mirror/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2024-12-13 07:59:27 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity
2db7f8e827
opencv/modules/core/src/matmul.simd.hpp
Alexander Smorkalov 0044047782
Merge pull request #25598 from asmorkalov:as/tables_range_check_core 
Check range for type-dependant function tables #25598

Address https://github.com/opencv/opencv/issues/24703

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-05-17 10:48:40 +03:00

2628 lines
93 KiB
C++
Raw Blame History

/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#ifdef HAVE_LAPACK
#define CV_GEMM_BASELINE_ONLY
#endif
#define CV_MAHALANOBIS_BASELINE_ONLY
#define CV_MULTRANSPOSED_BASELINE_ONLY
namespace cv {
// forward declarations
typedef void (*TransformFunc)(const uchar* src, uchar* dst, const uchar* m, int len, int scn, int dcn);
typedef void (*ScaleAddFunc)(const uchar* src1, const uchar* src2, uchar* dst, int len, const void* alpha);
typedef void (*MulTransposedFunc)(const Mat& src, const/*preallocated*/ Mat& dst, const Mat& delta, double scale);
typedef double (*MahalanobisImplFunc)(const Mat& v1, const Mat& v2, const Mat& icovar, double *diff_buffer /*[len]*/, int len /*=v1.total()*/);
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
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);
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);
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);
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);
TransformFunc getTransformFunc(int depth);
TransformFunc getDiagTransformFunc(int depth);
TransformFunc getPerspectiveTransform(int depth);
ScaleAddFunc getScaleAddFunc(int depth);
MahalanobisImplFunc getMahalanobisImplFunc(int depth);
MulTransposedFunc getMulTransposedFunc(int stype, int dtype, bool ata);
double dotProd_8u(const uchar* src1, const uchar* src2, int len);
double dotProd_8s(const schar* src1, const schar* src2, int len);
double dotProd_16u(const ushort* src1, const ushort* src2, int len);
double dotProd_16s(const short* src1, const short* src2, int len);
double dotProd_32s(const int* src1, const int* src2, int len);
double dotProd_32f(const float* src1, const float* src2, int len);
double dotProd_64f(const double* src1, const double* src2, int len);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
#if !defined(CV_GEMM_BASELINE_ONLY) || defined(CV_CPU_BASELINE_MODE)
/****************************************************************************************\
* GEMM *
\****************************************************************************************/
static void
GEMM_CopyBlock( const uchar* src, size_t src_step,
uchar* dst, size_t dst_step,
Size size, size_t pix_size )
{
int j;
size.width *= (int)(pix_size / sizeof(int));
for( ; size.height--; src += src_step, dst += dst_step )
{
j=0;
#if CV_ENABLE_UNROLLED
for( ; j <= size.width - 4; j += 4 )
{
int t0 = ((const int*)src)[j];
int t1 = ((const int*)src)[j+1];
((int*)dst)[j] = t0;
((int*)dst)[j+1] = t1;
t0 = ((const int*)src)[j+2];
t1 = ((const int*)src)[j+3];
((int*)dst)[j+2] = t0;
((int*)dst)[j+3] = t1;
}
#endif
for( ; j < size.width; j++ )
((int*)dst)[j] = ((const int*)src)[j];
}
}
static void
GEMM_TransposeBlock( const uchar* src, size_t src_step,
uchar* dst, size_t dst_step,
Size size, size_t pix_size )
{
int i, j;
for( i = 0; i < size.width; i++, dst += dst_step, src += pix_size )
{
const uchar* _src = src;
switch( pix_size )
{
case sizeof(int):
for( j = 0; j < size.height; j++, _src += src_step )
((int*)dst)[j] = ((int*)_src)[0];
break;
case sizeof(int)*2:
for( j = 0; j < size.height*2; j += 2, _src += src_step )
{
int t0 = ((int*)_src)[0];
int t1 = ((int*)_src)[1];
((int*)dst)[j] = t0;
((int*)dst)[j+1] = t1;
}
break;
case sizeof(int)*4:
for( j = 0; j < size.height*4; j += 4, _src += src_step )
{
int t0 = ((int*)_src)[0];
int t1 = ((int*)_src)[1];
((int*)dst)[j] = t0;
((int*)dst)[j+1] = t1;
t0 = ((int*)_src)[2];
t1 = ((int*)_src)[3];
((int*)dst)[j+2] = t0;
((int*)dst)[j+3] = t1;
}
break;
default:
CV_Assert(0);
return;
}
}
}
template<typename T, typename WT> static void
GEMMSingleMul( const T* a_data, size_t a_step,
const T* b_data, size_t b_step,
const T* c_data, size_t c_step,
T* d_data, size_t d_step,
Size a_size, Size d_size,
double alpha, double beta, int flags )
{
int i, j, k, n = a_size.width, m = d_size.width, drows = d_size.height;
const T *_a_data = a_data, *_b_data = b_data, *_c_data = c_data;
cv::AutoBuffer<T> _a_buf;
T* a_buf = 0;
size_t a_step0, a_step1, c_step0, c_step1, t_step;
a_step /= sizeof(a_data[0]);
b_step /= sizeof(b_data[0]);
c_step /= sizeof(c_data[0]);
d_step /= sizeof(d_data[0]);
a_step0 = a_step;
a_step1 = 1;
if( !c_data )
c_step0 = c_step1 = 0;
else if( !(flags & GEMM_3_T) )
c_step0 = c_step, c_step1 = 1;
else
c_step0 = 1, c_step1 = c_step;
if( flags & GEMM_1_T )
{
CV_SWAP( a_step0, a_step1, t_step );
n = a_size.height;
if( a_step > 1 && n > 1 )
{
_a_buf.allocate(n);
a_buf = _a_buf.data();
}
}
if( n == 1 ) /* external product */
{
cv::AutoBuffer<T> _b_buf;
T* b_buf = 0;
if( a_step > 1 && a_size.height > 1 )
{
_a_buf.allocate(drows);
a_buf = _a_buf.data();
for( k = 0; k < drows; k++ )
a_buf[k] = a_data[a_step*k];
a_data = a_buf;
}
if( b_step > 1 )
{
_b_buf.allocate(d_size.width);
b_buf = _b_buf.data();
for( j = 0; j < d_size.width; j++ )
b_buf[j] = b_data[j*b_step];
b_data = b_buf;
}
for( i = 0; i < drows; i++, _c_data += c_step0, d_data += d_step )
{
WT al = WT(a_data[i])*alpha;
c_data = _c_data;
for( j = 0; j <= d_size.width - 2; j += 2, c_data += 2*c_step1 )
{
WT s0 = al*WT(b_data[j]);
WT s1 = al*WT(b_data[j+1]);
if( !c_data )
{
d_data[j] = T(s0);
d_data[j+1] = T(s1);
}
else
{
d_data[j] = T(s0 + WT(c_data[0])*beta);
d_data[j+1] = T(s1 + WT(c_data[c_step1])*beta);
}
}
for( ; j < d_size.width; j++, c_data += c_step1 )
{
WT s0 = al*WT(b_data[j]);
if( !c_data )
d_data[j] = T(s0);
else
d_data[j] = T(s0 + WT(c_data[0])*beta);
}
}
}
else if( flags & GEMM_2_T ) /* A * Bt */
{
for( i = 0; i < drows; i++, _a_data += a_step0, _c_data += c_step0, d_data += d_step )
{
a_data = _a_data;
b_data = _b_data;
c_data = _c_data;
if( a_buf )
{
for( k = 0; k < n; k++ )
a_buf[k] = a_data[a_step1*k];
a_data = a_buf;
}
for( j = 0; j < d_size.width; j++, b_data += b_step,
c_data += c_step1 )
{
WT s0(0), s1(0), s2(0), s3(0);
k = 0;
#if CV_ENABLE_UNROLLED
for( ; k <= n - 4; k += 4 )
{
s0 += WT(a_data[k])*WT(b_data[k]);
s1 += WT(a_data[k+1])*WT(b_data[k+1]);
s2 += WT(a_data[k+2])*WT(b_data[k+2]);
s3 += WT(a_data[k+3])*WT(b_data[k+3]);
}
#endif
for( ; k < n; k++ )
s0 += WT(a_data[k])*WT(b_data[k]);
s0 = (s0+s1+s2+s3)*alpha;
if( !c_data )
d_data[j] = T(s0);
else
d_data[j] = T(s0 + WT(c_data[0])*beta);
}
}
}
else if( d_size.width*sizeof(d_data[0]) <= 1600 )
{
for( i = 0; i < drows; i++, _a_data += a_step0,
_c_data += c_step0,
d_data += d_step )
{
a_data = _a_data, c_data = _c_data;
if( a_buf )
{
for( k = 0; k < n; k++ )
a_buf[k] = a_data[a_step1*k];
a_data = a_buf;
}
for( j = 0; j <= m - 4; j += 4, c_data += 4*c_step1 )
{
const T* b = _b_data + j;
WT s0(0), s1(0), s2(0), s3(0);
for( k = 0; k < n; k++, b += b_step )
{
WT a(a_data[k]);
s0 += a * WT(b[0]); s1 += a * WT(b[1]);
s2 += a * WT(b[2]); s3 += a * WT(b[3]);
}
if( !c_data )
{
d_data[j] = T(s0*alpha);
d_data[j+1] = T(s1*alpha);
d_data[j+2] = T(s2*alpha);
d_data[j+3] = T(s3*alpha);
}
else
{
s0 = s0*alpha; s1 = s1*alpha;
s2 = s2*alpha; s3 = s3*alpha;
d_data[j] = T(s0 + WT(c_data[0])*beta);
d_data[j+1] = T(s1 + WT(c_data[c_step1])*beta);
d_data[j+2] = T(s2 + WT(c_data[c_step1*2])*beta);
d_data[j+3] = T(s3 + WT(c_data[c_step1*3])*beta);
}
}
for( ; j < m; j++, c_data += c_step1 )
{
const T* b = _b_data + j;
WT s0(0);
for( k = 0; k < n; k++, b += b_step )
s0 += WT(a_data[k]) * WT(b[0]);
s0 = s0*alpha;
if( !c_data )
d_data[j] = T(s0);
else
d_data[j] = T(s0 + WT(c_data[0])*beta);
}
}
}
else
{
cv::AutoBuffer<WT> _d_buf(m);
WT* d_buf = _d_buf.data();
for( i = 0; i < drows; i++, _a_data += a_step0, _c_data += c_step0, d_data += d_step )
{
a_data = _a_data;
b_data = _b_data;
c_data = _c_data;
if( a_buf )
{
for( k = 0; k < n; k++ )
a_buf[k] = _a_data[a_step1*k];
a_data = a_buf;
}
for( j = 0; j < m; j++ )
d_buf[j] = WT(0);
for( k = 0; k < n; k++, b_data += b_step )
{
WT al(a_data[k]);
j=0;
for( ; j < m; j++ )
d_buf[j] += WT(b_data[j])*al;
}
if( !c_data )
for( j = 0; j < m; j++ )
d_data[j] = T(d_buf[j]*alpha);
else
for( j = 0; j < m; j++, c_data += c_step1 )
{
WT t = d_buf[j]*alpha;
d_data[j] = T(t + WT(c_data[0])*beta);
}
}
}
}
template<typename T, typename WT> static void
GEMMBlockMul( const T* a_data, size_t a_step,
const T* b_data, size_t b_step,
WT* d_data, size_t d_step,
Size a_size, Size d_size, int flags )
{
int i, j, k, n = a_size.width, m = d_size.width;
const T *_a_data = a_data, *_b_data = b_data;
cv::AutoBuffer<T> _a_buf;
T* a_buf = 0;
size_t a_step0, a_step1, t_step;
int do_acc = flags & 16;
a_step /= sizeof(a_data[0]);
b_step /= sizeof(b_data[0]);
d_step /= sizeof(d_data[0]);
a_step0 = a_step;
a_step1 = 1;
if( flags & GEMM_1_T )
{
CV_SWAP( a_step0, a_step1, t_step );
n = a_size.height;
_a_buf.allocate(n);
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 || CV_SIMD_SCALABLE)
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 - VTraits<v_uint8>::vlanes()) * nChannels; x += VTraits<v_uint8>::vlanes() * 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_add(v_add(v_dotprod(v_reinterpret_as_s16(p0), m01), v_mul(p1, m2)), m3),
v_add(v_add(v_dotprod(v_reinterpret_as_s16(p2), m01), v_mul(p3, m2)), m3));
dgl = v_rshr_pack<BITS>(v_add(v_add(v_dotprod(v_reinterpret_as_s16(p0), m45), v_mul(p1, m6)), m7),
v_add(v_add(v_dotprod(v_reinterpret_as_s16(p2), m45), v_mul(p3, m6)), m7));
drl = v_rshr_pack<BITS>(v_add(v_add(v_dotprod(v_reinterpret_as_s16(p0), m89), v_mul(p1, m10)), m11),
v_add(v_add(v_dotprod(v_reinterpret_as_s16(p2), m89), v_mul(p3, m10)), m11));
v_expand(bgh, p0, p2);
v_expand(v_reinterpret_as_s16(rh), p1, p3);
dbh = v_rshr_pack<BITS>(v_add(v_add(v_dotprod(v_reinterpret_as_s16(p0), m01), v_mul(p1, m2)), m3),
v_add(v_add(v_dotprod(v_reinterpret_as_s16(p2), m01), v_mul(p3, m2)), m3));
dgh = v_rshr_pack<BITS>(v_add(v_add(v_dotprod(v_reinterpret_as_s16(p0), m45), v_mul(p1, m6)), m7),
v_add(v_add(v_dotprod(v_reinterpret_as_s16(p2), m45), v_mul(p3, m6)), m7));
drh = v_rshr_pack<BITS>(v_add(v_add(v_dotprod(v_reinterpret_as_s16(p0), m89), v_mul(p1, m10)), m11),
v_add(v_add(v_dotprod(v_reinterpret_as_s16(p2), m89), v_mul(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 || CV_SIMD_SCALABLE)
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 - VTraits<v_uint16>::vlanes())*3; x += VTraits<v_uint16>::vlanes()*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
#if CV_SIMD128
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 - VTraits<v_uint16x8>::vlanes(); x += 3*VTraits<v_uint16x8>::vlanes()/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))));
#endif //CV_SIMD128
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 || CV_SIMD_SCALABLE) && !defined(__aarch64__) && !defined(_M_ARM64)
int x = 0;
if( scn == 3 && dcn == 3 )
{
int idx[VTraits<v_float32>::max_nlanes/2];
for( int i = 0; i < VTraits<v_float32>::vlanes()/4; i++ )
{
idx[i] = 3*i;
idx[i + VTraits<v_float32>::vlanes()/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 + VTraits<v_float32>::vlanes()/4);
v_float32 m1 = vx_lut_quads(_m + 4, idx + VTraits<v_float32>::vlanes()/4);
v_float32 m2 = vx_lut_quads(_m + 8, idx + VTraits<v_float32>::vlanes()/4);
v_float32 m3 = vx_lut_quads(_m + 12, idx + VTraits<v_float32>::vlanes()/4);
for( ; x <= len*3 - VTraits<v_float32>::vlanes(); x += 3*VTraits<v_float32>::vlanes()/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[VTraits<v_float32>::max_nlanes/4];
for( int i = 0; i < VTraits<v_float32>::vlanes()/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 - VTraits<v_float32>::vlanes(); x += VTraits<v_float32>::vlanes() )
{
v_float32 v_src = vx_load(src + x);
v_store(dst + x, v_add(v_reduce_sum4(v_mul(v_src, m0), v_mul(v_src, m1), v_mul(v_src, m2), v_mul(v_src, m3)), m4));
}
#endif
#if CV_SIMD128
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 += VTraits<v_float32x4>::vlanes() )
{
v_float32x4 v_src = v_load(src + x);
v_store(dst + x, v_add(v_reduce_sum4(v_mul(v_src, _m0), v_mul(v_src, _m1), v_mul(v_src, _m2), v_mul(v_src, _m3)), _m4));
}
#else // CV_SIMD_WIDTH >= 16 && !CV_SIMD128
for( ; x < len*4; x += 4 )
{
float v0 = src[x], v1 = src[x+1], v2 = src[x+2], v3 = src[x+3];
float t0 = saturate_cast<float>(m[0]*v0 + m[1]*v1 + m[ 2]*v2 + m[ 3]*v3 + m[ 4]);
float t1 = saturate_cast<float>(m[5]*v0 + m[6]*v1 + m[ 7]*v2 + m[ 8]*v3 + m[ 9]);
float t2 = saturate_cast<float>(m[10]*v0 + m[11]*v1 + m[12]*v2 + m[13]*v3 + m[14]);
float t3 = saturate_cast<float>(m[15]*v0 + m[16]*v1 + m[17]*v2 + m[18]*v3 + m[19]);
dst[x] = t0; dst[x+1] = t1; dst[x+2] = t2; dst[x+3] = t3;
}
#endif
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[CV_DEPTH_MAX] =
{
(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[CV_DEPTH_MAX] =
{
(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 || CV_SIMD_SCALABLE)
v_float32 v_alpha = vx_setall_f32(alpha);
const int cWidth = VTraits<v_float32>::vlanes();
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 || CV_SIMD_SCALABLE_64F)
v_float64 a2 = vx_setall_f64(alpha);
const int cWidth = VTraits<v_float64>::vlanes();
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 )
{
CV_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_SIMD128_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_SIMD128_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 = v_add(s0, v_mul(a, v_load(tsrc + 0)));
s1 = v_add(s1, v_mul(a, v_load(tsrc + 2)));
}
v_store((double*)(tdst+j), v_mul(s0, v_scale));
v_store((double*)(tdst+j+2), v_mul(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_SIMD128_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 = v_add(s0, v_mul(a, v_sub(v_load(tsrc + 0), v_load(d + 0))));
s1 = v_add(s1, v_mul(a, v_sub(v_load(tsrc + 2), v_load(d + 2))));
}
v_store((double*)(tdst+j), v_mul(s0, v_scale));
v_store((double*)(tdst+j+2), v_mul(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_SIMD128_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_add(v_s, v_add(v_mul(v_load(v_tsrc1 + k), v_load(v_tsrc2 + k)), v_mul(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_SIMD128_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_add(v_s, v_add(v_mul(v_sub(v_load(v_tsrc2 + k), v_load(v_tdelta2)), v_load(v_row_buf + k)), v_mul(v_sub(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 || CV_SIMD_SCALABLE)
int len0 = len & -VTraits<v_uint16>::vlanes(), blockSize0 = (1 << 15), blockSize;
while (i < len0)
{
blockSize = std::min(len0 - i, blockSize0);
v_uint32 v_sum = vx_setzero_u32();
const int cWidth = VTraits<v_uint16>::vlanes();
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_add(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 || CV_SIMD_SCALABLE)
int len0 = len & -VTraits<v_int16>::vlanes(), blockSize0 = (1 << 14), blockSize;
while (i < len0)
{
blockSize = std::min(len0 - i, blockSize0);
v_int32 v_sum = vx_setzero_s32();
const int cWidth = VTraits<v_int16>::vlanes();
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 || CV_SIMD_SCALABLE)
int len0 = len & -VTraits<v_uint16>::vlanes(), blockSize0 = (1 << 24), blockSize;
while (i < len0)
{
blockSize = std::min(len0 - i, blockSize0);
v_uint64 v_sum = vx_setzero_u64();
const int cWidth = VTraits<v_uint16>::vlanes();
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 || CV_SIMD_SCALABLE)
int len0 = len & -VTraits<v_int16>::vlanes(), blockSize0 = (1 << 24), blockSize;
while (i < len0)
{
blockSize = std::min(len0 - i, blockSize0);
v_int64 v_sum = vx_setzero_s64();
const int cWidth = VTraits<v_int16>::vlanes();
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 // TODO: enable for CV_SIMD_SCALABLE_64F
// Test failed on RVV(QEMU): Too big difference (=1.20209e-08 > 1.11022e-12)
double r = .0;
int i = 0;
const int step = VTraits<v_int32>::vlanes();
v_float64 v_sum0 = vx_setzero_f64();
#if CV_SIMD_WIDTH == 16
const int wstep = step * 2;
v_float64 v_sum1 = vx_setzero_f64();
for (; i < len - wstep; i += wstep, src1 += wstep, src2 += wstep)
{
v_int32 v_src10 = vx_load(src1);
v_int32 v_src20 = vx_load(src2);
v_int32 v_src11 = vx_load(src1 + step);
v_int32 v_src21 = vx_load(src2 + step);
v_sum0 = v_dotprod_expand_fast(v_src10, v_src20, v_sum0);
v_sum1 = v_dotprod_expand_fast(v_src11, v_src21, v_sum1);
}
v_sum0 = v_add(v_sum0, v_sum1);
#endif
for (; i < len - step; i += step, src1 += step, src2 += step)
{
v_int32 v_src1 = vx_load(src1);
v_int32 v_src2 = vx_load(src2);
v_sum0 = v_dotprod_expand_fast(v_src1, v_src2, v_sum0);
}
r = v_reduce_sum(v_sum0);
vx_cleanup();
return r + dotProd_(src1, src2, len - i);
#else
return dotProd_(src1, src2, len);
#endif
}
double dotProd_32f(const float* src1, const float* src2, int len)
{
double r = 0.0;
int i = 0;
#if (CV_SIMD || CV_SIMD_SCALABLE)
int len0 = len & -VTraits<v_float32>::vlanes(), 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 = VTraits<v_float32>::vlanes();
#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_add(v_sum, v_add(v_add(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
Reference in New Issue View Git Blame Copy Permalink