)a, -1, 1./b), Mat, double)
+CV_MAT_AUG_OPERATOR_T(/=, a.convertTo((Mat&)a, -1, 1./b), Mat_<_Tp>, double)
+
+CV_MAT_AUG_OPERATOR (&=, cv::bitwise_and(a,b,a), Mat, Mat)
+CV_MAT_AUG_OPERATOR (&=, cv::bitwise_and(a,b,a), Mat, Scalar)
+CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Mat)
+CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Scalar)
+CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
+
+CV_MAT_AUG_OPERATOR (|=, cv::bitwise_or(a,b,a), Mat, Mat)
+CV_MAT_AUG_OPERATOR (|=, cv::bitwise_or(a,b,a), Mat, Scalar)
+CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Mat)
+CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Scalar)
+CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
+
+CV_MAT_AUG_OPERATOR (^=, cv::bitwise_xor(a,b,a), Mat, Mat)
+CV_MAT_AUG_OPERATOR (^=, cv::bitwise_xor(a,b,a), Mat, Scalar)
+CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Mat)
+CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Scalar)
+CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
+
+#undef CV_MAT_AUG_OPERATOR_T
+#undef CV_MAT_AUG_OPERATOR
+#undef CV_MAT_AUG_OPERATOR1
+
+
+
+///////////////////////////////////////////// SVD /////////////////////////////////////////////
+
+inline SVD::SVD() {}
+inline SVD::SVD( InputArray m, int flags ) { operator ()(m, flags); }
+inline void SVD::solveZ( InputArray m, OutputArray _dst )
+{
+ Mat mtx = m.getMat();
+ SVD svd(mtx, (mtx.rows >= mtx.cols ? 0 : SVD::FULL_UV));
+ _dst.create(svd.vt.cols, 1, svd.vt.type());
+ Mat dst = _dst.getMat();
+ svd.vt.row(svd.vt.rows-1).reshape(1,svd.vt.cols).copyTo(dst);
+}
+
+template<typename _Tp, int m, int n, int nm> inline void
+ SVD::compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt )
+{
+ CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
+ Mat _a(a, false), _u(u, false), _w(w, false), _vt(vt, false);
+ SVD::compute(_a, _w, _u, _vt);
+ CV_Assert(_w.data == (uchar*)&w.val[0] && _u.data == (uchar*)&u.val[0] && _vt.data == (uchar*)&vt.val[0]);
+}
+
+template<typename _Tp, int m, int n, int nm> inline void
+SVD::compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w )
+{
+ CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
+ Mat _a(a, false), _w(w, false);
+ SVD::compute(_a, _w);
+ CV_Assert(_w.data == (uchar*)&w.val[0]);
+}
+
+template<typename _Tp, int m, int n, int nm, int nb> inline void
+SVD::backSubst( const Matx<_Tp, nm, 1>& w, const Matx<_Tp, m, nm>& u,
+ const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs,
+ Matx<_Tp, n, nb>& dst )
+{
+ CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
+ Mat _u(u, false), _w(w, false), _vt(vt, false), _rhs(rhs, false), _dst(dst, false);
+ SVD::backSubst(_w, _u, _vt, _rhs, _dst);
+ CV_Assert(_dst.data == (uchar*)&dst.val[0]);
+}
+
+
+
+/////////////////////////////////// Multiply-with-Carry RNG ///////////////////////////////////
+
+inline RNG::RNG() { state = 0xffffffff; }
+inline RNG::RNG(uint64 _state) { state = _state ? _state : 0xffffffff; }
+
+inline RNG::operator uchar() { return (uchar)next(); }
+inline RNG::operator schar() { return (schar)next(); }
+inline RNG::operator ushort() { return (ushort)next(); }
+inline RNG::operator short() { return (short)next(); }
+inline RNG::operator int() { return (int)next(); }
+inline RNG::operator unsigned() { return next(); }
+inline RNG::operator float() { return next()*2.3283064365386962890625e-10f; }
+inline RNG::operator double() { unsigned t = next(); return (((uint64)t << 32) | next()) * 5.4210108624275221700372640043497e-20; }
+
+inline unsigned RNG::operator ()(unsigned N) { return (unsigned)uniform(0,N); }
+inline unsigned RNG::operator ()() { return next(); }
+
+inline int RNG::uniform(int a, int b) { return a == b ? a : (int)(next() % (b - a) + a); }
+inline float RNG::uniform(float a, float b) { return ((float)*this)*(b - a) + a; }
+inline double RNG::uniform(double a, double b) { return ((double)*this)*(b - a) + a; }
+
+inline unsigned RNG::next()
+{
+ state = (uint64)(unsigned)state* /*CV_RNG_COEFF*/ 4164903690U + (unsigned)(state >> 32);
+ return (unsigned)state;
+}
+
+//! returns the next unifomly-distributed random number of the specified type
+template<typename _Tp> static inline _Tp randu()
+{
+ return (_Tp)theRNG();
+}
+
+///////////////////////////////// Formatted string generation /////////////////////////////////
+
+CV_EXPORTS String format( const char* fmt, ... );
+
+///////////////////////////////// Formatted output of cv::Mat /////////////////////////////////
+
+static inline
+Ptr<Formatted> format(InputArray mtx, int fmt)
+{
+ return Formatter::get(fmt)->format(mtx.getMat());
+}
+
+static inline
+int print(Ptr<Formatted> fmtd, FILE* stream = stdout)
+{
+ int written = 0;
+ fmtd->reset();
+ for(const char* str = fmtd->next(); str; str = fmtd->next())
+ written += fputs(str, stream);
+
+ return written;
+}
+
+static inline
+int print(const Mat& mtx, FILE* stream = stdout)
+{
+ return print(Formatter::get()->format(mtx), stream);
+}
+
+static inline
+int print(const UMat& mtx, FILE* stream = stdout)
+{
+ return print(Formatter::get()->format(mtx.getMat(ACCESS_READ)), stream);
+}
+
+template<typename _Tp> static inline
+int print(const std::vector<Point_<_Tp> >& vec, FILE* stream = stdout)
+{
+ return print(Formatter::get()->format(Mat(vec)), stream);
+}
+
+template<typename _Tp> static inline
+int print(const std::vector<Point3_<_Tp> >& vec, FILE* stream = stdout)
+{
+ return print(Formatter::get()->format(Mat(vec)), stream);
+}
+
+template<typename _Tp, int m, int n> static inline
+int print(const Matx<_Tp, m, n>& matx, FILE* stream = stdout)
+{
+ return print(Formatter::get()->format(cv::Mat(matx)), stream);
+}
+
+//! @endcond
+
+/****************************************************************************************\
+* Auxiliary algorithms *
+\****************************************************************************************/
+
+/** @brief Splits an element set into equivalency classes.
+
+The generic function partition implements an \f$O(N^2)\f$ algorithm for splitting a set of \f$N\f$ elements
+into one or more equivalency classes, as described in
+<http://en.wikipedia.org/wiki/Disjoint-set_data_structure> . The function returns the number of
+equivalency classes.
+@param _vec Set of elements stored as a vector.
+@param labels Output vector of labels. It contains as many elements as vec. Each label labels[i] is
+a 0-based cluster index of `vec[i]`.
+@param predicate Equivalence predicate (pointer to a boolean function of two arguments or an
+instance of the class that has the method bool operator()(const _Tp& a, const _Tp& b) ). The
+predicate returns true when the elements are certainly in the same class, and returns false if they
+may or may not be in the same class.
+@ingroup core_cluster
+*/
+template<typename _Tp, class _EqPredicate> int
+partition( const std::vector<_Tp>& _vec, std::vector<int>& labels,
+ _EqPredicate predicate=_EqPredicate())
+{
+ int i, j, N = (int)_vec.size();
+ const _Tp* vec = &_vec[0];
+
+ const int PARENT=0;
+ const int RANK=1;
+
+ std::vector<int> _nodes(N*2);
+ int (*nodes)[2] = (int(*)[2])&_nodes[0];
+
+ // The first O(N) pass: create N single-vertex trees
+ for(i = 0; i < N; i++)
+ {
+ nodes[i][PARENT]=-1;
+ nodes[i][RANK] = 0;
+ }
+
+ // The main O(N^2) pass: merge connected components
+ for( i = 0; i < N; i++ )
+ {
+ int root = i;
+
+ // find root
+ while( nodes[root][PARENT] >= 0 )
+ root = nodes[root][PARENT];
+
+ for( j = 0; j < N; j++ )
+ {
+ if( i == j || !predicate(vec[i], vec[j]))
+ continue;
+ int root2 = j;
+
+ while( nodes[root2][PARENT] >= 0 )
+ root2 = nodes[root2][PARENT];
+
+ if( root2 != root )
+ {
+ // unite both trees
+ int rank = nodes[root][RANK], rank2 = nodes[root2][RANK];
+ if( rank > rank2 )
+ nodes[root2][PARENT] = root;
+ else
+ {
+ nodes[root][PARENT] = root2;
+ nodes[root2][RANK] += rank == rank2;
+ root = root2;
+ }
+ CV_Assert( nodes[root][PARENT] < 0 );
+
+ int k = j, parent;
+
+ // compress the path from node2 to root
+ while( (parent = nodes[k][PARENT]) >= 0 )
+ {
+ nodes[k][PARENT] = root;
+ k = parent;
+ }
+
+ // compress the path from node to root
+ k = i;
+ while( (parent = nodes[k][PARENT]) >= 0 )
+ {
+ nodes[k][PARENT] = root;
+ k = parent;
+ }
+ }
+ }
+ }
+
+ // Final O(N) pass: enumerate classes
+ labels.resize(N);
+ int nclasses = 0;
+
+ for( i = 0; i < N; i++ )
+ {
+ int root = i;
+ while( nodes[root][PARENT] >= 0 )
+ root = nodes[root][PARENT];
+ // re-use the rank as the class label
+ if( nodes[root][RANK] >= 0 )
+ nodes[root][RANK] = ~nclasses++;
+ labels[i] = ~nodes[root][RANK];
+ }
+
+ return nclasses;
+}
+
+} // cv
+
+#endif
+