--- /dev/null
+/*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 "_cxcore.h"
+
+namespace cv
+{
+
+/****************************************************************************************\
+* GEMM *
+\****************************************************************************************/
+
+static void
+GEMM_CopyBlock( const uchar* src, size_t src_step,
+ uchar* dst, size_t dst_step,
+ Size size, size_t pix_size )
+{
+ int j;
+ size.width *= (int)(pix_size / sizeof(int));
+
+ for( ; size.height--; src += src_step, dst += dst_step )
+ {
+ for( j = 0; j <= size.width - 4; j += 4 )
+ {
+ int t0 = ((const int*)src)[j];
+ int t1 = ((const int*)src)[j+1];
+ ((int*)dst)[j] = t0;
+ ((int*)dst)[j+1] = t1;
+ t0 = ((const int*)src)[j+2];
+ t1 = ((const int*)src)[j+3];
+ ((int*)dst)[j+2] = t0;
+ ((int*)dst)[j+3] = t1;
+ }
+
+ for( ; j < size.width; j++ )
+ ((int*)dst)[j] = ((const int*)src)[j];
+ }
+}
+
+
+static void
+GEMM_TransposeBlock( const uchar* src, size_t src_step,
+ uchar* dst, size_t dst_step,
+ Size size, size_t pix_size )
+{
+ int i, j;
+ for( i = 0; i < size.width; i++, dst += dst_step, src += pix_size )
+ {
+ const uchar* _src = src;
+ switch( pix_size )
+ {
+ case sizeof(int):
+ for( j = 0; j < size.height; j++, _src += src_step )
+ ((int*)dst)[j] = ((int*)_src)[0];
+ break;
+ case sizeof(int)*2:
+ for( j = 0; j < size.height*2; j += 2, _src += src_step )
+ {
+ int t0 = ((int*)_src)[0];
+ int t1 = ((int*)_src)[1];
+ ((int*)dst)[j] = t0;
+ ((int*)dst)[j+1] = t1;
+ }
+ break;
+ case sizeof(int)*4:
+ for( j = 0; j < size.height*4; j += 4, _src += src_step )
+ {
+ int t0 = ((int*)_src)[0];
+ int t1 = ((int*)_src)[1];
+ ((int*)dst)[j] = t0;
+ ((int*)dst)[j+1] = t1;
+ t0 = ((int*)_src)[2];
+ t1 = ((int*)_src)[3];
+ ((int*)dst)[j+2] = t0;
+ ((int*)dst)[j+3] = t1;
+ }
+ break;
+ default:
+ assert(0);
+ return;
+ }
+ }
+}
+
+
+template<typename T, typename WT> static void
+GEMMSingleMul( const T* a_data, size_t a_step,
+ const T* b_data, size_t b_step,
+ const T* c_data, size_t c_step,
+ T* d_data, size_t d_step,
+ Size a_size, Size d_size,
+ double alpha, double beta, int flags )
+{
+ int i, j, k, n = a_size.width, m = d_size.width, drows = d_size.height;
+ const T *_a_data = a_data, *_b_data = b_data, *_c_data = c_data;
+ T* a_buf = 0;
+ size_t a_step0, a_step1, c_step0, c_step1, t_step;
+
+ a_step /= sizeof(a_data[0]);
+ b_step /= sizeof(b_data[0]);
+ c_step /= sizeof(c_data[0]);
+ d_step /= sizeof(d_data[0]);
+ a_step0 = a_step;
+ a_step1 = 1;
+
+ if( !c_data )
+ c_step0 = c_step1 = 0;
+ else if( !(flags & GEMM_3_T) )
+ c_step0 = c_step, c_step1 = 1;
+ else
+ c_step0 = 1, c_step1 = c_step;
+
+ if( flags & GEMM_1_T )
+ {
+ CV_SWAP( a_step0, a_step1, t_step );
+ n = a_size.height;
+ if( a_step > 1 && n > 1 )
+ a_buf = (T*)cvStackAlloc(n*sizeof(a_data[0]));
+ }
+
+ if( n == 1 ) /* external product */
+ {
+ T* b_buf = 0;
+
+ if( a_step > 1 && a_size.height > 1 )
+ {
+ a_buf = (T*)cvStackAlloc(drows*sizeof(a_data[0]));
+ for( k = 0; k < drows; k++ )
+ a_buf[k] = a_data[a_step*k];
+ a_data = a_buf;
+ }
+
+ if( b_step > 1 )
+ {
+ b_buf = (T*)cvStackAlloc(d_size.width*sizeof(b_buf[0]) );
+ for( j = 0; j < d_size.width; j++ )
+ b_buf[j] = b_data[j*b_step];
+ b_data = b_buf;
+ }
+
+ for( i = 0; i < drows; i++, _c_data += c_step0, d_data += d_step )
+ {
+ WT al = WT(a_data[i])*alpha;
+ c_data = _c_data;
+ for( j = 0; j <= d_size.width - 2; j += 2, c_data += 2*c_step1 )
+ {
+ WT s0 = al*WT(b_data[j]);
+ WT s1 = al*WT(b_data[j+1]);
+ if( !c_data )
+ {
+ d_data[j] = T(s0);
+ d_data[j+1] = T(s1);
+ }
+ else
+ {
+ d_data[j] = T(s0 + WT(c_data[0])*beta);
+ d_data[j+1] = T(s1 + WT(c_data[c_step1])*beta);
+ }
+ }
+
+ for( ; j < d_size.width; j++, c_data += c_step1 )
+ {
+ WT s0 = al*WT(b_data[j]);
+ if( !c_data )
+ d_data[j] = T(s0);
+ else
+ d_data[j] = T(s0 + WT(c_data[0])*beta);
+ }
+ }
+ }
+ else if( flags & GEMM_2_T ) /* A * Bt */
+ {
+ for( i = 0; i < drows; i++, _a_data += a_step0, _c_data += c_step0, d_data += d_step )
+ {
+ a_data = _a_data;
+ b_data = _b_data;
+ c_data = _c_data;
+
+ if( a_buf )
+ {
+ for( k = 0; k < n; k++ )
+ a_buf[k] = a_data[a_step1*k];
+ a_data = a_buf;
+ }
+
+ for( j = 0; j < d_size.width; j++, b_data += b_step,
+ c_data += c_step1 )
+ {
+ WT s0(0), s1(0), s2(0), s3(0);
+
+ for( k = 0; k <= n - 4; k += 4 )
+ {
+ s0 += WT(a_data[k])*WT(b_data[k]);
+ s1 += WT(a_data[k+1])*WT(b_data[k+1]);
+ s2 += WT(a_data[k+2])*WT(b_data[k+2]);
+ s3 += WT(a_data[k+3])*WT(b_data[k+3]);
+ }
+
+ for( ; k < n; k++ )
+ s0 += WT(a_data[k])*WT(b_data[k]);
+ s0 = (s0+s1+s2+s3)*alpha;
+
+ if( !c_data )
+ d_data[j] = T(s0);
+ else
+ d_data[j] = T(s0 + WT(c_data[0])*beta);
+ }
+ }
+ }
+ else if( d_size.width*sizeof(d_data[0]) <= 1600 )
+ {
+ for( i = 0; i < drows; i++, _a_data += a_step0,
+ _c_data += c_step0,
+ d_data += d_step )
+ {
+ a_data = _a_data, c_data = _c_data;
+
+ if( a_buf )
+ {
+ for( k = 0; k < n; k++ )
+ a_buf[k] = a_data[a_step1*k];
+ a_data = a_buf;
+ }
+
+ for( j = 0; j <= m - 4; j += 4, c_data += 4*c_step1 )
+ {
+ const T* b = _b_data + j;
+ WT s0(0), s1(0), s2(0), s3(0);
+
+ for( k = 0; k < n; k++, b += b_step )
+ {
+ WT a(a_data[k]);
+ s0 += a * WT(b[0]); s1 += a * WT(b[1]);
+ s2 += a * WT(b[2]); s3 += a * WT(b[3]);
+ }
+
+ if( !c_data )
+ {
+ d_data[j] = T(s0*alpha);
+ d_data[j+1] = T(s1*alpha);
+ d_data[j+2] = T(s2*alpha);
+ d_data[j+3] = T(s3*alpha);
+ }
+ else
+ {
+ s0 = s0*alpha; s1 = s1*alpha;
+ s2 = s2*alpha; s3 = s3*alpha;
+ d_data[j] = T(s0 + WT(c_data[0])*beta);
+ d_data[j+1] = T(s1 + WT(c_data[c_step1])*beta);
+ d_data[j+2] = T(s2 + WT(c_data[c_step1*2])*beta);
+ d_data[j+3] = T(s3 + WT(c_data[c_step1*3])*beta);
+ }
+ }
+
+ for( ; j < m; j++, c_data += c_step1 )
+ {
+ const T* b = _b_data + j;
+ WT s0(0);
+
+ for( k = 0; k < n; k++, b += b_step )
+ s0 += WT(a_data[k]) * WT(b[0]);
+
+ s0 = s0*alpha;
+ if( !c_data )
+ d_data[j] = T(s0);
+ else
+ d_data[j] = T(s0 + WT(c_data[0])*beta);
+ }
+ }
+ }
+ else
+ {
+ WT* d_buf = (WT*)cvStackAlloc(m*sizeof(d_buf[0]));
+
+ for( i = 0; i < drows; i++, _a_data += a_step0, _c_data += c_step0, d_data += d_step )
+ {
+ a_data = _a_data;
+ b_data = _b_data;
+ c_data = _c_data;
+
+ if( a_buf )
+ {
+ for( k = 0; k < n; k++ )
+ a_buf[k] = _a_data[a_step1*k];
+ a_data = a_buf;
+ }
+
+ for( j = 0; j < m; j++ )
+ d_buf[j] = WT(0);
+
+ for( k = 0; k < n; k++, b_data += b_step )
+ {
+ WT al(a_data[k]);
+
+ for( j = 0; j <= m - 4; j += 4 )
+ {
+ WT t0 = d_buf[j] + WT(b_data[j])*al;
+ WT t1 = d_buf[j+1] + WT(b_data[j+1])*al;
+ d_buf[j] = t0;
+ d_buf[j+1] = t1;
+ t0 = d_buf[j+2] + WT(b_data[j+2])*al;
+ t1 = d_buf[j+3] + WT(b_data[j+3])*al;
+ d_buf[j+2] = t0;
+ d_buf[j+3] = t1;
+ }
+
+ for( ; j < m; j++ )
+ d_buf[j] += WT(b_data[j])*al;
+ }
+
+ if( !c_data )
+ for( j = 0; j < m; j++ )
+ d_data[j] = T(d_buf[j]*alpha);
+ else
+ for( j = 0; j < m; j++, c_data += c_step1 )
+ {
+ WT t = d_buf[j]*alpha;
+ d_data[j] = T(t + WT(c_data[0])*beta);
+ }
+ }
+ }
+}
+
+
+template<typename T, typename WT> static void
+GEMMBlockMul( const T* a_data, size_t a_step,
+ const T* b_data, size_t b_step,
+ WT* d_data, size_t d_step,
+ Size a_size, Size d_size, int flags )
+{
+ int i, j, k, n = a_size.width, m = d_size.width;
+ const T *_a_data = a_data, *_b_data = b_data;
+ T* a_buf = 0;
+ size_t a_step0, a_step1, t_step;
+ int do_acc = flags & 16;
+
+ a_step /= sizeof(a_data[0]);
+ b_step /= sizeof(b_data[0]);
+ d_step /= sizeof(d_data[0]);
+
+ a_step0 = a_step;
+ a_step1 = 1;
+
+ if( flags & GEMM_1_T )
+ {
+ CV_SWAP( a_step0, a_step1, t_step );
+ n = a_size.height;
+ a_buf = (T*)cvStackAlloc(n*sizeof(a_data[0]));
+ }
+
+ if( flags & GEMM_2_T )
+ {
+ /* second operand is transposed */
+ for( i = 0; i < d_size.height; i++, _a_data += a_step0, d_data += d_step )
+ {
+ a_data = _a_data; b_data = _b_data;
+
+ if( a_buf )
+ {
+ for( k = 0; k < n; k++ )
+ a_buf[k] = a_data[a_step1*k];
+ a_data = a_buf;
+ }
+
+ for( j = 0; j < d_size.width; j++, b_data += b_step )
+ {
+ WT s0 = do_acc ? d_data[j]:WT(0), s1(0);
+ for( k = 0; k <= n - 2; k += 2 )
+ {
+ s0 += WT(a_data[k])*WT(b_data[k]);
+ s1 += WT(a_data[k+1])*WT(b_data[k+1]);
+ }
+
+ for( ; k < n; k++ )
+ s0 += WT(a_data[k])*WT(b_data[k]);
+
+ d_data[j] = s0 + s1;
+ }
+ }
+ }
+ else
+ {
+ for( i = 0; i < d_size.height; i++, _a_data += a_step0, d_data += d_step )
+ {
+ a_data = _a_data, b_data = _b_data;
+
+ if( a_buf )
+ {
+ for( k = 0; k < n; k++ )
+ a_buf[k] = a_data[a_step1*k];
+ a_data = a_buf;
+ }
+
+ for( j = 0; j <= m - 4; j += 4 )
+ {
+ WT s0, s1, s2, s3;
+ const T* b = b_data + j;
+
+ if( do_acc )
+ {
+ s0 = d_data[j]; s1 = d_data[j+1];
+ s2 = d_data[j+2]; s3 = d_data[j+3];
+ }
+ else
+ s0 = s1 = s2 = s3 = WT(0);
+
+ for( k = 0; k < n; k++, b += b_step )
+ {
+ WT a(a_data[k]);
+ s0 += a * WT(b[0]); s1 += a * WT(b[1]);
+ s2 += a * WT(b[2]); s3 += a * WT(b[3]);
+ }
+
+ d_data[j] = s0; d_data[j+1] = s1;
+ d_data[j+2] = s2; d_data[j+3] = s3;
+ }
+
+ for( ; j < m; j++ )
+ {
+ const T* b = b_data + j;
+ WT s0 = do_acc ? d_data[j] : WT(0);
+
+ for( k = 0; k < n; k++, b += b_step )
+ s0 += WT(a_data[k]) * WT(b[0]);
+
+ d_data[j] = s0;
+ }
+ }
+ }
+}
+
+
+template<typename T, typename WT> static void
+GEMMStore( const T* c_data, size_t c_step,
+ const WT* d_buf, size_t d_buf_step,
+ T* d_data, size_t d_step, Size d_size,
+ double alpha, double beta, int flags )
+{
+ const T* _c_data = c_data;
+ int j;
+ size_t c_step0, c_step1;
+
+ c_step /= sizeof(c_data[0]);
+ d_buf_step /= sizeof(d_buf[0]);
+ d_step /= sizeof(d_data[0]);
+
+ if( !c_data )
+ c_step0 = c_step1 = 0;
+ else if( !(flags & GEMM_3_T) )
+ c_step0 = c_step, c_step1 = 1;
+ else
+ c_step0 = 1, c_step1 = c_step;
+
+ for( ; d_size.height--; _c_data += c_step0, d_buf += d_buf_step, d_data += d_step )
+ {
+ if( _c_data )
+ {
+ c_data = _c_data;
+ for( j = 0; j <= d_size.width - 4; j += 4, c_data += 4*c_step1 )
+ {
+ WT t0 = alpha*d_buf[j];
+ WT t1 = alpha*d_buf[j+1];
+ t0 += beta*WT(c_data[0]);
+ t1 += beta*WT(c_data[c_step1]);
+ d_data[j] = T(t0);
+ d_data[j+1] = T(t1);
+ t0 = alpha*d_buf[j+2];
+ t1 = alpha*d_buf[j+3];
+ t0 += beta*WT(c_data[c_step1*2]);
+ t1 += beta*WT(c_data[c_step1*3]);
+ d_data[j+2] = T(t0);
+ d_data[j+3] = T(t1);
+ }
+ for( ; j < d_size.width; j++, c_data += c_step1 )
+ {
+ WT t0 = alpha*d_buf[j];
+ d_data[j] = T(t0 + WT(c_data[0])*beta);
+ }
+ }
+ else
+ {
+ for( j = 0; j <= d_size.width - 4; j += 4 )
+ {
+ WT t0 = alpha*d_buf[j];
+ WT t1 = alpha*d_buf[j+1];
+ d_data[j] = T(t0);
+ d_data[j+1] = T(t1);
+ t0 = alpha*d_buf[j+2];
+ t1 = alpha*d_buf[j+3];
+ d_data[j+2] = T(t0);
+ d_data[j+3] = T(t1);
+ }
+ for( ; j < d_size.width; j++ )
+ d_data[j] = T(alpha*d_buf[j]);
+ }
+ }
+}
+
+
+typedef void (*GEMMSingleMulFunc)( const void* src1, size_t step1,
+ const void* src2, size_t step2, const void* src3, size_t step3,
+ void* dst, size_t dststep, Size srcsize, Size dstsize,
+ double alpha, double beta, int flags );
+
+typedef void (*GEMMBlockMulFunc)( const void* src1, size_t step1,
+ const void* src2, size_t step2, void* dst, size_t dststep,
+ Size srcsize, Size dstsize, int flags );
+
+typedef void (*GEMMStoreFunc)( const void* src1, size_t step1,
+ const void* src2, size_t step2, void* dst, size_t dststep,
+ Size dstsize, double alpha, double beta, int flags );
+
+static void GEMMSingleMul_32f( const float* a_data, size_t a_step,
+ const float* b_data, size_t b_step,
+ const float* c_data, size_t c_step,
+ float* d_data, size_t d_step,
+ Size a_size, Size d_size,
+ double alpha, double beta, int flags )
+{
+ GEMMSingleMul<float,double>(a_data, a_step, b_data, b_step, c_data,
+ c_step, d_data, d_step, a_size, d_size,
+ alpha, beta, flags);
+}
+
+static void GEMMSingleMul_64f( const double* a_data, size_t a_step,
+ const double* b_data, size_t b_step,
+ const double* c_data, size_t c_step,
+ double* d_data, size_t d_step,
+ Size a_size, Size d_size,
+ double alpha, double beta, int flags )
+{
+ GEMMSingleMul<double,double>(a_data, a_step, b_data, b_step, c_data,
+ c_step, d_data, d_step, a_size, d_size,
+ alpha, beta, flags);
+}
+
+
+static void GEMMSingleMul_32fc( const Complexf* a_data, size_t a_step,
+ const Complexf* b_data, size_t b_step,
+ const Complexf* c_data, size_t c_step,
+ Complexf* d_data, size_t d_step,
+ Size a_size, Size d_size,
+ double alpha, double beta, int flags )
+{
+ GEMMSingleMul<Complexf,Complexd>(a_data, a_step, b_data, b_step, c_data,
+ c_step, d_data, d_step, a_size, d_size,
+ alpha, beta, flags);
+}
+
+static void GEMMSingleMul_64fc( const Complexd* a_data, size_t a_step,
+ const Complexd* b_data, size_t b_step,
+ const Complexd* c_data, size_t c_step,
+ Complexd* d_data, size_t d_step,
+ Size a_size, Size d_size,
+ double alpha, double beta, int flags )
+{
+ GEMMSingleMul<Complexd,Complexd>(a_data, a_step, b_data, b_step, c_data,
+ c_step, d_data, d_step, a_size, d_size,
+ alpha, beta, flags);
+}
+
+static void GEMMBlockMul_32f( const float* a_data, size_t a_step,
+ const float* b_data, size_t b_step,
+ double* d_data, size_t d_step,
+ Size a_size, Size d_size, int flags )
+{
+ GEMMBlockMul(a_data, a_step, b_data, b_step, d_data, d_step, a_size, d_size, flags);
+}
+
+
+static void GEMMBlockMul_64f( const double* a_data, size_t a_step,
+ const double* b_data, size_t b_step,
+ double* d_data, size_t d_step,
+ Size a_size, Size d_size, int flags )
+{
+ GEMMBlockMul(a_data, a_step, b_data, b_step, d_data, d_step, a_size, d_size, flags);
+}
+
+
+static void GEMMBlockMul_32fc( const Complexf* a_data, size_t a_step,
+ const Complexf* b_data, size_t b_step,
+ Complexd* d_data, size_t d_step,
+ Size a_size, Size d_size, int flags )
+{
+ GEMMBlockMul(a_data, a_step, b_data, b_step, d_data, d_step, a_size, d_size, flags);
+}
+
+
+static void GEMMBlockMul_64fc( const Complexd* a_data, size_t a_step,
+ const Complexd* b_data, size_t b_step,
+ Complexd* d_data, size_t d_step,
+ Size a_size, Size d_size, int flags )
+{
+ GEMMBlockMul(a_data, a_step, b_data, b_step, d_data, d_step, a_size, d_size, flags);
+}
+
+
+static void GEMMStore_32f( const float* c_data, size_t c_step,
+ const double* d_buf, size_t d_buf_step,
+ float* d_data, size_t d_step, Size d_size,
+ double alpha, double beta, int flags )
+{
+ GEMMStore(c_data, c_step, d_buf, d_buf_step, d_data, d_step, d_size, alpha, beta, flags);
+}
+
+
+static void GEMMStore_64f( const double* c_data, size_t c_step,
+ const double* d_buf, size_t d_buf_step,
+ double* d_data, size_t d_step, Size d_size,
+ double alpha, double beta, int flags )
+{
+ GEMMStore(c_data, c_step, d_buf, d_buf_step, d_data, d_step, d_size, alpha, beta, flags);
+}
+
+
+static void GEMMStore_32fc( const Complexf* c_data, size_t c_step,
+ const Complexd* d_buf, size_t d_buf_step,
+ Complexf* d_data, size_t d_step, Size d_size,
+ double alpha, double beta, int flags )
+{
+ GEMMStore(c_data, c_step, d_buf, d_buf_step, d_data, d_step, d_size, alpha, beta, flags);
+}
+
+
+static void GEMMStore_64fc( const Complexd* c_data, size_t c_step,
+ const Complexd* d_buf, size_t d_buf_step,
+ Complexd* d_data, size_t d_step, Size d_size,
+ double alpha, double beta, int flags )
+{
+ GEMMStore(c_data, c_step, d_buf, d_buf_step, d_data, d_step, d_size, alpha, beta, flags);
+}
+
+
+void gemm( const Mat& _A, const Mat& _B, double alpha,
+ const Mat& _C, double beta, Mat& D, int flags )
+{
+ const int block_lin_size = 128;
+ const int block_size = block_lin_size * block_lin_size;
+
+ static double zero[] = {0,0,0,0};
+ static float zerof[] = {0,0,0,0};
+
+ Mat A = _A, B = _B;
+ const Mat* C = _C.data && beta != 0 ? &_C : 0;
+ Size a_size = A.size(), d_size;
+ int i, len = 0, type = A.type();
+
+ CV_Assert( type == B.type() && (type == CV_32FC1 || type == CV_64FC1 || type == CV_32FC2 || type == CV_64FC2) );
+
+ switch( flags & (GEMM_1_T|GEMM_2_T) )
+ {
+ case 0:
+ d_size = Size( B.cols, a_size.height );
+ len = B.rows;
+ CV_Assert( a_size.width == len );
+ break;
+ case 1:
+ d_size = Size( B.cols, a_size.width );
+ len = B.rows;
+ CV_Assert( a_size.height == len );
+ break;
+ case 2:
+ d_size = Size( B.rows, a_size.height );
+ len = B.cols;
+ CV_Assert( a_size.width == len );
+ break;
+ case 3:
+ d_size = Size( B.rows, a_size.width );
+ len = B.cols;
+ CV_Assert( a_size.height == len );
+ break;
+ }
+
+ if( C )
+ {
+ CV_Assert( C->type() == type &&
+ (((flags&GEMM_3_T) == 0 && C->rows == d_size.height && C->cols == d_size.width) ||
+ ((flags&GEMM_3_T) != 0 && C->rows == d_size.width && C->cols == d_size.height)));
+ if( (flags & GEMM_3_T) != 0 && C->data == D.data )
+ {
+ transpose( D, D );
+ flags &= ~GEMM_3_T;
+ }
+ }
+
+ D.create( d_size.height, d_size.width, type );
+
+ if( flags == 0 && 2 <= len && len <= 4 && (len == d_size.width || len == d_size.height) )
+ {
+ if( type == CV_32F )
+ {
+ float* d = (float*)D.data;
+ const float *a = (const float*)A.data,
+ *b = (const float*)B.data,
+ *c = (const float*)(C ? C->data : 0);
+ size_t d_step = D.step/sizeof(d[0]),
+ a_step = A.step/sizeof(a[0]),
+ b_step = B.step/sizeof(b[0]),
+ c_step = C ? C->step/sizeof(c[0]) : 0;
+
+ if( !c )
+ c = zerof;
+
+ switch( len )
+ {
+ case 2:
+ if( len == d_size.width && b != d )
+ {
+ for( i = 0; i < d_size.height; i++, d += d_step, a += a_step, c += c_step )
+ {
+ float t0 = a[0]*b[0] + a[1]*b[b_step];
+ float t1 = a[0]*b[1] + a[1]*b[b_step+1];
+ d[0] = (float)(t0*alpha + c[0]*beta);
+ d[1] = (float)(t1*alpha + c[1]*beta);
+ }
+ }
+ else if( a != d )
+ {
+ int c_step0 = 1;
+ if( c == zerof )
+ {
+ c_step0 = 0;
+ c_step = 1;
+ }
+
+ for( i = 0; i < d_size.width; i++, d++, b++, c += c_step0 )
+ {
+ float t0 = a[0]*b[0] + a[1]*b[b_step];
+ float t1 = a[a_step]*b[0] + a[a_step+1]*b[b_step];
+ d[0] = (float)(t0*alpha + c[0]*beta);
+ d[d_step] = (float)(t1*alpha + c[c_step]*beta);
+ }
+ }
+ else
+ break;
+ return;
+ case 3:
+ if( len == d_size.width && b != d )
+ {
+ for( i = 0; i < d_size.height; i++, d += d_step, a += a_step, c += c_step )
+ {
+ float t0 = a[0]*b[0] + a[1]*b[b_step] + a[2]*b[b_step*2];
+ float t1 = a[0]*b[1] + a[1]*b[b_step+1] + a[2]*b[b_step*2+1];
+ float t2 = a[0]*b[2] + a[1]*b[b_step+2] + a[2]*b[b_step*2+2];
+ d[0] = (float)(t0*alpha + c[0]*beta);
+ d[1] = (float)(t1*alpha + c[1]*beta);
+ d[2] = (float)(t2*alpha + c[2]*beta);
+ }
+ }
+ else if( a != d )
+ {
+ int c_step0 = 1;
+ if( c == zerof )
+ {
+ c_step0 = 0;
+ c_step = 1;
+ }
+
+ for( i = 0; i < d_size.width; i++, d++, b++, c += c_step0 )
+ {
+ float t0 = a[0]*b[0] + a[1]*b[b_step] + a[2]*b[b_step*2];
+ float t1 = a[a_step]*b[0] + a[a_step+1]*b[b_step] + a[a_step+2]*b[b_step*2];
+ float t2 = a[a_step*2]*b[0] + a[a_step*2+1]*b[b_step] + a[a_step*2+2]*b[b_step*2];
+
+ d[0] = (float)(t0*alpha + c[0]*beta);
+ d[d_step] = (float)(t1*alpha + c[c_step]*beta);
+ d[d_step*2] = (float)(t2*alpha + c[c_step*2]*beta);
+ }
+ }
+ else
+ break;
+ return;
+ case 4:
+ if( len == d_size.width && b != d )
+ {
+ for( i = 0; i < d_size.height; i++, d += d_step, a += a_step, c += c_step )
+ {
+ float t0 = a[0]*b[0] + a[1]*b[b_step] + a[2]*b[b_step*2] + a[3]*b[b_step*3];
+ float t1 = a[0]*b[1] + a[1]*b[b_step+1] + a[2]*b[b_step*2+1] + a[3]*b[b_step*3+1];
+ float t2 = a[0]*b[2] + a[1]*b[b_step+2] + a[2]*b[b_step*2+2] + a[3]*b[b_step*3+2];
+ float t3 = a[0]*b[3] + a[1]*b[b_step+3] + a[2]*b[b_step*2+3] + a[3]*b[b_step*3+3];
+ d[0] = (float)(t0*alpha + c[0]*beta);
+ d[1] = (float)(t1*alpha + c[1]*beta);
+ d[2] = (float)(t2*alpha + c[2]*beta);
+ d[3] = (float)(t3*alpha + c[3]*beta);
+ }
+ }
+ else if( len <= 16 && a != d )
+ {
+ int c_step0 = 1;
+ if( c == zerof )
+ {
+ c_step0 = 0;
+ c_step = 1;
+ }
+
+ for( i = 0; i < d_size.width; i++, d++, b++, c += c_step0 )
+ {
+ float t0 = a[0]*b[0] + a[1]*b[b_step] + a[2]*b[b_step*2] + a[3]*b[b_step*3];
+ float t1 = a[a_step]*b[0] + a[a_step+1]*b[b_step] +
+ a[a_step+2]*b[b_step*2] + a[a_step+3]*b[b_step*3];
+ float t2 = a[a_step*2]*b[0] + a[a_step*2+1]*b[b_step] +
+ a[a_step*2+2]*b[b_step*2] + a[a_step*2+3]*b[b_step*3];
+ float t3 = a[a_step*3]*b[0] + a[a_step*3+1]*b[b_step] +
+ a[a_step*3+2]*b[b_step*2] + a[a_step*3+3]*b[b_step*3];
+ d[0] = (float)(t0*alpha + c[0]*beta);
+ d[d_step] = (float)(t1*alpha + c[c_step]*beta);
+ d[d_step*2] = (float)(t2*alpha + c[c_step*2]*beta);
+ d[d_step*3] = (float)(t3*alpha + c[c_step*3]*beta);
+ }
+ }
+ else
+ break;
+ return;
+ }
+ }
+
+ if( type == CV_64F )
+ {
+ double* d = (double*)D.data;
+ const double *a = (const double*)A.data,
+ *b = (const double*)B.data,
+ *c = (const double*)(C ? C->data : 0);
+ size_t d_step = D.step/sizeof(d[0]),
+ a_step = A.step/sizeof(a[0]),
+ b_step = B.step/sizeof(b[0]),
+ c_step = C ? C->step/sizeof(c[0]) : 0;
+ if( !c )
+ c = zero;
+
+ switch( len )
+ {
+ case 2:
+ if( len == d_size.width && b != d )
+ {
+ for( i = 0; i < d_size.height; i++, d += d_step, a += a_step, c += c_step )
+ {
+ double t0 = a[0]*b[0] + a[1]*b[b_step];
+ double t1 = a[0]*b[1] + a[1]*b[b_step+1];
+ d[0] = t0*alpha + c[0]*beta;
+ d[1] = t1*alpha + c[1]*beta;
+ }
+ }
+ else if( a != d )
+ {
+ int c_step0 = 1;
+ if( c == zero )
+ {
+ c_step0 = 0;
+ c_step = 1;
+ }
+
+ for( i = 0; i < d_size.width; i++, d++, b++, c += c_step0 )
+ {
+ double t0 = a[0]*b[0] + a[1]*b[b_step];
+ double t1 = a[a_step]*b[0] + a[a_step+1]*b[b_step];
+ d[0] = t0*alpha + c[0]*beta;
+ d[d_step] = t1*alpha + c[c_step]*beta;
+ }
+ }
+ else
+ break;
+ return;
+ case 3:
+ if( len == d_size.width && b != d )
+ {
+ for( i = 0; i < d_size.height; i++, d += d_step, a += a_step, c += c_step )
+ {
+ double t0 = a[0]*b[0] + a[1]*b[b_step] + a[2]*b[b_step*2];
+ double t1 = a[0]*b[1] + a[1]*b[b_step+1] + a[2]*b[b_step*2+1];
+ double t2 = a[0]*b[2] + a[1]*b[b_step+2] + a[2]*b[b_step*2+2];
+ d[0] = t0*alpha + c[0]*beta;
+ d[1] = t1*alpha + c[1]*beta;
+ d[2] = t2*alpha + c[2]*beta;
+ }
+ }
+ else if( a != d )
+ {
+ int c_step0 = 1;
+ if( c == zero )
+ {
+ c_step0 = 0;
+ c_step = 1;
+ }
+
+ for( i = 0; i < d_size.width; i++, d++, b++, c += c_step0 )
+ {
+ double t0 = a[0]*b[0] + a[1]*b[b_step] + a[2]*b[b_step*2];
+ double t1 = a[a_step]*b[0] + a[a_step+1]*b[b_step] + a[a_step+2]*b[b_step*2];
+ double t2 = a[a_step*2]*b[0] + a[a_step*2+1]*b[b_step] + a[a_step*2+2]*b[b_step*2];
+
+ d[0] = t0*alpha + c[0]*beta;
+ d[d_step] = t1*alpha + c[c_step]*beta;
+ d[d_step*2] = t2*alpha + c[c_step*2]*beta;
+ }
+ }
+ else
+ break;
+ return;
+ case 4:
+ if( len == d_size.width && b != d )
+ {
+ for( i = 0; i < d_size.height; i++, d += d_step, a += a_step, c += c_step )
+ {
+ double t0 = a[0]*b[0] + a[1]*b[b_step] + a[2]*b[b_step*2] + a[3]*b[b_step*3];
+ double t1 = a[0]*b[1] + a[1]*b[b_step+1] + a[2]*b[b_step*2+1] + a[3]*b[b_step*3+1];
+ double t2 = a[0]*b[2] + a[1]*b[b_step+2] + a[2]*b[b_step*2+2] + a[3]*b[b_step*3+2];
+ double t3 = a[0]*b[3] + a[1]*b[b_step+3] + a[2]*b[b_step*2+3] + a[3]*b[b_step*3+3];
+ d[0] = t0*alpha + c[0]*beta;
+ d[1] = t1*alpha + c[1]*beta;
+ d[2] = t2*alpha + c[2]*beta;
+ d[3] = t3*alpha + c[3]*beta;
+ }
+ }
+ else if( d_size.width <= 16 && a != d )
+ {
+ int c_step0 = 1;
+ if( c == zero )
+ {
+ c_step0 = 0;
+ c_step = 1;
+ }
+
+ for( i = 0; i < d_size.width; i++, d++, b++, c += c_step0 )
+ {
+ double t0 = a[0]*b[0] + a[1]*b[b_step] + a[2]*b[b_step*2] + a[3]*b[b_step*3];
+ double t1 = a[a_step]*b[0] + a[a_step+1]*b[b_step] +
+ a[a_step+2]*b[b_step*2] + a[a_step+3]*b[b_step*3];
+ double t2 = a[a_step*2]*b[0] + a[a_step*2+1]*b[b_step] +
+ a[a_step*2+2]*b[b_step*2] + a[a_step*2+3]*b[b_step*3];
+ double t3 = a[a_step*3]*b[0] + a[a_step*3+1]*b[b_step] +
+ a[a_step*3+2]*b[b_step*2] + a[a_step*3+3]*b[b_step*3];
+ d[0] = t0*alpha + c[0]*beta;
+ d[d_step] = t1*alpha + c[c_step]*beta;
+ d[d_step*2] = t2*alpha + c[c_step*2]*beta;
+ d[d_step*3] = t3*alpha + c[c_step*3]*beta;
+ }
+ }
+ else
+ break;
+ return;
+ }
+ }
+ }
+
+ {
+ size_t b_step = B.step;
+ GEMMSingleMulFunc singleMulFunc;
+ GEMMBlockMulFunc blockMulFunc;
+ GEMMStoreFunc storeFunc;
+ Mat *_D = &D, tmat;
+ const uchar* Cdata = C ? C->data : 0;
+ size_t Cstep = C ? C->step : 0;
+ AutoBuffer<uchar> buf;
+
+ if( type == CV_32FC1 )
+ {
+ singleMulFunc = (GEMMSingleMulFunc)GEMMSingleMul_32f;
+ blockMulFunc = (GEMMBlockMulFunc)GEMMBlockMul_32f;
+ storeFunc = (GEMMStoreFunc)GEMMStore_32f;
+ }
+ else if( type == CV_64FC1 )
+ {
+ singleMulFunc = (GEMMSingleMulFunc)GEMMSingleMul_64f;
+ blockMulFunc = (GEMMBlockMulFunc)GEMMBlockMul_64f;
+ storeFunc = (GEMMStoreFunc)GEMMStore_64f;
+ }
+ else if( type == CV_32FC2 )
+ {
+ singleMulFunc = (GEMMSingleMulFunc)GEMMSingleMul_32fc;
+ blockMulFunc = (GEMMBlockMulFunc)GEMMBlockMul_32fc;
+ storeFunc = (GEMMStoreFunc)GEMMStore_32fc;
+ }
+ else
+ {
+ CV_Assert( type == CV_64FC2 );
+ singleMulFunc = (GEMMSingleMulFunc)GEMMSingleMul_64fc;
+ blockMulFunc = (GEMMBlockMulFunc)GEMMBlockMul_64fc;
+ storeFunc = (GEMMStoreFunc)GEMMStore_64fc;
+ }
+
+ if( D.data == A.data || D.data == B.data )
+ {
+ buf.allocate(d_size.width*d_size.height*CV_ELEM_SIZE(type));
+ tmat = Mat(d_size.height, d_size.width, type, (uchar*)buf );
+ _D = &tmat;
+ }
+
+ if( (d_size.width == 1 || len == 1) && !(flags & GEMM_2_T) && B.isContinuous() )
+ {
+ b_step = d_size.width == 1 ? 0 : CV_ELEM_SIZE(type);
+ flags |= GEMM_2_T;
+ }
+
+ /*if( (d_size.width | d_size.height | len) >= 16 && icvBLAS_GEMM_32f_p != 0 )
+ {
+ blas_func = type == CV_32FC1 ? (icvBLAS_GEMM_32f_t)icvBLAS_GEMM_32f_p :
+ type == CV_64FC1 ? (icvBLAS_GEMM_32f_t)icvBLAS_GEMM_64f_p :
+ type == CV_32FC2 ? (icvBLAS_GEMM_32f_t)icvBLAS_GEMM_32fc_p :
+ type == CV_64FC2 ? (icvBLAS_GEMM_32f_t)icvBLAS_GEMM_64fc_p : 0;
+ }
+
+ if( blas_func )
+ {
+ const char* transa = flags & GEMM_1_T ? "t" : "n";
+ const char* transb = flags & GEMM_2_T ? "t" : "n";
+ int lda, ldb, ldd;
+
+ if( C->data.ptr )
+ {
+ if( C->data.ptr != D->data.ptr )
+ {
+ if( !(flags & GEMM_3_T) )
+ cvCopy( C, D );
+ else
+ cvTranspose( C, D );
+ }
+ }
+
+ if( CV_MAT_DEPTH(type) == CV_32F )
+ {
+ Complex32f _alpha, _beta;
+
+ lda = A->step/sizeof(float);
+ ldb = b_step/sizeof(float);
+ ldd = D->step/sizeof(float);
+ _alpha.re = (float)alpha;
+ _alpha.im = 0;
+ _beta.re = C->data.ptr ? (float)beta : 0;
+ _beta.im = 0;
+ if( CV_MAT_CN(type) == 2 )
+ lda /= 2, ldb /= 2, ldd /= 2;
+
+ blas_func( transb, transa, &d_size.width, &d_size.height, &len,
+ &_alpha, B->data.ptr, &ldb, A->data.ptr, &lda,
+ &_beta, D->data.ptr, &ldd );
+ }
+ else
+ {
+ CvComplex64f _alpha, _beta;
+
+ lda = A->step/sizeof(double);
+ ldb = b_step/sizeof(double);
+ ldd = D->step/sizeof(double);
+ _alpha.re = alpha;
+ _alpha.im = 0;
+ _beta.re = C->data.ptr ? beta : 0;
+ _beta.im = 0;
+ if( CV_MAT_CN(type) == 2 )
+ lda /= 2, ldb /= 2, ldd /= 2;
+
+ blas_func( transb, transa, &d_size.width, &d_size.height, &len,
+ &_alpha, B->data.ptr, &ldb, A->data.ptr, &lda,
+ &_beta, D->data.ptr, &ldd );
+ }
+ }
+ else*/ if( ((d_size.height <= block_lin_size/2 || d_size.width <= block_lin_size/2) &&
+ len <= 10000) || len <= 10 ||
+ (d_size.width <= block_lin_size &&
+ d_size.height <= block_lin_size && len <= block_lin_size) )
+ {
+ singleMulFunc( A.data, A.step, B.data, b_step, Cdata, Cstep,
+ _D->data, _D->step, a_size, d_size, alpha, beta, flags );
+ }
+ else
+ {
+ int is_a_t = flags & GEMM_1_T;
+ int is_b_t = flags & GEMM_2_T;
+ int elem_size = CV_ELEM_SIZE(type);
+ int dk0_1, dk0_2;
+ int a_buf_size = 0, b_buf_size, d_buf_size;
+ uchar* a_buf = 0;
+ uchar* b_buf = 0;
+ uchar* d_buf = 0;
+ int j, k, di = 0, dj = 0, dk = 0;
+ int dm0, dn0, dk0;
+ size_t a_step0, a_step1, b_step0, b_step1, c_step0, c_step1;
+ int work_elem_size = elem_size << (CV_MAT_DEPTH(type) == CV_32F ? 1 : 0);
+
+ if( !is_a_t )
+ a_step0 = A.step, a_step1 = elem_size;
+ else
+ a_step0 = elem_size, a_step1 = A.step;
+
+ if( !is_b_t )
+ b_step0 = b_step, b_step1 = elem_size;
+ else
+ b_step0 = elem_size, b_step1 = b_step;
+
+ if( !C )
+ {
+ c_step0 = c_step1 = 0;
+ flags &= ~GEMM_3_T;
+ }
+ else if( !(flags & GEMM_3_T) )
+ c_step0 = C->step, c_step1 = elem_size;
+ else
+ c_step0 = elem_size, c_step1 = C->step;
+
+ dm0 = std::min( block_lin_size, d_size.height );
+ dn0 = std::min( block_lin_size, d_size.width );
+ dk0_1 = block_size / dm0;
+ dk0_2 = block_size / dn0;
+ dk0 = std::min( dk0_1, dk0_2 );
+ dk0 = std::min( dk0, len );
+ if( dk0*dm0 > block_size )
+ dm0 = block_size / dk0;
+ if( dk0*dn0 > block_size )
+ dn0 = block_size / dk0;
+
+ dk0_1 = (dn0+dn0/8+2) & -2;
+ b_buf_size = (dk0+dk0/8+1)*dk0_1*elem_size;
+ d_buf_size = (dk0+dk0/8+1)*dk0_1*work_elem_size;
+
+ if( is_a_t )
+ {
+ a_buf_size = (dm0+dm0/8+1)*((dk0+dk0/8+2)&-2)*elem_size;
+ flags &= ~GEMM_1_T;
+ }
+
+ buf.allocate(a_buf_size + b_buf_size + d_buf_size);
+ d_buf = (uchar*)buf;
+ b_buf = d_buf + d_buf_size;
+
+ if( is_a_t )
+ a_buf = b_buf + b_buf_size;
+
+ for( i = 0; i < d_size.height; i += di )
+ {
+ di = dm0;
+ if( i + di >= d_size.height || 8*(i + di) + di > 8*d_size.height )
+ di = d_size.height - i;
+
+ for( j = 0; j < d_size.width; j += dj )
+ {
+ uchar* _d = _D->data + i*_D->step + j*elem_size;
+ const uchar* _c = Cdata + i*c_step0 + j*c_step1;
+ size_t _d_step = _D->step;
+ dj = dn0;
+
+ if( j + dj >= d_size.width || 8*(j + dj) + dj > 8*d_size.width )
+ dj = d_size.width - j;
+
+ flags &= 15;
+ if( dk0 < len )
+ {
+ _d = d_buf;
+ _d_step = dj*work_elem_size;
+ }
+
+ for( k = 0; k < len; k += dk )
+ {
+ const uchar* _a = A.data + i*a_step0 + k*a_step1;
+ size_t _a_step = A.step;
+ const uchar* _b = B.data + k*b_step0 + j*b_step1;
+ size_t _b_step = b_step;
+ Size a_bl_size;
+
+ dk = dk0;
+ if( k + dk >= len || 8*(k + dk) + dk > 8*len )
+ dk = len - k;
+
+ if( !is_a_t )
+ a_bl_size.width = dk, a_bl_size.height = di;
+ else
+ a_bl_size.width = di, a_bl_size.height = dk;
+
+ if( a_buf && is_a_t )
+ {
+ _a_step = dk*elem_size;
+ GEMM_TransposeBlock( _a, A.step, a_buf, _a_step, a_bl_size, elem_size );
+ std::swap( a_bl_size.width, a_bl_size.height );
+ _a = a_buf;
+ }
+
+ if( dj < d_size.width )
+ {
+ Size b_size;
+ if( !is_b_t )
+ b_size.width = dj, b_size.height = dk;
+ else
+ b_size.width = dk, b_size.height = dj;
+
+ _b_step = b_size.width*elem_size;
+ GEMM_CopyBlock( _b, b_step, b_buf, _b_step, b_size, elem_size );
+ _b = b_buf;
+ }
+
+ if( dk0 < len )
+ blockMulFunc( _a, _a_step, _b, _b_step, _d, _d_step,
+ a_bl_size, Size(dj,di), flags );
+ else
+ singleMulFunc( _a, _a_step, _b, _b_step, _c, Cstep,
+ _d, _d_step, a_bl_size, Size(dj,di), alpha, beta, flags );
+ flags |= 16;
+ }
+
+ if( dk0 < len )
+ storeFunc( _c, Cstep, _d, _d_step,
+ _D->data + i*_D->step + j*elem_size,
+ _D->step, Size(dj,di), alpha, beta, flags );
+ }
+ }
+ }
+
+ if( _D != &D )
+ _D->copyTo(D);
+ }
+}
+
+/****************************************************************************************\
+* Transform *
+\****************************************************************************************/
+
+template<typename T, typename WT> static void
+transformC1_( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ Size size = getContinuousSize( srcmat, dstmat );
+ const WT* m = (const WT*)tmat.data;
+ int dst_cn = dstmat.channels();
+ int x, y, k;
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+ const WT* _m = m;
+
+ for( k = 0; k < dst_cn; k++, dst++, _m += 2 )
+ for( x = 0; x < size.width; x++ )
+ dst[x*dst_cn] = saturate_cast<T>(_m[0]*src[x] + _m[1]);
+ }
+}
+
+template<typename T, typename WT> static void
+transformC2_( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ Size size = getContinuousSize( srcmat, dstmat );
+ const WT* m = (const WT*)tmat.data;
+ int dst_cn = dstmat.channels();
+ int x, y, k;
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ if( dst_cn == 2 )
+ for( x = 0; x < size.width*2; x += 2 )
+ {
+ WT v0 = src[x], v1 = src[x+1];
+ T t0 = saturate_cast<T>(m[0]*v0 + m[1]*v1 + m[2]);
+ T t1 = saturate_cast<T>(m[3]*v0 + m[4]*v1 + m[5]);
+ dst[x] = t0; dst[x+1] = t1;
+ }
+ else
+ {
+ const WT* _m = m;
+ for( k = 0; k < dst_cn; k++, dst++, _m += 3 )
+ for( x = 0; x < size.width; x++ )
+ dst[x*dst_cn] = saturate_cast<T>(_m[0]*src[x*2] +
+ _m[1]*src[x*2+1] + _m[2]);
+ }
+ }
+}
+
+template<typename T, typename WT> static void
+transformC3_( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ Size size = getContinuousSize( srcmat, dstmat );
+ const WT* m = (const WT*)tmat.data;
+ int dst_cn = dstmat.channels();
+ int x, y, k;
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ if( dst_cn == 3 )
+ for( x = 0; x < size.width*3; x += 3 )
+ {
+ WT v0 = src[x], v1 = src[x+1], v2 = src[x+2];
+ T t0 = saturate_cast<T>(m[0]*v0 + m[1]*v1 + m[2]*v2 + m[3]);
+ T t1 = saturate_cast<T>(m[4]*v0 + m[5]*v1 + m[6]*v2 + m[7]);
+ T t2 = saturate_cast<T>(m[8]*v0 + m[9]*v1 + m[10]*v2 + m[11]);
+ dst[x] = t0; dst[x+1] = t1; dst[x+2] = t2;
+ }
+ else if( dst_cn == 1 )
+ for( x = 0; x < size.width; x++, src += 3 )
+ dst[x] = saturate_cast<T>(m[0]*src[0] + m[1]*src[1] + m[2]*src[2] + m[3]);
+ else
+ {
+ const WT* _m = m;
+ for( k = 0; k < dst_cn; k++, dst++, _m += 4 )
+ for( x = 0; x < size.width; x++ )
+ dst[x*dst_cn] = saturate_cast<T>(_m[0]*src[x*3] +
+ _m[1]*src[x*3+1] + _m[2]*src[x*3+2] + _m[3]);
+ }
+ }
+}
+
+
+template<typename T, typename WT> static void
+transformC4_( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ Size size = getContinuousSize( srcmat, dstmat );
+ const WT* m = (const WT*)tmat.data;
+ int dst_cn = dstmat.channels();
+ int x, y, k;
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ if( dst_cn == 4 )
+ for( x = 0; x < size.width*4; x += 4 )
+ {
+ WT v0 = src[x], v1 = src[x+1], v2 = src[x+2], v3 = src[x+3];
+ T t0 = saturate_cast<T>(m[0]*v0 + m[1]*v1 + m[2]*v2 + m[3]*v3 + m[4]);
+ T t1 = saturate_cast<T>(m[5]*v0 + m[6]*v1 + m[7]*v2 + m[8]*v3 + m[9]);
+ dst[x] = t0; dst[x+1] = t1;
+ t0 = saturate_cast<T>(m[10]*v0 + m[11]*v1 + m[12]*v2 + m[13]*v3 + m[14]);
+ t1 = saturate_cast<T>(m[15]*v0 + m[16]*v1 + m[17]*v2 + m[18]*v3 + m[19]);
+ dst[x+2] = t0; dst[x+3] = t1;
+ }
+ else
+ {
+ const WT* _m = m;
+ for( k = 0; k < dst_cn; k++, dst++, _m += 5 )
+ for( x = 0; x < size.width; x++ )
+ dst[x*dst_cn] = saturate_cast<T>(_m[0]*src[x*4] + _m[1]*src[x*4+1] +
+ _m[2]*src[x*4+2] + _m[3]*src[x*4+3] + _m[4]);
+ }
+ }
+}
+
+
+#if CV_SSE2
+
+static inline void
+load3x3Matrix( const float* m, __m128& m0, __m128& m1, __m128& m2, __m128& m3 )
+{
+ m0 = _mm_setr_ps(m[0], m[4], m[8], 0);
+ m1 = _mm_setr_ps(m[1], m[5], m[9], 0);
+ m2 = _mm_setr_ps(m[2], m[6], m[10], 0);
+ m3 = _mm_setr_ps(m[3], m[7], m[11], 0);
+}
+
+static inline void
+load4x4Matrix( const float* m, __m128& m0, __m128& m1, __m128& m2, __m128& m3, __m128& m4 )
+{
+ m0 = _mm_setr_ps(m[0], m[5], m[10], m[15]);
+ m1 = _mm_setr_ps(m[1], m[6], m[11], m[16]);
+ m2 = _mm_setr_ps(m[2], m[7], m[12], m[17]);
+ m3 = _mm_setr_ps(m[3], m[8], m[13], m[18]);
+ m4 = _mm_setr_ps(m[4], m[9], m[14], m[19]);
+}
+
+template<> void
+transformC3_<uchar, float>( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ typedef uchar T;
+ typedef float WT;
+ const int BITS = 10, SCALE = 1 << BITS;
+ const float MAX_M = (float)(1 << (15 - BITS));
+ Size size = getContinuousSize( srcmat, dstmat );
+ const float* m = (const float*)tmat.data;
+ int dst_cn = dstmat.channels();
+ int x, y, k;
+
+ if( dst_cn == 3 &&
+ std::abs(m[0]) < MAX_M && std::abs(m[1]) < MAX_M && std::abs(m[2]) < MAX_M && std::abs(m[3]) < MAX_M*256 &&
+ std::abs(m[4]) < MAX_M && std::abs(m[5]) < MAX_M && std::abs(m[6]) < MAX_M && std::abs(m[7]) < MAX_M*256 &&
+ std::abs(m[8]) < MAX_M && std::abs(m[9]) < MAX_M && std::abs(m[10]) < MAX_M && std::abs(m[11]) < MAX_M*256 )
+ {
+ // faster fixed-point transformation
+ short m00 = saturate_cast<short>(m[0]*SCALE), m01 = saturate_cast<short>(m[1]*SCALE),
+ m02 = saturate_cast<short>(m[2]*SCALE), m10 = saturate_cast<short>(m[4]*SCALE),
+ m11 = saturate_cast<short>(m[5]*SCALE), m12 = saturate_cast<short>(m[6]*SCALE),
+ m20 = saturate_cast<short>(m[8]*SCALE), m21 = saturate_cast<short>(m[9]*SCALE),
+ m22 = saturate_cast<short>(m[10]*SCALE);
+ int m03 = saturate_cast<int>((m[3]+0.5f)*SCALE), m13 = saturate_cast<int>((m[7]+0.5f)*SCALE ),
+ m23 = saturate_cast<int>((m[11]+0.5f)*SCALE);
+
+ __m128i m0 = _mm_setr_epi16(0, m00, m01, m02, m00, m01, m02, 0);
+ __m128i m1 = _mm_setr_epi16(0, m10, m11, m12, m10, m11, m12, 0);
+ __m128i m2 = _mm_setr_epi16(0, m20, m21, m22, m20, m21, m22, 0);
+ __m128i m3 = _mm_setr_epi32(m03, m13, m23, 0);
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+ int x = 0;
+
+ for( ; x <= (size.width - 8)*3; x += 8*3 )
+ {
+ __m128i z = _mm_setzero_si128(), t0, t1, t2, r0, r1;
+ __m128i v0 = _mm_loadl_epi64((const __m128i*)(src + x));
+ __m128i v1 = _mm_loadl_epi64((const __m128i*)(src + x + 8));
+ __m128i v2 = _mm_loadl_epi64((const __m128i*)(src + x + 16)), v3;
+ v0 = _mm_unpacklo_epi8(v0, z); // b0 g0 r0 b1 g1 r1 b2 g2
+ v1 = _mm_unpacklo_epi8(v1, z); // r2 b3 g3 r3 b4 g4 r4 b5
+ v2 = _mm_unpacklo_epi8(v2, z); // g5 r5 b6 g6 r6 b7 g7 r7
+
+ v3 = _mm_srli_si128(v2, 2); // ? b6 g6 r6 b7 g7 r7 0
+ v2 = _mm_or_si128(_mm_slli_si128(v2, 10), _mm_srli_si128(v1, 6)); // ? b4 g4 r4 b5 g5 r5 ?
+ v1 = _mm_or_si128(_mm_slli_si128(v1, 6), _mm_srli_si128(v0, 10)); // ? b2 g2 r2 b3 g3 r3 ?
+ v0 = _mm_slli_si128(v0, 2); // 0 b0 g0 r0 b1 g1 r1 ?
+
+ // process pixels 0 & 1
+ t0 = _mm_madd_epi16(v0, m0); // a0 b0 a1 b1
+ t1 = _mm_madd_epi16(v0, m1); // c0 d0 c1 d1
+ t2 = _mm_madd_epi16(v0, m2); // e0 f0 e1 f1
+ v0 = _mm_unpacklo_epi32(t0, t1); // a0 c0 b0 d0
+ t0 = _mm_unpackhi_epi32(t0, t1); // a1 b1 c1 d1
+ t1 = _mm_unpacklo_epi32(t2, z); // e0 0 f0 0
+ t2 = _mm_unpackhi_epi32(t2, z); // e1 0 f1 0
+ r0 = _mm_add_epi32(_mm_add_epi32(_mm_unpacklo_epi64(v0, t1), _mm_unpackhi_epi64(v0,t1)), m3); // B0 G0 R0 0
+ r1 = _mm_add_epi32(_mm_add_epi32(_mm_unpacklo_epi64(t0, t2), _mm_unpackhi_epi64(t0,t2)), m3); // B1 G1 R1 0
+ r0 = _mm_srai_epi32(r0, BITS);
+ r1 = _mm_srai_epi32(r1, BITS);
+ v0 = _mm_packus_epi16(_mm_packs_epi32(_mm_slli_si128(r0, 4), r1), z); // 0 B0 G0 R0 B1 G1 R1 0
+
+ // process pixels 2 & 3
+ t0 = _mm_madd_epi16(v1, m0); // a0 b0 a1 b1
+ t1 = _mm_madd_epi16(v1, m1); // c0 d0 c1 d1
+ t2 = _mm_madd_epi16(v1, m2); // e0 f0 e1 f1
+ v1 = _mm_unpacklo_epi32(t0, t1); // a0 c0 b0 d0
+ t0 = _mm_unpackhi_epi32(t0, t1); // a1 b1 c1 d1
+ t1 = _mm_unpacklo_epi32(t2, z); // e0 0 f0 0
+ t2 = _mm_unpackhi_epi32(t2, z); // e1 0 f1 0
+ r0 = _mm_add_epi32(_mm_add_epi32(_mm_unpacklo_epi64(v1, t1), _mm_unpackhi_epi64(v1,t1)), m3); // B2 G2 R2 0
+ r1 = _mm_add_epi32(_mm_add_epi32(_mm_unpacklo_epi64(t0, t2), _mm_unpackhi_epi64(t0,t2)), m3); // B3 G3 R3 0
+ r0 = _mm_srai_epi32(r0, BITS);
+ r1 = _mm_srai_epi32(r1, BITS);
+ v1 = _mm_packus_epi16(_mm_packs_epi32(_mm_slli_si128(r0, 4), r1), z); // 0 B2 G2 R2 B3 G3 R3 0
+
+ // process pixels 4 & 5
+ t0 = _mm_madd_epi16(v2, m0); // a0 b0 a1 b1
+ t1 = _mm_madd_epi16(v2, m1); // c0 d0 c1 d1
+ t2 = _mm_madd_epi16(v2, m2); // e0 f0 e1 f1
+ v2 = _mm_unpacklo_epi32(t0, t1); // a0 c0 b0 d0
+ t0 = _mm_unpackhi_epi32(t0, t1); // a1 b1 c1 d1
+ t1 = _mm_unpacklo_epi32(t2, z); // e0 0 f0 0
+ t2 = _mm_unpackhi_epi32(t2, z); // e1 0 f1 0
+ r0 = _mm_add_epi32(_mm_add_epi32(_mm_unpacklo_epi64(v2, t1), _mm_unpackhi_epi64(v2,t1)), m3); // B4 G4 R4 0
+ r1 = _mm_add_epi32(_mm_add_epi32(_mm_unpacklo_epi64(t0, t2), _mm_unpackhi_epi64(t0,t2)), m3); // B5 G5 R5 0
+ r0 = _mm_srai_epi32(r0, BITS);
+ r1 = _mm_srai_epi32(r1, BITS);
+ v2 = _mm_packus_epi16(_mm_packs_epi32(_mm_slli_si128(r0, 4), r1), z); // 0 B4 G4 R4 B5 G5 R5 0
+
+ // process pixels 6 & 7
+ t0 = _mm_madd_epi16(v3, m0); // a0 b0 a1 b1
+ t1 = _mm_madd_epi16(v3, m1); // c0 d0 c1 d1
+ t2 = _mm_madd_epi16(v3, m2); // e0 f0 e1 f1
+ v3 = _mm_unpacklo_epi32(t0, t1); // a0 c0 b0 d0
+ t0 = _mm_unpackhi_epi32(t0, t1); // a1 b1 c1 d1
+ t1 = _mm_unpacklo_epi32(t2, z); // e0 0 f0 0
+ t2 = _mm_unpackhi_epi32(t2, z); // e1 0 f1 0
+ r0 = _mm_add_epi32(_mm_add_epi32(_mm_unpacklo_epi64(v3, t1), _mm_unpackhi_epi64(v3,t1)), m3); // B6 G6 R6 0
+ r1 = _mm_add_epi32(_mm_add_epi32(_mm_unpacklo_epi64(t0, t2), _mm_unpackhi_epi64(t0,t2)), m3); // B7 G7 R7 0
+ r0 = _mm_srai_epi32(r0, BITS);
+ r1 = _mm_srai_epi32(r1, BITS);
+ v3 = _mm_packus_epi16(_mm_packs_epi32(_mm_slli_si128(r0, 4), r1), z); // 0 B6 G6 R6 B7 G7 R7 0
+
+ v0 = _mm_or_si128(_mm_srli_si128(v0, 1), _mm_slli_si128(v1, 5));
+ v1 = _mm_or_si128(_mm_srli_si128(v1, 3), _mm_slli_si128(v2, 3));
+ v2 = _mm_or_si128(_mm_srli_si128(v2, 5), _mm_slli_si128(v3, 1));
+ _mm_storel_epi64((__m128i*)(dst + x), v0);
+ _mm_storel_epi64((__m128i*)(dst + x + 8), v1);
+ _mm_storel_epi64((__m128i*)(dst + x + 16), v2);
+ }
+
+ for( ; x < size.width*3; x += 3 )
+ {
+ int v0 = src[x], v1 = src[x+1], v2 = src[x+2];
+ uchar t0 = saturate_cast<uchar>((m00*v0 + m01*v1 + m02*v2 + m03)>>BITS);
+ uchar t1 = saturate_cast<uchar>((m10*v0 + m11*v1 + m12*v2 + m13)>>BITS);
+ uchar t2 = saturate_cast<uchar>((m20*v0 + m21*v1 + m22*v2 + m23)>>BITS);
+ dst[x] = t0; dst[x+1] = t1; dst[x+2] = t2;
+ }
+ }
+ return;
+ }
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ if( dst_cn == 1 )
+ for( x = 0; x < size.width; x++, src += 3 )
+ dst[x] = saturate_cast<T>(m[0]*CV_8TO32F(src[0]) +
+ m[1]*CV_8TO32F(src[1]) + m[2]*CV_8TO32F(src[2]) + m[3]);
+ else
+ {
+ const WT* _m = m;
+ for( k = 0; k < dst_cn; k++, dst++, _m += 4 )
+ for( x = 0; x < size.width; x++ )
+ dst[x*dst_cn] = saturate_cast<T>(_m[0]*CV_8TO32F(src[x*3]) +
+ _m[1]*CV_8TO32F(src[x*3+1]) + _m[2]*CV_8TO32F(src[x*3+2]) + _m[3]);
+ }
+ }
+}
+
+template<> void
+transformC3_<ushort, float>( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ typedef ushort T;
+ typedef float WT;
+ Size size = getContinuousSize( srcmat, dstmat );
+ const float* m = (const float*)tmat.data;
+ int dst_cn = dstmat.channels();
+ int x, y, k;
+
+ if( dst_cn == 3 )
+ {
+ __m128 m0, m1, m2, m3;
+ __m128i delta = _mm_setr_epi16(0,-32768,-32768,-32768,-32768,-32768,-32768,0);
+ load3x3Matrix(m, m0, m1, m2, m3);
+ m3 = _mm_sub_ps(m3, _mm_setr_ps(32768.f, 32768.f, 32768.f, 0.f));
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+ int x = 0;
+
+ for( ; x <= (size.width - 4)*3; x += 4*3 )
+ {
+ __m128i z = _mm_setzero_si128();
+ __m128i v0 = _mm_loadu_si128((const __m128i*)(src + x)), v1;
+ __m128i v2 = _mm_loadl_epi64((const __m128i*)(src + x + 8)), v3;
+ v1 = _mm_unpacklo_epi16(_mm_srli_si128(v0, 6), z); // b1 g1 r1
+ v3 = _mm_unpacklo_epi16(_mm_srli_si128(v2, 2), z); // b3 g3 r3
+ v2 = _mm_or_si128(_mm_srli_si128(v0, 12), _mm_slli_si128(v2, 4));
+ v0 = _mm_unpacklo_epi16(v0, z); // b0 g0 r0
+ v2 = _mm_unpacklo_epi16(v2, z); // b2 g2 r2
+ __m128 x0 = _mm_cvtepi32_ps(v0), x1 = _mm_cvtepi32_ps(v1);
+ __m128 x2 = _mm_cvtepi32_ps(v2), x3 = _mm_cvtepi32_ps(v3);
+ __m128 y0 = _mm_add_ps(_mm_add_ps(_mm_add_ps(
+ _mm_mul_ps(m0, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(0,0,0,0))),
+ _mm_mul_ps(m1, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(1,1,1,1)))),
+ _mm_mul_ps(m2, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(2,2,2,2)))), m3);
+ __m128 y1 = _mm_add_ps(_mm_add_ps(_mm_add_ps(
+ _mm_mul_ps(m0, _mm_shuffle_ps(x1,x1,_MM_SHUFFLE(0,0,0,0))),
+ _mm_mul_ps(m1, _mm_shuffle_ps(x1,x1,_MM_SHUFFLE(1,1,1,1)))),
+ _mm_mul_ps(m2, _mm_shuffle_ps(x1,x1,_MM_SHUFFLE(2,2,2,2)))), m3);
+ __m128 y2 = _mm_add_ps(_mm_add_ps(_mm_add_ps(
+ _mm_mul_ps(m0, _mm_shuffle_ps(x2,x2,_MM_SHUFFLE(0,0,0,0))),
+ _mm_mul_ps(m1, _mm_shuffle_ps(x2,x2,_MM_SHUFFLE(1,1,1,1)))),
+ _mm_mul_ps(m2, _mm_shuffle_ps(x2,x2,_MM_SHUFFLE(2,2,2,2)))), m3);
+ __m128 y3 = _mm_add_ps(_mm_add_ps(_mm_add_ps(
+ _mm_mul_ps(m0, _mm_shuffle_ps(x3,x3,_MM_SHUFFLE(0,0,0,0))),
+ _mm_mul_ps(m1, _mm_shuffle_ps(x3,x3,_MM_SHUFFLE(1,1,1,1)))),
+ _mm_mul_ps(m2, _mm_shuffle_ps(x3,x3,_MM_SHUFFLE(2,2,2,2)))), m3);
+ v0 = _mm_cvtps_epi32(y0); v1 = _mm_cvtps_epi32(y1);
+ v2 = _mm_cvtps_epi32(y2); v3 = _mm_cvtps_epi32(y3);
+
+ v0 = _mm_add_epi16(_mm_packs_epi32(_mm_slli_si128(v0,4), v1), delta); // 0 b0 g0 r0 b1 g1 r1 0
+ v2 = _mm_add_epi16(_mm_packs_epi32(_mm_slli_si128(v2,4), v3), delta); // 0 b2 g2 r2 b3 g3 r3 0
+ v1 = _mm_or_si128(_mm_srli_si128(v0,2), _mm_slli_si128(v2,10)); // b0 g0 r0 b1 g1 r1 b2 g2
+ v2 = _mm_srli_si128(v2, 6); // r2 b3 g3 r3 0 0 0 0
+ _mm_storeu_si128((__m128i*)(dst + x), v1);
+ _mm_storel_epi64((__m128i*)(dst + x + 8), v2);
+ }
+
+ for( ; x < size.width*3; x += 3 )
+ {
+ WT v0 = src[x], v1 = src[x+1], v2 = src[x+2];
+ T t0 = saturate_cast<T>(m[0]*v0 + m[1]*v1 + m[2]*v2 + m[3]);
+ T t1 = saturate_cast<T>(m[4]*v0 + m[5]*v1 + m[6]*v2 + m[7]);
+ T t2 = saturate_cast<T>(m[8]*v0 + m[9]*v1 + m[10]*v2 + m[11]);
+ dst[x] = t0; dst[x+1] = t1; dst[x+2] = t2;
+ }
+ }
+ return;
+ }
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ if( dst_cn == 1 )
+ for( x = 0; x < size.width; x++, src += 3 )
+ dst[x] = saturate_cast<T>(m[0]*src[0] + m[1]*src[1] + m[2]*src[2] + m[3]);
+ else
+ {
+ const WT* _m = m;
+ for( k = 0; k < dst_cn; k++, dst++, _m += 4 )
+ for( x = 0; x < size.width; x++ )
+ dst[x*dst_cn] = saturate_cast<T>(_m[0]*src[x*3] + _m[1]*src[x*3+1] + _m[2]*src[x*3+2] + _m[3]);
+ }
+ }
+}
+
+template<> void
+transformC3_<float, float>( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ typedef float T;
+ typedef float WT;
+ Size size = getContinuousSize( srcmat, dstmat );
+ const float* m = (const float*)tmat.data;
+ int dst_cn = dstmat.channels();
+ int x, y, k;
+
+ if( dst_cn == 3 )
+ {
+ __m128 m0, m1, m2, m3;
+ load3x3Matrix(m, m0, m1, m2, m3);
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+ int x = 0;
+
+ for( ; x < (size.width - 1)*3; x += 3 )
+ {
+ __m128 x0 = _mm_loadu_ps(src + x);
+ __m128 y0 = _mm_add_ps(_mm_add_ps(_mm_add_ps(
+ _mm_mul_ps(m0, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(0,0,0,0))),
+ _mm_mul_ps(m1, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(1,1,1,1)))),
+ _mm_mul_ps(m2, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(2,2,2,2)))), m3);
+ _mm_storel_pi((__m64*)(dst + x), y0);
+ _mm_store_ss(dst + x + 2, _mm_movehl_ps(y0,y0));
+ }
+
+ for( ; x < size.width*3; x += 3 )
+ {
+ WT v0 = src[x], v1 = src[x+1], v2 = src[x+2];
+ T t0 = saturate_cast<T>(m[0]*v0 + m[1]*v1 + m[2]*v2 + m[3]);
+ T t1 = saturate_cast<T>(m[4]*v0 + m[5]*v1 + m[6]*v2 + m[7]);
+ T t2 = saturate_cast<T>(m[8]*v0 + m[9]*v1 + m[10]*v2 + m[11]);
+ dst[x] = t0; dst[x+1] = t1; dst[x+2] = t2;
+ }
+ }
+ return;
+ }
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ if( dst_cn == 1 )
+ for( x = 0; x < size.width; x++, src += 3 )
+ dst[x] = saturate_cast<T>(m[0]*src[0] + m[1]*src[1] + m[2]*src[2] + m[3]);
+ else
+ {
+ const WT* _m = m;
+ for( k = 0; k < dst_cn; k++, dst++, _m += 4 )
+ for( x = 0; x < size.width; x++ )
+ dst[x*dst_cn] = saturate_cast<T>(_m[0]*src[x*3] + _m[1]*src[x*3+1] + _m[2]*src[x*3+2] + _m[3]);
+ }
+ }
+}
+
+
+template<> void
+transformC4_<float, float>( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ typedef float T;
+ typedef float WT;
+ Size size = getContinuousSize( srcmat, dstmat );
+ const WT* m = (const WT*)tmat.data;
+ int dst_cn = dstmat.channels();
+ int x, y, k;
+
+ if( dst_cn == 4 )
+ {
+ __m128 m0, m1, m2, m3, m4;
+ load4x4Matrix(m, m0, m1, m2, m3, m4);
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+ for( x = 0; x < size.width*4; x += 4 )
+ {
+ __m128 x0 = _mm_loadu_ps(src + x);
+ __m128 y0 = _mm_add_ps(_mm_add_ps(_mm_add_ps(_mm_add_ps(
+ _mm_mul_ps(m0, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(0,0,0,0))),
+ _mm_mul_ps(m1, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(1,1,1,1)))),
+ _mm_mul_ps(m2, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(2,2,2,2)))),
+ _mm_mul_ps(m3, _mm_shuffle_ps(x0,x0,_MM_SHUFFLE(3,3,3,3)))), m4);
+ _mm_storeu_ps(dst + x, y0);
+ }
+ }
+ return;
+ }
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+ const WT* _m = m;
+ for( k = 0; k < dst_cn; k++, dst++, _m += 5 )
+ for( x = 0; x < size.width; x++ )
+ dst[x*dst_cn] = saturate_cast<T>(_m[0]*src[x*4] + _m[1]*src[x*4+1] +
+ _m[2]*src[x*4+2] + _m[3]*src[x*4+3] + _m[4]);
+ }
+}
+
+
+#endif
+
+
+template<typename T, typename WT> static void
+diagtransC2_( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ Size size = getContinuousSize( srcmat, dstmat );
+ const WT* m = (const WT*)tmat.data;
+ int x, y;
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ for( x = 0; x < size.width*2; x += 2 )
+ {
+ T t0 = saturate_cast<T>(m[0]*src[x] + m[2]);
+ T t1 = saturate_cast<T>(m[4]*src[x+1] + m[5]);
+ dst[x] = t0; dst[x+1] = t1;
+ }
+ }
+}
+
+template<typename T, typename WT> static void
+diagtransC3_( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ Size size = getContinuousSize( srcmat, dstmat );
+ const WT* m = (const WT*)tmat.data;
+ int x, y;
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ for( x = 0; x < size.width*3; x += 3 )
+ {
+ T t0 = saturate_cast<T>(m[0]*src[x] + m[3]);
+ T t1 = saturate_cast<T>(m[5]*src[x+1] + m[7]);
+ T t2 = saturate_cast<T>(m[10]*src[x+2] + m[11]);
+ dst[x] = t0; dst[x+1] = t1; dst[x+2] = t2;
+ }
+ }
+}
+
+template<typename T, typename WT> static void
+diagtransC4_( const Mat& srcmat, Mat& dstmat, Mat& tmat )
+{
+ Size size = getContinuousSize( srcmat, dstmat );
+ const WT* m = (const WT*)tmat.data;
+ int x, y;
+
+ for( y = 0; y < size.height; y++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*y);
+ T* dst = (T*)(dstmat.data + dstmat.step*y);
+
+ for( x = 0; x < size.width*4; x += 4 )
+ {
+ T t0 = saturate_cast<T>(m[0]*src[x] + m[4]);
+ T t1 = saturate_cast<T>(m[6]*src[x+1] + m[9]);
+ dst[x] = t0; dst[x+1] = t1;
+ t0 = saturate_cast<T>(m[12]*src[x+2] + m[14]);
+ t1 = saturate_cast<T>(m[18]*src[x+3] + m[19]);
+ dst[x+2] = t0; dst[x+3] = t1;
+ }
+ }
+}
+
+typedef void (*TransformFunc)( const Mat &src, Mat& dst, Mat& M );
+
+void transform( const Mat& src, Mat& dst, const Mat& _m )
+{
+ static TransformFunc tab[2][32] =
+ {
+ {transformC1_<uchar, float>, 0, transformC1_<ushort, float>, transformC1_<short,float>,
+ transformC1_<int, double>, transformC1_<float, float>, transformC1_<double, double>, 0,
+ transformC2_<uchar, float>, 0, transformC2_<ushort, float>, transformC2_<short,float>,
+ transformC2_<int, double>, transformC2_<float, float>, transformC2_<double, double>, 0,
+ transformC3_<uchar, float>, 0, transformC3_<ushort, float>, transformC3_<short,float>,
+ transformC3_<int, double>, transformC3_<float, float>, transformC3_<double, double>, 0,
+ transformC4_<uchar, float>, 0, transformC4_<ushort, float>, transformC4_<short,float>,
+ transformC4_<int, double>, transformC4_<float, float>, transformC4_<double, double>, 0},
+
+ {0, 0, 0, 0, 0, 0, 0, 0,
+ diagtransC2_<uchar, float>, 0, diagtransC2_<ushort, float>, diagtransC2_<short,float>,
+ diagtransC2_<int, double>, diagtransC2_<float, float>, diagtransC2_<double, double>, 0,
+ diagtransC3_<uchar, float>, 0, diagtransC3_<ushort, float>, diagtransC3_<short,float>,
+ diagtransC3_<int, double>, diagtransC3_<float, float>, diagtransC3_<double, double>, 0,
+ diagtransC4_<uchar, float>, 0, diagtransC4_<ushort, float>, diagtransC4_<short,float>,
+ diagtransC4_<int, double>, diagtransC4_<float, float>, diagtransC4_<double, double>, 0}
+ };
+
+ int type = src.type(), depth = src.depth(), scn = src.channels(), dcn = _m.rows;
+ bool isDiag = false;
+ CV_Assert( (scn == _m.cols || scn + 1 == _m.cols) && scn <= 4 && dcn <= 4 );
+
+ double mbuf[20] = {0};
+ Mat m = _m;
+
+ dst.create( src.size(), CV_MAKETYPE(depth, dcn) );
+ Size size = getContinuousSize( src, dst );
+
+ int mtype = depth == CV_32S || depth == CV_64F ? CV_64F : CV_32F;
+ if( !_m.isContinuous() || _m.type() != mtype || _m.cols != scn + 1 )
+ {
+ m = Mat(dcn, scn + 1, mtype, mbuf);
+ Mat tmat_part = m.colRange(0, _m.cols);
+ _m.convertTo(tmat_part, mtype);
+ }
+
+ if( scn == dcn )
+ {
+ int i, j;
+ double eps = mtype == CV_32F ? FLT_EPSILON : DBL_EPSILON;
+
+ if( scn == 1 )
+ {
+ double alpha, beta;
+ if( mtype == CV_32F )
+ alpha = ((float*)m.data)[0], beta = ((float*)m.data)[1];
+ else
+ alpha = ((double*)m.data)[0], beta = ((double*)m.data)[1];
+ src.convertTo( dst, dst.type(), alpha, beta );
+ return;
+ }
+
+ for( i = 0, isDiag = true; isDiag && i < scn; i++ )
+ {
+ for( j = 0; isDiag && j < scn; j++ )
+ {
+ double v = mtype == CV_32F ? ((float*)m.data)[i*(scn+1)+j] :
+ ((double*)m.data)[i*(scn+1)+j];
+ if( i != j && fabs(v) > eps )
+ isDiag = false;
+ }
+ }
+
+ if( isDiag && depth == CV_8U )
+ {
+ Mat lut(1, 256, CV_8UC(scn));
+ for( i = 0; i < scn; i++ )
+ {
+ uchar* data = lut.data + i;
+ double val, delta;
+ if( mtype == CV_32F )
+ {
+ val = ((float*)m.data)[i*(scn+1) + scn];
+ delta = ((float*)m.data)[i*(scn+1) + i];
+ }
+ else
+ {
+ val = ((double*)m.data)[i*(scn+1) + scn];
+ delta = ((double*)m.data)[i*(scn+1) + i];
+ }
+ for( j = 0; j < 256; j++, val += delta )
+ {
+ int ival = cvRound(val);
+ data[j] = CV_CAST_8U(ival);
+ }
+ }
+ LUT( src, lut, dst );
+ return;
+ }
+ }
+
+ TransformFunc func = tab[0][type];
+ CV_Assert( func != 0 );
+ func( src, dst, m );
+}
+
+
+/****************************************************************************************\
+* Perspective Transform *
+\****************************************************************************************/
+
+template<typename T> static void
+perspectiveTransform2_( const Mat& srcmat, Mat& dstmat, const double* mat )
+{
+ Size size = getContinuousSize( srcmat, dstmat, srcmat.channels() );
+
+ for( int i = 0; i < size.height; i++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*i);
+ T* dst = (T*)(dstmat.data + dstmat.step*i);
+
+ for( int j = 0; j < size.width; j += 2 )
+ {
+ T x = src[j], y = src[j + 1];
+ double w = x*mat[6] + y*mat[7] + mat[8];
+
+ if( fabs(w) > FLT_EPSILON )
+ {
+ w = 1./w;
+ dst[j] = (T)((x*mat[0] + y*mat[1] + mat[2])*w);
+ dst[j+1] = (T)((x*mat[3] + y*mat[4] + mat[5])*w);
+ }
+ else
+ dst[j] = dst[j+1] = (T)0;
+ }
+ }
+}
+
+template<typename T> static void
+perspectiveTransform3_( const Mat& srcmat, Mat& dstmat, const double* mat )
+{
+ Size size = getContinuousSize( srcmat, dstmat, srcmat.channels() );
+
+ for( int i = 0; i < size.height; i++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*i);
+ T* dst = (T*)(dstmat.data + dstmat.step*i);
+
+ for( int j = 0; j < size.width; j += 3 )
+ {
+ T x = src[j], y = src[j + 1], z = src[j + 2];
+ double w = x*mat[12] + y*mat[13] + z*mat[14] + mat[15];
+
+ if( fabs(w) > FLT_EPSILON )
+ {
+ w = 1./w;
+ dst[j] = (T)((x*mat[0] + y*mat[1] + z*mat[2] + mat[3]) * w);
+ dst[j+1] = (T)((x*mat[4] + y*mat[5] + z*mat[6] + mat[7]) * w);
+ dst[j+2] = (T)((x*mat[8] + y*mat[9] + z*mat[10] + mat[11]) * w);
+ }
+ else
+ dst[j] = dst[j+1] = dst[j+2] = (T)0;
+ }
+ }
+}
+
+template<typename T> static void
+perspectiveTransform23_( const Mat& srcmat, Mat& dstmat, const double* mat )
+{
+ Size size = getContinuousSize( srcmat, dstmat, srcmat.channels() );
+
+ for( int i = 0; i < size.height; i++ )
+ {
+ const T* src = (const T*)(srcmat.data + srcmat.step*i);
+ T* dst = (T*)(dstmat.data + dstmat.step*i);
+
+ for( int j = 0; j < size.width; j++, src += 3, dst += 2 )
+ {
+ T x = src[0], y = src[1], z = src[2];
+ double w = x*mat[8] + y*mat[9] + z*mat[10] + mat[11];
+
+ if( fabs(w) > FLT_EPSILON )
+ {
+ w = 1./w;
+ dst[0] = (T)((x*mat[0] + y*mat[1] + z*mat[2] + mat[3])*w);
+ dst[1] = (T)((x*mat[4] + y*mat[5] + z*mat[6] + mat[7])*w);
+ }
+ else
+ dst[0] = dst[1] = (T)0;
+ }
+ }
+}
+
+typedef void (*PerspectiveTransformFunc)(const Mat& src, Mat& dst, const double* mat );
+
+void perspectiveTransform( const Mat& src, Mat& dst, const Mat& _m )
+{
+ int depth = src.depth(), scn = src.channels(), dcn = _m.rows-1;
+ CV_Assert( (depth == CV_32F || depth == CV_64F) && scn+1 == _m.cols && scn <= 4 &&
+ ((scn == 2 && dcn == 2) || (scn == 3 && dcn == 3) || (scn == 2 && dcn == 3)));
+
+ double mbuf[16] = {0};
+ Mat tmat;
+ const double* m = (const double*)_m.data;
+
+ dst.create( src.size(), CV_MAKETYPE(depth, dcn) );
+
+ if( !_m.isContinuous() || _m.type() != CV_64F )
+ {
+ tmat = Mat(dcn + 1, scn + 1, CV_64F, mbuf);
+ _m.convertTo(tmat, CV_64F);
+ m = (const double*)tmat.data;
+ }
+
+ PerspectiveTransformFunc func = 0;
+ if( scn == 2 && dcn == 2 )
+ {
+ if(depth == CV_32F)
+ func = perspectiveTransform2_<float>;
+ else
+ func = perspectiveTransform2_<double>;
+ }
+ else if( scn == 2 && dcn == 3 )
+ {
+ if(depth == CV_32F)
+ func = perspectiveTransform23_<float>;
+ else
+ func = perspectiveTransform23_<double>;
+ }
+ else if( scn == 3 && dcn == 3 )
+ {
+ if(depth == CV_32F)
+ func = perspectiveTransform3_<float>;
+ else
+ func = perspectiveTransform3_<double>;
+ }
+ else
+ CV_Error( CV_StsNotImplemented, "Only 2->2, 2->3 and 3->3 perspective transformation is implemented" );
+ func( src, dst, m );
+}
+
+/****************************************************************************************\
+* ScaleAdd *
+\****************************************************************************************/
+
+void scaleAdd( const Mat& src1, double alpha, const Mat& src2, Mat& dst )
+{
+ int type = src1.type(), depth = CV_MAT_DEPTH(type);
+ CV_Assert( src1.size() == src2.size() && type == src2.type() );
+ dst.create( src1.size(), type );
+ Size size = getContinuousSize( src1, src2, dst, src1.channels() );
+
+ if( depth == CV_32F )
+ {
+ const float *s1 = (const float*)src1.data, *s2 = (const float*)src2.data;
+ float* d = (float*)dst.data;
+ size_t step1 = src1.step/sizeof(s1[0]), step2 = src2.step/sizeof(s2[0]);
+ size_t step = dst.step/sizeof(d[0]);
+ float a = (float)alpha;
+
+ if( size.width == 1 )
+ {
+ for( ; size.height--; s1 += step1, s2 += step2, d += step )
+ d[0] = s1[0]*a + s2[0];
+ return;
+ }
+
+ for( ; size.height--; s1 += step1, s2 += step2, d += step )
+ {
+ int i;
+ for( i = 0; i <= size.width - 4; i += 4 )
+ {
+ float t0 = s1[i]*a + s2[i];
+ float t1 = s1[i+1]*a + s2[i+1];
+ d[i] = t0;
+ d[i+1] = t1;
+ t0 = s1[i+2]*a + s2[i+2];
+ t1 = s1[i+3]*a + s2[i+3];
+ d[i+2] = t0;
+ d[i+3] = t1;
+ }
+
+ for( ; i < size.width; i++ )
+ d[i] = s1[i]*a + s2[i];
+ }
+ }
+ else if( depth == CV_64F )
+ {
+ const double *s1 = (const double*)src1.data, *s2 = (const double*)src2.data;
+ double* d = (double*)dst.data;
+ size_t step1 = src1.step/sizeof(s1[0]), step2 = src2.step/sizeof(s2[0]);
+ size_t step = dst.step/sizeof(d[0]);
+
+ if( size.width == 1 )
+ {
+ for( ; size.height--; s1 += step1, s2 += step2, d += step )
+ d[0] = s1[0]*alpha + s2[0];
+ return;
+ }
+
+ for( ; size.height--; s1 += step1, s2 += step2, d += step )
+ {
+ int i;
+ for( i = 0; i <= size.width - 4; i += 4 )
+ {
+ double t0 = s1[i]*alpha + s2[i];
+ double t1 = s1[i+1]*alpha + s2[i+1];
+ d[i] = t0;
+ d[i+1] = t1;
+ t0 = s1[i+2]*alpha + s2[i+2];
+ t1 = s1[i+3]*alpha + s2[i+3];
+ d[i+2] = t0;
+ d[i+3] = t1;
+ }
+
+ for( ; i < size.width; i++ )
+ d[i] = s1[i]*alpha + s2[i];
+ }
+ }
+ else
+ CV_Error( CV_StsUnsupportedFormat, "" );
+}
+
+/****************************************************************************************\
+* Covariation Matrix *
+\****************************************************************************************/
+
+void calcCovarMatrix( const Mat* data, int nsamples, Mat& covar, Mat& _mean, int flags, int ctype )
+{
+ CV_Assert( data && nsamples > 0 );
+ Size size = data[0].size();
+ int sz = size.width*size.height, esz = (int)data[0].elemSize();
+ int type = data[0].type();
+ Mat mean;
+ ctype = std::max(std::max(CV_MAT_DEPTH(ctype >= 0 ? ctype : type), _mean.depth()), CV_32F);
+
+ if( (flags & CV_COVAR_USE_AVG) != 0 )
+ {
+ CV_Assert( _mean.size() == size );
+ if( _mean.isContinuous() && _mean.type() == ctype )
+ mean = _mean.reshape(1, 1);
+ else
+ {
+ _mean.convertTo(mean, ctype);
+ mean = mean.reshape(1, 1);
+ }
+ }
+
+ Mat _data(nsamples, sz, type);
+ for( int i = 0; i < nsamples; i++ )
+ {
+ CV_Assert( data[i].size() == size && data[i].type() == type );
+ if( data[i].isContinuous() )
+ memcpy( _data.ptr(i), data[i].data, sz*esz );
+ else
+ {
+ Mat dataRow(size.height, size.width, type, _data.ptr(i));
+ data[i].copyTo(dataRow);
+ }
+ }
+
+ calcCovarMatrix( _data, covar, mean, (flags & ~(CV_COVAR_ROWS|CV_COVAR_COLS)) | CV_COVAR_ROWS, ctype );
+ if( (flags & CV_COVAR_USE_AVG) == 0 )
+ _mean = mean.reshape(1, size.height);
+}
+
+void calcCovarMatrix( const Mat& data, Mat& covar, Mat& _mean, int flags, int ctype )
+{
+ CV_Assert( ((flags & CV_COVAR_ROWS) != 0) ^ ((flags & CV_COVAR_COLS) != 0) );
+ bool takeRows = (flags & CV_COVAR_ROWS) != 0;
+ int type = data.type();
+ int nsamples = takeRows ? data.rows : data.cols;
+ CV_Assert( nsamples > 0 );
+ Size size = takeRows ? Size(data.cols, 1) : Size(1, data.rows);
+ Mat mean = _mean;
+ ctype = std::max(std::max(CV_MAT_DEPTH(ctype >= 0 ? ctype : type), _mean.depth()), CV_32F);
+
+ if( (flags & CV_COVAR_USE_AVG) != 0 )
+ {
+ CV_Assert( mean.size() == size );
+ if( mean.type() != ctype )
+ _mean.convertTo(mean, ctype);
+ }
+ else
+ {
+ reduce( data, _mean, takeRows ? 0 : 1, CV_REDUCE_AVG, ctype );
+ mean = _mean;
+ }
+
+ mulTransposed( data, covar, ((flags & CV_COVAR_NORMAL) == 0) ^ takeRows,
+ mean, (flags & CV_COVAR_SCALE) != 0 ? 1./nsamples : 1, ctype );
+}
+
+/****************************************************************************************\
+* Mahalanobis *
+\****************************************************************************************/
+
+double Mahalanobis( const Mat& v1, const Mat& v2, const Mat& icovar )
+{
+ int type = v1.type(), depth = v1.depth();
+ Size sz = v1.size();
+ int i, j, len = sz.width*sz.height*v1.channels();
+ AutoBuffer<uchar> buf(len*v1.elemSize());
+ double result = 0;
+
+ CV_Assert( type == v2.type() && type == icovar.type() &&
+ sz == v2.size() && len == icovar.rows && len == icovar.cols );
+
+ if( v1.isContinuous() && v2.isContinuous() )
+ {
+ sz.width *= sz.height;
+ sz.height = 1;
+ }
+
+ if( depth == CV_32F )
+ {
+ const float* src1 = (const float*)v1.data;
+ const float* src2 = (const float*)v2.data;
+ size_t step1 = v1.step/sizeof(src1[0]);
+ size_t step2 = v2.step/sizeof(src2[0]);
+ float* diff = (float*)(uchar*)buf;
+ const float* mat = (const float*)icovar.data;
+ size_t matstep = icovar.step/sizeof(mat[0]);
+
+ for( ; sz.height--; src1 += step1, src2 += step2, diff += sz.width )
+ {
+ for( i = 0; i < sz.width; i++ )
+ diff[i] = src1[i] - src2[i];
+ }
+
+ diff = (float*)(uchar*)buf;
+ for( i = 0; i < len; i++, mat += matstep )
+ {
+ double row_sum = 0;
+ for( j = 0; j <= len - 4; j += 4 )
+ row_sum += diff[j]*mat[j] + diff[j+1]*mat[j+1] +
+ diff[j+2]*mat[j+2] + diff[j+3]*mat[j+3];
+ for( ; j < len; j++ )
+ row_sum += diff[j]*mat[j];
+ result += row_sum * diff[i];
+ }
+ }
+ else if( depth == CV_64F )
+ {
+ const double* src1 = (const double*)v1.data;
+ const double* src2 = (const double*)v2.data;
+ size_t step1 = v1.step/sizeof(src1[0]);
+ size_t step2 = v2.step/sizeof(src2[0]);
+ double* diff = (double*)(uchar*)buf;
+ const double* mat = (const double*)icovar.data;
+ size_t matstep = icovar.step/sizeof(mat[0]);
+
+ for( ; sz.height--; src1 += step1, src2 += step2, diff += sz.width )
+ {
+ for( i = 0; i < sz.width; i++ )
+ diff[i] = src1[i] - src2[i];
+ }
+
+ diff = (double*)(uchar*)buf;
+ for( i = 0; i < len; i++, mat += matstep )
+ {
+ double row_sum = 0;
+ for( j = 0; j <= len - 4; j += 4 )
+ row_sum += diff[j]*mat[j] + diff[j+1]*mat[j+1] +
+ diff[j+2]*mat[j+2] + diff[j+3]*mat[j+3];
+ for( ; j < len; j++ )
+ row_sum += diff[j]*mat[j];
+ result += row_sum * diff[i];
+ }
+ }
+ else
+ CV_Error( CV_StsUnsupportedFormat, "" );
+
+ return std::sqrt(result);
+}
+
+
+/****************************************************************************************\
+* cvMulTransposed *
+\****************************************************************************************/
+
+template<typename sT, typename dT> static void
+MulTransposedR( const Mat& srcmat, Mat& dstmat, const Mat& deltamat, double scale )
+{
+ int i, j, k;
+ const sT* src = (const sT*)srcmat.data;
+ dT* dst = (dT*)dstmat.data;
+ const dT* delta = (const dT*)deltamat.data;
+ size_t srcstep = srcmat.step/sizeof(src[0]);
+ size_t dststep = dstmat.step/sizeof(dst[0]);
+ size_t deltastep = deltamat.rows > 1 ? deltamat.step/sizeof(delta[0]) : 0;
+ int delta_cols = deltamat.cols;
+ Size size = srcmat.size();
+ dT* tdst = dst;
+ dT* col_buf = 0;
+ dT* delta_buf = 0;
+ int buf_size = size.height*sizeof(dT);
+ AutoBuffer<uchar> buf;
+
+ if( delta && delta_cols < size.width )
+ {
+ assert( delta_cols == 1 );
+ buf_size *= 5;
+ }
+ buf.allocate(buf_size);
+ col_buf = (dT*)(uchar*)buf;
+
+ if( delta && delta_cols < size.width )
+ {
+ delta_buf = col_buf + size.height;
+ for( i = 0; i < size.height; i++ )
+ delta_buf[i*4] = delta_buf[i*4+1] =
+ delta_buf[i*4+2] = delta_buf[i*4+3] = delta[i*deltastep];
+ delta = delta_buf;
+ deltastep = deltastep ? 4 : 0;
+ }
+
+ if( !delta )
+ for( i = 0; i < size.width; i++, tdst += dststep )
+ {
+ for( k = 0; k < size.height; k++ )
+ col_buf[k] = src[k*srcstep+i];
+
+ for( j = i; j <= size.width - 4; j += 4 )
+ {
+ double s0 = 0, s1 = 0, s2 = 0, s3 = 0;
+ const sT *tsrc = src + j;
+
+ for( k = 0; k < size.height; k++, tsrc += srcstep )
+ {
+ double a = col_buf[k];
+ s0 += a * tsrc[0];
+ s1 += a * tsrc[1];
+ s2 += a * tsrc[2];
+ s3 += a * tsrc[3];
+ }
+
+ tdst[j] = (dT)(s0*scale);
+ tdst[j+1] = (dT)(s1*scale);
+ tdst[j+2] = (dT)(s2*scale);
+ tdst[j+3] = (dT)(s3*scale);
+ }
+
+ for( ; j < size.width; j++ )
+ {
+ double s0 = 0;
+ const sT *tsrc = src + j;
+
+ for( k = 0; k < size.height; k++, tsrc += srcstep )
+ s0 += col_buf[k] * tsrc[0];
+
+ tdst[j] = (dT)(s0*scale);
+ }
+ }
+ else
+ for( i = 0; i < size.width; i++, tdst += dststep )
+ {
+ if( !delta_buf )
+ for( k = 0; k < size.height; k++ )
+ col_buf[k] = src[k*srcstep+i] - delta[k*deltastep+i];
+ else
+ for( k = 0; k < size.height; k++ )
+ col_buf[k] = src[k*srcstep+i] - delta_buf[k*deltastep];
+
+ for( j = i; j <= size.width - 4; j += 4 )
+ {
+ double s0 = 0, s1 = 0, s2 = 0, s3 = 0;
+ const sT *tsrc = src + j;
+ const dT *d = delta_buf ? delta_buf : delta + j;
+
+ for( k = 0; k < size.height; k++, tsrc+=srcstep, d+=deltastep )
+ {
+ double a = col_buf[k];
+ s0 += a * (tsrc[0] - d[0]);
+ s1 += a * (tsrc[1] - d[1]);
+ s2 += a * (tsrc[2] - d[2]);
+ s3 += a * (tsrc[3] - d[3]);
+ }
+
+ tdst[j] = (dT)(s0*scale);
+ tdst[j+1] = (dT)(s1*scale);
+ tdst[j+2] = (dT)(s2*scale);
+ tdst[j+3] = (dT)(s3*scale);
+ }
+
+ for( ; j < size.width; j++ )
+ {
+ double s0 = 0;
+ const sT *tsrc = src + j;
+ const dT *d = delta_buf ? delta_buf : delta + j;
+
+ for( k = 0; k < size.height; k++, tsrc+=srcstep, d+=deltastep )
+ s0 += col_buf[k] * (tsrc[0] - d[0]);
+
+ tdst[j] = (dT)(s0*scale);
+ }
+ }
+}
+
+
+template<typename sT, typename dT> static void
+MulTransposedL( const Mat& srcmat, Mat& dstmat, const Mat& deltamat, double scale )
+{
+ int i, j, k;
+ const sT* src = (const sT*)srcmat.data;
+ dT* dst = (dT*)dstmat.data;
+ const dT* delta = (const dT*)deltamat.data;
+ size_t srcstep = srcmat.step/sizeof(src[0]);
+ size_t dststep = dstmat.step/sizeof(dst[0]);
+ size_t deltastep = deltamat.rows > 1 ? deltamat.step/sizeof(delta[0]) : 0;
+ int delta_cols = deltamat.cols;
+ Size size = srcmat.size();
+ dT* tdst = dst;
+
+ if( !delta )
+ for( i = 0; i < size.height; i++, tdst += dststep )
+ for( j = i; j < size.height; j++ )
+ {
+ double s = 0;
+ const sT *tsrc1 = src + i*srcstep;
+ const sT *tsrc2 = src + j*srcstep;
+
+ for( k = 0; k <= size.width - 4; k += 4 )
+ s += tsrc1[k]*tsrc2[k] + tsrc1[k+1]*tsrc2[k+1] +
+ tsrc1[k+2]*tsrc2[k+2] + tsrc1[k+3]*tsrc2[k+3];
+ for( ; k < size.width; k++ )
+ s += tsrc1[k] * tsrc2[k];
+ tdst[j] = (dT)(s*scale);
+ }
+ else
+ {
+ dT delta_buf[4];
+ int delta_shift = delta_cols == size.width ? 4 : 0;
+ AutoBuffer<uchar> buf(size.width*sizeof(dT));
+ dT* row_buf = (dT*)(uchar*)buf;
+
+ for( i = 0; i < size.height; i++, tdst += dststep )
+ {
+ const sT *tsrc1 = src + i*srcstep;
+ const dT *tdelta1 = delta + i*deltastep;
+
+ if( delta_cols < size.width )
+ for( k = 0; k < size.width; k++ )
+ row_buf[k] = tsrc1[k] - tdelta1[0];
+ else
+ for( k = 0; k < size.width; k++ )
+ row_buf[k] = tsrc1[k] - tdelta1[k];
+
+ for( j = i; j < size.height; j++ )
+ {
+ double s = 0;
+ const sT *tsrc2 = src + j*srcstep;
+ const dT *tdelta2 = delta + j*deltastep;
+ if( delta_cols < size.width )
+ {
+ delta_buf[0] = delta_buf[1] =
+ delta_buf[2] = delta_buf[3] = tdelta2[0];
+ tdelta2 = delta_buf;
+ }
+ for( k = 0; k <= size.width-4; k += 4, tdelta2 += delta_shift )
+ s += row_buf[k]*(tsrc2[k] - tdelta2[0]) +
+ row_buf[k+1]*(tsrc2[k+1] - tdelta2[1]) +
+ row_buf[k+2]*(tsrc2[k+2] - tdelta2[2]) +
+ row_buf[k+3]*(tsrc2[k+3] - tdelta2[3]);
+ for( ; k < size.width; k++, tdelta2++ )
+ s += row_buf[k]*(tsrc2[k] - tdelta2[0]);
+ tdst[j] = (dT)(s*scale);
+ }
+ }
+ }
+}
+
+typedef void (*MulTransposedFunc)(const Mat& src, Mat& dst, const Mat& delta, double scale);
+
+void mulTransposed( const Mat& src, Mat& dst, bool ata,
+ const Mat& _delta, double scale, int dtype )
+{
+ const int gemm_level = 100; // boundary above which GEMM is faster.
+ int stype = src.type();
+ Mat delta = _delta;
+ dtype = std::max(std::max(CV_MAT_DEPTH(dtype >= 0 ? dtype : stype), delta.depth()), CV_32F);
+ CV_Assert( src.channels() == 1 );
+
+ if( delta.data )
+ {
+ CV_Assert( delta.channels() == 1 &&
+ (delta.rows == src.rows || delta.rows == 1) &&
+ (delta.cols == src.cols || delta.cols == 1));
+ if( delta.type() != dtype )
+ _delta.convertTo(delta, dtype);
+ }
+
+ int dsize = ata ? src.cols : src.rows;
+ dst.create( dsize, dsize, dtype );
+
+ if( src.data == dst.data || (stype == dtype &&
+ (dst.cols >= gemm_level && dst.rows >= gemm_level &&
+ src.cols >= gemm_level && src.rows >= gemm_level)))
+ {
+ Mat src2;
+ const Mat* tsrc = &src;
+ if( delta.data )
+ {
+ if( delta.size() == src.size() )
+ subtract( src, delta, src2 );
+ else
+ {
+ repeat(delta, src.rows/delta.rows, src.cols/delta.cols, src2);
+ subtract( src, src2, src2 );
+ }
+ tsrc = &src2;
+ }
+ gemm( *tsrc, *tsrc, scale, Mat(), 0, dst, ata ? GEMM_1_T : GEMM_2_T );
+ }
+ else
+ {
+ MulTransposedFunc func = 0;
+ if(stype == CV_8U && dtype == CV_32F)
+ {
+ if(ata)
+ func = MulTransposedR<uchar,float>;
+ else
+ func = MulTransposedL<uchar,float>;
+ }
+ else if(stype == CV_8U && dtype == CV_64F)
+ {
+ if(ata)
+ func = MulTransposedR<uchar,double>;
+ else
+ func = MulTransposedL<uchar,double>;
+ }
+ else if(stype == CV_16U && dtype == CV_32F)
+ {
+ if(ata)
+ func = MulTransposedR<ushort,float>;
+ else
+ func = MulTransposedL<ushort,float>;
+ }
+ else if(stype == CV_16U && dtype == CV_64F)
+ {
+ if(ata)
+ func = MulTransposedR<ushort,double>;
+ else
+ func = MulTransposedL<ushort,double>;
+ }
+ else if(stype == CV_16S && dtype == CV_32F)
+ {
+ if(ata)
+ func = MulTransposedR<short,float>;
+ else
+ func = MulTransposedL<short,float>;
+ }
+ else if(stype == CV_16S && dtype == CV_64F)
+ {
+ if(ata)
+ func = MulTransposedR<short,double>;
+ else
+ func = MulTransposedL<short,double>;
+ }
+ else if(stype == CV_32F && dtype == CV_32F)
+ {
+ if(ata)
+ func = MulTransposedR<float,float>;
+ else
+ func = MulTransposedL<float,float>;
+ }
+ else if(stype == CV_32F && dtype == CV_64F)
+ {
+ if(ata)
+ func = MulTransposedR<float,double>;
+ else
+ func = MulTransposedL<float,double>;
+ }
+ else if(stype == CV_64F && dtype == CV_64F)
+ {
+ if(ata)
+ func = MulTransposedR<double,double>;
+ else
+ func = MulTransposedL<double,double>;
+ }
+ if( !func )
+ CV_Error( CV_StsUnsupportedFormat, "" );
+
+ func( src, dst, delta, scale );
+ completeSymm( dst, false );
+ }
+}
+
+/****************************************************************************************\
+* Dot Product *
+\****************************************************************************************/
+
+template<typename T, typename WT, typename ST> static double
+dotprod_( const Mat& srcmat1, const Mat& srcmat2 )
+{
+ const T *src1 = (const T*)srcmat1.data, *src2 = (const T*)srcmat2.data;
+ size_t step1 = srcmat1.step/sizeof(src1[0]), step2 = srcmat2.step/sizeof(src2[0]);
+ ST sum = 0;
+ Size size = getContinuousSize( srcmat1, srcmat2, srcmat1.channels() );
+
+ if( size.width == 1 )
+ {
+ WT t = 0;
+ for( ; size.height--; src1 += step1, src2 += step2 )
+ t += (WT)src1[0]*src2[0];
+ sum += t;
+ }
+ else
+ {
+ for( ; size.height--; src1 += step1, src2 += step2 )
+ {
+ int i;
+ WT t = 0;
+ for( i = 0; i <= size.width - 4; i += 4 )
+ {
+ sum += (WT)src1[i]*src2[i] +
+ (WT)src1[i+1]*src2[i+1] +
+ (WT)src1[i+2]*src2[i+2] +
+ (WT)src1[i+3]*src2[i+3];
+ }
+
+ for( ; i < size.width; i++ )
+ t += (WT)src1[i]*src2[i];
+ sum += t;
+ }
+ }
+ return (double)sum;
+}
+
+typedef double (*DotProductFunc)(const Mat& src1, const Mat& src2);
+
+double Mat::dot(const Mat& mat) const
+{
+ static DotProductFunc tab[] = {
+ dotprod_<uchar, int, int64>, 0,
+ dotprod_<ushort, double, double>,
+ dotprod_<short, double, double>,
+ dotprod_<int, double, double>,
+ dotprod_<float, double, double>,
+ dotprod_<double, double, double>, 0 };
+
+ DotProductFunc func = tab[depth()];
+ CV_Assert( mat.type() == type() && mat.size() == size() && func != 0 );
+ return func( *this, mat );
+}
+
+/****************************************************************************************\
+* PCA *
+\****************************************************************************************/
+
+PCA::PCA() {}
+
+PCA::PCA(const Mat& data, const Mat& mean, int flags, int maxComponents)
+{
+ operator()(data, mean, flags, maxComponents);
+}
+
+PCA& PCA::operator()(const Mat& data, const Mat& _mean, int flags, int maxComponents)
+{
+ int covar_flags = CV_COVAR_SCALE;
+ int i, len, in_count;
+ Size mean_sz;
+
+ CV_Assert( data.channels() == 1 );
+ if( flags & CV_PCA_DATA_AS_COL )
+ {
+ len = data.rows;
+ in_count = data.cols;
+ covar_flags |= CV_COVAR_COLS;
+ mean_sz = Size(1, len);
+ }
+ else
+ {
+ len = data.cols;
+ in_count = data.rows;
+ covar_flags |= CV_COVAR_ROWS;
+ mean_sz = Size(len, 1);
+ }
+
+ int count = std::min(len, in_count), out_count = count;
+ if( maxComponents > 0 )
+ out_count = std::min(count, maxComponents);
+
+ // "scrambled" way to compute PCA (when cols(A)>rows(A)):
+ // B = A'A; B*x=b*x; C = AA'; C*y=c*y -> AA'*y=c*y -> A'A*(A'*y)=c*(A'*y) -> c = b, x=A'*y
+ if( len <= in_count )
+ covar_flags |= CV_COVAR_NORMAL;
+
+ int ctype = std::max(CV_32F, data.depth());
+ mean.create( mean_sz, ctype );
+
+ Mat covar( count, count, ctype );
+
+ if( _mean.data )
+ {
+ CV_Assert( _mean.size() == mean_sz );
+ _mean.convertTo(mean, ctype);
+ }
+
+ calcCovarMatrix( data, covar, mean, covar_flags, ctype );
+ eigen( covar, eigenvalues, eigenvectors );
+
+ if( !(covar_flags & CV_COVAR_NORMAL) )
+ {
+ // CV_PCA_DATA_AS_ROW: cols(A)>rows(A). x=A'*y -> x'=y'*A
+ // CV_PCA_DATA_AS_COL: rows(A)>cols(A). x=A''*y -> x'=y'*A'
+ Mat tmp_data, tmp_mean = repeat(mean, data.rows/mean.rows, data.cols/mean.cols);
+ if( data.type() != ctype || tmp_mean.data == mean.data )
+ {
+ data.convertTo( tmp_data, ctype );
+ subtract( tmp_data, tmp_mean, tmp_data );
+ }
+ else
+ {
+ subtract( data, tmp_mean, tmp_mean );
+ tmp_data = tmp_mean;
+ }
+
+ Mat evects1(count, len, ctype);
+ gemm( eigenvectors, tmp_data, 1, Mat(), 0, evects1,
+ (flags & CV_PCA_DATA_AS_COL) ? CV_GEMM_B_T : 0);
+ eigenvectors = evects1;
+
+ // normalize eigenvectors
+ for( i = 0; i < out_count; i++ )
+ {
+ Mat vec = eigenvectors.row(i);
+ normalize(vec, vec);
+ }
+ }
+
+ if( count > out_count )
+ {
+ // use clone() to physically copy the data and thus deallocate the original matrices
+ eigenvalues = eigenvalues.rowRange(0,out_count).clone();
+ eigenvectors = eigenvectors.rowRange(0,out_count).clone();
+ }
+ return *this;
+}
+
+
+void PCA::project(const Mat& data, Mat& result) const
+{
+ CV_Assert( mean.data && eigenvectors.data &&
+ ((mean.rows == 1 && mean.cols == data.cols) || (mean.cols == 1 && mean.rows == data.rows)));
+ Mat tmp_data, tmp_mean = repeat(mean, data.rows/mean.rows, data.cols/mean.cols);
+ int ctype = mean.type();
+ if( data.type() != ctype || tmp_mean.data == mean.data )
+ {
+ data.convertTo( tmp_data, ctype );
+ subtract( tmp_data, tmp_mean, tmp_data );
+ }
+ else
+ {
+ subtract( data, tmp_mean, tmp_mean );
+ tmp_data = tmp_mean;
+ }
+ if( mean.rows == 1 )
+ gemm( tmp_data, eigenvectors, 1, Mat(), 0, result, GEMM_2_T );
+ else
+ gemm( eigenvectors, tmp_data, 1, Mat(), 0, result, 0 );
+}
+
+Mat PCA::project(const Mat& data) const
+{
+ Mat result;
+ project(data, result);
+ return result;
+}
+
+void PCA::backProject(const Mat& data, Mat& result) const
+{
+ CV_Assert( mean.data && eigenvectors.data &&
+ ((mean.rows == 1 && eigenvectors.rows == data.cols) ||
+ (mean.cols == 1 && eigenvectors.rows == data.rows)));
+
+ Mat tmp_data, tmp_mean;
+ data.convertTo(tmp_data, mean.type());
+ if( mean.rows == 1 )
+ {
+ tmp_mean = repeat(mean, data.rows, 1);
+ gemm( tmp_data, eigenvectors, 1, tmp_mean, 1, result, 0 );
+ }
+ else
+ {
+ tmp_mean = repeat(mean, 1, data.cols);
+ gemm( eigenvectors, tmp_data, 1, tmp_mean, 1, result, GEMM_1_T );
+ }
+}
+
+Mat PCA::backProject(const Mat& data) const
+{
+ Mat result;
+ backProject(data, result);
+ return result;
+}
+
+}
+
+/****************************************************************************************\
+* Earlier API *
+\****************************************************************************************/
+
+CV_IMPL void cvGEMM( const CvArr* Aarr, const CvArr* Barr, double alpha,
+ const CvArr* Carr, double beta, CvArr* Darr, int flags )
+{
+ cv::Mat A = cv::cvarrToMat(Aarr), B = cv::cvarrToMat(Barr);
+ cv::Mat C, D = cv::cvarrToMat(Darr);
+
+ if( Carr )
+ C = cv::cvarrToMat(Carr);
+
+ CV_Assert( (D.rows == ((flags & CV_GEMM_A_T) == 0 ? A.rows : A.cols)) &&
+ (D.cols == ((flags & CV_GEMM_B_T) == 0 ? B.cols : B.rows)) &&
+ D.type() == A.type() );
+
+ gemm( A, B, alpha, C, beta, D, flags );
+}
+
+
+CV_IMPL void
+cvTransform( const CvArr* srcarr, CvArr* dstarr,
+ const CvMat* transmat, const CvMat* shiftvec )
+{
+ cv::Mat m = cv::cvarrToMat(transmat), src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
+
+ if( shiftvec )
+ {
+ cv::Mat v = cv::cvarrToMat(shiftvec).reshape(1,m.rows),
+ _m(m.rows, m.cols + 1, m.type()), m1 = _m.colRange(0,m.cols), v1 = _m.col(m.cols);
+ m.convertTo(m1, m1.type());
+ v.convertTo(v1, v1.type());
+ m = _m;
+ }
+
+ CV_Assert( dst.depth() == src.depth() && dst.channels() == m.rows );
+ cv::transform( src, dst, m );
+}
+
+
+CV_IMPL void
+cvPerspectiveTransform( const CvArr* srcarr, CvArr* dstarr, const CvMat* mat )
+{
+ cv::Mat m = cv::cvarrToMat(mat), src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
+
+ CV_Assert( dst.type() == src.type() && dst.channels() == m.rows-1 );
+ cv::perspectiveTransform( src, dst, m );
+}
+
+
+CV_IMPL void cvScaleAdd( const CvArr* srcarr1, CvScalar scale,
+ const CvArr* srcarr2, CvArr* dstarr )
+{
+ cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
+
+ CV_Assert( src1.size() == dst.size() && src1.type() == dst.type() );
+ cv::scaleAdd( src1, scale.val[0], cv::cvarrToMat(srcarr2), dst );
+}
+
+
+CV_IMPL void
+cvCalcCovarMatrix( const CvArr** vecarr, int count,
+ CvArr* covarr, CvArr* avgarr, int flags )
+{
+ cv::Mat cov0 = cv::cvarrToMat(covarr), cov = cov0, mean0, mean;
+ CV_Assert( vecarr != 0 && count >= 1 );
+
+ if( avgarr )
+ mean = mean0 = cv::cvarrToMat(avgarr);
+
+ if( count == 1 || (flags & CV_COVAR_COLS) != 0 || (flags & CV_COVAR_ROWS) != 0 )
+ {
+ cv::Mat data = cv::cvarrToMat(vecarr[0]);
+ cv::calcCovarMatrix( data, cov, mean, flags, cov.type() );
+ }
+ else
+ {
+ std::vector<cv::Mat> data(count);
+ for( int i = 0; i < count; i++ )
+ data[i] = cv::cvarrToMat(vecarr[i]);
+ cv::calcCovarMatrix( &data[0], count, cov, mean, flags, cov.type() );
+ }
+
+ if( mean.data != mean0.data && mean0.data )
+ mean.convertTo(mean0, mean0.type());
+
+ if( cov.data != cov0.data )
+ cov.convertTo(cov0, cov0.type());
+}
+
+
+CV_IMPL double
+cvMahalanobis( const CvArr* srcAarr, const CvArr* srcBarr, const CvArr* matarr )
+{
+ return cv::Mahalanobis(cv::cvarrToMat(srcAarr),
+ cv::cvarrToMat(srcBarr), cv::cvarrToMat(matarr));
+}
+
+CV_IMPL void
+cvMulTransposed( const CvArr* srcarr, CvArr* dstarr,
+ int order, const CvArr* deltaarr, double scale )
+{
+ cv::Mat src = cv::cvarrToMat(srcarr), dst0 = cv::cvarrToMat(dstarr), dst = dst0, delta;
+ if( deltaarr )
+ delta = cv::cvarrToMat(deltaarr);
+ cv::mulTransposed( src, dst, order != 0, delta, scale, dst.type());
+ if( dst.data != dst0.data )
+ dst.convertTo(dst0, dst0.type());
+}
+
+CV_IMPL double cvDotProduct( const CvArr* srcAarr, const CvArr* srcBarr )
+{
+ return cv::cvarrToMat(srcAarr).dot(cv::cvarrToMat(srcBarr));
+}
+
+
+CV_IMPL void
+cvCalcPCA( const CvArr* data_arr, CvArr* avg_arr, CvArr* eigenvals, CvArr* eigenvects, int flags )
+{
+ cv::Mat data = cv::cvarrToMat(data_arr), mean0 = cv::cvarrToMat(avg_arr);
+ cv::Mat evals0 = cv::cvarrToMat(eigenvals), evects0 = cv::cvarrToMat(eigenvects);
+ cv::Mat mean = mean0, evals = evals0, evects = evects0;
+
+ cv::PCA pca;
+ pca.mean = mean;
+ pca.eigenvalues = evals;
+ pca.eigenvectors = evects;
+
+ pca(data, (flags & CV_PCA_USE_AVG) ? mean : cv::Mat(),
+ flags, evals.data ? evals.rows + evals.cols - 1 : 0);
+
+ if( pca.mean.size() == mean.size() )
+ pca.mean.convertTo( mean, mean.type() );
+ else
+ {
+ cv::Mat temp; pca.mean.convertTo( temp, mean.type() );
+ transpose( temp, mean );
+ }
+
+ if( pca.eigenvalues.size() == evals.size() )
+ pca.eigenvalues.convertTo( evals, evals.type() );
+ else
+ {
+ cv::Mat temp; pca.eigenvalues.convertTo( temp, evals.type() );
+ transpose( temp, evals );
+ }
+
+ pca.eigenvectors.convertTo( evects, evects.type() );
+
+ // otherwise some datatype's or size's were incorrect, so the output arrays have been reallocated
+ CV_Assert( mean0.data == mean.data && evals0.data == evals.data && evects0.data == evects.data );
+}
+
+
+CV_IMPL void
+cvProjectPCA( const CvArr* data_arr, const CvArr* avg_arr,
+ const CvArr* eigenvects, CvArr* result_arr )
+{
+ cv::Mat data = cv::cvarrToMat(data_arr), mean = cv::cvarrToMat(avg_arr);
+ cv::Mat evects = cv::cvarrToMat(eigenvects), dst0 = cv::cvarrToMat(result_arr), dst = dst0;
+
+ cv::PCA pca;
+ pca.mean = mean;
+ pca.eigenvectors = evects;
+
+ cv::Mat result = pca.project(data);
+ if( result.cols != dst.cols )
+ result = result.reshape(1, 1);
+ result.convertTo(dst, dst.type());
+
+ CV_Assert(dst0.data == dst.data);
+}
+
+
+CV_IMPL void
+cvBackProjectPCA( const CvArr* proj_arr, const CvArr* avg_arr,
+ const CvArr* eigenvects, CvArr* result_arr )
+{
+ cv::Mat data = cv::cvarrToMat(proj_arr), mean = cv::cvarrToMat(avg_arr);
+ cv::Mat evects = cv::cvarrToMat(eigenvects), dst0 = cv::cvarrToMat(result_arr), dst = dst0;
+
+ cv::PCA pca;
+ pca.mean = mean;
+ pca.eigenvectors = evects;
+
+ cv::Mat result = pca.backProject(data);
+ result.convertTo(dst, dst.type());
+
+ CV_Assert(dst0.data == dst.data);
+}
+
+/* End of file. */
projects / opencv / blobdiff