/*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. // 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*/ #include "precomp.hpp" namespace cv { /****************************************************************************************\ * LU & Cholesky implementation for small matrices * \****************************************************************************************/ template static inline int LUImpl(_Tp* A, size_t astep, int m, _Tp* b, size_t bstep, int n) { int i, j, k, p = 1; astep /= sizeof(A[0]); bstep /= sizeof(b[0]); for( i = 0; i < m; i++ ) { k = i; for( j = i+1; j < m; j++ ) if( std::abs(A[j*astep + i]) > std::abs(A[k*astep + i]) ) k = j; if( std::abs(A[k*astep + i]) < std::numeric_limits<_Tp>::epsilon() ) return 0; if( k != i ) { for( j = i; j < m; j++ ) std::swap(A[i*astep + j], A[k*astep + j]); if( b ) for( j = 0; j < n; j++ ) std::swap(b[i*bstep + j], b[k*bstep + j]); p = -p; } _Tp d = -1/A[i*astep + i]; for( j = i+1; j < m; j++ ) { _Tp alpha = A[j*astep + i]*d; for( k = i+1; k < m; k++ ) A[j*astep + k] += alpha*A[i*astep + k]; if( b ) for( k = 0; k < n; k++ ) b[j*bstep + k] += alpha*b[i*bstep + k]; } A[i*astep + i] = -d; } if( b ) { for( i = m-1; i >= 0; i-- ) for( j = 0; j < n; j++ ) { _Tp s = b[i*bstep + j]; for( k = i+1; k < m; k++ ) s -= A[i*astep + k]*b[k*bstep + j]; b[i*bstep + j] = s*A[i*astep + i]; } } return p; } int LU(float* A, size_t astep, int m, float* b, size_t bstep, int n) { return LUImpl(A, astep, m, b, bstep, n); } int LU(double* A, size_t astep, int m, double* b, size_t bstep, int n) { return LUImpl(A, astep, m, b, bstep, n); } template static inline bool CholImpl(_Tp* A, size_t astep, int m, _Tp* b, size_t bstep, int n) { _Tp* L = A; int i, j, k; double s; astep /= sizeof(A[0]); bstep /= sizeof(b[0]); for( i = 0; i < m; i++ ) { for( j = 0; j < i; j++ ) { s = A[i*astep + j]; for( k = 0; k < j; k++ ) s -= L[i*astep + k]*L[j*astep + k]; L[i*astep + j] = (_Tp)(s*L[j*astep + j]); } s = A[i*astep + i]; for( k = 0; k < j; k++ ) { double t = L[i*astep + k]; s -= t*t; } if( s < std::numeric_limits<_Tp>::epsilon() ) return false; L[i*astep + i] = (_Tp)(1./std::sqrt(s)); } if( !b ) return true; // LLt x = b // 1: L y = b // 2. Lt x = y /* [ L00 ] y0 b0 [ L10 L11 ] y1 = b1 [ L20 L21 L22 ] y2 b2 [ L30 L31 L32 L33 ] y3 b3 [ L00 L10 L20 L30 ] x0 y0 [ L11 L21 L31 ] x1 = y1 [ L22 L32 ] x2 y2 [ L33 ] x3 y3 */ for( i = 0; i < m; i++ ) { for( j = 0; j < n; j++ ) { s = b[i*bstep + j]; for( k = 0; k < i; k++ ) s -= L[i*astep + k]*b[k*bstep + j]; b[i*bstep + j] = (_Tp)(s*L[i*astep + i]); } } for( i = m-1; i >= 0; i-- ) { for( j = 0; j < n; j++ ) { s = b[i*bstep + j]; for( k = m-1; k > i; k-- ) s -= L[k*astep + i]*b[k*bstep + j]; b[i*bstep + j] = (_Tp)(s*L[i*astep + i]); } } return true; } bool Cholesky(float* A, size_t astep, int m, float* b, size_t bstep, int n) { return CholImpl(A, astep, m, b, bstep, n); } bool Cholesky(double* A, size_t astep, int m, double* b, size_t bstep, int n) { return CholImpl(A, astep, m, b, bstep, n); } template static inline _Tp hypot(_Tp a, _Tp b) { a = std::abs(a); b = std::abs(b); if( a > b ) { b /= a; return a*std::sqrt(1 + b*b); } if( b > 0 ) { a /= b; return b*std::sqrt(1 + a*a); } return 0; } template bool JacobiImpl_( _Tp* A, size_t astep, _Tp* W, _Tp* V, size_t vstep, int n, uchar* buf ) { const _Tp eps = std::numeric_limits<_Tp>::epsilon(); int i, j, k, m; astep /= sizeof(A[0]); if( V ) { vstep /= sizeof(V[0]); for( i = 0; i < n; i++ ) { for( j = 0; j < n; j++ ) V[i*vstep + j] = (_Tp)0; V[i*vstep + i] = (_Tp)1; } } int iters, maxIters = n*n*30; _Tp* maxSR = (_Tp*)alignPtr(buf, sizeof(_Tp)); _Tp* maxSC = maxSR + n; int* indR = (int*)(maxSC + n); int* indC = indR + n; _Tp mv = (_Tp)0; for( k = 0; k < n; k++ ) { W[k] = A[(astep + 1)*k]; if( k < n - 1 ) { for( m = k+1, mv = std::abs(A[astep*k + m]), i = k+2; i < n; i++ ) { _Tp val = std::abs(A[astep*k+i]); if( mv < val ) mv = val, m = i; } maxSR[k] = mv; indR[k] = m; } if( k > 0 ) { for( m = 0, mv = std::abs(A[k]), i = 1; i < k; i++ ) { _Tp val = std::abs(A[astep*i+k]); if( mv < val ) mv = val, m = i; } maxSC[k] = mv; indC[k] = m; } } for( iters = 0; iters < maxIters; iters++ ) { // find index (k,l) of pivot p for( k = 0, mv = maxSR[0], i = 1; i < n-1; i++ ) { _Tp val = maxSR[i]; if( mv < val ) mv = val, k = i; } int l = indR[k]; for( i = 1; i < n; i++ ) { _Tp val = maxSC[i]; if( mv < val ) mv = val, k = indC[i], l = i; } _Tp p = A[astep*k + l]; if( std::abs(p) <= eps ) break; _Tp y = (_Tp)((W[l] - W[k])*0.5); _Tp t = std::abs(y) + hypot(p, y); _Tp s = hypot(p, t); _Tp c = t/s; s = p/s; t = (p/t)*p; if( y < 0 ) s = -s, t = -t; A[astep*k + l] = 0; W[k] -= t; W[l] += t; _Tp a0, b0; #undef rotate #define rotate(v0, v1) a0 = v0, b0 = v1, v0 = a0*c - b0*s, v1 = a0*s + b0*c // rotate rows and columns k and l for( i = 0; i < k; i++ ) rotate(A[astep*i+k], A[astep*i+l]); for( i = k+1; i < l; i++ ) rotate(A[astep*k+i], A[astep*i+l]); for( i = l+1; i < n; i++ ) rotate(A[astep*k+i], A[astep*l+i]); // rotate eigenvectors if( V ) for( i = 0; i < n; i++ ) rotate(V[vstep*k+i], V[vstep*l+i]); #undef rotate for( j = 0; j < 2; j++ ) { int idx = j == 0 ? k : l; if( idx < n - 1 ) { for( m = idx+1, mv = std::abs(A[astep*idx + m]), i = idx+2; i < n; i++ ) { _Tp val = std::abs(A[astep*idx+i]); if( mv < val ) mv = val, m = i; } maxSR[idx] = mv; indR[idx] = m; } if( idx > 0 ) { for( m = 0, mv = std::abs(A[idx]), i = 1; i < idx; i++ ) { _Tp val = std::abs(A[astep*i+idx]); if( mv < val ) mv = val, m = i; } maxSC[idx] = mv; indC[idx] = m; } } } // sort eigenvalues & eigenvectors for( k = 0; k < n-1; k++ ) { m = k; for( i = k+1; i < n; i++ ) { if( W[m] < W[i] ) m = i; } if( k != m ) { std::swap(W[m], W[k]); if( V ) for( i = 0; i < n; i++ ) std::swap(V[vstep*m + i], V[vstep*k + i]); } } return true; } static bool Jacobi( float* S, size_t sstep, float* e, float* E, size_t estep, int n, uchar* buf ) { return JacobiImpl_(S, sstep, e, E, estep, n, buf); } static bool Jacobi( double* S, size_t sstep, double* e, double* E, size_t estep, int n, uchar* buf ) { return JacobiImpl_(S, sstep, e, E, estep, n, buf); } template struct VBLAS { int dot(const T*, const T*, int, T*) const { return 0; } int givens(T*, T*, int, T, T) const { return 0; } int givensx(T*, T*, int, T, T, T*, T*) const { return 0; } }; #if CV_SSE2 template<> inline int VBLAS::dot(const float* a, const float* b, int n, float* result) const { if( n < 8 ) return 0; int k = 0; __m128 s0 = _mm_setzero_ps(), s1 = _mm_setzero_ps(); for( ; k <= n - 8; k += 8 ) { __m128 a0 = _mm_load_ps(a + k), a1 = _mm_load_ps(a + k + 4); __m128 b0 = _mm_load_ps(b + k), b1 = _mm_load_ps(b + k + 4); s0 = _mm_add_ps(s0, _mm_mul_ps(a0, b0)); s1 = _mm_add_ps(s1, _mm_mul_ps(a1, b1)); } s0 = _mm_add_ps(s0, s1); float sbuf[4]; _mm_storeu_ps(sbuf, s0); *result = sbuf[0] + sbuf[1] + sbuf[2] + sbuf[3]; return k; } template<> inline int VBLAS::givens(float* a, float* b, int n, float c, float s) const { if( n < 4 ) return 0; int k = 0; __m128 c4 = _mm_set1_ps(c), s4 = _mm_set1_ps(s); for( ; k <= n - 4; k += 4 ) { __m128 a0 = _mm_load_ps(a + k); __m128 b0 = _mm_load_ps(b + k); __m128 t0 = _mm_add_ps(_mm_mul_ps(a0, c4), _mm_mul_ps(b0, s4)); __m128 t1 = _mm_sub_ps(_mm_mul_ps(b0, c4), _mm_mul_ps(a0, s4)); _mm_store_ps(a + k, t0); _mm_store_ps(b + k, t1); } return k; } template<> inline int VBLAS::givensx(float* a, float* b, int n, float c, float s, float* anorm, float* bnorm) const { if( n < 4 ) return 0; int k = 0; __m128 c4 = _mm_set1_ps(c), s4 = _mm_set1_ps(s); __m128 sa = _mm_setzero_ps(), sb = _mm_setzero_ps(); for( ; k <= n - 4; k += 4 ) { __m128 a0 = _mm_load_ps(a + k); __m128 b0 = _mm_load_ps(b + k); __m128 t0 = _mm_add_ps(_mm_mul_ps(a0, c4), _mm_mul_ps(b0, s4)); __m128 t1 = _mm_sub_ps(_mm_mul_ps(b0, c4), _mm_mul_ps(a0, s4)); _mm_store_ps(a + k, t0); _mm_store_ps(b + k, t1); sa = _mm_add_ps(sa, _mm_mul_ps(t0, t0)); sb = _mm_add_ps(sb, _mm_mul_ps(t1, t1)); } float abuf[4], bbuf[4]; _mm_storeu_ps(abuf, sa); _mm_storeu_ps(bbuf, sb); *anorm = abuf[0] + abuf[1] + abuf[2] + abuf[3]; *bnorm = bbuf[0] + bbuf[1] + bbuf[2] + bbuf[3]; return k; } template<> inline int VBLAS::dot(const double* a, const double* b, int n, double* result) const { if( n < 4 ) return 0; int k = 0; __m128d s0 = _mm_setzero_pd(), s1 = _mm_setzero_pd(); for( ; k <= n - 4; k += 4 ) { __m128d a0 = _mm_load_pd(a + k), a1 = _mm_load_pd(a + k + 2); __m128d b0 = _mm_load_pd(b + k), b1 = _mm_load_pd(b + k + 2); s0 = _mm_add_pd(s0, _mm_mul_pd(a0, b0)); s1 = _mm_add_pd(s1, _mm_mul_pd(a1, b1)); } s0 = _mm_add_pd(s0, s1); double sbuf[2]; _mm_storeu_pd(sbuf, s0); *result = sbuf[0] + sbuf[1]; return k; } template<> inline int VBLAS::givens(double* a, double* b, int n, double c, double s) const { int k = 0; __m128d c2 = _mm_set1_pd(c), s2 = _mm_set1_pd(s); for( ; k <= n - 2; k += 2 ) { __m128d a0 = _mm_load_pd(a + k); __m128d b0 = _mm_load_pd(b + k); __m128d t0 = _mm_add_pd(_mm_mul_pd(a0, c2), _mm_mul_pd(b0, s2)); __m128d t1 = _mm_sub_pd(_mm_mul_pd(b0, c2), _mm_mul_pd(a0, s2)); _mm_store_pd(a + k, t0); _mm_store_pd(b + k, t1); } return k; } template<> inline int VBLAS::givensx(double* a, double* b, int n, double c, double s, double* anorm, double* bnorm) const { int k = 0; __m128d c2 = _mm_set1_pd(c), s2 = _mm_set1_pd(s); __m128d sa = _mm_setzero_pd(), sb = _mm_setzero_pd(); for( ; k <= n - 2; k += 2 ) { __m128d a0 = _mm_load_pd(a + k); __m128d b0 = _mm_load_pd(b + k); __m128d t0 = _mm_add_pd(_mm_mul_pd(a0, c2), _mm_mul_pd(b0, s2)); __m128d t1 = _mm_sub_pd(_mm_mul_pd(b0, c2), _mm_mul_pd(a0, s2)); _mm_store_pd(a + k, t0); _mm_store_pd(b + k, t1); sa = _mm_add_pd(sa, _mm_mul_pd(t0, t0)); sb = _mm_add_pd(sb, _mm_mul_pd(t1, t1)); } double abuf[2], bbuf[2]; _mm_storeu_pd(abuf, sa); _mm_storeu_pd(bbuf, sb); *anorm = abuf[0] + abuf[1]; *bnorm = bbuf[0] + bbuf[1]; return k; } #endif template void JacobiSVDImpl_(_Tp* At, size_t astep, _Tp* W, _Tp* Vt, size_t vstep, int m, int n, int n1) { VBLAS<_Tp> vblas; _Tp eps = std::numeric_limits<_Tp>::epsilon()*10; int i, j, k, iter, max_iter = std::max(m, 30); _Tp c, s; double sd; astep /= sizeof(At[0]); vstep /= sizeof(Vt[0]); for( i = 0; i < n; i++ ) { for( k = 0, s = 0; k < m; k++ ) { _Tp t = At[i*astep + k]; s += t*t; } W[i] = s; if( Vt ) { for( k = 0; k < n; k++ ) Vt[i*vstep + k] = 0; Vt[i*vstep + i] = 1; } } for( iter = 0; iter < max_iter; iter++ ) { bool changed = false; for( i = 0; i < n-1; i++ ) for( j = i+1; j < n; j++ ) { _Tp *Ai = At + i*astep, *Aj = At + j*astep, a = W[i], p = 0, b = W[j]; k = vblas.dot(Ai, Aj, m, &p); for( ; k < m; k++ ) p += Ai[k]*Aj[k]; if( std::abs(p) <= eps*std::sqrt((double)a*b) ) continue; p *= 2; double beta = a - b, gamma = hypot((double)p, beta), delta; if( beta < 0 ) { delta = (_Tp)((gamma - beta)*0.5); s = (_Tp)std::sqrt(delta/gamma); c = (_Tp)(p/(gamma*s*2)); } else { c = (_Tp)std::sqrt((gamma + beta)/(gamma*2)); s = (_Tp)(p/(gamma*c*2)); delta = (_Tp)(p*p*0.5/(gamma + beta)); } if( iter % 2 ) { W[i] = (_Tp)(W[i] + delta); W[j] = (_Tp)(W[j] - delta); k = vblas.givens(Ai, Aj, m, c, s); for( ; k < m; k++ ) { _Tp t0 = c*Ai[k] + s*Aj[k]; _Tp t1 = -s*Ai[k] + c*Aj[k]; Ai[k] = t0; Aj[k] = t1; } } else { a = b = 0; k = vblas.givensx(Ai, Aj, m, c, s, &a, &b); for( ; k < m; k++ ) { _Tp t0 = c*Ai[k] + s*Aj[k]; _Tp t1 = -s*Ai[k] + c*Aj[k]; Ai[k] = t0; Aj[k] = t1; a += t0*t0; b += t1*t1; } W[i] = a; W[j] = b; } changed = true; if( Vt ) { _Tp *Vi = Vt + i*vstep, *Vj = Vt + j*vstep; k = vblas.givens(Vi, Vj, n, c, s); for( ; k < n; k++ ) { _Tp t0 = c*Vi[k] + s*Vj[k]; _Tp t1 = -s*Vi[k] + c*Vj[k]; Vi[k] = t0; Vj[k] = t1; } } } if( !changed ) break; } for( i = 0; i < n; i++ ) { for( k = 0, sd = 0; k < m; k++ ) { _Tp t = At[i*astep + k]; sd += (double)t*t; } W[i] = s = (_Tp)std::sqrt(sd); } for( i = 0; i < n-1; i++ ) { j = i; for( k = i+1; k < n; k++ ) { if( W[j] < W[k] ) j = k; } if( i != j ) { std::swap(W[i], W[j]); if( Vt ) { for( k = 0; k < m; k++ ) std::swap(At[i*astep + k], At[j*astep + k]); for( k = 0; k < n; k++ ) std::swap(Vt[i*vstep + k], Vt[j*vstep + k]); } } } if( !Vt ) return; RNG rng; for( i = 0; i < n1; i++ ) { s = i < n ? W[i] : 0; while( s == 0 ) { // if we got a zero singular value, then in order to get the corresponding left singular vector // we generate a random vector, project it to the previously computed left singular vectors, // subtract the projection and normalize the difference. const _Tp val0 = (_Tp)(1./m); for( k = 0; k < m; k++ ) { _Tp val = (rng.next() & 256) ? val0 : -val0; At[i*astep + k] = val; } for( iter = 0; iter < 2; iter++ ) { for( j = 0; j < i; j++ ) { sd = 0; for( k = 0; k < m; k++ ) sd += At[i*astep + k]*At[j*astep + k]; _Tp asum = 0; for( k = 0; k < m; k++ ) { _Tp t = (_Tp)(At[i*astep + k] - sd*At[j*astep + k]); At[i*astep + k] = t; asum += std::abs(t); } asum = asum ? 1/asum : 0; for( k = 0; k < m; k++ ) At[i*astep + k] *= asum; } } sd = 0; for( k = 0; k < m; k++ ) { _Tp t = At[i*astep + k]; sd += (double)t*t; } s = (_Tp)std::sqrt(sd); } s = 1/s; for( k = 0; k < m; k++ ) At[i*astep + k] *= s; } } static void JacobiSVD(float* At, size_t astep, float* W, float* Vt, size_t vstep, int m, int n, int n1=-1) { JacobiSVDImpl_(At, astep, W, Vt, vstep, m, n, !Vt ? 0 : n1 < 0 ? n : n1); } static void JacobiSVD(double* At, size_t astep, double* W, double* Vt, size_t vstep, int m, int n, int n1=-1) { JacobiSVDImpl_(At, astep, W, Vt, vstep, m, n, !Vt ? 0 : n1 < 0 ? n : n1); } /* y[0:m,0:n] += diag(a[0:1,0:m]) * x[0:m,0:n] */ template static void MatrAXPY( int m, int n, const T1* x, int dx, const T2* a, int inca, T3* y, int dy ) { int i, j; for( i = 0; i < m; i++, x += dx, y += dy ) { T2 s = a[i*inca]; for( j = 0; j <= n - 4; j += 4 ) { T3 t0 = (T3)(y[j] + s*x[j]); T3 t1 = (T3)(y[j+1] + s*x[j+1]); y[j] = t0; y[j+1] = t1; t0 = (T3)(y[j+2] + s*x[j+2]); t1 = (T3)(y[j+3] + s*x[j+3]); y[j+2] = t0; y[j+3] = t1; } for( ; j < n; j++ ) y[j] = (T3)(y[j] + s*x[j]); } } template static void SVBkSbImpl_( int m, int n, const T* w, int incw, const T* u, int ldu, bool uT, const T* v, int ldv, bool vT, const T* b, int ldb, int nb, T* x, int ldx, double* buffer, T eps ) { double threshold = 0; int udelta0 = uT ? ldu : 1, udelta1 = uT ? 1 : ldu; int vdelta0 = vT ? ldv : 1, vdelta1 = vT ? 1 : ldv; int i, j, nm = std::min(m, n); if( !b ) nb = m; for( i = 0; i < n; i++ ) for( j = 0; j < nb; j++ ) x[i*ldx + j] = 0; for( i = 0; i < nm; i++ ) threshold += w[i*incw]; threshold *= eps; // v * inv(w) * uT * b for( i = 0; i < nm; i++, u += udelta0, v += vdelta0 ) { double wi = w[i*incw]; if( (double)std::abs(wi) <= threshold ) continue; wi = 1/wi; if( nb == 1 ) { double s = 0; if( b ) for( j = 0; j < m; j++ ) s += u[j*udelta1]*b[j*ldb]; else s = u[0]; s *= wi; for( j = 0; j < n; j++ ) x[j*ldx] = (T)(x[j*ldx] + s*v[j*vdelta1]); } else { if( b ) { for( j = 0; j < nb; j++ ) buffer[j] = 0; MatrAXPY( m, nb, b, ldb, u, udelta1, buffer, 0 ); for( j = 0; j < nb; j++ ) buffer[j] *= wi; } else { for( j = 0; j < nb; j++ ) buffer[j] = u[j*udelta1]*wi; } MatrAXPY( n, nb, buffer, 0, v, vdelta1, x, ldx ); } } } static void SVBkSb( int m, int n, const float* w, size_t wstep, const float* u, size_t ustep, bool uT, const float* v, size_t vstep, bool vT, const float* b, size_t bstep, int nb, float* x, size_t xstep, uchar* buffer ) { SVBkSbImpl_(m, n, w, wstep ? (int)(wstep/sizeof(w[0])) : 1, u, (int)(ustep/sizeof(u[0])), uT, v, (int)(vstep/sizeof(v[0])), vT, b, (int)(bstep/sizeof(b[0])), nb, x, (int)(xstep/sizeof(x[0])), (double*)alignPtr(buffer, sizeof(double)), FLT_EPSILON*10 ); } static void SVBkSb( int m, int n, const double* w, size_t wstep, const double* u, size_t ustep, bool uT, const double* v, size_t vstep, bool vT, const double* b, size_t bstep, int nb, double* x, size_t xstep, uchar* buffer ) { SVBkSbImpl_(m, n, w, wstep ? (int)(wstep/sizeof(w[0])) : 1, u, (int)(ustep/sizeof(u[0])), uT, v, (int)(vstep/sizeof(v[0])), vT, b, (int)(bstep/sizeof(b[0])), nb, x, (int)(xstep/sizeof(x[0])), (double*)alignPtr(buffer, sizeof(double)), DBL_EPSILON*2 ); } } /****************************************************************************************\ * Determinant of the matrix * \****************************************************************************************/ #define det2(m) ((double)m(0,0)*m(1,1) - (double)m(0,1)*m(1,0)) #define det3(m) (m(0,0)*((double)m(1,1)*m(2,2) - (double)m(1,2)*m(2,1)) - \ m(0,1)*((double)m(1,0)*m(2,2) - (double)m(1,2)*m(2,0)) + \ m(0,2)*((double)m(1,0)*m(2,1) - (double)m(1,1)*m(2,0))) double cv::determinant( InputArray _mat ) { Mat mat = _mat.getMat(); double result = 0; int type = mat.type(), rows = mat.rows; size_t step = mat.step; const uchar* m = mat.data; CV_Assert( mat.rows == mat.cols && (type == CV_32F || type == CV_64F)); #define Mf(y, x) ((float*)(m + y*step))[x] #define Md(y, x) ((double*)(m + y*step))[x] if( type == CV_32F ) { if( rows == 2 ) result = det2(Mf); else if( rows == 3 ) result = det3(Mf); else if( rows == 1 ) result = Mf(0,0); else { size_t bufSize = rows*rows*sizeof(float); AutoBuffer buffer(bufSize); Mat a(rows, rows, CV_32F, (uchar*)buffer); mat.copyTo(a); result = LU((float*)a.data, a.step, rows, 0, 0, 0); if( result ) { for( int i = 0; i < rows; i++ ) result *= ((const float*)(a.data + a.step*i))[i]; result = 1./result; } } } else { if( rows == 2 ) result = det2(Md); else if( rows == 3 ) result = det3(Md); else if( rows == 1 ) result = Md(0,0); else { size_t bufSize = rows*rows*sizeof(double); AutoBuffer buffer(bufSize); Mat a(rows, rows, CV_64F, (uchar*)buffer); mat.copyTo(a); result = LU((double*)a.data, a.step, rows, 0, 0, 0); if( result ) { for( int i = 0; i < rows; i++ ) result *= ((const double*)(a.data + a.step*i))[i]; result = 1./result; } } } #undef Mf #undef Md return result; } /****************************************************************************************\ * Inverse (or pseudo-inverse) of a matrix * \****************************************************************************************/ #define Sf( y, x ) ((float*)(srcdata + y*srcstep))[x] #define Sd( y, x ) ((double*)(srcdata + y*srcstep))[x] #define Df( y, x ) ((float*)(dstdata + y*dststep))[x] #define Dd( y, x ) ((double*)(dstdata + y*dststep))[x] double cv::invert( InputArray _src, OutputArray _dst, int method ) { bool result = false; Mat src = _src.getMat(); int type = src.type(); CV_Assert( method == DECOMP_LU || method == DECOMP_CHOLESKY || method == DECOMP_SVD ); _dst.create( src.cols, src.rows, type ); Mat dst = _dst.getMat(); if( method == DECOMP_SVD ) { int n = std::min(src.rows, src.cols); SVD svd(src); svd.backSubst(Mat(), dst); return type == CV_32F ? (((float*)svd.w.data)[0] >= FLT_EPSILON ? ((float*)svd.w.data)[n-1]/((float*)svd.w.data)[0] : 0) : (((double*)svd.w.data)[0] >= DBL_EPSILON ? ((double*)svd.w.data)[n-1]/((double*)svd.w.data)[0] : 0); } CV_Assert( src.rows == src.cols && (type == CV_32F || type == CV_64F)); if( src.rows <= 3 ) { uchar* srcdata = src.data; uchar* dstdata = dst.data; size_t srcstep = src.step; size_t dststep = dst.step; if( src.rows == 2 ) { if( type == CV_32FC1 ) { double d = det2(Sf); if( d != 0. ) { double t0, t1; result = true; d = 1./d; t0 = Sf(0,0)*d; t1 = Sf(1,1)*d; Df(1,1) = (float)t0; Df(0,0) = (float)t1; t0 = -Sf(0,1)*d; t1 = -Sf(1,0)*d; Df(0,1) = (float)t0; Df(1,0) = (float)t1; } } else { double d = det2(Sd); if( d != 0. ) { double t0, t1; result = true; d = 1./d; t0 = Sd(0,0)*d; t1 = Sd(1,1)*d; Dd(1,1) = t0; Dd(0,0) = t1; t0 = -Sd(0,1)*d; t1 = -Sd(1,0)*d; Dd(0,1) = t0; Dd(1,0) = t1; } } } else if( src.rows == 3 ) { if( type == CV_32FC1 ) { double d = det3(Sf); if( d != 0. ) { float t[9]; result = true; d = 1./d; t[0] = (float)(((double)Sf(1,1) * Sf(2,2) - (double)Sf(1,2) * Sf(2,1)) * d); t[1] = (float)(((double)Sf(0,2) * Sf(2,1) - (double)Sf(0,1) * Sf(2,2)) * d); t[2] = (float)(((double)Sf(0,1) * Sf(1,2) - (double)Sf(0,2) * Sf(1,1)) * d); t[3] = (float)(((double)Sf(1,2) * Sf(2,0) - (double)Sf(1,0) * Sf(2,2)) * d); t[4] = (float)(((double)Sf(0,0) * Sf(2,2) - (double)Sf(0,2) * Sf(2,0)) * d); t[5] = (float)(((double)Sf(0,2) * Sf(1,0) - (double)Sf(0,0) * Sf(1,2)) * d); t[6] = (float)(((double)Sf(1,0) * Sf(2,1) - (double)Sf(1,1) * Sf(2,0)) * d); t[7] = (float)(((double)Sf(0,1) * Sf(2,0) - (double)Sf(0,0) * Sf(2,1)) * d); t[8] = (float)(((double)Sf(0,0) * Sf(1,1) - (double)Sf(0,1) * Sf(1,0)) * d); Df(0,0) = t[0]; Df(0,1) = t[1]; Df(0,2) = t[2]; Df(1,0) = t[3]; Df(1,1) = t[4]; Df(1,2) = t[5]; Df(2,0) = t[6]; Df(2,1) = t[7]; Df(2,2) = t[8]; } } else { double d = det3(Sd); if( d != 0. ) { double t[9]; result = true; d = 1./d; t[0] = (Sd(1,1) * Sd(2,2) - Sd(1,2) * Sd(2,1)) * d; t[1] = (Sd(0,2) * Sd(2,1) - Sd(0,1) * Sd(2,2)) * d; t[2] = (Sd(0,1) * Sd(1,2) - Sd(0,2) * Sd(1,1)) * d; t[3] = (Sd(1,2) * Sd(2,0) - Sd(1,0) * Sd(2,2)) * d; t[4] = (Sd(0,0) * Sd(2,2) - Sd(0,2) * Sd(2,0)) * d; t[5] = (Sd(0,2) * Sd(1,0) - Sd(0,0) * Sd(1,2)) * d; t[6] = (Sd(1,0) * Sd(2,1) - Sd(1,1) * Sd(2,0)) * d; t[7] = (Sd(0,1) * Sd(2,0) - Sd(0,0) * Sd(2,1)) * d; t[8] = (Sd(0,0) * Sd(1,1) - Sd(0,1) * Sd(1,0)) * d; Dd(0,0) = t[0]; Dd(0,1) = t[1]; Dd(0,2) = t[2]; Dd(1,0) = t[3]; Dd(1,1) = t[4]; Dd(1,2) = t[5]; Dd(2,0) = t[6]; Dd(2,1) = t[7]; Dd(2,2) = t[8]; } } } else { assert( src.rows == 1 ); if( type == CV_32FC1 ) { double d = Sf(0,0); if( d != 0. ) { result = true; Df(0,0) = (float)(1./d); } } else { double d = Sd(0,0); if( d != 0. ) { result = true; Dd(0,0) = 1./d; } } } if( !result ) dst = Scalar(0); return result; } int n = dst.cols, elem_size = CV_ELEM_SIZE(type); AutoBuffer buf(n*n*elem_size); Mat src1(n, n, type, (uchar*)buf); src.copyTo(src1); setIdentity(dst); if( method == DECOMP_LU && type == CV_32F ) result = LU((float*)src1.data, src1.step, n, (float*)dst.data, dst.step, n) != 0; else if( method == DECOMP_LU && type == CV_64F ) result = LU((double*)src1.data, src1.step, n, (double*)dst.data, dst.step, n) != 0; else if( method == DECOMP_CHOLESKY && type == CV_32F ) result = Cholesky((float*)src1.data, src1.step, n, (float*)dst.data, dst.step, n); else result = Cholesky((double*)src1.data, src1.step, n, (double*)dst.data, dst.step, n); if( !result ) dst = Scalar(0); return result; } /****************************************************************************************\ * Solving a linear system * \****************************************************************************************/ bool cv::solve( InputArray _src, InputArray _src2arg, OutputArray _dst, int method ) { bool result = true; Mat src = _src.getMat(), _src2 = _src2arg.getMat(); int type = src.type(); bool is_normal = (method & DECOMP_NORMAL) != 0; CV_Assert( type == _src2.type() && (type == CV_32F || type == CV_64F) ); method &= ~DECOMP_NORMAL; CV_Assert( (method != DECOMP_LU && method != DECOMP_CHOLESKY) || is_normal || src.rows == src.cols ); // check case of a single equation and small matrix if( (method == DECOMP_LU || method == DECOMP_CHOLESKY) && !is_normal && src.rows <= 3 && src.rows == src.cols && _src2.cols == 1 ) { _dst.create( src.cols, _src2.cols, src.type() ); Mat dst = _dst.getMat(); #define bf(y) ((float*)(bdata + y*src2step))[0] #define bd(y) ((double*)(bdata + y*src2step))[0] uchar* srcdata = src.data; uchar* bdata = _src2.data; uchar* dstdata = dst.data; size_t srcstep = src.step; size_t src2step = _src2.step; size_t dststep = dst.step; if( src.rows == 2 ) { if( type == CV_32FC1 ) { double d = det2(Sf); if( d != 0. ) { double t; d = 1./d; t = (float)(((double)bf(0)*Sf(1,1) - (double)bf(1)*Sf(0,1))*d); Df(1,0) = (float)(((double)bf(1)*Sf(0,0) - (double)bf(0)*Sf(1,0))*d); Df(0,0) = (float)t; } else result = false; } else { double d = det2(Sd); if( d != 0. ) { double t; d = 1./d; t = (bd(0)*Sd(1,1) - bd(1)*Sd(0,1))*d; Dd(1,0) = (bd(1)*Sd(0,0) - bd(0)*Sd(1,0))*d; Dd(0,0) = t; } else result = false; } } else if( src.rows == 3 ) { if( type == CV_32FC1 ) { double d = det3(Sf); if( d != 0. ) { float t[3]; d = 1./d; t[0] = (float)(d* (bf(0)*((double)Sf(1,1)*Sf(2,2) - (double)Sf(1,2)*Sf(2,1)) - Sf(0,1)*((double)bf(1)*Sf(2,2) - (double)Sf(1,2)*bf(2)) + Sf(0,2)*((double)bf(1)*Sf(2,1) - (double)Sf(1,1)*bf(2)))); t[1] = (float)(d* (Sf(0,0)*(double)(bf(1)*Sf(2,2) - (double)Sf(1,2)*bf(2)) - bf(0)*((double)Sf(1,0)*Sf(2,2) - (double)Sf(1,2)*Sf(2,0)) + Sf(0,2)*((double)Sf(1,0)*bf(2) - (double)bf(1)*Sf(2,0)))); t[2] = (float)(d* (Sf(0,0)*((double)Sf(1,1)*bf(2) - (double)bf(1)*Sf(2,1)) - Sf(0,1)*((double)Sf(1,0)*bf(2) - (double)bf(1)*Sf(2,0)) + bf(0)*((double)Sf(1,0)*Sf(2,1) - (double)Sf(1,1)*Sf(2,0)))); Df(0,0) = t[0]; Df(1,0) = t[1]; Df(2,0) = t[2]; } else result = false; } else { double d = det3(Sd); if( d != 0. ) { double t[9]; d = 1./d; t[0] = ((Sd(1,1) * Sd(2,2) - Sd(1,2) * Sd(2,1))*bd(0) + (Sd(0,2) * Sd(2,1) - Sd(0,1) * Sd(2,2))*bd(1) + (Sd(0,1) * Sd(1,2) - Sd(0,2) * Sd(1,1))*bd(2))*d; t[1] = ((Sd(1,2) * Sd(2,0) - Sd(1,0) * Sd(2,2))*bd(0) + (Sd(0,0) * Sd(2,2) - Sd(0,2) * Sd(2,0))*bd(1) + (Sd(0,2) * Sd(1,0) - Sd(0,0) * Sd(1,2))*bd(2))*d; t[2] = ((Sd(1,0) * Sd(2,1) - Sd(1,1) * Sd(2,0))*bd(0) + (Sd(0,1) * Sd(2,0) - Sd(0,0) * Sd(2,1))*bd(1) + (Sd(0,0) * Sd(1,1) - Sd(0,1) * Sd(1,0))*bd(2))*d; Dd(0,0) = t[0]; Dd(1,0) = t[1]; Dd(2,0) = t[2]; } else result = false; } } else { assert( src.rows == 1 ); if( type == CV_32FC1 ) { double d = Sf(0,0); if( d != 0. ) Df(0,0) = (float)(bf(0)/d); else result = false; } else { double d = Sd(0,0); if( d != 0. ) Dd(0,0) = (bd(0)/d); else result = false; } } return result; } if( method == DECOMP_QR ) method = DECOMP_SVD; int m = src.rows, m_ = m, n = src.cols, nb = _src2.cols; size_t esz = CV_ELEM_SIZE(type), bufsize = 0; size_t vstep = alignSize(n*esz, 16); size_t astep = method == DECOMP_SVD && !is_normal ? alignSize(m*esz, 16) : vstep; AutoBuffer buffer; Mat src2 = _src2; _dst.create( src.cols, src2.cols, src.type() ); Mat dst = _dst.getMat(); if( m < n ) CV_Error(CV_StsBadArg, "The function can not solve under-determined linear systems" ); if( m == n ) is_normal = false; else if( is_normal ) { m_ = n; if( method == DECOMP_SVD ) method = DECOMP_EIG; } size_t asize = astep*(method == DECOMP_SVD || is_normal ? n : m); bufsize += asize + 32; if( is_normal ) bufsize += n*nb*esz; if( method == DECOMP_SVD || method == DECOMP_EIG ) bufsize += n*5*esz + n*vstep + nb*sizeof(double) + 32; buffer.allocate(bufsize); uchar* ptr = alignPtr((uchar*)buffer, 16); Mat a(m_, n, type, ptr, astep); if( is_normal ) mulTransposed(src, a, true); else if( method != DECOMP_SVD ) src.copyTo(a); else { a = Mat(n, m_, type, ptr, astep); transpose(src, a); } ptr += asize; if( !is_normal ) { if( method == DECOMP_LU || method == DECOMP_CHOLESKY ) src2.copyTo(dst); } else { // a'*b if( method == DECOMP_LU || method == DECOMP_CHOLESKY ) gemm( src, src2, 1, Mat(), 0, dst, GEMM_1_T ); else { Mat tmp(n, nb, type, ptr); ptr += n*nb*esz; gemm( src, src2, 1, Mat(), 0, tmp, GEMM_1_T ); src2 = tmp; } } if( method == DECOMP_LU ) { if( type == CV_32F ) result = LU(a.ptr(), a.step, n, dst.ptr(), dst.step, nb) != 0; else result = LU(a.ptr(), a.step, n, dst.ptr(), dst.step, nb) != 0; } else if( method == DECOMP_CHOLESKY ) { if( type == CV_32F ) result = Cholesky(a.ptr(), a.step, n, dst.ptr(), dst.step, nb); else result = Cholesky(a.ptr(), a.step, n, dst.ptr(), dst.step, nb); } else { ptr = alignPtr(ptr, 16); Mat v(n, n, type, ptr, vstep), w(n, 1, type, ptr + vstep*n), u; ptr += n*(vstep + esz); if( method == DECOMP_EIG ) { if( type == CV_32F ) Jacobi(a.ptr(), a.step, w.ptr(), v.ptr(), v.step, n, ptr); else Jacobi(a.ptr(), a.step, w.ptr(), v.ptr(), v.step, n, ptr); u = v; } else { if( type == CV_32F ) JacobiSVD(a.ptr(), a.step, w.ptr(), v.ptr(), v.step, m_, n); else JacobiSVD(a.ptr(), a.step, w.ptr(), v.ptr(), v.step, m_, n); u = a; } if( type == CV_32F ) { SVBkSb(m_, n, w.ptr(), 0, u.ptr(), u.step, true, v.ptr(), v.step, true, src2.ptr(), src2.step, nb, dst.ptr(), dst.step, ptr); } else { SVBkSb(m_, n, w.ptr(), 0, u.ptr(), u.step, true, v.ptr(), v.step, true, src2.ptr(), src2.step, nb, dst.ptr(), dst.step, ptr); } result = true; } if( !result ) dst = Scalar(0); return result; } /////////////////// finding eigenvalues and eigenvectors of a symmetric matrix /////////////// bool cv::eigen( InputArray _src, bool computeEvects, OutputArray _evals, OutputArray _evects ) { Mat src = _src.getMat(); int type = src.type(); int n = src.rows; CV_Assert( src.rows == src.cols ); CV_Assert (type == CV_32F || type == CV_64F); Mat v; if( computeEvects ) { _evects.create(n, n, type); v = _evects.getMat(); } size_t elemSize = src.elemSize(), astep = alignSize(n*elemSize, 16); AutoBuffer buf(n*astep + n*5*elemSize + 32); uchar* ptr = alignPtr((uchar*)buf, 16); Mat a(n, n, type, ptr, astep), w(n, 1, type, ptr + astep*n); ptr += astep*n + elemSize*n; src.copyTo(a); bool ok = type == CV_32F ? Jacobi(a.ptr(), a.step, w.ptr(), v.ptr(), v.step, n, ptr) : Jacobi(a.ptr(), a.step, w.ptr(), v.ptr(), v.step, n, ptr); w.copyTo(_evals); return ok; } bool cv::eigen( InputArray src, OutputArray evals, int, int ) { return eigen(src, false, evals, noArray()); } bool cv::eigen( InputArray src, OutputArray evals, OutputArray evects, int, int) { return eigen(src, true, evals, evects); } namespace cv { static void _SVDcompute( InputArray _aarr, OutputArray _w, OutputArray _u, OutputArray _vt, int flags ) { Mat src = _aarr.getMat(); int m = src.rows, n = src.cols; int type = src.type(); bool compute_uv = _u.needed() || _vt.needed(); bool full_uv = (flags & SVD::FULL_UV) != 0; CV_Assert( type == CV_32F || type == CV_64F ); if( flags & SVD::NO_UV ) { _u.release(); _vt.release(); compute_uv = full_uv = false; } bool at = false; if( m < n ) { std::swap(m, n); at = true; } int urows = full_uv ? m : n; size_t esz = src.elemSize(), astep = alignSize(m*esz, 16), vstep = alignSize(n*esz, 16); AutoBuffer _buf(urows*astep + n*vstep + n*esz + 32); uchar* buf = alignPtr((uchar*)_buf, 16); Mat temp_a(n, m, type, buf, astep); Mat temp_w(n, 1, type, buf + urows*astep); Mat temp_u(urows, m, type, buf, astep), temp_v; if( compute_uv ) temp_v = Mat(n, n, type, alignPtr(buf + urows*astep + n*esz, 16), vstep); if( !at ) transpose(src, temp_a); else src.copyTo(temp_a); if( type == CV_32F ) { JacobiSVD(temp_a.ptr(), temp_a.step, temp_w.ptr(), temp_v.ptr(), temp_v.step, m, n, compute_uv ? urows : 0); } else { JacobiSVD(temp_a.ptr(), temp_a.step, temp_w.ptr(), temp_v.ptr(), temp_v.step, m, n, compute_uv ? urows : 0); } temp_w.copyTo(_w); if( compute_uv ) { if( !at ) { transpose(temp_u, _u); temp_v.copyTo(_vt); } else { transpose(temp_v, _u); temp_u.copyTo(_vt); } } } void SVD::compute( InputArray a, OutputArray w, OutputArray u, OutputArray vt, int flags ) { _SVDcompute(a, w, u, vt, flags); } void SVD::compute( InputArray a, OutputArray w, int flags ) { _SVDcompute(a, w, noArray(), noArray(), flags); } void SVD::backSubst( InputArray _w, InputArray _u, InputArray _vt, InputArray _rhs, OutputArray _dst ) { Mat w = _w.getMat(), u = _u.getMat(), vt = _vt.getMat(), rhs = _rhs.getMat(); int type = w.type(), esz = (int)w.elemSize(); int m = u.rows, n = vt.cols, nb = rhs.data ? rhs.cols : m, nm = std::min(m, n); size_t wstep = w.rows == 1 ? esz : w.cols == 1 ? (size_t)w.step : (size_t)w.step + esz; AutoBuffer buffer(nb*sizeof(double) + 16); CV_Assert( w.type() == u.type() && u.type() == vt.type() && u.data && vt.data && w.data ); CV_Assert( u.cols >= nm && vt.rows >= nm && (w.size() == Size(nm, 1) || w.size() == Size(1, nm) || w.size() == Size(vt.rows, u.cols)) ); CV_Assert( rhs.data == 0 || (rhs.type() == type && rhs.rows == m) ); _dst.create( n, nb, type ); Mat dst = _dst.getMat(); if( type == CV_32F ) SVBkSb(m, n, w.ptr(), wstep, u.ptr(), u.step, false, vt.ptr(), vt.step, true, rhs.ptr(), rhs.step, nb, dst.ptr(), dst.step, buffer); else if( type == CV_64F ) SVBkSb(m, n, w.ptr(), wstep, u.ptr(), u.step, false, vt.ptr(), vt.step, true, rhs.ptr(), rhs.step, nb, dst.ptr(), dst.step, buffer); else CV_Error( CV_StsUnsupportedFormat, "" ); } SVD& SVD::operator ()(InputArray a, int flags) { _SVDcompute(a, w, u, vt, flags); return *this; } void SVD::backSubst( InputArray rhs, OutputArray dst ) const { backSubst( w, u, vt, rhs, dst ); } } void cv::SVDecomp(InputArray src, OutputArray w, OutputArray u, OutputArray vt, int flags) { SVD::compute(src, w, u, vt, flags); } void cv::SVBackSubst(InputArray w, InputArray u, InputArray vt, InputArray rhs, OutputArray dst) { SVD::backSubst(w, u, vt, rhs, dst); } CV_IMPL double cvDet( const CvArr* arr ) { if( CV_IS_MAT(arr) && ((CvMat*)arr)->rows <= 3 ) { CvMat* mat = (CvMat*)arr; int type = CV_MAT_TYPE(mat->type); int rows = mat->rows; uchar* m = mat->data.ptr; int step = mat->step; CV_Assert( rows == mat->cols ); #define Mf(y, x) ((float*)(m + y*step))[x] #define Md(y, x) ((double*)(m + y*step))[x] if( type == CV_32F ) { if( rows == 2 ) return det2(Mf); if( rows == 3 ) return det3(Mf); } else if( type == CV_64F ) { if( rows == 2 ) return det2(Md); if( rows == 3 ) return det3(Md); } return cv::determinant(cv::Mat(mat)); } return cv::determinant(cv::cvarrToMat(arr)); } CV_IMPL double cvInvert( const CvArr* srcarr, CvArr* dstarr, int method ) { cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr); CV_Assert( src.type() == dst.type() && src.rows == dst.cols && src.cols == dst.rows ); return cv::invert( src, dst, method == CV_CHOLESKY ? cv::DECOMP_CHOLESKY : method == CV_SVD || method == CV_SVD_SYM ? cv::DECOMP_SVD : cv::DECOMP_LU ); } CV_IMPL int cvSolve( const CvArr* Aarr, const CvArr* barr, CvArr* xarr, int method ) { cv::Mat A = cv::cvarrToMat(Aarr), b = cv::cvarrToMat(barr), x = cv::cvarrToMat(xarr); CV_Assert( A.type() == x.type() && A.cols == x.rows && x.cols == b.cols ); bool is_normal = (method & CV_NORMAL) != 0; method &= ~CV_NORMAL; return cv::solve( A, b, x, (method == CV_CHOLESKY ? cv::DECOMP_CHOLESKY : method == CV_SVD || method == CV_SVD_SYM ? cv::DECOMP_SVD : A.rows > A.cols ? cv::DECOMP_QR : cv::DECOMP_LU) + (is_normal ? cv::DECOMP_NORMAL : 0) ); } CV_IMPL void cvEigenVV( CvArr* srcarr, CvArr* evectsarr, CvArr* evalsarr, double, int lowindex, int highindex) { cv::Mat src = cv::cvarrToMat(srcarr), evals = cv::cvarrToMat(evalsarr); if( evectsarr ) { cv::Mat evects = cv::cvarrToMat(evectsarr); eigen(src, evals, evects, lowindex, highindex); } else eigen(src, evals, lowindex, highindex); } CV_IMPL void cvSVD( CvArr* aarr, CvArr* warr, CvArr* uarr, CvArr* varr, int flags ) { cv::Mat a = cv::cvarrToMat(aarr), w = cv::cvarrToMat(warr), u, v; int m = a.rows, n = a.cols, type = a.type(), mn = std::max(m, n), nm = std::min(m, n); CV_Assert( w.type() == type && (w.size() == cv::Size(nm,1) || w.size() == cv::Size(1, nm) || w.size() == cv::Size(nm, nm) || w.size() == cv::Size(n, m)) ); cv::SVD svd; if( w.size() == cv::Size(nm, 1) ) svd.w = cv::Mat(nm, 1, type, w.data ); else if( w.isContinuous() ) svd.w = w; if( uarr ) { u = cv::cvarrToMat(uarr); CV_Assert( u.type() == type ); svd.u = u; } if( varr ) { v = cv::cvarrToMat(varr); CV_Assert( v.type() == type ); svd.vt = v; } svd(a, ((flags & CV_SVD_MODIFY_A) ? cv::SVD::MODIFY_A : 0) | ((!svd.u.data && !svd.vt.data) ? cv::SVD::NO_UV : 0) | ((m != n && (svd.u.size() == cv::Size(mn, mn) || svd.vt.size() == cv::Size(mn, mn))) ? cv::SVD::FULL_UV : 0)); if( u.data ) { if( flags & CV_SVD_U_T ) cv::transpose( svd.u, u ); else if( u.data != svd.u.data ) { CV_Assert( u.size() == svd.u.size() ); svd.u.copyTo(u); } } if( v.data ) { if( !(flags & CV_SVD_V_T) ) cv::transpose( svd.vt, v ); else if( v.data != svd.vt.data ) { CV_Assert( v.size() == svd.vt.size() ); svd.vt.copyTo(v); } } if( w.data != svd.w.data ) { if( w.size() == svd.w.size() ) svd.w.copyTo(w); else { w = cv::Scalar(0); cv::Mat wd = w.diag(); svd.w.copyTo(wd); } } } CV_IMPL void cvSVBkSb( const CvArr* warr, const CvArr* uarr, const CvArr* varr, const CvArr* rhsarr, CvArr* dstarr, int flags ) { cv::Mat w = cv::cvarrToMat(warr), u = cv::cvarrToMat(uarr), v = cv::cvarrToMat(varr), rhs, dst = cv::cvarrToMat(dstarr), dst0 = dst; if( flags & CV_SVD_U_T ) { cv::Mat tmp; transpose(u, tmp); u = tmp; } if( !(flags & CV_SVD_V_T) ) { cv::Mat tmp; transpose(v, tmp); v = tmp; } if( rhsarr ) rhs = cv::cvarrToMat(rhsarr); cv::SVD::backSubst(w, u, v, rhs, dst); CV_Assert( dst.data == dst0.data ); }