opencv/modules/imgproc/src/accum.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
/
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
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// 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,
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//M*/
#include "precomp.hpp"
#include "opencl_kernels.hpp"
namespace cv
{
template<typename T, typename AT> void
acc_( const T* src, AT* dst, const uchar* mask, int len, int cn )
{
int i = 0;
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if( !mask )
{
len *= cn;
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#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
{
AT t0, t1;
t0 = src[i] + dst[i];
t1 = src[i+1] + dst[i+1];
dst[i] = t0; dst[i+1] = t1;
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t0 = src[i+2] + dst[i+2];
t1 = src[i+3] + dst[i+3];
dst[i+2] = t0; dst[i+3] = t1;
}
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#endif
for( ; i < len; i++ )
dst[i] += src[i];
}
else if( cn == 1 )
{
for( ; i < len; i++ )
{
if( mask[i] )
dst[i] += src[i];
}
}
else if( cn == 3 )
{
for( ; i < len; i++, src += 3, dst += 3 )
{
if( mask[i] )
{
AT t0 = src[0] + dst[0];
AT t1 = src[1] + dst[1];
AT t2 = src[2] + dst[2];
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dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
}
else
{
for( ; i < len; i++, src += cn, dst += cn )
if( mask[i] )
{
for( int k = 0; k < cn; k++ )
dst[k] += src[k];
}
}
}
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template<typename T, typename AT> void
accSqr_( const T* src, AT* dst, const uchar* mask, int len, int cn )
{
int i = 0;
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if( !mask )
{
len *= cn;
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#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
{
AT t0, t1;
t0 = (AT)src[i]*src[i] + dst[i];
t1 = (AT)src[i+1]*src[i+1] + dst[i+1];
dst[i] = t0; dst[i+1] = t1;
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t0 = (AT)src[i+2]*src[i+2] + dst[i+2];
t1 = (AT)src[i+3]*src[i+3] + dst[i+3];
dst[i+2] = t0; dst[i+3] = t1;
}
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#endif
for( ; i < len; i++ )
dst[i] += (AT)src[i]*src[i];
}
else if( cn == 1 )
{
for( ; i < len; i++ )
{
if( mask[i] )
dst[i] += (AT)src[i]*src[i];
}
}
else if( cn == 3 )
{
for( ; i < len; i++, src += 3, dst += 3 )
{
if( mask[i] )
{
AT t0 = (AT)src[0]*src[0] + dst[0];
AT t1 = (AT)src[1]*src[1] + dst[1];
AT t2 = (AT)src[2]*src[2] + dst[2];
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dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
}
else
{
for( ; i < len; i++, src += cn, dst += cn )
if( mask[i] )
{
for( int k = 0; k < cn; k++ )
dst[k] += (AT)src[k]*src[k];
}
}
}
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template<typename T, typename AT> void
accProd_( const T* src1, const T* src2, AT* dst, const uchar* mask, int len, int cn )
{
int i = 0;
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if( !mask )
{
len *= cn;
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#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
{
AT t0, t1;
t0 = (AT)src1[i]*src2[i] + dst[i];
t1 = (AT)src1[i+1]*src2[i+1] + dst[i+1];
dst[i] = t0; dst[i+1] = t1;
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t0 = (AT)src1[i+2]*src2[i+2] + dst[i+2];
t1 = (AT)src1[i+3]*src2[i+3] + dst[i+3];
dst[i+2] = t0; dst[i+3] = t1;
}
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#endif
for( ; i < len; i++ )
dst[i] += (AT)src1[i]*src2[i];
}
else if( cn == 1 )
{
for( ; i < len; i++ )
{
if( mask[i] )
dst[i] += (AT)src1[i]*src2[i];
}
}
else if( cn == 3 )
{
for( ; i < len; i++, src1 += 3, src2 += 3, dst += 3 )
{
if( mask[i] )
{
AT t0 = (AT)src1[0]*src2[0] + dst[0];
AT t1 = (AT)src1[1]*src2[1] + dst[1];
AT t2 = (AT)src1[2]*src2[2] + dst[2];
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dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
}
else
{
for( ; i < len; i++, src1 += cn, src2 += cn, dst += cn )
if( mask[i] )
{
for( int k = 0; k < cn; k++ )
dst[k] += (AT)src1[k]*src2[k];
}
}
}
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template<typename T, typename AT> void
accW_( const T* src, AT* dst, const uchar* mask, int len, int cn, double alpha )
{
AT a = (AT)alpha, b = 1 - a;
int i = 0;
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if( !mask )
{
len *= cn;
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#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
{
AT t0, t1;
t0 = src[i]*a + dst[i]*b;
t1 = src[i+1]*a + dst[i+1]*b;
dst[i] = t0; dst[i+1] = t1;
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t0 = src[i+2]*a + dst[i+2]*b;
t1 = src[i+3]*a + dst[i+3]*b;
dst[i+2] = t0; dst[i+3] = t1;
}
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#endif
for( ; i < len; i++ )
dst[i] = src[i]*a + dst[i]*b;
}
else if( cn == 1 )
{
for( ; i < len; i++ )
{
if( mask[i] )
dst[i] = src[i]*a + dst[i]*b;
}
}
else if( cn == 3 )
{
for( ; i < len; i++, src += 3, dst += 3 )
{
if( mask[i] )
{
AT t0 = src[0]*a + dst[0]*b;
AT t1 = src[1]*a + dst[1]*b;
AT t2 = src[2]*a + dst[2]*b;
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dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
}
else
{
for( ; i < len; i++, src += cn, dst += cn )
if( mask[i] )
{
for( int k = 0; k < cn; k++ )
dst[k] = src[k]*a + dst[k]*b;
}
}
}
#define DEF_ACC_FUNCS(suffix, type, acctype) \
static void acc_##suffix(const type* src, acctype* dst, \
const uchar* mask, int len, int cn) \
{ acc_(src, dst, mask, len, cn); } \
\
static void accSqr_##suffix(const type* src, acctype* dst, \
const uchar* mask, int len, int cn) \
{ accSqr_(src, dst, mask, len, cn); } \
\
static void accProd_##suffix(const type* src1, const type* src2, \
acctype* dst, const uchar* mask, int len, int cn) \
{ accProd_(src1, src2, dst, mask, len, cn); } \
\
static void accW_##suffix(const type* src, acctype* dst, \
const uchar* mask, int len, int cn, double alpha) \
{ accW_(src, dst, mask, len, cn, alpha); }
DEF_ACC_FUNCS(8u32f, uchar, float)
DEF_ACC_FUNCS(8u64f, uchar, double)
DEF_ACC_FUNCS(16u32f, ushort, float)
DEF_ACC_FUNCS(16u64f, ushort, double)
DEF_ACC_FUNCS(32f, float, float)
DEF_ACC_FUNCS(32f64f, float, double)
DEF_ACC_FUNCS(64f, double, double)
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typedef void (*AccFunc)(const uchar*, uchar*, const uchar*, int, int);
typedef void (*AccProdFunc)(const uchar*, const uchar*, uchar*, const uchar*, int, int);
typedef void (*AccWFunc)(const uchar*, uchar*, const uchar*, int, int, double);
static AccFunc accTab[] =
{
(AccFunc)acc_8u32f, (AccFunc)acc_8u64f,
(AccFunc)acc_16u32f, (AccFunc)acc_16u64f,
(AccFunc)acc_32f, (AccFunc)acc_32f64f,
(AccFunc)acc_64f
};
static AccFunc accSqrTab[] =
{
(AccFunc)accSqr_8u32f, (AccFunc)accSqr_8u64f,
(AccFunc)accSqr_16u32f, (AccFunc)accSqr_16u64f,
(AccFunc)accSqr_32f, (AccFunc)accSqr_32f64f,
(AccFunc)accSqr_64f
};
static AccProdFunc accProdTab[] =
{
(AccProdFunc)accProd_8u32f, (AccProdFunc)accProd_8u64f,
(AccProdFunc)accProd_16u32f, (AccProdFunc)accProd_16u64f,
(AccProdFunc)accProd_32f, (AccProdFunc)accProd_32f64f,
(AccProdFunc)accProd_64f
};
static AccWFunc accWTab[] =
{
(AccWFunc)accW_8u32f, (AccWFunc)accW_8u64f,
(AccWFunc)accW_16u32f, (AccWFunc)accW_16u64f,
(AccWFunc)accW_32f, (AccWFunc)accW_32f64f,
(AccWFunc)accW_64f
};
inline int getAccTabIdx(int sdepth, int ddepth)
{
return sdepth == CV_8U && ddepth == CV_32F ? 0 :
sdepth == CV_8U && ddepth == CV_64F ? 1 :
sdepth == CV_16U && ddepth == CV_32F ? 2 :
sdepth == CV_16U && ddepth == CV_64F ? 3 :
sdepth == CV_32F && ddepth == CV_32F ? 4 :
sdepth == CV_32F && ddepth == CV_64F ? 5 :
sdepth == CV_64F && ddepth == CV_64F ? 6 : -1;
}
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#ifdef HAVE_OPENCL
enum
{
ACCUMULATE = 0,
ACCUMULATE_SQUARE = 1,
ACCUMULATE_PRODUCT = 2,
ACCUMULATE_WEIGHTED = 3
};
static bool ocl_accumulate( InputArray _src, InputArray _src2, InputOutputArray _dst, double alpha,
InputArray _mask, int op_type )
{
CV_Assert(op_type == ACCUMULATE || op_type == ACCUMULATE_SQUARE ||
op_type == ACCUMULATE_PRODUCT || op_type == ACCUMULATE_WEIGHTED);
int stype = _src.type(), cn = CV_MAT_CN(stype);
int sdepth = CV_MAT_DEPTH(stype), ddepth = _dst.depth();
bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0,
haveMask = !_mask.empty();
if (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F))
return false;
const char * const opMap[4] = { "ACCUMULATE", "ACCUMULATE_SQUARE", "ACCUMULATE_PRODUCT",
"ACCUMULATE_WEIGHTED" };
ocl::Kernel k("accumulate", ocl::imgproc::accumulate_oclsrc,
format("-D %s%s -D srcT=%s -D cn=%d -D dstT=%s%s",
opMap[op_type], haveMask ? " -D HAVE_MASK" : "",
ocl::typeToStr(sdepth), cn, ocl::typeToStr(ddepth),
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
UMat src = _src.getUMat(), src2 = _src2.getUMat(), dst = _dst.getUMat(), mask = _mask.getUMat();
ocl::KernelArg srcarg = ocl::KernelArg::ReadOnlyNoSize(src),
src2arg = ocl::KernelArg::ReadOnlyNoSize(src2),
dstarg = ocl::KernelArg::ReadWrite(dst),
maskarg = ocl::KernelArg::ReadOnlyNoSize(mask);
int argidx = k.set(0, srcarg);
if (op_type == ACCUMULATE_PRODUCT)
argidx = k.set(argidx, src2arg);
argidx = k.set(argidx, dstarg);
if (op_type == ACCUMULATE_WEIGHTED)
{
if (ddepth == CV_32F)
argidx = k.set(argidx, (float)alpha);
else
argidx = k.set(argidx, alpha);
}
if (haveMask)
argidx = k.set(argidx, maskarg);
size_t globalsize[2] = { src.cols, src.rows };
return k.run(2, globalsize, NULL, false);
}
#endif
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}
void cv::accumulate( InputArray _src, InputOutputArray _dst, InputArray _mask )
{
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), scn = CV_MAT_CN(stype);
int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), dcn = CV_MAT_CN(dtype);
CV_Assert( _src.sameSize(_dst) && dcn == scn );
CV_Assert( _mask.empty() || (_src.sameSize(_mask) && _mask.type() == CV_8U) );
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CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_accumulate(_src, noArray(), _dst, 0.0, _mask, ACCUMULATE))
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
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int fidx = getAccTabIdx(sdepth, ddepth);
AccFunc func = fidx >= 0 ? accTab[fidx] : 0;
CV_Assert( func != 0 );
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const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
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for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, scn);
}
void cv::accumulateSquare( InputArray _src, InputOutputArray _dst, InputArray _mask )
{
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), scn = CV_MAT_CN(stype);
int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), dcn = CV_MAT_CN(dtype);
CV_Assert( _src.sameSize(_dst) && dcn == scn );
CV_Assert( _mask.empty() || (_src.sameSize(_mask) && _mask.type() == CV_8U) );
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CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_accumulate(_src, noArray(), _dst, 0.0, _mask, ACCUMULATE_SQUARE))
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
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int fidx = getAccTabIdx(sdepth, ddepth);
AccFunc func = fidx >= 0 ? accSqrTab[fidx] : 0;
CV_Assert( func != 0 );
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const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
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for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, scn);
}
void cv::accumulateProduct( InputArray _src1, InputArray _src2,
InputOutputArray _dst, InputArray _mask )
{
int stype = _src1.type(), sdepth = CV_MAT_DEPTH(stype), scn = CV_MAT_CN(stype);
int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), dcn = CV_MAT_CN(dtype);
CV_Assert( _src1.sameSize(_src2) && stype == _src2.type() );
CV_Assert( _src1.sameSize(_dst) && dcn == scn );
CV_Assert( _mask.empty() || (_src1.sameSize(_mask) && _mask.type() == CV_8U) );
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CV_OCL_RUN(_src1.dims() <= 2 && _dst.isUMat(),
ocl_accumulate(_src1, _src2, _dst, 0.0, _mask, ACCUMULATE_PRODUCT))
Mat src1 = _src1.getMat(), src2 = _src2.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
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int fidx = getAccTabIdx(sdepth, ddepth);
AccProdFunc func = fidx >= 0 ? accProdTab[fidx] : 0;
CV_Assert( func != 0 );
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const Mat* arrays[] = {&src1, &src2, &dst, &mask, 0};
uchar* ptrs[4];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
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for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], ptrs[3], len, scn);
}
void cv::accumulateWeighted( InputArray _src, InputOutputArray _dst,
double alpha, InputArray _mask )
{
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), scn = CV_MAT_CN(stype);
int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), dcn = CV_MAT_CN(dtype);
CV_Assert( _src.sameSize(_dst) && dcn == scn );
CV_Assert( _mask.empty() || (_src.sameSize(_mask) && _mask.type() == CV_8U) );
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CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_accumulate(_src, noArray(), _dst, alpha, _mask, ACCUMULATE_WEIGHTED))
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
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int fidx = getAccTabIdx(sdepth, ddepth);
AccWFunc func = fidx >= 0 ? accWTab[fidx] : 0;
CV_Assert( func != 0 );
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const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
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for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, scn, alpha);
}
CV_IMPL void
cvAcc( const void* arr, void* sumarr, const void* maskarr )
{
cv::Mat src = cv::cvarrToMat(arr), dst = cv::cvarrToMat(sumarr), mask;
if( maskarr )
mask = cv::cvarrToMat(maskarr);
cv::accumulate( src, dst, mask );
}
CV_IMPL void
cvSquareAcc( const void* arr, void* sumarr, const void* maskarr )
{
cv::Mat src = cv::cvarrToMat(arr), dst = cv::cvarrToMat(sumarr), mask;
if( maskarr )
mask = cv::cvarrToMat(maskarr);
cv::accumulateSquare( src, dst, mask );
}
CV_IMPL void
cvMultiplyAcc( const void* arr1, const void* arr2,
void* sumarr, const void* maskarr )
{
cv::Mat src1 = cv::cvarrToMat(arr1), src2 = cv::cvarrToMat(arr2);
cv::Mat dst = cv::cvarrToMat(sumarr), mask;
if( maskarr )
mask = cv::cvarrToMat(maskarr);
cv::accumulateProduct( src1, src2, dst, mask );
}
CV_IMPL void
cvRunningAvg( const void* arr, void* sumarr, double alpha, const void* maskarr )
{
cv::Mat src = cv::cvarrToMat(arr), dst = cv::cvarrToMat(sumarr), mask;
if( maskarr )
mask = cv::cvarrToMat(maskarr);
cv::accumulateWeighted( src, dst, alpha, mask );
}
/* End of file. */