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opencv/modules/core/src/convert.cpp
Andrey Kamaev 2a6fb2867e Remove all using directives for STL namespace and members 
Made all STL usages explicit to be able automatically find all usages of
particular class or function.
2013-02-25 15:04:17 +04:00

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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) 2009-2011, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
namespace cv
{
/****************************************************************************************\
* split & merge *
\****************************************************************************************/
template<typename T> static void
split_( const T* src, T** dst, int len, int cn )
{
int k = cn % 4 ? cn % 4 : 4;
int i, j;
if( k == 1 )
{
T* dst0 = dst[0];
for( i = j = 0; i < len; i++, j += cn )
dst0[i] = src[j];
}
else if( k == 2 )
{
T *dst0 = dst[0], *dst1 = dst[1];
for( i = j = 0; i < len; i++, j += cn )
{
dst0[i] = src[j];
dst1[i] = src[j+1];
}
}
else if( k == 3 )
{
T *dst0 = dst[0], *dst1 = dst[1], *dst2 = dst[2];
for( i = j = 0; i < len; i++, j += cn )
{
dst0[i] = src[j];
dst1[i] = src[j+1];
dst2[i] = src[j+2];
}
}
else
{
T *dst0 = dst[0], *dst1 = dst[1], *dst2 = dst[2], *dst3 = dst[3];
for( i = j = 0; i < len; i++, j += cn )
{
dst0[i] = src[j]; dst1[i] = src[j+1];
dst2[i] = src[j+2]; dst3[i] = src[j+3];
}
}
for( ; k < cn; k += 4 )
{
T *dst0 = dst[k], *dst1 = dst[k+1], *dst2 = dst[k+2], *dst3 = dst[k+3];
for( i = 0, j = k; i < len; i++, j += cn )
{
dst0[i] = src[j]; dst1[i] = src[j+1];
dst2[i] = src[j+2]; dst3[i] = src[j+3];
}
}
}
template<typename T> static void
merge_( const T** src, T* dst, int len, int cn )
{
int k = cn % 4 ? cn % 4 : 4;
int i, j;
if( k == 1 )
{
const T* src0 = src[0];
for( i = j = 0; i < len; i++, j += cn )
dst[j] = src0[i];
}
else if( k == 2 )
{
const T *src0 = src[0], *src1 = src[1];
for( i = j = 0; i < len; i++, j += cn )
{
dst[j] = src0[i];
dst[j+1] = src1[i];
}
}
else if( k == 3 )
{
const T *src0 = src[0], *src1 = src[1], *src2 = src[2];
for( i = j = 0; i < len; i++, j += cn )
{
dst[j] = src0[i];
dst[j+1] = src1[i];
dst[j+2] = src2[i];
}
}
else
{
const T *src0 = src[0], *src1 = src[1], *src2 = src[2], *src3 = src[3];
for( i = j = 0; i < len; i++, j += cn )
{
dst[j] = src0[i]; dst[j+1] = src1[i];
dst[j+2] = src2[i]; dst[j+3] = src3[i];
}
}
for( ; k < cn; k += 4 )
{
const T *src0 = src[k], *src1 = src[k+1], *src2 = src[k+2], *src3 = src[k+3];
for( i = 0, j = k; i < len; i++, j += cn )
{
dst[j] = src0[i]; dst[j+1] = src1[i];
dst[j+2] = src2[i]; dst[j+3] = src3[i];
}
}
}
static void split8u(const uchar* src, uchar** dst, int len, int cn )
{
split_(src, dst, len, cn);
}
static void split16u(const ushort* src, ushort** dst, int len, int cn )
{
split_(src, dst, len, cn);
}
static void split32s(const int* src, int** dst, int len, int cn )
{
split_(src, dst, len, cn);
}
static void split64s(const int64* src, int64** dst, int len, int cn )
{
split_(src, dst, len, cn);
}
static void merge8u(const uchar** src, uchar* dst, int len, int cn )
{
merge_(src, dst, len, cn);
}
static void merge16u(const ushort** src, ushort* dst, int len, int cn )
{
merge_(src, dst, len, cn);
}
static void merge32s(const int** src, int* dst, int len, int cn )
{
merge_(src, dst, len, cn);
}
static void merge64s(const int64** src, int64* dst, int len, int cn )
{
merge_(src, dst, len, cn);
}
typedef void (*SplitFunc)(const uchar* src, uchar** dst, int len, int cn);
typedef void (*MergeFunc)(const uchar** src, uchar* dst, int len, int cn);
static SplitFunc splitTab[] =
{
(SplitFunc)GET_OPTIMIZED(split8u), (SplitFunc)GET_OPTIMIZED(split8u), (SplitFunc)GET_OPTIMIZED(split16u), (SplitFunc)GET_OPTIMIZED(split16u),
(SplitFunc)GET_OPTIMIZED(split32s), (SplitFunc)GET_OPTIMIZED(split32s), (SplitFunc)GET_OPTIMIZED(split64s), 0
};
static MergeFunc mergeTab[] =
{
(MergeFunc)GET_OPTIMIZED(merge8u), (MergeFunc)GET_OPTIMIZED(merge8u), (MergeFunc)GET_OPTIMIZED(merge16u), (MergeFunc)GET_OPTIMIZED(merge16u),
(MergeFunc)GET_OPTIMIZED(merge32s), (MergeFunc)GET_OPTIMIZED(merge32s), (MergeFunc)GET_OPTIMIZED(merge64s), 0
};
}
void cv::split(const Mat& src, Mat* mv)
{
int k, depth = src.depth(), cn = src.channels();
if( cn == 1 )
{
src.copyTo(mv[0]);
return;
}
SplitFunc func = splitTab[depth];
CV_Assert( func != 0 );
int esz = (int)src.elemSize(), esz1 = (int)src.elemSize1();
int blocksize0 = (BLOCK_SIZE + esz-1)/esz;
AutoBuffer<uchar> _buf((cn+1)*(sizeof(Mat*) + sizeof(uchar*)) + 16);
const Mat** arrays = (const Mat**)(uchar*)_buf;
uchar** ptrs = (uchar**)alignPtr(arrays + cn + 1, 16);
arrays[0] = &src;
for( k = 0; k < cn; k++ )
{
mv[k].create(src.dims, src.size, depth);
arrays[k+1] = &mv[k];
}
NAryMatIterator it(arrays, ptrs, cn+1);
int total = (int)it.size, blocksize = cn <= 4 ? total : std::min(total, blocksize0);
for( size_t i = 0; i < it.nplanes; i++, ++it )
{
for( int j = 0; j < total; j += blocksize )
{
int bsz = std::min(total - j, blocksize);
func( ptrs[0], &ptrs[1], bsz, cn );
if( j + blocksize < total )
{
ptrs[0] += bsz*esz;
for( k = 0; k < cn; k++ )
ptrs[k+1] += bsz*esz1;
}
}
}
}
void cv::split(InputArray _m, OutputArrayOfArrays _mv)
{
Mat m = _m.getMat();
if( m.empty() )
{
_mv.release();
return;
}
CV_Assert( !_mv.fixedType() || CV_MAT_TYPE(_mv.flags) == m.depth() );
_mv.create(m.channels(), 1, m.depth());
Mat* dst = &_mv.getMatRef(0);
split(m, dst);
}
void cv::merge(const Mat* mv, size_t n, OutputArray _dst)
{
CV_Assert( mv && n > 0 );
int depth = mv[0].depth();
bool allch1 = true;
int k, cn = 0;
size_t i;
for( i = 0; i < n; i++ )
{
CV_Assert(mv[i].size == mv[0].size && mv[i].depth() == depth);
allch1 = allch1 && mv[i].channels() == 1;
cn += mv[i].channels();
}
CV_Assert( 0 < cn && cn <= CV_CN_MAX );
_dst.create(mv[0].dims, mv[0].size, CV_MAKETYPE(depth, cn));
Mat dst = _dst.getMat();
if( n == 1 )
{
mv[0].copyTo(dst);
return;
}
if( !allch1 )
{
AutoBuffer<int> pairs(cn*2);
int j, ni=0;
for( i = 0, j = 0; i < n; i++, j += ni )
{
ni = mv[i].channels();
for( k = 0; k < ni; k++ )
{
pairs[(j+k)*2] = j + k;
pairs[(j+k)*2+1] = j + k;
}
}
mixChannels( mv, n, &dst, 1, &pairs[0], cn );
return;
}
size_t esz = dst.elemSize(), esz1 = dst.elemSize1();
int blocksize0 = (int)((BLOCK_SIZE + esz-1)/esz);
AutoBuffer<uchar> _buf((cn+1)*(sizeof(Mat*) + sizeof(uchar*)) + 16);
const Mat** arrays = (const Mat**)(uchar*)_buf;
uchar** ptrs = (uchar**)alignPtr(arrays + cn + 1, 16);
arrays[0] = &dst;
for( k = 0; k < cn; k++ )
arrays[k+1] = &mv[k];
NAryMatIterator it(arrays, ptrs, cn+1);
int total = (int)it.size, blocksize = cn <= 4 ? total : std::min(total, blocksize0);
MergeFunc func = mergeTab[depth];
for( i = 0; i < it.nplanes; i++, ++it )
{
for( int j = 0; j < total; j += blocksize )
{
int bsz = std::min(total - j, blocksize);
func( (const uchar**)&ptrs[1], ptrs[0], bsz, cn );
if( j + blocksize < total )
{
ptrs[0] += bsz*esz;
for( int t = 0; t < cn; t++ )
ptrs[t+1] += bsz*esz1;
}
}
}
}
void cv::merge(InputArrayOfArrays _mv, OutputArray _dst)
{
std::vector<Mat> mv;
_mv.getMatVector(mv);
merge(!mv.empty() ? &mv[0] : 0, mv.size(), _dst);
}
/****************************************************************************************\
* Generalized split/merge: mixing channels *
\****************************************************************************************/
namespace cv
{
template<typename T> static void
mixChannels_( const T** src, const int* sdelta,
T** dst, const int* ddelta,
int len, int npairs )
{
int i, k;
for( k = 0; k < npairs; k++ )
{
const T* s = src[k];
T* d = dst[k];
int ds = sdelta[k], dd = ddelta[k];
if( s )
{
for( i = 0; i <= len - 2; i += 2, s += ds*2, d += dd*2 )
{
T t0 = s[0], t1 = s[ds];
d[0] = t0; d[dd] = t1;
}
if( i < len )
d[0] = s[0];
}
else
{
for( i = 0; i <= len - 2; i += 2, d += dd*2 )
d[0] = d[dd] = 0;
if( i < len )
d[0] = 0;
}
}
}
static void mixChannels8u( const uchar** src, const int* sdelta,
uchar** dst, const int* ddelta,
int len, int npairs )
{
mixChannels_(src, sdelta, dst, ddelta, len, npairs);
}
static void mixChannels16u( const ushort** src, const int* sdelta,
ushort** dst, const int* ddelta,
int len, int npairs )
{
mixChannels_(src, sdelta, dst, ddelta, len, npairs);
}
static void mixChannels32s( const int** src, const int* sdelta,
int** dst, const int* ddelta,
int len, int npairs )
{
mixChannels_(src, sdelta, dst, ddelta, len, npairs);
}
static void mixChannels64s( const int64** src, const int* sdelta,
int64** dst, const int* ddelta,
int len, int npairs )
{
mixChannels_(src, sdelta, dst, ddelta, len, npairs);
}
typedef void (*MixChannelsFunc)( const uchar** src, const int* sdelta,
uchar** dst, const int* ddelta, int len, int npairs );
static MixChannelsFunc mixchTab[] =
{
(MixChannelsFunc)mixChannels8u, (MixChannelsFunc)mixChannels8u, (MixChannelsFunc)mixChannels16u,
(MixChannelsFunc)mixChannels16u, (MixChannelsFunc)mixChannels32s, (MixChannelsFunc)mixChannels32s,
(MixChannelsFunc)mixChannels64s, 0
};
}
void cv::mixChannels( const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts, const int* fromTo, size_t npairs )
{
if( npairs == 0 )
return;
CV_Assert( src && nsrcs > 0 && dst && ndsts > 0 && fromTo && npairs > 0 );
size_t i, j, k, esz1 = dst[0].elemSize1();
int depth = dst[0].depth();
AutoBuffer<uchar> buf((nsrcs + ndsts + 1)*(sizeof(Mat*) + sizeof(uchar*)) + npairs*(sizeof(uchar*)*2 + sizeof(int)*6));
const Mat** arrays = (const Mat**)(uchar*)buf;
uchar** ptrs = (uchar**)(arrays + nsrcs + ndsts);
const uchar** srcs = (const uchar**)(ptrs + nsrcs + ndsts + 1);
uchar** dsts = (uchar**)(srcs + npairs);
int* tab = (int*)(dsts + npairs);
int *sdelta = (int*)(tab + npairs*4), *ddelta = sdelta + npairs;
for( i = 0; i < nsrcs; i++ )
arrays[i] = &src[i];
for( i = 0; i < ndsts; i++ )
arrays[i + nsrcs] = &dst[i];
ptrs[nsrcs + ndsts] = 0;
for( i = 0; i < npairs; i++ )
{
int i0 = fromTo[i*2], i1 = fromTo[i*2+1];
if( i0 >= 0 )
{
for( j = 0; j < nsrcs; i0 -= src[j].channels(), j++ )
if( i0 < src[j].channels() )
break;
CV_Assert(j < nsrcs && src[j].depth() == depth);
tab[i*4] = (int)j; tab[i*4+1] = (int)(i0*esz1);
sdelta[i] = src[j].channels();
}
else
{
tab[i*4] = (int)(nsrcs + ndsts); tab[i*4+1] = 0;
sdelta[i] = 0;
}
for( j = 0; j < ndsts; i1 -= dst[j].channels(), j++ )
if( i1 < dst[j].channels() )
break;
CV_Assert(i1 >= 0 && j < ndsts && dst[j].depth() == depth);
tab[i*4+2] = (int)(j + nsrcs); tab[i*4+3] = (int)(i1*esz1);
ddelta[i] = dst[j].channels();
}
NAryMatIterator it(arrays, ptrs, (int)(nsrcs + ndsts));
int total = (int)it.size, blocksize = std::min(total, (int)((BLOCK_SIZE + esz1-1)/esz1));
MixChannelsFunc func = mixchTab[depth];
for( i = 0; i < it.nplanes; i++, ++it )
{
for( k = 0; k < npairs; k++ )
{
srcs[k] = ptrs[tab[k*4]] + tab[k*4+1];
dsts[k] = ptrs[tab[k*4+2]] + tab[k*4+3];
}
for( int t = 0; t < total; t += blocksize )
{
int bsz = std::min(total - t, blocksize);
func( srcs, sdelta, dsts, ddelta, bsz, (int)npairs );
if( t + blocksize < total )
for( k = 0; k < npairs; k++ )
{
srcs[k] += blocksize*sdelta[k]*esz1;
dsts[k] += blocksize*ddelta[k]*esz1;
}
}
}
}
void cv::mixChannels(const std::vector<Mat>& src, std::vector<Mat>& dst,
const int* fromTo, size_t npairs)
{
mixChannels(!src.empty() ? &src[0] : 0, src.size(),
!dst.empty() ? &dst[0] : 0, dst.size(), fromTo, npairs);
}
void cv::mixChannels(InputArrayOfArrays src, InputArrayOfArrays dst,
const std::vector<int>& fromTo)
{
if(fromTo.empty())
return;
bool src_is_mat = src.kind() != _InputArray::STD_VECTOR_MAT &&
src.kind() != _InputArray::STD_VECTOR_VECTOR;
bool dst_is_mat = dst.kind() != _InputArray::STD_VECTOR_MAT &&
dst.kind() != _InputArray::STD_VECTOR_VECTOR;
int i;
int nsrc = src_is_mat ? 1 : (int)src.total();
int ndst = dst_is_mat ? 1 : (int)dst.total();
CV_Assert(fromTo.size()%2 == 0 && nsrc > 0 && ndst > 0);
cv::AutoBuffer<Mat> _buf(nsrc + ndst);
Mat* buf = _buf;
for( i = 0; i < nsrc; i++ )
buf[i] = src.getMat(src_is_mat ? -1 : i);
for( i = 0; i < ndst; i++ )
buf[nsrc + i] = dst.getMat(dst_is_mat ? -1 : i);
mixChannels(&buf[0], nsrc, &buf[nsrc], ndst, &fromTo[0], fromTo.size()/2);
}
void cv::extractChannel(InputArray _src, OutputArray _dst, int coi)
{
Mat src = _src.getMat();
CV_Assert( 0 <= coi && coi < src.channels() );
_dst.create(src.dims, &src.size[0], src.depth());
Mat dst = _dst.getMat();
int ch[] = { coi, 0 };
mixChannels(&src, 1, &dst, 1, ch, 1);
}
void cv::insertChannel(InputArray _src, InputOutputArray _dst, int coi)
{
Mat src = _src.getMat(), dst = _dst.getMat();
CV_Assert( src.size == dst.size && src.depth() == dst.depth() );
CV_Assert( 0 <= coi && coi < dst.channels() && src.channels() == 1 );
int ch[] = { 0, coi };
mixChannels(&src, 1, &dst, 1, ch, 1);
}
/****************************************************************************************\
* convertScale[Abs] *
\****************************************************************************************/
namespace cv
{
template<typename T, typename DT, typename WT> static void
cvtScaleAbs_( const T* src, size_t sstep,
DT* dst, size_t dstep, Size size,
WT scale, WT shift )
{
sstep /= sizeof(src[0]);
dstep /= sizeof(dst[0]);
for( ; size.height--; src += sstep, dst += dstep )
{
int x = 0;
#if CV_ENABLE_UNROLLED
for( ; x <= size.width - 4; x += 4 )
{
DT t0, t1;
t0 = saturate_cast<DT>(std::abs(src[x]*scale + shift));
t1 = saturate_cast<DT>(std::abs(src[x+1]*scale + shift));
dst[x] = t0; dst[x+1] = t1;
t0 = saturate_cast<DT>(std::abs(src[x+2]*scale + shift));
t1 = saturate_cast<DT>(std::abs(src[x+3]*scale + shift));
dst[x+2] = t0; dst[x+3] = t1;
}
#endif
for( ; x < size.width; x++ )
dst[x] = saturate_cast<DT>(std::abs(src[x]*scale + shift));
}
}
template<typename T, typename DT, typename WT> static void
cvtScale_( const T* src, size_t sstep,
DT* dst, size_t dstep, Size size,
WT scale, WT shift )
{
sstep /= sizeof(src[0]);
dstep /= sizeof(dst[0]);
for( ; size.height--; src += sstep, dst += dstep )
{
int x = 0;
#if CV_ENABLE_UNROLLED
for( ; x <= size.width - 4; x += 4 )
{
DT t0, t1;
t0 = saturate_cast<DT>(src[x]*scale + shift);
t1 = saturate_cast<DT>(src[x+1]*scale + shift);
dst[x] = t0; dst[x+1] = t1;
t0 = saturate_cast<DT>(src[x+2]*scale + shift);
t1 = saturate_cast<DT>(src[x+3]*scale + shift);
dst[x+2] = t0; dst[x+3] = t1;
}
#endif
for( ; x < size.width; x++ )
dst[x] = saturate_cast<DT>(src[x]*scale + shift);
}
}
//vz optimized template specialization
template<> void
cvtScale_<short, short, float>( const short* src, size_t sstep,
short* dst, size_t dstep, Size size,
float scale, float shift )
{
sstep /= sizeof(src[0]);
dstep /= sizeof(dst[0]);
for( ; size.height--; src += sstep, dst += dstep )
{
int x = 0;
#if CV_SSE2
if(USE_SSE2)
{
__m128 scale128 = _mm_set1_ps (scale);
__m128 shift128 = _mm_set1_ps (shift);
for(; x <= size.width - 8; x += 8 )
{
__m128i r0 = _mm_loadl_epi64((const __m128i*)(src + x));
__m128i r1 = _mm_loadl_epi64((const __m128i*)(src + x + 4));
__m128 rf0 =_mm_cvtepi32_ps(_mm_srai_epi32(_mm_unpacklo_epi16(r0, r0), 16));
__m128 rf1 =_mm_cvtepi32_ps(_mm_srai_epi32(_mm_unpacklo_epi16(r1, r1), 16));
rf0 = _mm_add_ps(_mm_mul_ps(rf0, scale128), shift128);
rf1 = _mm_add_ps(_mm_mul_ps(rf1, scale128), shift128);
r0 = _mm_cvtps_epi32(rf0);
r1 = _mm_cvtps_epi32(rf1);
r0 = _mm_packs_epi32(r0, r1);
_mm_storeu_si128((__m128i*)(dst + x), r0);
}
}
#endif
for(; x < size.width; x++ )
dst[x] = saturate_cast<short>(src[x]*scale + shift);
}
}
template<> void
cvtScale_<short, int, float>( const short* src, size_t sstep,
int* dst, size_t dstep, Size size,
float scale, float shift )
{
sstep /= sizeof(src[0]);
dstep /= sizeof(dst[0]);
for( ; size.height--; src += sstep, dst += dstep )
{
int x = 0;
#if CV_SSE2
if(USE_SSE2)//~5X
{
__m128 scale128 = _mm_set1_ps (scale);
__m128 shift128 = _mm_set1_ps (shift);
for(; x <= size.width - 8; x += 8 )
{
__m128i r0 = _mm_loadl_epi64((const __m128i*)(src + x));
__m128i r1 = _mm_loadl_epi64((const __m128i*)(src + x + 4));
__m128 rf0 =_mm_cvtepi32_ps(_mm_srai_epi32(_mm_unpacklo_epi16(r0, r0), 16));
__m128 rf1 =_mm_cvtepi32_ps(_mm_srai_epi32(_mm_unpacklo_epi16(r1, r1), 16));
rf0 = _mm_add_ps(_mm_mul_ps(rf0, scale128), shift128);
rf1 = _mm_add_ps(_mm_mul_ps(rf1, scale128), shift128);
r0 = _mm_cvtps_epi32(rf0);
r1 = _mm_cvtps_epi32(rf1);
_mm_storeu_si128((__m128i*)(dst + x), r0);
_mm_storeu_si128((__m128i*)(dst + x + 4), r1);
}
}
#endif
//We will wait Haswell
/*
#if CV_AVX
if(USE_AVX)//2X - bad variant
{
////TODO:AVX implementation (optimization?) required
__m256 scale256 = _mm256_set1_ps (scale);
__m256 shift256 = _mm256_set1_ps (shift);
for(; x <= size.width - 8; x += 8 )
{
__m256i buf = _mm256_set_epi32((int)(*(src+x+7)),(int)(*(src+x+6)),(int)(*(src+x+5)),(int)(*(src+x+4)),(int)(*(src+x+3)),(int)(*(src+x+2)),(int)(*(src+x+1)),(int)(*(src+x)));
__m256 r0 = _mm256_add_ps( _mm256_mul_ps(_mm256_cvtepi32_ps (buf), scale256), shift256);
__m256i res = _mm256_cvtps_epi32(r0);
_mm256_storeu_si256 ((__m256i*)(dst+x), res);
}
}
#endif*/
for(; x < size.width; x++ )
dst[x] = saturate_cast<int>(src[x]*scale + shift);
}
}
template<typename T, typename DT> static void
cvt_( const T* src, size_t sstep,
DT* dst, size_t dstep, Size size )
{
sstep /= sizeof(src[0]);
dstep /= sizeof(dst[0]);
for( ; size.height--; src += sstep, dst += dstep )
{
int x = 0;
#if CV_ENABLE_UNROLLED
for( ; x <= size.width - 4; x += 4 )
{
DT t0, t1;
t0 = saturate_cast<DT>(src[x]);
t1 = saturate_cast<DT>(src[x+1]);
dst[x] = t0; dst[x+1] = t1;
t0 = saturate_cast<DT>(src[x+2]);
t1 = saturate_cast<DT>(src[x+3]);
dst[x+2] = t0; dst[x+3] = t1;
}
#endif
for( ; x < size.width; x++ )
dst[x] = saturate_cast<DT>(src[x]);
}
}
//vz optimized template specialization, test Core_ConvertScale/ElemWiseTest
template<> void
cvt_<float, short>( const float* src, size_t sstep,
short* dst, size_t dstep, Size size )
{
sstep /= sizeof(src[0]);
dstep /= sizeof(dst[0]);
for( ; size.height--; src += sstep, dst += dstep )
{
int x = 0;
#if CV_SSE2
if(USE_SSE2){
for( ; x <= size.width - 8; x += 8 )
{
__m128 src128 = _mm_loadu_ps (src + x);
__m128i src_int128 = _mm_cvtps_epi32 (src128);
src128 = _mm_loadu_ps (src + x + 4);
__m128i src1_int128 = _mm_cvtps_epi32 (src128);
src1_int128 = _mm_packs_epi32(src_int128, src1_int128);
_mm_storeu_si128((__m128i*)(dst + x),src1_int128);
}
}
#endif
for( ; x < size.width; x++ )
dst[x] = saturate_cast<short>(src[x]);
}
}
template<typename T> static void
cpy_( const T* src, size_t sstep, T* dst, size_t dstep, Size size )
{
sstep /= sizeof(src[0]);
dstep /= sizeof(dst[0]);
for( ; size.height--; src += sstep, dst += dstep )
memcpy(dst, src, size.width*sizeof(src[0]));
}
#define DEF_CVT_SCALE_ABS_FUNC(suffix, tfunc, stype, dtype, wtype) \
static void cvtScaleAbs##suffix( const stype* src, size_t sstep, const uchar*, size_t, \
dtype* dst, size_t dstep, Size size, double* scale) \
{ \
tfunc(src, sstep, dst, dstep, size, (wtype)scale[0], (wtype)scale[1]); \
}
#define DEF_CVT_SCALE_FUNC(suffix, stype, dtype, wtype) \
static void cvtScale##suffix( const stype* src, size_t sstep, const uchar*, size_t, \
dtype* dst, size_t dstep, Size size, double* scale) \
{ \
cvtScale_(src, sstep, dst, dstep, size, (wtype)scale[0], (wtype)scale[1]); \
}
#define DEF_CVT_FUNC(suffix, stype, dtype) \
static void cvt##suffix( const stype* src, size_t sstep, const uchar*, size_t, \
dtype* dst, size_t dstep, Size size, double*) \
{ \
cvt_(src, sstep, dst, dstep, size); \
}
#define DEF_CPY_FUNC(suffix, stype) \
static void cvt##suffix( const stype* src, size_t sstep, const uchar*, size_t, \
stype* dst, size_t dstep, Size size, double*) \
{ \
cpy_(src, sstep, dst, dstep, size); \
}
DEF_CVT_SCALE_ABS_FUNC(8u, cvtScaleAbs_, uchar, uchar, float);
DEF_CVT_SCALE_ABS_FUNC(8s8u, cvtScaleAbs_, schar, uchar, float);
DEF_CVT_SCALE_ABS_FUNC(16u8u, cvtScaleAbs_, ushort, uchar, float);
DEF_CVT_SCALE_ABS_FUNC(16s8u, cvtScaleAbs_, short, uchar, float);
DEF_CVT_SCALE_ABS_FUNC(32s8u, cvtScaleAbs_, int, uchar, float);
DEF_CVT_SCALE_ABS_FUNC(32f8u, cvtScaleAbs_, float, uchar, float);
DEF_CVT_SCALE_ABS_FUNC(64f8u, cvtScaleAbs_, double, uchar, float);
DEF_CVT_SCALE_FUNC(8u, uchar, uchar, float);
DEF_CVT_SCALE_FUNC(8s8u, schar, uchar, float);
DEF_CVT_SCALE_FUNC(16u8u, ushort, uchar, float);
DEF_CVT_SCALE_FUNC(16s8u, short, uchar, float);
DEF_CVT_SCALE_FUNC(32s8u, int, uchar, float);
DEF_CVT_SCALE_FUNC(32f8u, float, uchar, float);
DEF_CVT_SCALE_FUNC(64f8u, double, uchar, float);
DEF_CVT_SCALE_FUNC(8u8s, uchar, schar, float);
DEF_CVT_SCALE_FUNC(8s, schar, schar, float);
DEF_CVT_SCALE_FUNC(16u8s, ushort, schar, float);
DEF_CVT_SCALE_FUNC(16s8s, short, schar, float);
DEF_CVT_SCALE_FUNC(32s8s, int, schar, float);
DEF_CVT_SCALE_FUNC(32f8s, float, schar, float);
DEF_CVT_SCALE_FUNC(64f8s, double, schar, float);
DEF_CVT_SCALE_FUNC(8u16u, uchar, ushort, float);
DEF_CVT_SCALE_FUNC(8s16u, schar, ushort, float);
DEF_CVT_SCALE_FUNC(16u, ushort, ushort, float);
DEF_CVT_SCALE_FUNC(16s16u, short, ushort, float);
DEF_CVT_SCALE_FUNC(32s16u, int, ushort, float);
DEF_CVT_SCALE_FUNC(32f16u, float, ushort, float);
DEF_CVT_SCALE_FUNC(64f16u, double, ushort, float);
DEF_CVT_SCALE_FUNC(8u16s, uchar, short, float);
DEF_CVT_SCALE_FUNC(8s16s, schar, short, float);
DEF_CVT_SCALE_FUNC(16u16s, ushort, short, float);
DEF_CVT_SCALE_FUNC(16s, short, short, float);
DEF_CVT_SCALE_FUNC(32s16s, int, short, float);
DEF_CVT_SCALE_FUNC(32f16s, float, short, float);
DEF_CVT_SCALE_FUNC(64f16s, double, short, float);
DEF_CVT_SCALE_FUNC(8u32s, uchar, int, float);
DEF_CVT_SCALE_FUNC(8s32s, schar, int, float);
DEF_CVT_SCALE_FUNC(16u32s, ushort, int, float);
DEF_CVT_SCALE_FUNC(16s32s, short, int, float);
DEF_CVT_SCALE_FUNC(32s, int, int, double);
DEF_CVT_SCALE_FUNC(32f32s, float, int, float);
DEF_CVT_SCALE_FUNC(64f32s, double, int, double);
DEF_CVT_SCALE_FUNC(8u32f, uchar, float, float);
DEF_CVT_SCALE_FUNC(8s32f, schar, float, float);
DEF_CVT_SCALE_FUNC(16u32f, ushort, float, float);
DEF_CVT_SCALE_FUNC(16s32f, short, float, float);
DEF_CVT_SCALE_FUNC(32s32f, int, float, double);
DEF_CVT_SCALE_FUNC(32f, float, float, float);
DEF_CVT_SCALE_FUNC(64f32f, double, float, double);
DEF_CVT_SCALE_FUNC(8u64f, uchar, double, double);
DEF_CVT_SCALE_FUNC(8s64f, schar, double, double);
DEF_CVT_SCALE_FUNC(16u64f, ushort, double, double);
DEF_CVT_SCALE_FUNC(16s64f, short, double, double);
DEF_CVT_SCALE_FUNC(32s64f, int, double, double);
DEF_CVT_SCALE_FUNC(32f64f, float, double, double);
DEF_CVT_SCALE_FUNC(64f, double, double, double);
DEF_CPY_FUNC(8u, uchar);
DEF_CVT_FUNC(8s8u, schar, uchar);
DEF_CVT_FUNC(16u8u, ushort, uchar);
DEF_CVT_FUNC(16s8u, short, uchar);
DEF_CVT_FUNC(32s8u, int, uchar);
DEF_CVT_FUNC(32f8u, float, uchar);
DEF_CVT_FUNC(64f8u, double, uchar);
DEF_CVT_FUNC(8u8s, uchar, schar);
DEF_CVT_FUNC(16u8s, ushort, schar);
DEF_CVT_FUNC(16s8s, short, schar);
DEF_CVT_FUNC(32s8s, int, schar);
DEF_CVT_FUNC(32f8s, float, schar);
DEF_CVT_FUNC(64f8s, double, schar);
DEF_CVT_FUNC(8u16u, uchar, ushort);
DEF_CVT_FUNC(8s16u, schar, ushort);
DEF_CPY_FUNC(16u, ushort);
DEF_CVT_FUNC(16s16u, short, ushort);
DEF_CVT_FUNC(32s16u, int, ushort);
DEF_CVT_FUNC(32f16u, float, ushort);
DEF_CVT_FUNC(64f16u, double, ushort);
DEF_CVT_FUNC(8u16s, uchar, short);
DEF_CVT_FUNC(8s16s, schar, short);
DEF_CVT_FUNC(16u16s, ushort, short);
DEF_CVT_FUNC(32s16s, int, short);
DEF_CVT_FUNC(32f16s, float, short);
DEF_CVT_FUNC(64f16s, double, short);
DEF_CVT_FUNC(8u32s, uchar, int);
DEF_CVT_FUNC(8s32s, schar, int);
DEF_CVT_FUNC(16u32s, ushort, int);
DEF_CVT_FUNC(16s32s, short, int);
DEF_CPY_FUNC(32s, int);
DEF_CVT_FUNC(32f32s, float, int);
DEF_CVT_FUNC(64f32s, double, int);
DEF_CVT_FUNC(8u32f, uchar, float);
DEF_CVT_FUNC(8s32f, schar, float);
DEF_CVT_FUNC(16u32f, ushort, float);
DEF_CVT_FUNC(16s32f, short, float);
DEF_CVT_FUNC(32s32f, int, float);
DEF_CVT_FUNC(64f32f, double, float);
DEF_CVT_FUNC(8u64f, uchar, double);
DEF_CVT_FUNC(8s64f, schar, double);
DEF_CVT_FUNC(16u64f, ushort, double);
DEF_CVT_FUNC(16s64f, short, double);
DEF_CVT_FUNC(32s64f, int, double);
DEF_CVT_FUNC(32f64f, float, double);
DEF_CPY_FUNC(64s, int64);
static BinaryFunc cvtScaleAbsTab[] =
{
(BinaryFunc)cvtScaleAbs8u, (BinaryFunc)cvtScaleAbs8s8u, (BinaryFunc)cvtScaleAbs16u8u,
(BinaryFunc)cvtScaleAbs16s8u, (BinaryFunc)cvtScaleAbs32s8u, (BinaryFunc)cvtScaleAbs32f8u,
(BinaryFunc)cvtScaleAbs64f8u, 0
};
static BinaryFunc cvtScaleTab[][8] =
{
{
(BinaryFunc)GET_OPTIMIZED(cvtScale8u), (BinaryFunc)GET_OPTIMIZED(cvtScale8s8u), (BinaryFunc)GET_OPTIMIZED(cvtScale16u8u),
(BinaryFunc)GET_OPTIMIZED(cvtScale16s8u), (BinaryFunc)GET_OPTIMIZED(cvtScale32s8u), (BinaryFunc)GET_OPTIMIZED(cvtScale32f8u),
(BinaryFunc)cvtScale64f8u, 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvtScale8u8s), (BinaryFunc)GET_OPTIMIZED(cvtScale8s), (BinaryFunc)GET_OPTIMIZED(cvtScale16u8s),
(BinaryFunc)GET_OPTIMIZED(cvtScale16s8s), (BinaryFunc)GET_OPTIMIZED(cvtScale32s8s), (BinaryFunc)GET_OPTIMIZED(cvtScale32f8s),
(BinaryFunc)cvtScale64f8s, 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvtScale8u16u), (BinaryFunc)GET_OPTIMIZED(cvtScale8s16u), (BinaryFunc)GET_OPTIMIZED(cvtScale16u),
(BinaryFunc)GET_OPTIMIZED(cvtScale16s16u), (BinaryFunc)GET_OPTIMIZED(cvtScale32s16u), (BinaryFunc)GET_OPTIMIZED(cvtScale32f16u),
(BinaryFunc)cvtScale64f16u, 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvtScale8u16s), (BinaryFunc)GET_OPTIMIZED(cvtScale8s16s), (BinaryFunc)GET_OPTIMIZED(cvtScale16u16s),
(BinaryFunc)GET_OPTIMIZED(cvtScale16s), (BinaryFunc)GET_OPTIMIZED(cvtScale32s16s), (BinaryFunc)GET_OPTIMIZED(cvtScale32f16s),
(BinaryFunc)cvtScale64f16s, 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvtScale8u32s), (BinaryFunc)GET_OPTIMIZED(cvtScale8s32s), (BinaryFunc)GET_OPTIMIZED(cvtScale16u32s),
(BinaryFunc)GET_OPTIMIZED(cvtScale16s32s), (BinaryFunc)GET_OPTIMIZED(cvtScale32s), (BinaryFunc)GET_OPTIMIZED(cvtScale32f32s),
(BinaryFunc)cvtScale64f32s, 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvtScale8u32f), (BinaryFunc)GET_OPTIMIZED(cvtScale8s32f), (BinaryFunc)GET_OPTIMIZED(cvtScale16u32f),
(BinaryFunc)GET_OPTIMIZED(cvtScale16s32f), (BinaryFunc)GET_OPTIMIZED(cvtScale32s32f), (BinaryFunc)GET_OPTIMIZED(cvtScale32f),
(BinaryFunc)cvtScale64f32f, 0
},
{
(BinaryFunc)cvtScale8u64f, (BinaryFunc)cvtScale8s64f, (BinaryFunc)cvtScale16u64f,
(BinaryFunc)cvtScale16s64f, (BinaryFunc)cvtScale32s64f, (BinaryFunc)cvtScale32f64f,
(BinaryFunc)cvtScale64f, 0
},
{
0, 0, 0, 0, 0, 0, 0, 0
}
};
static BinaryFunc cvtTab[][8] =
{
{
(BinaryFunc)(cvt8u), (BinaryFunc)GET_OPTIMIZED(cvt8s8u), (BinaryFunc)GET_OPTIMIZED(cvt16u8u),
(BinaryFunc)GET_OPTIMIZED(cvt16s8u), (BinaryFunc)GET_OPTIMIZED(cvt32s8u), (BinaryFunc)GET_OPTIMIZED(cvt32f8u),
(BinaryFunc)GET_OPTIMIZED(cvt64f8u), 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvt8u8s), (BinaryFunc)cvt8u, (BinaryFunc)GET_OPTIMIZED(cvt16u8s),
(BinaryFunc)GET_OPTIMIZED(cvt16s8s), (BinaryFunc)GET_OPTIMIZED(cvt32s8s), (BinaryFunc)GET_OPTIMIZED(cvt32f8s),
(BinaryFunc)GET_OPTIMIZED(cvt64f8s), 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvt8u16u), (BinaryFunc)GET_OPTIMIZED(cvt8s16u), (BinaryFunc)cvt16u,
(BinaryFunc)GET_OPTIMIZED(cvt16s16u), (BinaryFunc)GET_OPTIMIZED(cvt32s16u), (BinaryFunc)GET_OPTIMIZED(cvt32f16u),
(BinaryFunc)GET_OPTIMIZED(cvt64f16u), 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvt8u16s), (BinaryFunc)GET_OPTIMIZED(cvt8s16s), (BinaryFunc)GET_OPTIMIZED(cvt16u16s),
(BinaryFunc)cvt16u, (BinaryFunc)GET_OPTIMIZED(cvt32s16s), (BinaryFunc)GET_OPTIMIZED(cvt32f16s),
(BinaryFunc)GET_OPTIMIZED(cvt64f16s), 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvt8u32s), (BinaryFunc)GET_OPTIMIZED(cvt8s32s), (BinaryFunc)GET_OPTIMIZED(cvt16u32s),
(BinaryFunc)GET_OPTIMIZED(cvt16s32s), (BinaryFunc)cvt32s, (BinaryFunc)GET_OPTIMIZED(cvt32f32s),
(BinaryFunc)GET_OPTIMIZED(cvt64f32s), 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvt8u32f), (BinaryFunc)GET_OPTIMIZED(cvt8s32f), (BinaryFunc)GET_OPTIMIZED(cvt16u32f),
(BinaryFunc)GET_OPTIMIZED(cvt16s32f), (BinaryFunc)GET_OPTIMIZED(cvt32s32f), (BinaryFunc)cvt32s,
(BinaryFunc)GET_OPTIMIZED(cvt64f32f), 0
},
{
(BinaryFunc)GET_OPTIMIZED(cvt8u64f), (BinaryFunc)GET_OPTIMIZED(cvt8s64f), (BinaryFunc)GET_OPTIMIZED(cvt16u64f),
(BinaryFunc)GET_OPTIMIZED(cvt16s64f), (BinaryFunc)GET_OPTIMIZED(cvt32s64f), (BinaryFunc)GET_OPTIMIZED(cvt32f64f),
(BinaryFunc)(cvt64s), 0
},
{
0, 0, 0, 0, 0, 0, 0, 0
}
};
BinaryFunc getConvertFunc(int sdepth, int ddepth)
{
return cvtTab[CV_MAT_DEPTH(ddepth)][CV_MAT_DEPTH(sdepth)];
}
BinaryFunc getConvertScaleFunc(int sdepth, int ddepth)
{
return cvtScaleTab[CV_MAT_DEPTH(ddepth)][CV_MAT_DEPTH(sdepth)];
}
}
void cv::convertScaleAbs( InputArray _src, OutputArray _dst, double alpha, double beta )
{
Mat src = _src.getMat();
int cn = src.channels();
double scale[] = {alpha, beta};
_dst.create( src.dims, src.size, CV_8UC(cn) );
Mat dst = _dst.getMat();
BinaryFunc func = cvtScaleAbsTab[src.depth()];
CV_Assert( func != 0 );
if( src.dims <= 2 )
{
Size sz = getContinuousSize(src, dst, cn);
func( src.data, src.step, 0, 0, dst.data, dst.step, sz, scale );
}
else
{
const Mat* arrays[] = {&src, &dst, 0};
uchar* ptrs[2];
NAryMatIterator it(arrays, ptrs);
Size sz((int)it.size*cn, 1);
for( size_t i = 0; i < it.nplanes; i++, ++it )
func( ptrs[0], 0, 0, 0, ptrs[1], 0, sz, scale );
}
}
void cv::Mat::convertTo(OutputArray _dst, int _type, double alpha, double beta) const
{
bool noScale = fabs(alpha-1) < DBL_EPSILON && fabs(beta) < DBL_EPSILON;
if( _type < 0 )
_type = _dst.fixedType() ? _dst.type() : type();
else
_type = CV_MAKETYPE(CV_MAT_DEPTH(_type), channels());
int sdepth = depth(), ddepth = CV_MAT_DEPTH(_type);
if( sdepth == ddepth && noScale )
{
copyTo(_dst);
return;
}
Mat src = *this;
BinaryFunc func = noScale ? getConvertFunc(sdepth, ddepth) : getConvertScaleFunc(sdepth, ddepth);
double scale[] = {alpha, beta};
int cn = channels();
CV_Assert( func != 0 );
if( dims <= 2 )
{
_dst.create( size(), _type );
Mat dst = _dst.getMat();
Size sz = getContinuousSize(src, dst, cn);
func( src.data, src.step, 0, 0, dst.data, dst.step, sz, scale );
}
else
{
_dst.create( dims, size, _type );
Mat dst = _dst.getMat();
const Mat* arrays[] = {&src, &dst, 0};
uchar* ptrs[2];
NAryMatIterator it(arrays, ptrs);
Size sz((int)(it.size*cn), 1);
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], 0, 0, 0, ptrs[1], 0, sz, scale);
}
}
/****************************************************************************************\
* LUT Transform *
\****************************************************************************************/
namespace cv
{
template<typename T> static void
LUT8u_( const uchar* src, const T* lut, T* dst, int len, int cn, int lutcn )
{
if( lutcn == 1 )
{
for( int i = 0; i < len*cn; i++ )
dst[i] = lut[src[i]];
}
else
{
for( int i = 0; i < len*cn; i += cn )
for( int k = 0; k < cn; k++ )
dst[i+k] = lut[src[i+k]*cn+k];
}
}
static void LUT8u_8u( const uchar* src, const uchar* lut, uchar* dst, int len, int cn, int lutcn )
{
LUT8u_( src, lut, dst, len, cn, lutcn );
}
static void LUT8u_8s( const uchar* src, const schar* lut, schar* dst, int len, int cn, int lutcn )
{
LUT8u_( src, lut, dst, len, cn, lutcn );
}
static void LUT8u_16u( const uchar* src, const ushort* lut, ushort* dst, int len, int cn, int lutcn )
{
LUT8u_( src, lut, dst, len, cn, lutcn );
}
static void LUT8u_16s( const uchar* src, const short* lut, short* dst, int len, int cn, int lutcn )
{
LUT8u_( src, lut, dst, len, cn, lutcn );
}
static void LUT8u_32s( const uchar* src, const int* lut, int* dst, int len, int cn, int lutcn )
{
LUT8u_( src, lut, dst, len, cn, lutcn );
}
static void LUT8u_32f( const uchar* src, const float* lut, float* dst, int len, int cn, int lutcn )
{
LUT8u_( src, lut, dst, len, cn, lutcn );
}
static void LUT8u_64f( const uchar* src, const double* lut, double* dst, int len, int cn, int lutcn )
{
LUT8u_( src, lut, dst, len, cn, lutcn );
}
typedef void (*LUTFunc)( const uchar* src, const uchar* lut, uchar* dst, int len, int cn, int lutcn );
static LUTFunc lutTab[] =
{
(LUTFunc)LUT8u_8u, (LUTFunc)LUT8u_8s, (LUTFunc)LUT8u_16u, (LUTFunc)LUT8u_16s,
(LUTFunc)LUT8u_32s, (LUTFunc)LUT8u_32f, (LUTFunc)LUT8u_64f, 0
};
}
void cv::LUT( InputArray _src, InputArray _lut, OutputArray _dst, int interpolation )
{
Mat src = _src.getMat(), lut = _lut.getMat();
CV_Assert( interpolation == 0 );
int cn = src.channels();
int lutcn = lut.channels();
CV_Assert( (lutcn == cn || lutcn == 1) &&
lut.total() == 256 && lut.isContinuous() &&
(src.depth() == CV_8U || src.depth() == CV_8S) );
_dst.create( src.dims, src.size, CV_MAKETYPE(lut.depth(), cn));
Mat dst = _dst.getMat();
LUTFunc func = lutTab[lut.depth()];
CV_Assert( func != 0 );
const Mat* arrays[] = {&src, &dst, 0};
uchar* ptrs[2];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], lut.data, ptrs[1], len, cn, lutcn);
}
void cv::normalize( InputArray _src, OutputArray _dst, double a, double b,
int norm_type, int rtype, InputArray _mask )
{
Mat src = _src.getMat(), mask = _mask.getMat();
double scale = 1, shift = 0;
if( norm_type == CV_MINMAX )
{
double smin = 0, smax = 0;
double dmin = MIN( a, b ), dmax = MAX( a, b );
minMaxLoc( _src, &smin, &smax, 0, 0, mask );
scale = (dmax - dmin)*(smax - smin > DBL_EPSILON ? 1./(smax - smin) : 0);
shift = dmin - smin*scale;
}
else if( norm_type == CV_L2 || norm_type == CV_L1 || norm_type == CV_C )
{
scale = norm( src, norm_type, mask );
scale = scale > DBL_EPSILON ? a/scale : 0.;
shift = 0;
}
else
CV_Error( CV_StsBadArg, "Unknown/unsupported norm type" );
if( rtype < 0 )
rtype = _dst.fixedType() ? _dst.depth() : src.depth();
_dst.create(src.dims, src.size, CV_MAKETYPE(rtype, src.channels()));
Mat dst = _dst.getMat();
if( !mask.data )
src.convertTo( dst, rtype, scale, shift );
else
{
Mat temp;
src.convertTo( temp, rtype, scale, shift );
temp.copyTo( dst, mask );
}
}
CV_IMPL void
cvSplit( const void* srcarr, void* dstarr0, void* dstarr1, void* dstarr2, void* dstarr3 )
{
void* dptrs[] = { dstarr0, dstarr1, dstarr2, dstarr3 };
cv::Mat src = cv::cvarrToMat(srcarr);
int i, j, nz = 0;
for( i = 0; i < 4; i++ )
nz += dptrs[i] != 0;
CV_Assert( nz > 0 );
std::vector<cv::Mat> dvec(nz);
std::vector<int> pairs(nz*2);
for( i = j = 0; i < 4; i++ )
{
if( dptrs[i] != 0 )
{
dvec[j] = cv::cvarrToMat(dptrs[i]);
CV_Assert( dvec[j].size() == src.size() );
CV_Assert( dvec[j].depth() == src.depth() );
CV_Assert( dvec[j].channels() == 1 );
CV_Assert( i < src.channels() );
pairs[j*2] = i;
pairs[j*2+1] = j;
j++;
}
}
if( nz == src.channels() )
cv::split( src, dvec );
else
{
cv::mixChannels( &src, 1, &dvec[0], nz, &pairs[0], nz );
}
}
CV_IMPL void
cvMerge( const void* srcarr0, const void* srcarr1, const void* srcarr2,
const void* srcarr3, void* dstarr )
{
const void* sptrs[] = { srcarr0, srcarr1, srcarr2, srcarr3 };
cv::Mat dst = cv::cvarrToMat(dstarr);
int i, j, nz = 0;
for( i = 0; i < 4; i++ )
nz += sptrs[i] != 0;
CV_Assert( nz > 0 );
std::vector<cv::Mat> svec(nz);
std::vector<int> pairs(nz*2);
for( i = j = 0; i < 4; i++ )
{
if( sptrs[i] != 0 )
{
svec[j] = cv::cvarrToMat(sptrs[i]);
CV_Assert( svec[j].size == dst.size &&
svec[j].depth() == dst.depth() &&
svec[j].channels() == 1 && i < dst.channels() );
pairs[j*2] = j;
pairs[j*2+1] = i;
j++;
}
}
if( nz == dst.channels() )
cv::merge( svec, dst );
else
{
cv::mixChannels( &svec[0], nz, &dst, 1, &pairs[0], nz );
}
}
CV_IMPL void
cvMixChannels( const CvArr** src, int src_count,
CvArr** dst, int dst_count,
const int* from_to, int pair_count )
{
cv::AutoBuffer<cv::Mat> buf(src_count + dst_count);
int i;
for( i = 0; i < src_count; i++ )
buf[i] = cv::cvarrToMat(src[i]);
for( i = 0; i < dst_count; i++ )
buf[i+src_count] = cv::cvarrToMat(dst[i]);
cv::mixChannels(&buf[0], src_count, &buf[src_count], dst_count, from_to, pair_count);
}
CV_IMPL void
cvConvertScaleAbs( const void* srcarr, void* dstarr,
double scale, double shift )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( src.size == dst.size && dst.type() == CV_8UC(src.channels()));
cv::convertScaleAbs( src, dst, scale, shift );
}
CV_IMPL void
cvConvertScale( const void* srcarr, void* dstarr,
double scale, double shift )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( src.size == dst.size && src.channels() == dst.channels() );
src.convertTo(dst, dst.type(), scale, shift);
}
CV_IMPL void cvLUT( const void* srcarr, void* dstarr, const void* lutarr )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), lut = cv::cvarrToMat(lutarr);
CV_Assert( dst.size() == src.size() && dst.type() == CV_MAKETYPE(lut.depth(), src.channels()) );
cv::LUT( src, lut, dst );
}
CV_IMPL void cvNormalize( const CvArr* srcarr, CvArr* dstarr,
double a, double b, int norm_type, const CvArr* maskarr )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), mask;
if( maskarr )
mask = cv::cvarrToMat(maskarr);
CV_Assert( dst.size() == src.size() && src.channels() == dst.channels() );
cv::normalize( src, dst, a, b, norm_type, dst.type(), mask );
}
/* End of file. */
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