Open Source Computer Vision Library https://opencv.org/
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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.
//
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// 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.
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// This software is provided by the copyright holders and contributors "as is" and
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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;
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// and on any theory of liability, whether in contract, strict liability,
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//M*/
#include "precomp.hpp"
namespace cv
{
template<typename T, int shift> struct FixPtCast
{
typedef int type1;
typedef T rtype;
rtype operator ()(type1 arg) const { return (T)((arg + (1 << (shift-1))) >> shift); }
};
template<typename T, int shift> struct FltCast
{
typedef T type1;
typedef T rtype;
rtype operator ()(type1 arg) const { return arg*(T)(1./(1 << shift)); }
};
template<typename T1, typename T2> struct NoVec
{
int operator()(T1**, T2*, int, int) const { return 0; }
};
#if CV_SSE2
struct PyrDownVec_32s8u
{
int operator()(int** src, uchar* dst, int, int width) const
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
int x = 0;
const int *row0 = src[0], *row1 = src[1], *row2 = src[2], *row3 = src[3], *row4 = src[4];
__m128i delta = _mm_set1_epi16(128);
for( ; x <= width - 16; x += 16 )
{
__m128i r0, r1, r2, r3, r4, t0, t1;
r0 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row0 + x)),
_mm_load_si128((const __m128i*)(row0 + x + 4)));
r1 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row1 + x)),
_mm_load_si128((const __m128i*)(row1 + x + 4)));
r2 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row2 + x)),
_mm_load_si128((const __m128i*)(row2 + x + 4)));
r3 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row3 + x)),
_mm_load_si128((const __m128i*)(row3 + x + 4)));
r4 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row4 + x)),
_mm_load_si128((const __m128i*)(row4 + x + 4)));
r0 = _mm_add_epi16(r0, r4);
r1 = _mm_add_epi16(_mm_add_epi16(r1, r3), r2);
r0 = _mm_add_epi16(r0, _mm_add_epi16(r2, r2));
t0 = _mm_add_epi16(r0, _mm_slli_epi16(r1, 2));
r0 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row0 + x + 8)),
_mm_load_si128((const __m128i*)(row0 + x + 12)));
r1 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row1 + x + 8)),
_mm_load_si128((const __m128i*)(row1 + x + 12)));
r2 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row2 + x + 8)),
_mm_load_si128((const __m128i*)(row2 + x + 12)));
r3 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row3 + x + 8)),
_mm_load_si128((const __m128i*)(row3 + x + 12)));
r4 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row4 + x + 8)),
_mm_load_si128((const __m128i*)(row4 + x + 12)));
r0 = _mm_add_epi16(r0, r4);
r1 = _mm_add_epi16(_mm_add_epi16(r1, r3), r2);
r0 = _mm_add_epi16(r0, _mm_add_epi16(r2, r2));
t1 = _mm_add_epi16(r0, _mm_slli_epi16(r1, 2));
t0 = _mm_srli_epi16(_mm_add_epi16(t0, delta), 8);
t1 = _mm_srli_epi16(_mm_add_epi16(t1, delta), 8);
_mm_storeu_si128((__m128i*)(dst + x), _mm_packus_epi16(t0, t1));
}
for( ; x <= width - 4; x += 4 )
{
__m128i r0, r1, r2, r3, r4, z = _mm_setzero_si128();
r0 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row0 + x)), z);
r1 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row1 + x)), z);
r2 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row2 + x)), z);
r3 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row3 + x)), z);
r4 = _mm_packs_epi32(_mm_load_si128((const __m128i*)(row4 + x)), z);
r0 = _mm_add_epi16(r0, r4);
r1 = _mm_add_epi16(_mm_add_epi16(r1, r3), r2);
r0 = _mm_add_epi16(r0, _mm_add_epi16(r2, r2));
r0 = _mm_add_epi16(r0, _mm_slli_epi16(r1, 2));
r0 = _mm_srli_epi16(_mm_add_epi16(r0, delta), 8);
*(int*)(dst + x) = _mm_cvtsi128_si32(_mm_packus_epi16(r0, r0));
}
return x;
}
};
struct PyrDownVec_32f
{
int operator()(float** src, float* dst, int, int width) const
{
if( !checkHardwareSupport(CV_CPU_SSE) )
return 0;
int x = 0;
const float *row0 = src[0], *row1 = src[1], *row2 = src[2], *row3 = src[3], *row4 = src[4];
__m128 _4 = _mm_set1_ps(4.f), _scale = _mm_set1_ps(1.f/256);
for( ; x <= width - 8; x += 8 )
{
__m128 r0, r1, r2, r3, r4, t0, t1;
r0 = _mm_load_ps(row0 + x);
r1 = _mm_load_ps(row1 + x);
r2 = _mm_load_ps(row2 + x);
r3 = _mm_load_ps(row3 + x);
r4 = _mm_load_ps(row4 + x);
r0 = _mm_add_ps(r0, r4);
r1 = _mm_add_ps(_mm_add_ps(r1, r3), r2);
r0 = _mm_add_ps(r0, _mm_add_ps(r2, r2));
t0 = _mm_add_ps(r0, _mm_mul_ps(r1, _4));
r0 = _mm_load_ps(row0 + x + 4);
r1 = _mm_load_ps(row1 + x + 4);
r2 = _mm_load_ps(row2 + x + 4);
r3 = _mm_load_ps(row3 + x + 4);
r4 = _mm_load_ps(row4 + x + 4);
r0 = _mm_add_ps(r0, r4);
r1 = _mm_add_ps(_mm_add_ps(r1, r3), r2);
r0 = _mm_add_ps(r0, _mm_add_ps(r2, r2));
t1 = _mm_add_ps(r0, _mm_mul_ps(r1, _4));
t0 = _mm_mul_ps(t0, _scale);
t1 = _mm_mul_ps(t1, _scale);
_mm_storeu_ps(dst + x, t0);
_mm_storeu_ps(dst + x + 4, t1);
}
return x;
}
};
#else
typedef NoVec<int, uchar> PyrDownVec_32s8u;
typedef NoVec<float, float> PyrDownVec_32f;
#endif
template<class CastOp, class VecOp> void
pyrDown_( const Mat& _src, Mat& _dst )
{
const int PD_SZ = 5;
typedef typename CastOp::type1 WT;
typedef typename CastOp::rtype T;
Size ssize = _src.size(), dsize = _dst.size();
int cn = _src.channels();
int bufstep = (int)alignSize(dsize.width*cn, 16);
AutoBuffer<WT> _buf(bufstep*PD_SZ + 16);
WT* buf = alignPtr((WT*)_buf, 16);
int tabL[CV_CN_MAX*(PD_SZ+2)], tabR[CV_CN_MAX*(PD_SZ+2)];
AutoBuffer<int> _tabM(dsize.width*cn);
int* tabM = _tabM;
WT* rows[PD_SZ];
CastOp castOp;
VecOp vecOp;
CV_Assert( std::abs(dsize.width*2 - ssize.width) <= 2 &&
std::abs(dsize.height*2 - ssize.height) <= 2 );
int k, x, sy0 = -PD_SZ/2, sy = sy0, width0 = std::min((ssize.width-PD_SZ/2-1)/2 + 1, dsize.width);
for( x = 0; x <= PD_SZ+1; x++ )
{
int sx0 = borderInterpolate(x - PD_SZ/2, ssize.width, BORDER_REFLECT_101)*cn;
int sx1 = borderInterpolate(x + width0*2 - PD_SZ/2, ssize.width, BORDER_REFLECT_101)*cn;
for( k = 0; k < cn; k++ )
{
tabL[x*cn + k] = sx0 + k;
tabR[x*cn + k] = sx1 + k;
}
}
ssize.width *= cn;
dsize.width *= cn;
width0 *= cn;
for( x = 0; x < dsize.width; x++ )
tabM[x] = (x/cn)*2*cn + x % cn;
for( int y = 0; y < dsize.height; y++ )
{
T* dst = (T*)(_dst.data + _dst.step*y);
WT *row0, *row1, *row2, *row3, *row4;
// fill the ring buffer (horizontal convolution and decimation)
for( ; sy <= y*2 + 2; sy++ )
{
WT* row = buf + ((sy - sy0) % PD_SZ)*bufstep;
int _sy = borderInterpolate(sy, ssize.height, BORDER_REFLECT_101);
const T* src = (const T*)(_src.data + _src.step*_sy);
int limit = cn;
const int* tab = tabL;
for( x = 0;;)
{
for( ; x < limit; x++ )
{
row[x] = src[tab[x+cn*2]]*6 + (src[tab[x+cn]] + src[tab[x+cn*3]])*4 +
src[tab[x]] + src[tab[x+cn*4]];
}
if( x == dsize.width )
break;
if( cn == 1 )
{
for( ; x < width0; x++ )
row[x] = src[x*2]*6 + (src[x*2 - 1] + src[x*2 + 1])*4 +
src[x*2 - 2] + src[x*2 + 2];
}
else if( cn == 3 )
{
for( ; x < width0; x += 3 )
{
const T* s = src + x*2;
WT t0 = s[0]*6 + (s[-3] + s[3])*4 + s[-6] + s[6];
WT t1 = s[1]*6 + (s[-2] + s[4])*4 + s[-5] + s[7];
WT t2 = s[2]*6 + (s[-1] + s[5])*4 + s[-4] + s[8];
row[x] = t0; row[x+1] = t1; row[x+2] = t2;
}
}
else if( cn == 4 )
{
for( ; x < width0; x += 4 )
{
const T* s = src + x*2;
WT t0 = s[0]*6 + (s[-4] + s[4])*4 + s[-8] + s[8];
WT t1 = s[1]*6 + (s[-3] + s[5])*4 + s[-7] + s[9];
row[x] = t0; row[x+1] = t1;
t0 = s[2]*6 + (s[-2] + s[6])*4 + s[-6] + s[10];
t1 = s[3]*6 + (s[-1] + s[7])*4 + s[-5] + s[11];
row[x+2] = t0; row[x+3] = t1;
}
}
else
{
for( ; x < width0; x++ )
{
int sx = tabM[x];
row[x] = src[sx]*6 + (src[sx - cn] + src[sx + cn])*4 +
src[sx - cn*2] + src[sx + cn*2];
}
}
limit = dsize.width;
tab = tabR - x;
}
}
// do vertical convolution and decimation and write the result to the destination image
for( k = 0; k < PD_SZ; k++ )
rows[k] = buf + ((y*2 - PD_SZ/2 + k - sy0) % PD_SZ)*bufstep;
row0 = rows[0]; row1 = rows[1]; row2 = rows[2]; row3 = rows[3]; row4 = rows[4];
x = vecOp(rows, dst, (int)_dst.step, dsize.width);
for( ; x < dsize.width; x++ )
dst[x] = castOp(row2[x]*6 + (row1[x] + row3[x])*4 + row0[x] + row4[x]);
}
}
template<class CastOp, class VecOp> void
pyrUp_( const Mat& _src, Mat& _dst )
{
const int PU_SZ = 3;
typedef typename CastOp::type1 WT;
typedef typename CastOp::rtype T;
Size ssize = _src.size(), dsize = _dst.size();
int cn = _src.channels();
int bufstep = (int)alignSize((dsize.width+1)*cn, 16);
AutoBuffer<WT> _buf(bufstep*PU_SZ + 16);
WT* buf = alignPtr((WT*)_buf, 16);
AutoBuffer<int> _dtab(ssize.width*cn);
int* dtab = _dtab;
WT* rows[PU_SZ];
CastOp castOp;
VecOp vecOp;
CV_Assert( std::abs(dsize.width - ssize.width*2) == dsize.width % 2 &&
std::abs(dsize.height - ssize.height*2) == dsize.height % 2);
int k, x, sy0 = -PU_SZ/2, sy = sy0, width0 = ssize.width - 1;
ssize.width *= cn;
dsize.width *= cn;
width0 *= cn;
for( x = 0; x < ssize.width; x++ )
dtab[x] = (x/cn)*2*cn + x % cn;
for( int y = 0; y < ssize.height; y++ )
{
T* dst0 = (T*)(_dst.data + _dst.step*y*2);
T* dst1 = (T*)(_dst.data + _dst.step*(y*2+1));
WT *row0, *row1, *row2;
if( y*2+1 >= dsize.height )
dst1 = dst0;
// fill the ring buffer (horizontal convolution and decimation)
for( ; sy <= y + 1; sy++ )
{
WT* row = buf + ((sy - sy0) % PU_SZ)*bufstep;
int _sy = borderInterpolate(sy*2, dsize.height, BORDER_REFLECT_101)/2;
const T* src = (const T*)(_src.data + _src.step*_sy);
if( ssize.width == cn )
{
for( x = 0; x < cn; x++ )
row[x] = row[x + cn] = src[x]*8;
continue;
}
for( x = 0; x < cn; x++ )
{
int dx = dtab[x];
WT t0 = src[x]*6 + src[x + cn]*2;
WT t1 = (src[x] + src[x + cn])*4;
row[dx] = t0; row[dx + cn] = t1;
dx = dtab[ssize.width - cn + x];
int sx = ssize.width - cn + x;
t0 = src[sx - cn] + src[sx]*7;
t1 = src[sx]*8;
row[dx] = t0; row[dx + cn] = t1;
}
for( x = cn; x < ssize.width - cn; x++ )
{
int dx = dtab[x];
WT t0 = src[x-cn] + src[x]*6 + src[x+cn];
WT t1 = (src[x] + src[x+cn])*4;
row[dx] = t0;
row[dx+cn] = t1;
}
}
// do vertical convolution and decimation and write the result to the destination image
for( k = 0; k < PU_SZ; k++ )
rows[k] = buf + ((y - PU_SZ/2 + k - sy0) % PU_SZ)*bufstep;
row0 = rows[0]; row1 = rows[1]; row2 = rows[2];
x = vecOp(rows, dst0, (int)_dst.step, dsize.width);
for( ; x < dsize.width; x++ )
{
T t1 = castOp((row1[x] + row2[x])*4);
T t0 = castOp(row0[x] + row1[x]*6 + row2[x]);
dst1[x] = t1; dst0[x] = t0;
}
}
}
typedef void (*PyrFunc)(const Mat&, Mat&);
}
void cv::pyrDown( InputArray _src, OutputArray _dst, const Size& _dsz )
{
Mat src = _src.getMat();
Size dsz = _dsz == Size() ? Size((src.cols + 1)/2, (src.rows + 1)/2) : _dsz;
_dst.create( dsz, src.type() );
Mat dst = _dst.getMat();
#ifdef HAVE_TEGRA_OPTIMIZATION
if(tegra::pyrDown(src, dst))
return;
#endif
int depth = src.depth();
PyrFunc func = 0;
if( depth == CV_8U )
func = pyrDown_<FixPtCast<uchar, 8>, PyrDownVec_32s8u>;
else if( depth == CV_16S )
func = pyrDown_<FixPtCast<short, 8>, NoVec<int, short> >;
else if( depth == CV_16U )
func = pyrDown_<FixPtCast<ushort, 8>, NoVec<int, ushort> >;
else if( depth == CV_32F )
func = pyrDown_<FltCast<float, 8>, PyrDownVec_32f>;
else if( depth == CV_64F )
func = pyrDown_<FltCast<double, 8>, NoVec<double, double> >;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src, dst );
}
void cv::pyrUp( InputArray _src, OutputArray _dst, const Size& _dsz )
{
Mat src = _src.getMat();
Size dsz = _dsz == Size() ? Size(src.cols*2, src.rows*2) : _dsz;
_dst.create( dsz, src.type() );
Mat dst = _dst.getMat();
#ifdef HAVE_TEGRA_OPTIMIZATION
if(tegra::pyrUp(src, dst))
return;
#endif
int depth = src.depth();
PyrFunc func = 0;
if( depth == CV_8U )
func = pyrUp_<FixPtCast<uchar, 6>, NoVec<int, uchar> >;
else if( depth == CV_16S )
func = pyrUp_<FixPtCast<short, 6>, NoVec<int, short> >;
else if( depth == CV_16U )
func = pyrUp_<FixPtCast<ushort, 6>, NoVec<int, ushort> >;
else if( depth == CV_32F )
func = pyrUp_<FltCast<float, 6>, NoVec<float, float> >;
else if( depth == CV_64F )
func = pyrUp_<FltCast<double, 6>, NoVec<double, double> >;
else
CV_Error( CV_StsUnsupportedFormat, "" );
func( src, dst );
}
void cv::buildPyramid( InputArray _src, OutputArrayOfArrays _dst, int maxlevel )
{
Mat src = _src.getMat();
_dst.create( maxlevel + 1, 1, 0 );
_dst.getMatRef(0) = src;
for( int i = 1; i <= maxlevel; i++ )
pyrDown( _dst.getMatRef(i-1), _dst.getMatRef(i) );
}
CV_IMPL void cvPyrDown( const void* srcarr, void* dstarr, int _filter )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( _filter == CV_GAUSSIAN_5x5 && src.type() == dst.type());
cv::pyrDown( src, dst, dst.size() );
}
CV_IMPL void cvPyrUp( const void* srcarr, void* dstarr, int _filter )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( _filter == CV_GAUSSIAN_5x5 && src.type() == dst.type());
cv::pyrUp( src, dst, dst.size() );
}
CV_IMPL void
cvReleasePyramid( CvMat*** _pyramid, int extra_layers )
{
if( !_pyramid )
CV_Error( CV_StsNullPtr, "" );
if( *_pyramid )
for( int i = 0; i <= extra_layers; i++ )
cvReleaseMat( &(*_pyramid)[i] );
cvFree( _pyramid );
}
CV_IMPL CvMat**
cvCreatePyramid( const CvArr* srcarr, int extra_layers, double rate,
const CvSize* layer_sizes, CvArr* bufarr,
int calc, int filter )
{
const float eps = 0.1f;
uchar* ptr = 0;
CvMat stub, *src = cvGetMat( srcarr, &stub );
if( extra_layers < 0 )
CV_Error( CV_StsOutOfRange, "The number of extra layers must be non negative" );
int i, layer_step, elem_size = CV_ELEM_SIZE(src->type);
CvSize layer_size, size = cvGetMatSize(src);
if( bufarr )
{
CvMat bstub, *buf;
int bufsize = 0;
buf = cvGetMat( bufarr, &bstub );
bufsize = buf->rows*buf->cols*CV_ELEM_SIZE(buf->type);
layer_size = size;
for( i = 1; i <= extra_layers; i++ )
{
if( !layer_sizes )
{
layer_size.width = cvRound(layer_size.width*rate+eps);
layer_size.height = cvRound(layer_size.height*rate+eps);
}
else
layer_size = layer_sizes[i-1];
layer_step = layer_size.width*elem_size;
bufsize -= layer_step*layer_size.height;
}
if( bufsize < 0 )
CV_Error( CV_StsOutOfRange, "The buffer is too small to fit the pyramid" );
ptr = buf->data.ptr;
}
CvMat** pyramid = (CvMat**)cvAlloc( (extra_layers+1)*sizeof(pyramid[0]) );
memset( pyramid, 0, (extra_layers+1)*sizeof(pyramid[0]) );
pyramid[0] = cvCreateMatHeader( size.height, size.width, src->type );
cvSetData( pyramid[0], src->data.ptr, src->step );
layer_size = size;
for( i = 1; i <= extra_layers; i++ )
{
if( !layer_sizes )
{
layer_size.width = cvRound(layer_size.width*rate + eps);
layer_size.height = cvRound(layer_size.height*rate + eps);
}
else
layer_size = layer_sizes[i];
if( bufarr )
{
pyramid[i] = cvCreateMatHeader( layer_size.height, layer_size.width, src->type );
layer_step = layer_size.width*elem_size;
cvSetData( pyramid[i], ptr, layer_step );
ptr += layer_step*layer_size.height;
}
else
pyramid[i] = cvCreateMat( layer_size.height, layer_size.width, src->type );
if( calc )
cvPyrDown( pyramid[i-1], pyramid[i], filter );
//cvResize( pyramid[i-1], pyramid[i], CV_INTER_LINEAR );
}
return pyramid;
}
/* End of file. */