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https://github.com/opencv/opencv.git
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2628 lines
92 KiB
C++
2628 lines
92 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
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// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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#ifdef HAVE_LAPACK
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#define CV_GEMM_BASELINE_ONLY
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#endif
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#define CV_MAHALANOBIS_BASELINE_ONLY
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#define CV_MULTRANSPOSED_BASELINE_ONLY
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namespace cv {
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// forward declarations
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typedef void (*TransformFunc)(const uchar* src, uchar* dst, const uchar* m, int len, int scn, int dcn);
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typedef void (*ScaleAddFunc)(const uchar* src1, const uchar* src2, uchar* dst, int len, const void* alpha);
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typedef void (*MulTransposedFunc)(const Mat& src, const/*preallocated*/ Mat& dst, const Mat& delta, double scale);
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typedef double (*MahalanobisImplFunc)(const Mat& v1, const Mat& v2, const Mat& icovar, double *diff_buffer /*[len]*/, int len /*=v1.total()*/);
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CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
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// forward declarations
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void gemm32f(const float* src1, size_t src1_step, const float* src2, size_t src2_step,
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float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step,
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int m_a, int n_a, int n_d, int flags);
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void gemm64f(const double* src1, size_t src1_step, const double* src2, size_t src2_step,
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double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step,
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int m_a, int n_a, int n_d, int flags);
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void gemm32fc(const float* src1, size_t src1_step, const float* src2, size_t src2_step,
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float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step,
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int m_a, int n_a, int n_d, int flags);
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void gemm64fc(const double* src1, size_t src1_step, const double* src2, size_t src2_step,
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double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step,
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int m_a, int n_a, int n_d, int flags);
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TransformFunc getTransformFunc(int depth);
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TransformFunc getDiagTransformFunc(int depth);
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TransformFunc getPerspectiveTransform(int depth);
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ScaleAddFunc getScaleAddFunc(int depth);
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MahalanobisImplFunc getMahalanobisImplFunc(int depth);
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MulTransposedFunc getMulTransposedFunc(int stype, int dtype, bool ata);
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double dotProd_8u(const uchar* src1, const uchar* src2, int len);
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double dotProd_8s(const schar* src1, const schar* src2, int len);
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double dotProd_16u(const ushort* src1, const ushort* src2, int len);
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double dotProd_16s(const short* src1, const short* src2, int len);
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double dotProd_32s(const int* src1, const int* src2, int len);
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double dotProd_32f(const float* src1, const float* src2, int len);
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double dotProd_64f(const double* src1, const double* src2, int len);
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#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
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#if !defined(CV_GEMM_BASELINE_ONLY) || defined(CV_CPU_BASELINE_MODE)
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/****************************************************************************************\
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* GEMM *
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\****************************************************************************************/
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static void
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GEMM_CopyBlock( const uchar* src, size_t src_step,
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uchar* dst, size_t dst_step,
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Size size, size_t pix_size )
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{
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int j;
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size.width *= (int)(pix_size / sizeof(int));
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for( ; size.height--; src += src_step, dst += dst_step )
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{
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j=0;
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#if CV_ENABLE_UNROLLED
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for( ; j <= size.width - 4; j += 4 )
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{
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int t0 = ((const int*)src)[j];
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int t1 = ((const int*)src)[j+1];
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((int*)dst)[j] = t0;
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((int*)dst)[j+1] = t1;
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t0 = ((const int*)src)[j+2];
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t1 = ((const int*)src)[j+3];
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((int*)dst)[j+2] = t0;
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((int*)dst)[j+3] = t1;
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}
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#endif
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for( ; j < size.width; j++ )
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((int*)dst)[j] = ((const int*)src)[j];
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}
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}
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static void
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GEMM_TransposeBlock( const uchar* src, size_t src_step,
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uchar* dst, size_t dst_step,
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Size size, size_t pix_size )
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{
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int i, j;
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for( i = 0; i < size.width; i++, dst += dst_step, src += pix_size )
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{
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const uchar* _src = src;
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switch( pix_size )
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{
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case sizeof(int):
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for( j = 0; j < size.height; j++, _src += src_step )
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((int*)dst)[j] = ((int*)_src)[0];
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break;
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case sizeof(int)*2:
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for( j = 0; j < size.height*2; j += 2, _src += src_step )
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{
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int t0 = ((int*)_src)[0];
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int t1 = ((int*)_src)[1];
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((int*)dst)[j] = t0;
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((int*)dst)[j+1] = t1;
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}
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break;
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case sizeof(int)*4:
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for( j = 0; j < size.height*4; j += 4, _src += src_step )
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{
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int t0 = ((int*)_src)[0];
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int t1 = ((int*)_src)[1];
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((int*)dst)[j] = t0;
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((int*)dst)[j+1] = t1;
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t0 = ((int*)_src)[2];
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t1 = ((int*)_src)[3];
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((int*)dst)[j+2] = t0;
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((int*)dst)[j+3] = t1;
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}
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break;
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default:
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assert(0);
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return;
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}
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}
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}
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template<typename T, typename WT> static void
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GEMMSingleMul( const T* a_data, size_t a_step,
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const T* b_data, size_t b_step,
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const T* c_data, size_t c_step,
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T* d_data, size_t d_step,
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Size a_size, Size d_size,
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double alpha, double beta, int flags )
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{
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int i, j, k, n = a_size.width, m = d_size.width, drows = d_size.height;
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const T *_a_data = a_data, *_b_data = b_data, *_c_data = c_data;
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cv::AutoBuffer<T> _a_buf;
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T* a_buf = 0;
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size_t a_step0, a_step1, c_step0, c_step1, t_step;
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a_step /= sizeof(a_data[0]);
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b_step /= sizeof(b_data[0]);
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c_step /= sizeof(c_data[0]);
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d_step /= sizeof(d_data[0]);
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a_step0 = a_step;
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a_step1 = 1;
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if( !c_data )
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c_step0 = c_step1 = 0;
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else if( !(flags & GEMM_3_T) )
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c_step0 = c_step, c_step1 = 1;
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else
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c_step0 = 1, c_step1 = c_step;
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if( flags & GEMM_1_T )
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{
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CV_SWAP( a_step0, a_step1, t_step );
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n = a_size.height;
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if( a_step > 1 && n > 1 )
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{
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_a_buf.allocate(n);
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a_buf = _a_buf.data();
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}
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}
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if( n == 1 ) /* external product */
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{
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cv::AutoBuffer<T> _b_buf;
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T* b_buf = 0;
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if( a_step > 1 && a_size.height > 1 )
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{
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_a_buf.allocate(drows);
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a_buf = _a_buf.data();
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for( k = 0; k < drows; k++ )
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a_buf[k] = a_data[a_step*k];
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a_data = a_buf;
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}
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if( b_step > 1 )
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{
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_b_buf.allocate(d_size.width);
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b_buf = _b_buf.data();
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for( j = 0; j < d_size.width; j++ )
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b_buf[j] = b_data[j*b_step];
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b_data = b_buf;
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}
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for( i = 0; i < drows; i++, _c_data += c_step0, d_data += d_step )
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{
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WT al = WT(a_data[i])*alpha;
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c_data = _c_data;
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for( j = 0; j <= d_size.width - 2; j += 2, c_data += 2*c_step1 )
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{
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WT s0 = al*WT(b_data[j]);
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WT s1 = al*WT(b_data[j+1]);
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if( !c_data )
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{
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d_data[j] = T(s0);
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d_data[j+1] = T(s1);
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}
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else
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{
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d_data[j] = T(s0 + WT(c_data[0])*beta);
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d_data[j+1] = T(s1 + WT(c_data[c_step1])*beta);
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}
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}
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for( ; j < d_size.width; j++, c_data += c_step1 )
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{
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WT s0 = al*WT(b_data[j]);
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if( !c_data )
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d_data[j] = T(s0);
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else
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d_data[j] = T(s0 + WT(c_data[0])*beta);
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}
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}
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}
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else if( flags & GEMM_2_T ) /* A * Bt */
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{
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for( i = 0; i < drows; i++, _a_data += a_step0, _c_data += c_step0, d_data += d_step )
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{
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a_data = _a_data;
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b_data = _b_data;
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c_data = _c_data;
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if( a_buf )
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{
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for( k = 0; k < n; k++ )
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a_buf[k] = a_data[a_step1*k];
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a_data = a_buf;
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}
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for( j = 0; j < d_size.width; j++, b_data += b_step,
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c_data += c_step1 )
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{
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WT s0(0), s1(0), s2(0), s3(0);
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k = 0;
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#if CV_ENABLE_UNROLLED
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for( ; k <= n - 4; k += 4 )
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{
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s0 += WT(a_data[k])*WT(b_data[k]);
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s1 += WT(a_data[k+1])*WT(b_data[k+1]);
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s2 += WT(a_data[k+2])*WT(b_data[k+2]);
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s3 += WT(a_data[k+3])*WT(b_data[k+3]);
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}
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#endif
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for( ; k < n; k++ )
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s0 += WT(a_data[k])*WT(b_data[k]);
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s0 = (s0+s1+s2+s3)*alpha;
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if( !c_data )
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d_data[j] = T(s0);
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else
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d_data[j] = T(s0 + WT(c_data[0])*beta);
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}
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}
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}
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else if( d_size.width*sizeof(d_data[0]) <= 1600 )
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{
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for( i = 0; i < drows; i++, _a_data += a_step0,
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_c_data += c_step0,
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d_data += d_step )
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{
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a_data = _a_data, c_data = _c_data;
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if( a_buf )
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{
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for( k = 0; k < n; k++ )
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a_buf[k] = a_data[a_step1*k];
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a_data = a_buf;
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}
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for( j = 0; j <= m - 4; j += 4, c_data += 4*c_step1 )
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{
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const T* b = _b_data + j;
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WT s0(0), s1(0), s2(0), s3(0);
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for( k = 0; k < n; k++, b += b_step )
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{
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WT a(a_data[k]);
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s0 += a * WT(b[0]); s1 += a * WT(b[1]);
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s2 += a * WT(b[2]); s3 += a * WT(b[3]);
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}
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if( !c_data )
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{
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d_data[j] = T(s0*alpha);
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d_data[j+1] = T(s1*alpha);
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d_data[j+2] = T(s2*alpha);
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d_data[j+3] = T(s3*alpha);
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}
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else
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{
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s0 = s0*alpha; s1 = s1*alpha;
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s2 = s2*alpha; s3 = s3*alpha;
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d_data[j] = T(s0 + WT(c_data[0])*beta);
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d_data[j+1] = T(s1 + WT(c_data[c_step1])*beta);
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d_data[j+2] = T(s2 + WT(c_data[c_step1*2])*beta);
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d_data[j+3] = T(s3 + WT(c_data[c_step1*3])*beta);
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}
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}
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for( ; j < m; j++, c_data += c_step1 )
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{
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const T* b = _b_data + j;
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WT s0(0);
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for( k = 0; k < n; k++, b += b_step )
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s0 += WT(a_data[k]) * WT(b[0]);
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s0 = s0*alpha;
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if( !c_data )
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d_data[j] = T(s0);
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else
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d_data[j] = T(s0 + WT(c_data[0])*beta);
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}
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}
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}
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else
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{
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cv::AutoBuffer<WT> _d_buf(m);
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WT* d_buf = _d_buf.data();
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for( i = 0; i < drows; i++, _a_data += a_step0, _c_data += c_step0, d_data += d_step )
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{
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a_data = _a_data;
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b_data = _b_data;
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c_data = _c_data;
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if( a_buf )
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{
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for( k = 0; k < n; k++ )
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a_buf[k] = _a_data[a_step1*k];
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a_data = a_buf;
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}
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for( j = 0; j < m; j++ )
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d_buf[j] = WT(0);
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for( k = 0; k < n; k++, b_data += b_step )
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{
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WT al(a_data[k]);
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j=0;
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#if CV_ENABLE_UNROLLED
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for(; j <= m - 4; j += 4 )
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{
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WT t0 = d_buf[j] + WT(b_data[j])*al;
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WT t1 = d_buf[j+1] + WT(b_data[j+1])*al;
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d_buf[j] = t0;
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d_buf[j+1] = t1;
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t0 = d_buf[j+2] + WT(b_data[j+2])*al;
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t1 = d_buf[j+3] + WT(b_data[j+3])*al;
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d_buf[j+2] = t0;
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d_buf[j+3] = t1;
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}
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#endif
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for( ; j < m; j++ )
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d_buf[j] += WT(b_data[j])*al;
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}
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if( !c_data )
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for( j = 0; j < m; j++ )
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d_data[j] = T(d_buf[j]*alpha);
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else
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for( j = 0; j < m; j++, c_data += c_step1 )
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{
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WT t = d_buf[j]*alpha;
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d_data[j] = T(t + WT(c_data[0])*beta);
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}
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}
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}
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}
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template<typename T, typename WT> static void
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GEMMBlockMul( const T* a_data, size_t a_step,
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const T* b_data, size_t b_step,
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WT* d_data, size_t d_step,
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Size a_size, Size d_size, int flags )
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{
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int i, j, k, n = a_size.width, m = d_size.width;
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const T *_a_data = a_data, *_b_data = b_data;
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cv::AutoBuffer<T> _a_buf;
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T* a_buf = 0;
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size_t a_step0, a_step1, t_step;
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int do_acc = flags & 16;
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a_step /= sizeof(a_data[0]);
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b_step /= sizeof(b_data[0]);
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d_step /= sizeof(d_data[0]);
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a_step0 = a_step;
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a_step1 = 1;
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if( flags & GEMM_1_T )
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{
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CV_SWAP( a_step0, a_step1, t_step );
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n = a_size.height;
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_a_buf.allocate(n);
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a_buf = _a_buf.data();
|
|
}
|
|
|
|
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;
|
|
j=0;
|
|
#if CV_ENABLE_UNROLLED
|
|
for(; 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);
|
|
}
|
|
#endif
|
|
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
|
|
{
|
|
j = 0;
|
|
#if CV_ENABLE_UNROLLED
|
|
for( ; 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);
|
|
}
|
|
#endif
|
|
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);
|
|
}
|
|
|
|
static void gemmImpl( Mat A, Mat B, double alpha,
|
|
Mat C, double beta, Mat D, int flags )
|
|
{
|
|
CV_INSTRUMENT_REGION();
|
|
|
|
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};
|
|
|
|
Size a_size = A.size(), d_size;
|
|
int i, len = 0, type = A.type();
|
|
|
|
switch( flags & (GEMM_1_T|GEMM_2_T) )
|
|
{
|
|
case 0:
|
|
d_size = Size( B.cols, a_size.height );
|
|
len = B.rows;
|
|
break;
|
|
case 1:
|
|
d_size = Size( B.cols, a_size.width );
|
|
len = B.rows;
|
|
break;
|
|
case 2:
|
|
d_size = Size( B.rows, a_size.height );
|
|
len = B.cols;
|
|
break;
|
|
case 3:
|
|
d_size = Size( B.rows, a_size.width );
|
|
len = B.cols;
|
|
break;
|
|
}
|
|
|
|
if( flags == 0 && 2 <= len && len <= 4 && (len == d_size.width || len == d_size.height) )
|
|
{
|
|
if( type == CV_32F )
|
|
{
|
|
float* d = D.ptr<float>();
|
|
const float *a = A.ptr<float>(),
|
|
*b = B.ptr<float>(),
|
|
*c = (const float*)C.data;
|
|
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.data ? 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 = D.ptr<double>();
|
|
const double *a = A.ptr<double>(),
|
|
*b = B.ptr<double>(),
|
|
*c = (const double*)C.data;
|
|
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.data ? 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 *matD = &D;
|
|
const uchar* Cdata = C.data;
|
|
size_t Cstep = C.data ? (size_t)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_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.ptr(), A.step, B.ptr(), b_step, Cdata, Cstep,
|
|
matD->ptr(), matD->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;
|
|
size_t 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.empty() )
|
|
{
|
|
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 = (size_t)(dk0+dk0/8+1)*dk0_1*elem_size;
|
|
d_buf_size = (size_t)(dk0+dk0/8+1)*dk0_1*work_elem_size;
|
|
|
|
if( is_a_t )
|
|
{
|
|
a_buf_size = (size_t)(dm0+dm0/8+1)*((dk0+dk0/8+2)&-2)*elem_size;
|
|
flags &= ~GEMM_1_T;
|
|
}
|
|
|
|
buf.allocate(d_buf_size + b_buf_size + a_buf_size);
|
|
d_buf = buf.data();
|
|
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 = matD->ptr() + i*matD->step + j*elem_size;
|
|
const uchar* _c = Cdata + i*c_step0 + j*c_step1;
|
|
size_t _d_step = matD->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.ptr() + i*a_step0 + k*a_step1;
|
|
size_t _a_step = A.step;
|
|
const uchar* _b = B.ptr() + 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,
|
|
matD->ptr(i) + j*elem_size,
|
|
matD->step, Size(dj,di), alpha, beta, flags );
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename fptype>inline static void
|
|
callGemmImpl(const fptype *src1, size_t src1_step, const fptype *src2, size_t src2_step, fptype alpha,
|
|
const fptype *src3, size_t src3_step, fptype beta, fptype *dst, size_t dst_step, int m_a, int n_a, int n_d, int flags, int type)
|
|
{
|
|
CV_StaticAssert(GEMM_1_T == CV_HAL_GEMM_1_T, "Incompatible GEMM_1_T flag in HAL");
|
|
CV_StaticAssert(GEMM_2_T == CV_HAL_GEMM_2_T, "Incompatible GEMM_2_T flag in HAL");
|
|
CV_StaticAssert(GEMM_3_T == CV_HAL_GEMM_3_T, "Incompatible GEMM_3_T flag in HAL");
|
|
|
|
int b_m, b_n, c_m, c_n, m_d;
|
|
|
|
if(flags & GEMM_2_T)
|
|
{
|
|
b_m = n_d;
|
|
if(flags & GEMM_1_T )
|
|
{
|
|
b_n = m_a;
|
|
m_d = n_a;
|
|
}
|
|
else
|
|
{
|
|
b_n = n_a;
|
|
m_d = m_a;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
b_n = n_d;
|
|
if(flags & GEMM_1_T )
|
|
{
|
|
b_m = m_a;
|
|
m_d = n_a;
|
|
}
|
|
else
|
|
{
|
|
m_d = m_a;
|
|
b_m = n_a;
|
|
}
|
|
}
|
|
|
|
if(flags & GEMM_3_T)
|
|
{
|
|
c_m = n_d;
|
|
c_n = m_d;
|
|
}
|
|
else
|
|
{
|
|
c_m = m_d;
|
|
c_n = n_d;
|
|
}
|
|
|
|
Mat A, B, C;
|
|
if(src1 != NULL)
|
|
A = Mat(m_a, n_a, type, (void*)src1, src1_step);
|
|
if(src2 != NULL)
|
|
B = Mat(b_m, b_n, type, (void*)src2, src2_step);
|
|
if(src3 != NULL && beta != 0.0)
|
|
C = Mat(c_m, c_n, type, (void*)src3, src3_step);
|
|
Mat D(m_d, n_d, type, (void*)dst, dst_step);
|
|
|
|
gemmImpl(A, B, alpha, C, beta, D, flags);
|
|
}
|
|
|
|
void gemm32f(const float* src1, size_t src1_step, const float* src2, size_t src2_step,
|
|
float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step,
|
|
int m_a, int n_a, int n_d, int flags)
|
|
{
|
|
CV_INSTRUMENT_REGION();
|
|
callGemmImpl(src1, src1_step, src2, src2_step, alpha, src3, src3_step, beta, dst, dst_step, m_a, n_a, n_d, flags, CV_32F);
|
|
}
|
|
|
|
void gemm64f(const double* src1, size_t src1_step, const double* src2, size_t src2_step,
|
|
double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step,
|
|
int m_a, int n_a, int n_d, int flags)
|
|
{
|
|
CV_INSTRUMENT_REGION();
|
|
callGemmImpl(src1, src1_step, src2, src2_step, alpha, src3, src3_step, beta, dst, dst_step, m_a, n_a, n_d, flags, CV_64F);
|
|
}
|
|
|
|
void gemm32fc(const float* src1, size_t src1_step, const float* src2, size_t src2_step,
|
|
float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step,
|
|
int m_a, int n_a, int n_d, int flags)
|
|
{
|
|
CV_INSTRUMENT_REGION();
|
|
callGemmImpl(src1, src1_step, src2, src2_step, alpha, src3, src3_step, beta, dst, dst_step, m_a, n_a, n_d, flags, CV_32FC2);
|
|
}
|
|
|
|
void gemm64fc(const double* src1, size_t src1_step, const double* src2, size_t src2_step,
|
|
double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step,
|
|
int m_a, int n_a, int n_d, int flags)
|
|
{
|
|
CV_INSTRUMENT_REGION();
|
|
callGemmImpl(src1, src1_step, src2, src2_step, alpha, src3, src3_step, beta, dst, dst_step, m_a, n_a, n_d, flags, CV_64FC2);
|
|
}
|
|
|
|
#endif // !defined(CV_GEMM_BASELINE_ONLY) || defined(CV_CPU_BASELINE_MODE)
|
|
|
|
|
|
|
|
/****************************************************************************************\
|
|
* Transform *
|
|
\****************************************************************************************/
|
|
|
|
template<typename T, typename WT> static void
|
|
transform_( const T* src, T* dst, const WT* m, int len, int scn, int dcn )
|
|
{
|
|
int x;
|
|
|
|
if( scn == 2 && dcn == 2 )
|
|
{
|
|
for( x = 0; x < len*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 if( scn == 3 && dcn == 3 )
|
|
{
|
|
for( x = 0; x < len*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( scn == 3 && dcn == 1 )
|
|
{
|
|
for( x = 0; x < len; x++, src += 3 )
|
|
dst[x] = saturate_cast<T>(m[0]*src[0] + m[1]*src[1] + m[2]*src[2] + m[3]);
|
|
}
|
|
else if( scn == 4 && dcn == 4 )
|
|
{
|
|
for( x = 0; x < len*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
|
|
{
|
|
for( x = 0; x < len; x++, src += scn, dst += dcn )
|
|
{
|
|
const WT* _m = m;
|
|
int j, k;
|
|
for( j = 0; j < dcn; j++, _m += scn + 1 )
|
|
{
|
|
WT s = _m[scn];
|
|
for( k = 0; k < scn; k++ )
|
|
s += _m[k]*src[k];
|
|
dst[j] = saturate_cast<T>(s);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
static void
|
|
transform_8u( const uchar* src, uchar* dst, const float* m, int len, int scn, int dcn )
|
|
{
|
|
#if CV_SIMD
|
|
const int BITS = 10, SCALE = 1 << BITS;
|
|
const float MAX_M = (float)(1 << (15 - BITS));
|
|
|
|
if( scn == 3 && dcn == 3 &&
|
|
std::abs(m[0]) < MAX_M && std::abs(m[1]) < MAX_M && std::abs(m[ 2]) < MAX_M*256 && 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*256 && 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*256 && std::abs(m[11]) < MAX_M*256 )
|
|
{
|
|
const int nChannels = 3;
|
|
|
|
union {
|
|
short s[6];
|
|
int p[3];
|
|
} m16;
|
|
m16.s[0] = saturate_cast<short>(m[0] * SCALE); m16.s[1] = saturate_cast<short>(m[1] * SCALE);
|
|
m16.s[2] = saturate_cast<short>(m[4] * SCALE); m16.s[3] = saturate_cast<short>(m[5] * SCALE);
|
|
m16.s[4] = saturate_cast<short>(m[8] * SCALE); m16.s[5] = saturate_cast<short>(m[9] * SCALE);
|
|
int m32[] = {saturate_cast<int>(m[ 2] * SCALE), saturate_cast<int>(m[ 3] * SCALE),
|
|
saturate_cast<int>(m[ 6] * SCALE), saturate_cast<int>(m[ 7] * SCALE),
|
|
saturate_cast<int>(m[10] * SCALE), saturate_cast<int>(m[11] * SCALE)};
|
|
v_int16 m01 = v_reinterpret_as_s16(vx_setall_s32(m16.p[0]));
|
|
v_int32 m2 = vx_setall_s32(m32[0]);
|
|
v_int32 m3 = vx_setall_s32(m32[1]);
|
|
v_int16 m45 = v_reinterpret_as_s16(vx_setall_s32(m16.p[1]));
|
|
v_int32 m6 = vx_setall_s32(m32[2]);
|
|
v_int32 m7 = vx_setall_s32(m32[3]);
|
|
v_int16 m89 = v_reinterpret_as_s16(vx_setall_s32(m16.p[2]));
|
|
v_int32 m10 = vx_setall_s32(m32[4]);
|
|
v_int32 m11 = vx_setall_s32(m32[5]);
|
|
int x = 0;
|
|
for (; x <= (len - v_uint8::nlanes) * nChannels; x += v_uint8::nlanes * nChannels)
|
|
{
|
|
v_uint8 b, g, r;
|
|
v_load_deinterleave(src + x, b, g, r);
|
|
v_uint8 bgl, bgh;
|
|
v_zip(b, g, bgl, bgh);
|
|
v_uint16 rl, rh;
|
|
v_expand(r, rl, rh);
|
|
|
|
v_int16 dbl, dbh, dgl, dgh, drl, drh;
|
|
v_uint16 p0, p2;
|
|
v_int32 p1, p3;
|
|
v_expand(bgl, p0, p2);
|
|
v_expand(v_reinterpret_as_s16(rl), p1, p3);
|
|
dbl = v_rshr_pack<BITS>(v_dotprod(v_reinterpret_as_s16(p0), m01) + p1 * m2 + m3,
|
|
v_dotprod(v_reinterpret_as_s16(p2), m01) + p3 * m2 + m3);
|
|
dgl = v_rshr_pack<BITS>(v_dotprod(v_reinterpret_as_s16(p0), m45) + p1 * m6 + m7,
|
|
v_dotprod(v_reinterpret_as_s16(p2), m45) + p3 * m6 + m7);
|
|
drl = v_rshr_pack<BITS>(v_dotprod(v_reinterpret_as_s16(p0), m89) + p1 * m10 + m11,
|
|
v_dotprod(v_reinterpret_as_s16(p2), m89) + p3 * m10 + m11);
|
|
v_expand(bgh, p0, p2);
|
|
v_expand(v_reinterpret_as_s16(rh), p1, p3);
|
|
dbh = v_rshr_pack<BITS>(v_dotprod(v_reinterpret_as_s16(p0), m01) + p1 * m2 + m3,
|
|
v_dotprod(v_reinterpret_as_s16(p2), m01) + p3 * m2 + m3);
|
|
dgh = v_rshr_pack<BITS>(v_dotprod(v_reinterpret_as_s16(p0), m45) + p1 * m6 + m7,
|
|
v_dotprod(v_reinterpret_as_s16(p2), m45) + p3 * m6 + m7);
|
|
drh = v_rshr_pack<BITS>(v_dotprod(v_reinterpret_as_s16(p0), m89) + p1 * m10 + m11,
|
|
v_dotprod(v_reinterpret_as_s16(p2), m89) + p3 * m10 + m11);
|
|
v_store_interleave(dst + x, v_pack_u(dbl, dbh), v_pack_u(dgl, dgh), v_pack_u(drl, drh));
|
|
}
|
|
m32[1] = saturate_cast<int>((m[3] + 0.5f)*SCALE);
|
|
m32[3] = saturate_cast<int>((m[7] + 0.5f)*SCALE);
|
|
m32[5] = saturate_cast<int>((m[11] + 0.5f)*SCALE);
|
|
for( ; x < len * nChannels; x += nChannels )
|
|
{
|
|
int v0 = src[x], v1 = src[x+1], v2 = src[x+2];
|
|
uchar t0 = saturate_cast<uchar>((m16.s[0] * v0 + m16.s[1] * v1 + m32[0] * v2 + m32[1]) >> BITS);
|
|
uchar t1 = saturate_cast<uchar>((m16.s[2] * v0 + m16.s[3] * v1 + m32[2] * v2 + m32[3]) >> BITS);
|
|
uchar t2 = saturate_cast<uchar>((m16.s[4] * v0 + m16.s[5] * v1 + m32[4] * v2 + m32[5]) >> BITS);
|
|
dst[x] = t0; dst[x+1] = t1; dst[x+2] = t2;
|
|
}
|
|
vx_cleanup();
|
|
return;
|
|
}
|
|
#endif
|
|
|
|
transform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
transform_16u( const ushort* src, ushort* dst, const float* m, int len, int scn, int dcn )
|
|
{
|
|
#if CV_SIMD
|
|
if( scn == 3 && dcn == 3 )
|
|
{
|
|
int x = 0;
|
|
#if CV_SIMD_WIDTH > 16
|
|
v_float32 m0 = vx_setall_f32(m[ 0]);
|
|
v_float32 m1 = vx_setall_f32(m[ 1]);
|
|
v_float32 m2 = vx_setall_f32(m[ 2]);
|
|
v_float32 m3 = vx_setall_f32(m[ 3] - 32768.f);
|
|
v_float32 m4 = vx_setall_f32(m[ 4]);
|
|
v_float32 m5 = vx_setall_f32(m[ 5]);
|
|
v_float32 m6 = vx_setall_f32(m[ 6]);
|
|
v_float32 m7 = vx_setall_f32(m[ 7] - 32768.f);
|
|
v_float32 m8 = vx_setall_f32(m[ 8]);
|
|
v_float32 m9 = vx_setall_f32(m[ 9]);
|
|
v_float32 m10 = vx_setall_f32(m[10]);
|
|
v_float32 m11 = vx_setall_f32(m[11] - 32768.f);
|
|
v_int16 delta = vx_setall_s16(-32768);
|
|
for (; x <= (len - v_uint16::nlanes)*3; x += v_uint16::nlanes*3)
|
|
{
|
|
v_uint16 b, g, r;
|
|
v_load_deinterleave(src + x, b, g, r);
|
|
v_uint32 bl, bh, gl, gh, rl, rh;
|
|
v_expand(b, bl, bh);
|
|
v_expand(g, gl, gh);
|
|
v_expand(r, rl, rh);
|
|
|
|
v_int16 db, dg, dr;
|
|
db = v_add_wrap(v_pack(v_round(v_muladd(v_cvt_f32(v_reinterpret_as_s32(bl)), m0, v_muladd(v_cvt_f32(v_reinterpret_as_s32(gl)), m1, v_muladd(v_cvt_f32(v_reinterpret_as_s32(rl)), m2, m3)))),
|
|
v_round(v_muladd(v_cvt_f32(v_reinterpret_as_s32(bh)), m0, v_muladd(v_cvt_f32(v_reinterpret_as_s32(gh)), m1, v_muladd(v_cvt_f32(v_reinterpret_as_s32(rh)), m2, m3))))), delta);
|
|
dg = v_add_wrap(v_pack(v_round(v_muladd(v_cvt_f32(v_reinterpret_as_s32(bl)), m4, v_muladd(v_cvt_f32(v_reinterpret_as_s32(gl)), m5, v_muladd(v_cvt_f32(v_reinterpret_as_s32(rl)), m6, m7)))),
|
|
v_round(v_muladd(v_cvt_f32(v_reinterpret_as_s32(bh)), m4, v_muladd(v_cvt_f32(v_reinterpret_as_s32(gh)), m5, v_muladd(v_cvt_f32(v_reinterpret_as_s32(rh)), m6, m7))))), delta);
|
|
dr = v_add_wrap(v_pack(v_round(v_muladd(v_cvt_f32(v_reinterpret_as_s32(bl)), m8, v_muladd(v_cvt_f32(v_reinterpret_as_s32(gl)), m9, v_muladd(v_cvt_f32(v_reinterpret_as_s32(rl)), m10, m11)))),
|
|
v_round(v_muladd(v_cvt_f32(v_reinterpret_as_s32(bh)), m8, v_muladd(v_cvt_f32(v_reinterpret_as_s32(gh)), m9, v_muladd(v_cvt_f32(v_reinterpret_as_s32(rh)), m10, m11))))), delta);
|
|
v_store_interleave(dst + x, v_reinterpret_as_u16(db), v_reinterpret_as_u16(dg), v_reinterpret_as_u16(dr));
|
|
}
|
|
#endif
|
|
v_float32x4 _m0l(m[0], m[4], m[ 8], 0.f);
|
|
v_float32x4 _m1l(m[1], m[5], m[ 9], 0.f);
|
|
v_float32x4 _m2l(m[2], m[6], m[10], 0.f);
|
|
v_float32x4 _m3l(m[3] - 32768.f, m[7] - 32768.f, m[11] - 32768.f, 0.f);
|
|
v_float32x4 _m0h = v_rotate_left<1>(_m0l);
|
|
v_float32x4 _m1h = v_rotate_left<1>(_m1l);
|
|
v_float32x4 _m2h = v_rotate_left<1>(_m2l);
|
|
v_float32x4 _m3h = v_rotate_left<1>(_m3l);
|
|
v_int16x8 _delta(0, -32768, -32768, -32768, -32768, -32768, -32768, 0);
|
|
for( ; x <= len*3 - v_uint16x8::nlanes; x += 3*v_uint16x8::nlanes/4 )
|
|
v_store(dst + x, v_rotate_right<1>(v_reinterpret_as_u16(v_add_wrap(v_pack(
|
|
v_round(v_matmuladd(v_cvt_f32(v_reinterpret_as_s32(v_load_expand(src + x ))), _m0h, _m1h, _m2h, _m3h)),
|
|
v_round(v_matmuladd(v_cvt_f32(v_reinterpret_as_s32(v_load_expand(src + x + 3))), _m0l, _m1l, _m2l, _m3l))), _delta))));
|
|
for( ; x < len * 3; x += 3 )
|
|
{
|
|
float v0 = src[x], v1 = src[x + 1], v2 = src[x + 2];
|
|
ushort t0 = saturate_cast<ushort>(m[0] * v0 + m[1] * v1 + m[ 2] * v2 + m[ 3]);
|
|
ushort t1 = saturate_cast<ushort>(m[4] * v0 + m[5] * v1 + m[ 6] * v2 + m[ 7]);
|
|
ushort t2 = saturate_cast<ushort>(m[8] * v0 + m[9] * v1 + m[10] * v2 + m[11]);
|
|
dst[x] = t0; dst[x + 1] = t1; dst[x + 2] = t2;
|
|
}
|
|
vx_cleanup();
|
|
return;
|
|
}
|
|
#endif
|
|
|
|
transform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
transform_32f( const float* src, float* dst, const float* m, int len, int scn, int dcn )
|
|
{
|
|
#if CV_SIMD && !defined(__aarch64__) && !defined(_M_ARM64)
|
|
int x = 0;
|
|
if( scn == 3 && dcn == 3 )
|
|
{
|
|
int idx[v_float32::nlanes/2];
|
|
for( int i = 0; i < v_float32::nlanes/4; i++ )
|
|
{
|
|
idx[i] = 3*i;
|
|
idx[i + v_float32::nlanes/4] = 0;
|
|
}
|
|
float _m[] = { m[0], m[4], m[ 8], 0.f,
|
|
m[1], m[5], m[ 9], 0.f,
|
|
m[2], m[6], m[10], 0.f,
|
|
m[3], m[7], m[11], 0.f };
|
|
v_float32 m0 = vx_lut_quads(_m , idx + v_float32::nlanes/4);
|
|
v_float32 m1 = vx_lut_quads(_m + 4, idx + v_float32::nlanes/4);
|
|
v_float32 m2 = vx_lut_quads(_m + 8, idx + v_float32::nlanes/4);
|
|
v_float32 m3 = vx_lut_quads(_m + 12, idx + v_float32::nlanes/4);
|
|
for( ; x <= len*3 - v_float32::nlanes; x += 3*v_float32::nlanes/4 )
|
|
v_store(dst + x, v_pack_triplets(v_matmuladd(vx_lut_quads(src + x, idx), m0, m1, m2, m3)));
|
|
for( ; x < len*3; x += 3 )
|
|
{
|
|
float v0 = src[x], v1 = src[x+1], v2 = src[x+2];
|
|
float t0 = saturate_cast<float>(m[0]*v0 + m[1]*v1 + m[ 2]*v2 + m[ 3]);
|
|
float t1 = saturate_cast<float>(m[4]*v0 + m[5]*v1 + m[ 6]*v2 + m[ 7]);
|
|
float t2 = saturate_cast<float>(m[8]*v0 + m[9]*v1 + m[10]*v2 + m[11]);
|
|
dst[x] = t0; dst[x+1] = t1; dst[x+2] = t2;
|
|
}
|
|
vx_cleanup();
|
|
return;
|
|
}
|
|
|
|
if( scn == 4 && dcn == 4 )
|
|
{
|
|
#if CV_SIMD_WIDTH > 16
|
|
int idx[v_float32::nlanes/4];
|
|
for( int i = 0; i < v_float32::nlanes/4; i++ )
|
|
idx[i] = 0;
|
|
float _m[] = { m[4], m[9], m[14], m[19] };
|
|
v_float32 m0 = vx_lut_quads(m , idx);
|
|
v_float32 m1 = vx_lut_quads(m+ 5, idx);
|
|
v_float32 m2 = vx_lut_quads(m+10, idx);
|
|
v_float32 m3 = vx_lut_quads(m+15, idx);
|
|
v_float32 m4 = vx_lut_quads(_m, idx);
|
|
for( ; x <= len*4 - v_float32::nlanes; x += v_float32::nlanes )
|
|
{
|
|
v_float32 v_src = vx_load(src + x);
|
|
v_store(dst + x, v_reduce_sum4(v_src * m0, v_src * m1, v_src * m2, v_src * m3) + m4);
|
|
}
|
|
#endif
|
|
v_float32x4 _m0 = v_load(m );
|
|
v_float32x4 _m1 = v_load(m + 5);
|
|
v_float32x4 _m2 = v_load(m + 10);
|
|
v_float32x4 _m3 = v_load(m + 15);
|
|
v_float32x4 _m4(m[4], m[9], m[14], m[19]);
|
|
for( ; x < len*4; x += v_float32x4::nlanes )
|
|
{
|
|
v_float32x4 v_src = v_load(src + x);
|
|
v_store(dst + x, v_reduce_sum4(v_src * _m0, v_src * _m1, v_src * _m2, v_src * _m3) + _m4);
|
|
}
|
|
vx_cleanup();
|
|
return;
|
|
}
|
|
#endif
|
|
|
|
transform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
|
|
static void
|
|
transform_8s(const schar* src, schar* dst, const float* m, int len, int scn, int dcn)
|
|
{
|
|
transform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
transform_16s(const short* src, short* dst, const float* m, int len, int scn, int dcn)
|
|
{
|
|
transform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
transform_32s(const int* src, int* dst, const double* m, int len, int scn, int dcn)
|
|
{
|
|
transform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
transform_64f(const double* src, double* dst, const double* m, int len, int scn, int dcn)
|
|
{
|
|
transform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
template<typename T, typename WT> static void
|
|
diagtransform_( const T* src, T* dst, const WT* m, int len, int cn, int )
|
|
{
|
|
int x;
|
|
|
|
if( cn == 2 )
|
|
{
|
|
for( x = 0; x < len*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;
|
|
}
|
|
}
|
|
else if( cn == 3 )
|
|
{
|
|
for( x = 0; x < len*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;
|
|
}
|
|
}
|
|
else if( cn == 4 )
|
|
{
|
|
for( x = 0; x < len*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;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for( x = 0; x < len; x++, src += cn, dst += cn )
|
|
{
|
|
const WT* _m = m;
|
|
for( int j = 0; j < cn; j++, _m += cn + 1 )
|
|
dst[j] = saturate_cast<T>(src[j]*_m[j] + _m[cn]);
|
|
}
|
|
}
|
|
}
|
|
|
|
static void
|
|
diagtransform_8u(const uchar* src, uchar* dst, const float* m, int len, int scn, int dcn)
|
|
{
|
|
diagtransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
diagtransform_8s(const schar* src, schar* dst, const float* m, int len, int scn, int dcn)
|
|
{
|
|
diagtransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
diagtransform_16u(const ushort* src, ushort* dst, const float* m, int len, int scn, int dcn)
|
|
{
|
|
diagtransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
diagtransform_16s(const short* src, short* dst, const float* m, int len, int scn, int dcn)
|
|
{
|
|
diagtransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
diagtransform_32s(const int* src, int* dst, const double* m, int len, int scn, int dcn)
|
|
{
|
|
diagtransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
diagtransform_32f(const float* src, float* dst, const float* m, int len, int scn, int dcn)
|
|
{
|
|
diagtransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
diagtransform_64f(const double* src, double* dst, const double* m, int len, int scn, int dcn)
|
|
{
|
|
diagtransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
|
|
TransformFunc getTransformFunc(int depth)
|
|
{
|
|
static TransformFunc transformTab[] =
|
|
{
|
|
(TransformFunc)transform_8u, (TransformFunc)transform_8s, (TransformFunc)transform_16u,
|
|
(TransformFunc)transform_16s, (TransformFunc)transform_32s, (TransformFunc)transform_32f,
|
|
(TransformFunc)transform_64f, 0
|
|
};
|
|
|
|
return transformTab[depth];
|
|
}
|
|
|
|
TransformFunc getDiagTransformFunc(int depth)
|
|
{
|
|
static TransformFunc diagTransformTab[] =
|
|
{
|
|
(TransformFunc)diagtransform_8u, (TransformFunc)diagtransform_8s, (TransformFunc)diagtransform_16u,
|
|
(TransformFunc)diagtransform_16s, (TransformFunc)diagtransform_32s, (TransformFunc)diagtransform_32f,
|
|
(TransformFunc)diagtransform_64f, 0
|
|
};
|
|
|
|
return diagTransformTab[depth];
|
|
}
|
|
|
|
|
|
|
|
/****************************************************************************************\
|
|
* Perspective Transform *
|
|
\****************************************************************************************/
|
|
|
|
template<typename T> static void
|
|
perspectiveTransform_( const T* src, T* dst, const double* m, int len, int scn, int dcn )
|
|
{
|
|
const double eps = FLT_EPSILON;
|
|
int i;
|
|
|
|
if( scn == 2 && dcn == 2 )
|
|
{
|
|
for( i = 0; i < len*2; i += 2 )
|
|
{
|
|
T x = src[i], y = src[i + 1];
|
|
double w = x*m[6] + y*m[7] + m[8];
|
|
|
|
if( fabs(w) > eps )
|
|
{
|
|
w = 1./w;
|
|
dst[i] = (T)((x*m[0] + y*m[1] + m[2])*w);
|
|
dst[i+1] = (T)((x*m[3] + y*m[4] + m[5])*w);
|
|
}
|
|
else
|
|
dst[i] = dst[i+1] = (T)0;
|
|
}
|
|
}
|
|
else if( scn == 3 && dcn == 3 )
|
|
{
|
|
for( i = 0; i < len*3; i += 3 )
|
|
{
|
|
T x = src[i], y = src[i + 1], z = src[i + 2];
|
|
double w = x*m[12] + y*m[13] + z*m[14] + m[15];
|
|
|
|
if( fabs(w) > eps )
|
|
{
|
|
w = 1./w;
|
|
dst[i] = (T)((x*m[0] + y*m[1] + z*m[2] + m[3]) * w);
|
|
dst[i+1] = (T)((x*m[4] + y*m[5] + z*m[6] + m[7]) * w);
|
|
dst[i+2] = (T)((x*m[8] + y*m[9] + z*m[10] + m[11]) * w);
|
|
}
|
|
else
|
|
dst[i] = dst[i+1] = dst[i+2] = (T)0;
|
|
}
|
|
}
|
|
else if( scn == 3 && dcn == 2 )
|
|
{
|
|
for( i = 0; i < len; i++, src += 3, dst += 2 )
|
|
{
|
|
T x = src[0], y = src[1], z = src[2];
|
|
double w = x*m[8] + y*m[9] + z*m[10] + m[11];
|
|
|
|
if( fabs(w) > eps )
|
|
{
|
|
w = 1./w;
|
|
dst[0] = (T)((x*m[0] + y*m[1] + z*m[2] + m[3])*w);
|
|
dst[1] = (T)((x*m[4] + y*m[5] + z*m[6] + m[7])*w);
|
|
}
|
|
else
|
|
dst[0] = dst[1] = (T)0;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for( i = 0; i < len; i++, src += scn, dst += dcn )
|
|
{
|
|
const double* _m = m + dcn*(scn + 1);
|
|
double w = _m[scn];
|
|
int j, k;
|
|
for( k = 0; k < scn; k++ )
|
|
w += _m[k]*src[k];
|
|
if( fabs(w) > eps )
|
|
{
|
|
_m = m;
|
|
for( j = 0; j < dcn; j++, _m += scn + 1 )
|
|
{
|
|
double s = _m[scn];
|
|
for( k = 0; k < scn; k++ )
|
|
s += _m[k]*src[k];
|
|
dst[j] = (T)(s*w);
|
|
}
|
|
}
|
|
else
|
|
for( j = 0; j < dcn; j++ )
|
|
dst[j] = 0;
|
|
}
|
|
}
|
|
}
|
|
|
|
static void
|
|
perspectiveTransform_32f(const float* src, float* dst, const double* m, int len, int scn, int dcn)
|
|
{
|
|
perspectiveTransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
static void
|
|
perspectiveTransform_64f(const double* src, double* dst, const double* m, int len, int scn, int dcn)
|
|
{
|
|
perspectiveTransform_(src, dst, m, len, scn, dcn);
|
|
}
|
|
|
|
TransformFunc getPerspectiveTransform(int depth)
|
|
{
|
|
if (depth == CV_32F)
|
|
return (TransformFunc)perspectiveTransform_32f;
|
|
if (depth == CV_64F)
|
|
return (TransformFunc)perspectiveTransform_64f;
|
|
CV_Assert(0 && "Not supported");
|
|
}
|
|
|
|
|
|
|
|
/****************************************************************************************\
|
|
* ScaleAdd *
|
|
\****************************************************************************************/
|
|
|
|
static void scaleAdd_32f(const float* src1, const float* src2, float* dst,
|
|
int len, float* _alpha)
|
|
{
|
|
float alpha = *_alpha;
|
|
int i = 0;
|
|
#if CV_SIMD
|
|
v_float32 v_alpha = vx_setall_f32(alpha);
|
|
const int cWidth = v_float32::nlanes;
|
|
for (; i <= len - cWidth; i += cWidth)
|
|
v_store(dst + i, v_muladd(vx_load(src1 + i), v_alpha, vx_load(src2 + i)));
|
|
vx_cleanup();
|
|
#endif
|
|
for (; i < len; i++)
|
|
dst[i] = src1[i] * alpha + src2[i];
|
|
}
|
|
|
|
|
|
static void scaleAdd_64f(const double* src1, const double* src2, double* dst,
|
|
int len, double* _alpha)
|
|
{
|
|
double alpha = *_alpha;
|
|
int i = 0;
|
|
#if CV_SIMD_64F
|
|
v_float64 a2 = vx_setall_f64(alpha);
|
|
const int cWidth = v_float64::nlanes;
|
|
for (; i <= len - cWidth; i += cWidth)
|
|
v_store(dst + i, v_muladd(vx_load(src1 + i), a2, vx_load(src2 + i)));
|
|
vx_cleanup();
|
|
#endif
|
|
for (; i < len; i++)
|
|
dst[i] = src1[i] * alpha + src2[i];
|
|
}
|
|
|
|
ScaleAddFunc getScaleAddFunc(int depth)
|
|
{
|
|
if (depth == CV_32F)
|
|
return (ScaleAddFunc)scaleAdd_32f;
|
|
if (depth == CV_64F)
|
|
return (ScaleAddFunc)scaleAdd_64f;
|
|
CV_Assert(0 && "Not supported");
|
|
}
|
|
|
|
|
|
|
|
/****************************************************************************************\
|
|
* Mahalanobis *
|
|
\****************************************************************************************/
|
|
|
|
template<typename T> static inline
|
|
double MahalanobisImpl(const Mat& v1, const Mat& v2, const Mat& icovar, double *diff_buffer /*[len]*/, int len /*=v1.total()*/)
|
|
{
|
|
CV_INSTRUMENT_REGION();
|
|
|
|
Size sz = v1.size();
|
|
double result = 0;
|
|
|
|
sz.width *= v1.channels();
|
|
if (v1.isContinuous() && v2.isContinuous())
|
|
{
|
|
sz.width *= sz.height;
|
|
sz.height = 1;
|
|
}
|
|
|
|
{
|
|
const T* src1 = v1.ptr<T>();
|
|
const T* src2 = v2.ptr<T>();
|
|
size_t step1 = v1.step/sizeof(src1[0]);
|
|
size_t step2 = v2.step/sizeof(src2[0]);
|
|
double* diff = diff_buffer;
|
|
const T* mat = icovar.ptr<T>();
|
|
size_t matstep = icovar.step/sizeof(mat[0]);
|
|
|
|
for (; sz.height--; src1 += step1, src2 += step2, diff += sz.width)
|
|
{
|
|
for (int i = 0; i < sz.width; i++)
|
|
diff[i] = src1[i] - src2[i];
|
|
}
|
|
|
|
diff = diff_buffer;
|
|
for (int i = 0; i < len; i++, mat += matstep)
|
|
{
|
|
double row_sum = 0;
|
|
int j = 0;
|
|
#if CV_ENABLE_UNROLLED
|
|
for(; 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];
|
|
#endif
|
|
for (; j < len; j++)
|
|
row_sum += diff[j]*mat[j];
|
|
result += row_sum * diff[i];
|
|
}
|
|
}
|
|
return result;
|
|
}
|
|
|
|
MahalanobisImplFunc getMahalanobisImplFunc(int depth)
|
|
{
|
|
if (depth == CV_32F)
|
|
return (MahalanobisImplFunc)MahalanobisImpl<float>;
|
|
if (depth == CV_64F)
|
|
return (MahalanobisImplFunc)MahalanobisImpl<double>;
|
|
CV_Assert(0 && "Not supported");
|
|
}
|
|
|
|
|
|
#if !defined(CV_MULTRANSPOSED_BASELINE_ONLY) || defined(CV_CPU_BASELINE_MODE)
|
|
/****************************************************************************************\
|
|
* MulTransposed *
|
|
\****************************************************************************************/
|
|
|
|
template<typename sT, typename dT> static void
|
|
MulTransposedR(const Mat& srcmat, const Mat& dstmat, const Mat& deltamat, double scale)
|
|
{
|
|
int i, j, k;
|
|
const sT* src = srcmat.ptr<sT>();
|
|
dT* dst = (dT*)dstmat.ptr<dT>();
|
|
const dT* delta = deltamat.ptr<dT>();
|
|
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*)buf.data();
|
|
|
|
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 CV_SIMD_64F
|
|
v_float64x2 v_scale = v_setall_f64(scale);
|
|
#endif
|
|
|
|
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 )
|
|
{
|
|
#if CV_SIMD_64F
|
|
if (DataType<sT>::depth == CV_64F && DataType<dT>::depth == CV_64F)
|
|
{
|
|
v_float64x2 s0 = v_setzero_f64(), s1 = v_setzero_f64();
|
|
const double *tsrc = (double*)(src + j);
|
|
|
|
for( k = 0; k < size.height; k++, tsrc += srcstep )
|
|
{
|
|
v_float64x2 a = v_setall_f64((double)col_buf[k]);
|
|
s0 += a * v_load(tsrc+0);
|
|
s1 += a * v_load(tsrc+2);
|
|
}
|
|
|
|
v_store((double*)(tdst+j), s0*v_scale);
|
|
v_store((double*)(tdst+j+2), s1*v_scale);
|
|
} else
|
|
#endif
|
|
{
|
|
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 += (double)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 )
|
|
{
|
|
#if CV_SIMD_64F
|
|
if (DataType<sT>::depth == CV_64F && DataType<dT>::depth == CV_64F)
|
|
{
|
|
v_float64x2 s0 = v_setzero_f64(), s1 = v_setzero_f64();
|
|
const double *tsrc = (double*)(src + j);
|
|
const double *d = (double*)(delta_buf ? delta_buf : delta + j);
|
|
|
|
for( k = 0; k < size.height; k++, tsrc+=srcstep, d+=deltastep )
|
|
{
|
|
v_float64x2 a = v_setall_f64((double)col_buf[k]);
|
|
s0 += a * (v_load(tsrc+0) - v_load(d+0));
|
|
s1 += a * (v_load(tsrc+2) - v_load(d+2));
|
|
}
|
|
|
|
v_store((double*)(tdst+j), s0*v_scale);
|
|
v_store((double*)(tdst+j+2), s1*v_scale);
|
|
}
|
|
else
|
|
#endif
|
|
|
|
{
|
|
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 += (double)col_buf[k] * (tsrc[0] - d[0]);
|
|
|
|
tdst[j] = (dT)(s0*scale);
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
template<typename sT, typename dT> static void
|
|
MulTransposedL(const Mat& srcmat, const Mat& dstmat, const Mat& deltamat, double scale)
|
|
{
|
|
int i, j, k;
|
|
const sT* src = srcmat.ptr<sT>();
|
|
dT* dst = (dT*)dstmat.ptr<dT>();
|
|
const dT* delta = deltamat.ptr<dT>();
|
|
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;
|
|
#if CV_SIMD_64F
|
|
if (DataType<sT>::depth == CV_64F && DataType<dT>::depth == CV_64F)
|
|
{
|
|
const double *v_tsrc1 = (double *)(tsrc1);
|
|
const double *v_tsrc2 = (double *)(tsrc2);
|
|
v_float64x2 v_s = v_setzero_f64();
|
|
|
|
for( k = 0; k <= size.width - 4; k += 4 )
|
|
v_s += (v_load(v_tsrc1+k) * v_load(v_tsrc2+k)) +
|
|
(v_load(v_tsrc1+k+2) * v_load(v_tsrc2+k+2));
|
|
s += v_reduce_sum(v_s);
|
|
}
|
|
else
|
|
#endif
|
|
{
|
|
for( k = 0; k <= size.width - 4; k += 4 )
|
|
s += (double)tsrc1[k]*tsrc2[k] + (double)tsrc1[k+1]*tsrc2[k+1] +
|
|
(double)tsrc1[k+2]*tsrc2[k+2] + (double)tsrc1[k+3]*tsrc2[k+3];
|
|
}
|
|
for( ; k < size.width; k++ )
|
|
s += (double)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*)buf.data();
|
|
|
|
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;
|
|
}
|
|
#if CV_SIMD_64F
|
|
if (DataType<sT>::depth == CV_64F && DataType<dT>::depth == CV_64F)
|
|
{
|
|
const double *v_tsrc2 = (double *)(tsrc2);
|
|
const double *v_tdelta2 = (double *)(tdelta2);
|
|
const double *v_row_buf = (double *)(row_buf);
|
|
v_float64x2 v_s = v_setzero_f64();
|
|
|
|
for( k = 0; k <= size.width - 4; k += 4, v_tdelta2 += delta_shift )
|
|
v_s += ((v_load(v_tsrc2+k) - v_load(v_tdelta2)) * v_load(v_row_buf+k)) +
|
|
((v_load(v_tsrc2+k+2) - v_load(v_tdelta2+2)) * v_load(v_row_buf+k+2));
|
|
s += v_reduce_sum(v_s);
|
|
|
|
tdelta2 = (const dT *)(v_tdelta2);
|
|
}
|
|
else
|
|
#endif
|
|
{
|
|
for( k = 0; k <= size.width-4; k += 4, tdelta2 += delta_shift )
|
|
s += (double)row_buf[k]*(tsrc2[k] - tdelta2[0]) +
|
|
(double)row_buf[k+1]*(tsrc2[k+1] - tdelta2[1]) +
|
|
(double)row_buf[k+2]*(tsrc2[k+2] - tdelta2[2]) +
|
|
(double)row_buf[k+3]*(tsrc2[k+3] - tdelta2[3]);
|
|
}
|
|
for( ; k < size.width; k++, tdelta2++ )
|
|
s += (double)row_buf[k]*(tsrc2[k] - tdelta2[0]);
|
|
tdst[j] = (dT)(s*scale);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
MulTransposedFunc getMulTransposedFunc(int stype, int dtype, bool ata)
|
|
{
|
|
MulTransposedFunc func = NULL;
|
|
if (stype == CV_8U && dtype == CV_32F)
|
|
{
|
|
func = ata ? MulTransposedR<uchar,float>
|
|
: MulTransposedL<uchar,float>;
|
|
}
|
|
else if (stype == CV_8U && dtype == CV_64F)
|
|
{
|
|
func = ata ? MulTransposedR<uchar,double>
|
|
: MulTransposedL<uchar,double>;
|
|
}
|
|
else if(stype == CV_16U && dtype == CV_32F)
|
|
{
|
|
func = ata ? MulTransposedR<ushort,float>
|
|
: MulTransposedL<ushort,float>;
|
|
}
|
|
else if(stype == CV_16U && dtype == CV_64F)
|
|
{
|
|
func = ata ? MulTransposedR<ushort,double>
|
|
: MulTransposedL<ushort,double>;
|
|
}
|
|
else if(stype == CV_16S && dtype == CV_32F)
|
|
{
|
|
func = ata ? MulTransposedR<short,float>
|
|
: MulTransposedL<short,float>;
|
|
}
|
|
else if(stype == CV_16S && dtype == CV_64F)
|
|
{
|
|
func = ata ? MulTransposedR<short,double>
|
|
: MulTransposedL<short,double>;
|
|
}
|
|
else if(stype == CV_32F && dtype == CV_32F)
|
|
{
|
|
func = ata ? MulTransposedR<float,float>
|
|
: MulTransposedL<float,float>;
|
|
}
|
|
else if(stype == CV_32F && dtype == CV_64F)
|
|
{
|
|
func = ata ? MulTransposedR<float,double>
|
|
: MulTransposedL<float,double>;
|
|
}
|
|
else if(stype == CV_64F && dtype == CV_64F)
|
|
{
|
|
func = ata ? MulTransposedR<double,double>
|
|
: MulTransposedL<double,double>;
|
|
}
|
|
CV_Assert(func && "Not supported");
|
|
return func;
|
|
}
|
|
#endif // !defined(CV_MULTRANSPOSED_BASELINE_ONLY) || defined(CV_CPU_BASELINE_MODE)
|
|
|
|
|
|
/****************************************************************************************\
|
|
* Dot Product *
|
|
\****************************************************************************************/
|
|
|
|
template<typename T> static inline
|
|
double dotProd_(const T* src1, const T* src2, int len)
|
|
{
|
|
int i = 0;
|
|
double result = 0;
|
|
|
|
#if CV_ENABLE_UNROLLED
|
|
for( ; i <= len - 4; i += 4 )
|
|
result += (double)src1[i]*src2[i] + (double)src1[i+1]*src2[i+1] +
|
|
(double)src1[i+2]*src2[i+2] + (double)src1[i+3]*src2[i+3];
|
|
#endif
|
|
for( ; i < len; i++ )
|
|
result += (double)src1[i]*src2[i];
|
|
|
|
return result;
|
|
}
|
|
|
|
|
|
double dotProd_8u(const uchar* src1, const uchar* src2, int len)
|
|
{
|
|
double r = 0;
|
|
int i = 0;
|
|
|
|
#if CV_SIMD
|
|
int len0 = len & -v_uint16::nlanes, blockSize0 = (1 << 15), blockSize;
|
|
|
|
while (i < len0)
|
|
{
|
|
blockSize = std::min(len0 - i, blockSize0);
|
|
v_uint32 v_sum = vx_setzero_u32();
|
|
const int cWidth = v_uint16::nlanes;
|
|
|
|
int j = 0;
|
|
for (; j <= blockSize - cWidth * 2; j += cWidth * 2)
|
|
{
|
|
v_uint8 v_src1 = vx_load(src1 + j);
|
|
v_uint8 v_src2 = vx_load(src2 + j);
|
|
v_sum = v_dotprod_expand_fast(v_src1, v_src2, v_sum);
|
|
}
|
|
|
|
for (; j <= blockSize - cWidth; j += cWidth)
|
|
{
|
|
v_int16 v_src10 = v_reinterpret_as_s16(vx_load_expand(src1 + j));
|
|
v_int16 v_src20 = v_reinterpret_as_s16(vx_load_expand(src2 + j));
|
|
v_sum += v_reinterpret_as_u32(v_dotprod_fast(v_src10, v_src20));
|
|
}
|
|
r += (double)v_reduce_sum(v_sum);
|
|
|
|
src1 += blockSize;
|
|
src2 += blockSize;
|
|
i += blockSize;
|
|
}
|
|
vx_cleanup();
|
|
#endif
|
|
return r + dotProd_(src1, src2, len - i);
|
|
}
|
|
|
|
|
|
double dotProd_8s(const schar* src1, const schar* src2, int len)
|
|
{
|
|
double r = 0.0;
|
|
int i = 0;
|
|
|
|
#if CV_SIMD
|
|
int len0 = len & -v_int16::nlanes, blockSize0 = (1 << 14), blockSize;
|
|
|
|
while (i < len0)
|
|
{
|
|
blockSize = std::min(len0 - i, blockSize0);
|
|
v_int32 v_sum = vx_setzero_s32();
|
|
const int cWidth = v_int16::nlanes;
|
|
|
|
int j = 0;
|
|
for (; j <= blockSize - cWidth * 2; j += cWidth * 2)
|
|
{
|
|
v_int8 v_src1 = vx_load(src1 + j);
|
|
v_int8 v_src2 = vx_load(src2 + j);
|
|
v_sum = v_dotprod_expand_fast(v_src1, v_src2, v_sum);
|
|
}
|
|
|
|
for (; j <= blockSize - cWidth; j += cWidth)
|
|
{
|
|
v_int16 v_src1 = vx_load_expand(src1 + j);
|
|
v_int16 v_src2 = vx_load_expand(src2 + j);
|
|
v_sum = v_dotprod_fast(v_src1, v_src2, v_sum);
|
|
}
|
|
r += (double)v_reduce_sum(v_sum);
|
|
|
|
src1 += blockSize;
|
|
src2 += blockSize;
|
|
i += blockSize;
|
|
}
|
|
vx_cleanup();
|
|
#endif
|
|
|
|
return r + dotProd_(src1, src2, len - i);
|
|
}
|
|
|
|
double dotProd_16u(const ushort* src1, const ushort* src2, int len)
|
|
{
|
|
double r = 0.0;
|
|
int i = 0;
|
|
|
|
#if CV_SIMD
|
|
int len0 = len & -v_uint16::nlanes, blockSize0 = (1 << 24), blockSize;
|
|
|
|
while (i < len0)
|
|
{
|
|
blockSize = std::min(len0 - i, blockSize0);
|
|
v_uint64 v_sum = vx_setzero_u64();
|
|
const int cWidth = v_uint16::nlanes;
|
|
|
|
int j = 0;
|
|
for (; j <= blockSize - cWidth; j += cWidth)
|
|
{
|
|
v_uint16 v_src1 = vx_load(src1 + j);
|
|
v_uint16 v_src2 = vx_load(src2 + j);
|
|
v_sum = v_dotprod_expand_fast(v_src1, v_src2, v_sum);
|
|
}
|
|
r += (double)v_reduce_sum(v_sum);
|
|
|
|
src1 += blockSize;
|
|
src2 += blockSize;
|
|
i += blockSize;
|
|
}
|
|
vx_cleanup();
|
|
#endif
|
|
return r + dotProd_(src1, src2, len - i);
|
|
}
|
|
|
|
double dotProd_16s(const short* src1, const short* src2, int len)
|
|
{
|
|
double r = 0.0;
|
|
int i = 0;
|
|
|
|
#if CV_SIMD
|
|
int len0 = len & -v_int16::nlanes, blockSize0 = (1 << 24), blockSize;
|
|
|
|
while (i < len0)
|
|
{
|
|
blockSize = std::min(len0 - i, blockSize0);
|
|
v_int64 v_sum = vx_setzero_s64();
|
|
const int cWidth = v_int16::nlanes;
|
|
|
|
int j = 0;
|
|
for (; j <= blockSize - cWidth; j += cWidth)
|
|
{
|
|
v_int16 v_src1 = vx_load(src1 + j);
|
|
v_int16 v_src2 = vx_load(src2 + j);
|
|
v_sum = v_dotprod_expand_fast(v_src1, v_src2, v_sum);
|
|
}
|
|
r += (double)v_reduce_sum(v_sum);
|
|
|
|
src1 += blockSize;
|
|
src2 += blockSize;
|
|
i += blockSize;
|
|
}
|
|
vx_cleanup();
|
|
#endif
|
|
return r + dotProd_(src1, src2, len - i);
|
|
}
|
|
|
|
double dotProd_32s(const int* src1, const int* src2, int len)
|
|
{
|
|
#if CV_SIMD_64F
|
|
double r = .0;
|
|
int i = 0;
|
|
const int step = v_int32::nlanes;
|
|
v_float64 v_sum0 = vx_setzero_f64();
|
|
#if CV_SIMD_WIDTH == 16
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const int wstep = step * 2;
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v_float64 v_sum1 = vx_setzero_f64();
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for (; i < len - wstep; i += wstep, src1 += wstep, src2 += wstep)
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{
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v_int32 v_src10 = vx_load(src1);
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v_int32 v_src20 = vx_load(src2);
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v_int32 v_src11 = vx_load(src1 + step);
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v_int32 v_src21 = vx_load(src2 + step);
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v_sum0 = v_dotprod_expand_fast(v_src10, v_src20, v_sum0);
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v_sum1 = v_dotprod_expand_fast(v_src11, v_src21, v_sum1);
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}
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v_sum0 += v_sum1;
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#endif
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for (; i < len - step; i += step, src1 += step, src2 += step)
|
|
{
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v_int32 v_src1 = vx_load(src1);
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|
v_int32 v_src2 = vx_load(src2);
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v_sum0 = v_dotprod_expand_fast(v_src1, v_src2, v_sum0);
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}
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r = v_reduce_sum(v_sum0);
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|
vx_cleanup();
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|
return r + dotProd_(src1, src2, len - i);
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|
#else
|
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return dotProd_(src1, src2, len);
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|
#endif
|
|
}
|
|
|
|
double dotProd_32f(const float* src1, const float* src2, int len)
|
|
{
|
|
double r = 0.0;
|
|
int i = 0;
|
|
|
|
#if CV_SIMD
|
|
int len0 = len & -v_float32::nlanes, blockSize0 = (1 << 13), blockSize;
|
|
|
|
while (i < len0)
|
|
{
|
|
blockSize = std::min(len0 - i, blockSize0);
|
|
v_float32 v_sum = vx_setzero_f32();
|
|
|
|
int j = 0;
|
|
int cWidth = v_float32::nlanes;
|
|
|
|
#if CV_ENABLE_UNROLLED
|
|
v_float32 v_sum1 = vx_setzero_f32();
|
|
v_float32 v_sum2 = vx_setzero_f32();
|
|
v_float32 v_sum3 = vx_setzero_f32();
|
|
|
|
for (; j <= blockSize - (cWidth * 4); j += (cWidth * 4))
|
|
{
|
|
v_sum = v_muladd(vx_load(src1 + j),
|
|
vx_load(src2 + j), v_sum);
|
|
v_sum1 = v_muladd(vx_load(src1 + j + cWidth),
|
|
vx_load(src2 + j + cWidth), v_sum1);
|
|
v_sum2 = v_muladd(vx_load(src1 + j + (cWidth * 2)),
|
|
vx_load(src2 + j + (cWidth * 2)), v_sum2);
|
|
v_sum3 = v_muladd(vx_load(src1 + j + (cWidth * 3)),
|
|
vx_load(src2 + j + (cWidth * 3)), v_sum3);
|
|
}
|
|
|
|
v_sum += v_sum1 + v_sum2 + v_sum3;
|
|
#endif
|
|
|
|
for (; j <= blockSize - cWidth; j += cWidth)
|
|
v_sum = v_muladd(vx_load(src1 + j), vx_load(src2 + j), v_sum);
|
|
|
|
r += v_reduce_sum(v_sum);
|
|
|
|
src1 += blockSize;
|
|
src2 += blockSize;
|
|
i += blockSize;
|
|
}
|
|
vx_cleanup();
|
|
#endif
|
|
return r + dotProd_(src1, src2, len - i);
|
|
}
|
|
|
|
double dotProd_64f(const double* src1, const double* src2, int len)
|
|
{
|
|
return dotProd_(src1, src2, len);
|
|
}
|
|
|
|
#endif
|
|
CV_CPU_OPTIMIZATION_NAMESPACE_END
|
|
} // namespace
|