opencv/modules/imgproc/src/imgwarp.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
// 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*/
/* ////////////////////////////////////////////////////////////////////
//
// Geometrical transforms on images and matrices: rotation, zoom etc.
//
// */
#include "precomp.hpp"
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#include "opencl_kernels_imgproc.hpp"
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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
static IppStatus sts = ippInit();
#endif
namespace cv
{
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#if IPP_VERSION_X100 >= 701
typedef IppStatus (CV_STDCALL* ippiResizeFunc)(const void*, int, const void*, int, IppiPoint, IppiSize, IppiBorderType, void*, void*, Ipp8u*);
typedef IppStatus (CV_STDCALL* ippiResizeGetBufferSize)(void*, IppiSize, Ipp32u, int*);
typedef IppStatus (CV_STDCALL* ippiResizeGetSrcOffset)(void*, IppiPoint, IppiPoint*);
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#endif
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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7) && 0
typedef IppStatus (CV_STDCALL* ippiSetFunc)(const void*, void *, int, IppiSize);
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typedef IppStatus (CV_STDCALL* ippiWarpPerspectiveFunc)(const void*, IppiSize, int, IppiRect, void *, int, IppiRect, double [3][3], int);
typedef IppStatus (CV_STDCALL* ippiWarpAffineBackFunc)(const void*, IppiSize, int, IppiRect, void *, int, IppiRect, double [2][3], int);
template <int channels, typename Type>
bool IPPSetSimple(cv::Scalar value, void *dataPointer, int step, IppiSize &size, ippiSetFunc func)
{
Type values[channels];
for( int i = 0; i < channels; i++ )
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values[i] = saturate_cast<Type>(value[i]);
return func(values, dataPointer, step, size) >= 0;
}
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static bool IPPSet(const cv::Scalar &value, void *dataPointer, int step, IppiSize &size, int channels, int depth)
{
if( channels == 1 )
{
switch( depth )
{
case CV_8U:
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return ippiSet_8u_C1R(saturate_cast<Ipp8u>(value[0]), (Ipp8u *)dataPointer, step, size) >= 0;
case CV_16U:
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return ippiSet_16u_C1R(saturate_cast<Ipp16u>(value[0]), (Ipp16u *)dataPointer, step, size) >= 0;
case CV_32F:
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return ippiSet_32f_C1R(saturate_cast<Ipp32f>(value[0]), (Ipp32f *)dataPointer, step, size) >= 0;
}
}
else
{
if( channels == 3 )
{
switch( depth )
{
case CV_8U:
return IPPSetSimple<3, Ipp8u>(value, dataPointer, step, size, (ippiSetFunc)ippiSet_8u_C3R);
case CV_16U:
return IPPSetSimple<3, Ipp16u>(value, dataPointer, step, size, (ippiSetFunc)ippiSet_16u_C3R);
case CV_32F:
return IPPSetSimple<3, Ipp32f>(value, dataPointer, step, size, (ippiSetFunc)ippiSet_32f_C3R);
}
}
else if( channels == 4 )
{
switch( depth )
{
case CV_8U:
return IPPSetSimple<4, Ipp8u>(value, dataPointer, step, size, (ippiSetFunc)ippiSet_8u_C4R);
case CV_16U:
return IPPSetSimple<4, Ipp16u>(value, dataPointer, step, size, (ippiSetFunc)ippiSet_16u_C4R);
case CV_32F:
return IPPSetSimple<4, Ipp32f>(value, dataPointer, step, size, (ippiSetFunc)ippiSet_32f_C4R);
}
}
}
return false;
}
#endif
/************** interpolation formulas and tables ***************/
const int INTER_RESIZE_COEF_BITS=11;
const int INTER_RESIZE_COEF_SCALE=1 << INTER_RESIZE_COEF_BITS;
const int INTER_REMAP_COEF_BITS=15;
const int INTER_REMAP_COEF_SCALE=1 << INTER_REMAP_COEF_BITS;
static uchar NNDeltaTab_i[INTER_TAB_SIZE2][2];
static float BilinearTab_f[INTER_TAB_SIZE2][2][2];
static short BilinearTab_i[INTER_TAB_SIZE2][2][2];
#if CV_SSE2
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static short BilinearTab_iC4_buf[INTER_TAB_SIZE2+2][2][8];
static short (*BilinearTab_iC4)[2][8] = (short (*)[2][8])alignPtr(BilinearTab_iC4_buf, 16);
#endif
static float BicubicTab_f[INTER_TAB_SIZE2][4][4];
static short BicubicTab_i[INTER_TAB_SIZE2][4][4];
static float Lanczos4Tab_f[INTER_TAB_SIZE2][8][8];
static short Lanczos4Tab_i[INTER_TAB_SIZE2][8][8];
static inline void interpolateLinear( float x, float* coeffs )
{
coeffs[0] = 1.f - x;
coeffs[1] = x;
}
static inline void interpolateCubic( float x, float* coeffs )
{
const float A = -0.75f;
coeffs[0] = ((A*(x + 1) - 5*A)*(x + 1) + 8*A)*(x + 1) - 4*A;
coeffs[1] = ((A + 2)*x - (A + 3))*x*x + 1;
coeffs[2] = ((A + 2)*(1 - x) - (A + 3))*(1 - x)*(1 - x) + 1;
coeffs[3] = 1.f - coeffs[0] - coeffs[1] - coeffs[2];
}
static inline void interpolateLanczos4( float x, float* coeffs )
{
static const double s45 = 0.70710678118654752440084436210485;
static const double cs[][2]=
{{1, 0}, {-s45, -s45}, {0, 1}, {s45, -s45}, {-1, 0}, {s45, s45}, {0, -1}, {-s45, s45}};
if( x < FLT_EPSILON )
{
for( int i = 0; i < 8; i++ )
coeffs[i] = 0;
coeffs[3] = 1;
return;
}
float sum = 0;
double y0=-(x+3)*CV_PI*0.25, s0 = sin(y0), c0=cos(y0);
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for(int i = 0; i < 8; i++ )
{
double y = -(x+3-i)*CV_PI*0.25;
coeffs[i] = (float)((cs[i][0]*s0 + cs[i][1]*c0)/(y*y));
sum += coeffs[i];
}
sum = 1.f/sum;
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for(int i = 0; i < 8; i++ )
coeffs[i] *= sum;
}
static void initInterTab1D(int method, float* tab, int tabsz)
{
float scale = 1.f/tabsz;
if( method == INTER_LINEAR )
{
for( int i = 0; i < tabsz; i++, tab += 2 )
interpolateLinear( i*scale, tab );
}
else if( method == INTER_CUBIC )
{
for( int i = 0; i < tabsz; i++, tab += 4 )
interpolateCubic( i*scale, tab );
}
else if( method == INTER_LANCZOS4 )
{
for( int i = 0; i < tabsz; i++, tab += 8 )
interpolateLanczos4( i*scale, tab );
}
else
CV_Error( CV_StsBadArg, "Unknown interpolation method" );
}
static const void* initInterTab2D( int method, bool fixpt )
{
static bool inittab[INTER_MAX+1] = {false};
float* tab = 0;
short* itab = 0;
int ksize = 0;
if( method == INTER_LINEAR )
tab = BilinearTab_f[0][0], itab = BilinearTab_i[0][0], ksize=2;
else if( method == INTER_CUBIC )
tab = BicubicTab_f[0][0], itab = BicubicTab_i[0][0], ksize=4;
else if( method == INTER_LANCZOS4 )
tab = Lanczos4Tab_f[0][0], itab = Lanczos4Tab_i[0][0], ksize=8;
else
CV_Error( CV_StsBadArg, "Unknown/unsupported interpolation type" );
if( !inittab[method] )
{
AutoBuffer<float> _tab(8*INTER_TAB_SIZE);
int i, j, k1, k2;
initInterTab1D(method, _tab, INTER_TAB_SIZE);
for( i = 0; i < INTER_TAB_SIZE; i++ )
for( j = 0; j < INTER_TAB_SIZE; j++, tab += ksize*ksize, itab += ksize*ksize )
{
int isum = 0;
NNDeltaTab_i[i*INTER_TAB_SIZE+j][0] = j < INTER_TAB_SIZE/2;
NNDeltaTab_i[i*INTER_TAB_SIZE+j][1] = i < INTER_TAB_SIZE/2;
for( k1 = 0; k1 < ksize; k1++ )
{
float vy = _tab[i*ksize + k1];
for( k2 = 0; k2 < ksize; k2++ )
{
float v = vy*_tab[j*ksize + k2];
tab[k1*ksize + k2] = v;
isum += itab[k1*ksize + k2] = saturate_cast<short>(v*INTER_REMAP_COEF_SCALE);
}
}
if( isum != INTER_REMAP_COEF_SCALE )
{
int diff = isum - INTER_REMAP_COEF_SCALE;
int ksize2 = ksize/2, Mk1=ksize2, Mk2=ksize2, mk1=ksize2, mk2=ksize2;
for( k1 = ksize2; k1 < ksize2+2; k1++ )
for( k2 = ksize2; k2 < ksize2+2; k2++ )
{
if( itab[k1*ksize+k2] < itab[mk1*ksize+mk2] )
mk1 = k1, mk2 = k2;
else if( itab[k1*ksize+k2] > itab[Mk1*ksize+Mk2] )
Mk1 = k1, Mk2 = k2;
}
if( diff < 0 )
itab[Mk1*ksize + Mk2] = (short)(itab[Mk1*ksize + Mk2] - diff);
else
itab[mk1*ksize + mk2] = (short)(itab[mk1*ksize + mk2] - diff);
}
}
tab -= INTER_TAB_SIZE2*ksize*ksize;
itab -= INTER_TAB_SIZE2*ksize*ksize;
#if CV_SSE2
if( method == INTER_LINEAR )
{
for( i = 0; i < INTER_TAB_SIZE2; i++ )
for( j = 0; j < 4; j++ )
{
BilinearTab_iC4[i][0][j*2] = BilinearTab_i[i][0][0];
BilinearTab_iC4[i][0][j*2+1] = BilinearTab_i[i][0][1];
BilinearTab_iC4[i][1][j*2] = BilinearTab_i[i][1][0];
BilinearTab_iC4[i][1][j*2+1] = BilinearTab_i[i][1][1];
}
}
#endif
inittab[method] = true;
}
return fixpt ? (const void*)itab : (const void*)tab;
}
#ifndef __MINGW32__
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static bool initAllInterTab2D()
{
return initInterTab2D( INTER_LINEAR, false ) &&
initInterTab2D( INTER_LINEAR, true ) &&
initInterTab2D( INTER_CUBIC, false ) &&
initInterTab2D( INTER_CUBIC, true ) &&
initInterTab2D( INTER_LANCZOS4, false ) &&
initInterTab2D( INTER_LANCZOS4, true );
}
static volatile bool doInitAllInterTab2D = initAllInterTab2D();
#endif
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template<typename ST, typename DT> struct Cast
{
typedef ST type1;
typedef DT rtype;
DT operator()(ST val) const { return saturate_cast<DT>(val); }
};
template<typename ST, typename DT, int bits> struct FixedPtCast
{
typedef ST type1;
typedef DT rtype;
enum { SHIFT = bits, DELTA = 1 << (bits-1) };
DT operator()(ST val) const { return saturate_cast<DT>((val + DELTA)>>SHIFT); }
};
/****************************************************************************************\
* Resize *
\****************************************************************************************/
class resizeNNInvoker :
public ParallelLoopBody
{
public:
resizeNNInvoker(const Mat& _src, Mat &_dst, int *_x_ofs, int _pix_size4, double _ify) :
ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs), pix_size4(_pix_size4),
ify(_ify)
{
}
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virtual void operator() (const Range& range) const
{
Size ssize = src.size(), dsize = dst.size();
int y, x, pix_size = (int)src.elemSize();
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for( y = range.start; y < range.end; y++ )
{
uchar* D = dst.data + dst.step*y;
int sy = std::min(cvFloor(y*ify), ssize.height-1);
const uchar* S = src.data + src.step*sy;
switch( pix_size )
{
case 1:
for( x = 0; x <= dsize.width - 2; x += 2 )
{
uchar t0 = S[x_ofs[x]];
uchar t1 = S[x_ofs[x+1]];
D[x] = t0;
D[x+1] = t1;
}
for( ; x < dsize.width; x++ )
D[x] = S[x_ofs[x]];
break;
case 2:
for( x = 0; x < dsize.width; x++ )
*(ushort*)(D + x*2) = *(ushort*)(S + x_ofs[x]);
break;
case 3:
for( x = 0; x < dsize.width; x++, D += 3 )
{
const uchar* _tS = S + x_ofs[x];
D[0] = _tS[0]; D[1] = _tS[1]; D[2] = _tS[2];
}
break;
case 4:
for( x = 0; x < dsize.width; x++ )
*(int*)(D + x*4) = *(int*)(S + x_ofs[x]);
break;
case 6:
for( x = 0; x < dsize.width; x++, D += 6 )
{
const ushort* _tS = (const ushort*)(S + x_ofs[x]);
ushort* _tD = (ushort*)D;
_tD[0] = _tS[0]; _tD[1] = _tS[1]; _tD[2] = _tS[2];
}
break;
case 8:
for( x = 0; x < dsize.width; x++, D += 8 )
{
const int* _tS = (const int*)(S + x_ofs[x]);
int* _tD = (int*)D;
_tD[0] = _tS[0]; _tD[1] = _tS[1];
}
break;
case 12:
for( x = 0; x < dsize.width; x++, D += 12 )
{
const int* _tS = (const int*)(S + x_ofs[x]);
int* _tD = (int*)D;
_tD[0] = _tS[0]; _tD[1] = _tS[1]; _tD[2] = _tS[2];
}
break;
default:
for( x = 0; x < dsize.width; x++, D += pix_size )
{
const int* _tS = (const int*)(S + x_ofs[x]);
int* _tD = (int*)D;
for( int k = 0; k < pix_size4; k++ )
_tD[k] = _tS[k];
}
}
}
}
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private:
const Mat src;
Mat dst;
int* x_ofs, pix_size4;
double ify;
resizeNNInvoker(const resizeNNInvoker&);
resizeNNInvoker& operator=(const resizeNNInvoker&);
};
static void
resizeNN( const Mat& src, Mat& dst, double fx, double fy )
{
Size ssize = src.size(), dsize = dst.size();
AutoBuffer<int> _x_ofs(dsize.width);
int* x_ofs = _x_ofs;
int pix_size = (int)src.elemSize();
int pix_size4 = (int)(pix_size / sizeof(int));
double ifx = 1./fx, ify = 1./fy;
int x;
for( x = 0; x < dsize.width; x++ )
{
int sx = cvFloor(x*ifx);
x_ofs[x] = std::min(sx, ssize.width-1)*pix_size;
}
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Range range(0, dsize.height);
resizeNNInvoker invoker(src, dst, x_ofs, pix_size4, ify);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
}
struct VResizeNoVec
{
int operator()(const uchar**, uchar*, const uchar*, int ) const { return 0; }
};
struct HResizeNoVec
{
int operator()(const uchar**, uchar**, int, const int*,
const uchar*, int, int, int, int, int) const { return 0; }
};
#if CV_SSE2
struct VResizeLinearVec_32s8u
{
int operator()(const uchar** _src, uchar* dst, const uchar* _beta, int width ) const
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
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const int** src = (const int**)_src;
const short* beta = (const short*)_beta;
const int *S0 = src[0], *S1 = src[1];
int x = 0;
__m128i b0 = _mm_set1_epi16(beta[0]), b1 = _mm_set1_epi16(beta[1]);
__m128i delta = _mm_set1_epi16(2);
if( (((size_t)S0|(size_t)S1)&15) == 0 )
for( ; x <= width - 16; x += 16 )
{
__m128i x0, x1, x2, y0, y1, y2;
x0 = _mm_load_si128((const __m128i*)(S0 + x));
x1 = _mm_load_si128((const __m128i*)(S0 + x + 4));
y0 = _mm_load_si128((const __m128i*)(S1 + x));
y1 = _mm_load_si128((const __m128i*)(S1 + x + 4));
x0 = _mm_packs_epi32(_mm_srai_epi32(x0, 4), _mm_srai_epi32(x1, 4));
y0 = _mm_packs_epi32(_mm_srai_epi32(y0, 4), _mm_srai_epi32(y1, 4));
x1 = _mm_load_si128((const __m128i*)(S0 + x + 8));
x2 = _mm_load_si128((const __m128i*)(S0 + x + 12));
y1 = _mm_load_si128((const __m128i*)(S1 + x + 8));
y2 = _mm_load_si128((const __m128i*)(S1 + x + 12));
x1 = _mm_packs_epi32(_mm_srai_epi32(x1, 4), _mm_srai_epi32(x2, 4));
y1 = _mm_packs_epi32(_mm_srai_epi32(y1, 4), _mm_srai_epi32(y2, 4));
x0 = _mm_adds_epi16(_mm_mulhi_epi16( x0, b0 ), _mm_mulhi_epi16( y0, b1 ));
x1 = _mm_adds_epi16(_mm_mulhi_epi16( x1, b0 ), _mm_mulhi_epi16( y1, b1 ));
x0 = _mm_srai_epi16(_mm_adds_epi16(x0, delta), 2);
x1 = _mm_srai_epi16(_mm_adds_epi16(x1, delta), 2);
_mm_storeu_si128( (__m128i*)(dst + x), _mm_packus_epi16(x0, x1));
}
else
for( ; x <= width - 16; x += 16 )
{
__m128i x0, x1, x2, y0, y1, y2;
x0 = _mm_loadu_si128((const __m128i*)(S0 + x));
x1 = _mm_loadu_si128((const __m128i*)(S0 + x + 4));
y0 = _mm_loadu_si128((const __m128i*)(S1 + x));
y1 = _mm_loadu_si128((const __m128i*)(S1 + x + 4));
x0 = _mm_packs_epi32(_mm_srai_epi32(x0, 4), _mm_srai_epi32(x1, 4));
y0 = _mm_packs_epi32(_mm_srai_epi32(y0, 4), _mm_srai_epi32(y1, 4));
x1 = _mm_loadu_si128((const __m128i*)(S0 + x + 8));
x2 = _mm_loadu_si128((const __m128i*)(S0 + x + 12));
y1 = _mm_loadu_si128((const __m128i*)(S1 + x + 8));
y2 = _mm_loadu_si128((const __m128i*)(S1 + x + 12));
x1 = _mm_packs_epi32(_mm_srai_epi32(x1, 4), _mm_srai_epi32(x2, 4));
y1 = _mm_packs_epi32(_mm_srai_epi32(y1, 4), _mm_srai_epi32(y2, 4));
x0 = _mm_adds_epi16(_mm_mulhi_epi16( x0, b0 ), _mm_mulhi_epi16( y0, b1 ));
x1 = _mm_adds_epi16(_mm_mulhi_epi16( x1, b0 ), _mm_mulhi_epi16( y1, b1 ));
x0 = _mm_srai_epi16(_mm_adds_epi16(x0, delta), 2);
x1 = _mm_srai_epi16(_mm_adds_epi16(x1, delta), 2);
_mm_storeu_si128( (__m128i*)(dst + x), _mm_packus_epi16(x0, x1));
}
for( ; x < width - 4; x += 4 )
{
__m128i x0, y0;
x0 = _mm_srai_epi32(_mm_loadu_si128((const __m128i*)(S0 + x)), 4);
y0 = _mm_srai_epi32(_mm_loadu_si128((const __m128i*)(S1 + x)), 4);
x0 = _mm_packs_epi32(x0, x0);
y0 = _mm_packs_epi32(y0, y0);
x0 = _mm_adds_epi16(_mm_mulhi_epi16(x0, b0), _mm_mulhi_epi16(y0, b1));
x0 = _mm_srai_epi16(_mm_adds_epi16(x0, delta), 2);
x0 = _mm_packus_epi16(x0, x0);
*(int*)(dst + x) = _mm_cvtsi128_si32(x0);
}
return x;
}
};
template<int shiftval> struct VResizeLinearVec_32f16
{
int operator()(const uchar** _src, uchar* _dst, const uchar* _beta, int width ) const
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
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const float** src = (const float**)_src;
const float* beta = (const float*)_beta;
const float *S0 = src[0], *S1 = src[1];
ushort* dst = (ushort*)_dst;
int x = 0;
__m128 b0 = _mm_set1_ps(beta[0]), b1 = _mm_set1_ps(beta[1]);
__m128i preshift = _mm_set1_epi32(shiftval);
__m128i postshift = _mm_set1_epi16((short)shiftval);
if( (((size_t)S0|(size_t)S1)&15) == 0 )
for( ; x <= width - 16; x += 16 )
{
__m128 x0, x1, y0, y1;
__m128i t0, t1, t2;
x0 = _mm_load_ps(S0 + x);
x1 = _mm_load_ps(S0 + x + 4);
y0 = _mm_load_ps(S1 + x);
y1 = _mm_load_ps(S1 + x + 4);
x0 = _mm_add_ps(_mm_mul_ps(x0, b0), _mm_mul_ps(y0, b1));
x1 = _mm_add_ps(_mm_mul_ps(x1, b0), _mm_mul_ps(y1, b1));
t0 = _mm_add_epi32(_mm_cvtps_epi32(x0), preshift);
t2 = _mm_add_epi32(_mm_cvtps_epi32(x1), preshift);
t0 = _mm_add_epi16(_mm_packs_epi32(t0, t2), postshift);
x0 = _mm_load_ps(S0 + x + 8);
x1 = _mm_load_ps(S0 + x + 12);
y0 = _mm_load_ps(S1 + x + 8);
y1 = _mm_load_ps(S1 + x + 12);
x0 = _mm_add_ps(_mm_mul_ps(x0, b0), _mm_mul_ps(y0, b1));
x1 = _mm_add_ps(_mm_mul_ps(x1, b0), _mm_mul_ps(y1, b1));
t1 = _mm_add_epi32(_mm_cvtps_epi32(x0), preshift);
t2 = _mm_add_epi32(_mm_cvtps_epi32(x1), preshift);
t1 = _mm_add_epi16(_mm_packs_epi32(t1, t2), postshift);
_mm_storeu_si128( (__m128i*)(dst + x), t0);
_mm_storeu_si128( (__m128i*)(dst + x + 8), t1);
}
else
for( ; x <= width - 16; x += 16 )
{
__m128 x0, x1, y0, y1;
__m128i t0, t1, t2;
x0 = _mm_loadu_ps(S0 + x);
x1 = _mm_loadu_ps(S0 + x + 4);
y0 = _mm_loadu_ps(S1 + x);
y1 = _mm_loadu_ps(S1 + x + 4);
x0 = _mm_add_ps(_mm_mul_ps(x0, b0), _mm_mul_ps(y0, b1));
x1 = _mm_add_ps(_mm_mul_ps(x1, b0), _mm_mul_ps(y1, b1));
t0 = _mm_add_epi32(_mm_cvtps_epi32(x0), preshift);
t2 = _mm_add_epi32(_mm_cvtps_epi32(x1), preshift);
t0 = _mm_add_epi16(_mm_packs_epi32(t0, t2), postshift);
x0 = _mm_loadu_ps(S0 + x + 8);
x1 = _mm_loadu_ps(S0 + x + 12);
y0 = _mm_loadu_ps(S1 + x + 8);
y1 = _mm_loadu_ps(S1 + x + 12);
x0 = _mm_add_ps(_mm_mul_ps(x0, b0), _mm_mul_ps(y0, b1));
x1 = _mm_add_ps(_mm_mul_ps(x1, b0), _mm_mul_ps(y1, b1));
t1 = _mm_add_epi32(_mm_cvtps_epi32(x0), preshift);
t2 = _mm_add_epi32(_mm_cvtps_epi32(x1), preshift);
t1 = _mm_add_epi16(_mm_packs_epi32(t1, t2), postshift);
_mm_storeu_si128( (__m128i*)(dst + x), t0);
_mm_storeu_si128( (__m128i*)(dst + x + 8), t1);
}
for( ; x < width - 4; x += 4 )
{
__m128 x0, y0;
__m128i t0;
x0 = _mm_loadu_ps(S0 + x);
y0 = _mm_loadu_ps(S1 + x);
x0 = _mm_add_ps(_mm_mul_ps(x0, b0), _mm_mul_ps(y0, b1));
t0 = _mm_add_epi32(_mm_cvtps_epi32(x0), preshift);
t0 = _mm_add_epi16(_mm_packs_epi32(t0, t0), postshift);
_mm_storel_epi64( (__m128i*)(dst + x), t0);
}
return x;
}
};
typedef VResizeLinearVec_32f16<SHRT_MIN> VResizeLinearVec_32f16u;
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typedef VResizeLinearVec_32f16<0> VResizeLinearVec_32f16s;
struct VResizeLinearVec_32f
{
int operator()(const uchar** _src, uchar* _dst, const uchar* _beta, int width ) const
{
if( !checkHardwareSupport(CV_CPU_SSE) )
return 0;
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const float** src = (const float**)_src;
const float* beta = (const float*)_beta;
const float *S0 = src[0], *S1 = src[1];
float* dst = (float*)_dst;
int x = 0;
__m128 b0 = _mm_set1_ps(beta[0]), b1 = _mm_set1_ps(beta[1]);
if( (((size_t)S0|(size_t)S1)&15) == 0 )
for( ; x <= width - 8; x += 8 )
{
__m128 x0, x1, y0, y1;
x0 = _mm_load_ps(S0 + x);
x1 = _mm_load_ps(S0 + x + 4);
y0 = _mm_load_ps(S1 + x);
y1 = _mm_load_ps(S1 + x + 4);
x0 = _mm_add_ps(_mm_mul_ps(x0, b0), _mm_mul_ps(y0, b1));
x1 = _mm_add_ps(_mm_mul_ps(x1, b0), _mm_mul_ps(y1, b1));
_mm_storeu_ps( dst + x, x0);
_mm_storeu_ps( dst + x + 4, x1);
}
else
for( ; x <= width - 8; x += 8 )
{
__m128 x0, x1, y0, y1;
x0 = _mm_loadu_ps(S0 + x);
x1 = _mm_loadu_ps(S0 + x + 4);
y0 = _mm_loadu_ps(S1 + x);
y1 = _mm_loadu_ps(S1 + x + 4);
x0 = _mm_add_ps(_mm_mul_ps(x0, b0), _mm_mul_ps(y0, b1));
x1 = _mm_add_ps(_mm_mul_ps(x1, b0), _mm_mul_ps(y1, b1));
_mm_storeu_ps( dst + x, x0);
_mm_storeu_ps( dst + x + 4, x1);
}
return x;
}
};
struct VResizeCubicVec_32s8u
{
int operator()(const uchar** _src, uchar* dst, const uchar* _beta, int width ) const
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
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const int** src = (const int**)_src;
const short* beta = (const short*)_beta;
const int *S0 = src[0], *S1 = src[1], *S2 = src[2], *S3 = src[3];
int x = 0;
float scale = 1.f/(INTER_RESIZE_COEF_SCALE*INTER_RESIZE_COEF_SCALE);
__m128 b0 = _mm_set1_ps(beta[0]*scale), b1 = _mm_set1_ps(beta[1]*scale),
b2 = _mm_set1_ps(beta[2]*scale), b3 = _mm_set1_ps(beta[3]*scale);
if( (((size_t)S0|(size_t)S1|(size_t)S2|(size_t)S3)&15) == 0 )
for( ; x <= width - 8; x += 8 )
{
__m128i x0, x1, y0, y1;
__m128 s0, s1, f0, f1;
x0 = _mm_load_si128((const __m128i*)(S0 + x));
x1 = _mm_load_si128((const __m128i*)(S0 + x + 4));
y0 = _mm_load_si128((const __m128i*)(S1 + x));
y1 = _mm_load_si128((const __m128i*)(S1 + x + 4));
s0 = _mm_mul_ps(_mm_cvtepi32_ps(x0), b0);
s1 = _mm_mul_ps(_mm_cvtepi32_ps(x1), b0);
f0 = _mm_mul_ps(_mm_cvtepi32_ps(y0), b1);
f1 = _mm_mul_ps(_mm_cvtepi32_ps(y1), b1);
s0 = _mm_add_ps(s0, f0);
s1 = _mm_add_ps(s1, f1);
x0 = _mm_load_si128((const __m128i*)(S2 + x));
x1 = _mm_load_si128((const __m128i*)(S2 + x + 4));
y0 = _mm_load_si128((const __m128i*)(S3 + x));
y1 = _mm_load_si128((const __m128i*)(S3 + x + 4));
f0 = _mm_mul_ps(_mm_cvtepi32_ps(x0), b2);
f1 = _mm_mul_ps(_mm_cvtepi32_ps(x1), b2);
s0 = _mm_add_ps(s0, f0);
s1 = _mm_add_ps(s1, f1);
f0 = _mm_mul_ps(_mm_cvtepi32_ps(y0), b3);
f1 = _mm_mul_ps(_mm_cvtepi32_ps(y1), b3);
s0 = _mm_add_ps(s0, f0);
s1 = _mm_add_ps(s1, f1);
x0 = _mm_cvtps_epi32(s0);
x1 = _mm_cvtps_epi32(s1);
x0 = _mm_packs_epi32(x0, x1);
_mm_storel_epi64( (__m128i*)(dst + x), _mm_packus_epi16(x0, x0));
}
else
for( ; x <= width - 8; x += 8 )
{
__m128i x0, x1, y0, y1;
__m128 s0, s1, f0, f1;
x0 = _mm_loadu_si128((const __m128i*)(S0 + x));
x1 = _mm_loadu_si128((const __m128i*)(S0 + x + 4));
y0 = _mm_loadu_si128((const __m128i*)(S1 + x));
y1 = _mm_loadu_si128((const __m128i*)(S1 + x + 4));
s0 = _mm_mul_ps(_mm_cvtepi32_ps(x0), b0);
s1 = _mm_mul_ps(_mm_cvtepi32_ps(x1), b0);
f0 = _mm_mul_ps(_mm_cvtepi32_ps(y0), b1);
f1 = _mm_mul_ps(_mm_cvtepi32_ps(y1), b1);
s0 = _mm_add_ps(s0, f0);
s1 = _mm_add_ps(s1, f1);
x0 = _mm_loadu_si128((const __m128i*)(S2 + x));
x1 = _mm_loadu_si128((const __m128i*)(S2 + x + 4));
y0 = _mm_loadu_si128((const __m128i*)(S3 + x));
y1 = _mm_loadu_si128((const __m128i*)(S3 + x + 4));
f0 = _mm_mul_ps(_mm_cvtepi32_ps(x0), b2);
f1 = _mm_mul_ps(_mm_cvtepi32_ps(x1), b2);
s0 = _mm_add_ps(s0, f0);
s1 = _mm_add_ps(s1, f1);
f0 = _mm_mul_ps(_mm_cvtepi32_ps(y0), b3);
f1 = _mm_mul_ps(_mm_cvtepi32_ps(y1), b3);
s0 = _mm_add_ps(s0, f0);
s1 = _mm_add_ps(s1, f1);
x0 = _mm_cvtps_epi32(s0);
x1 = _mm_cvtps_epi32(s1);
x0 = _mm_packs_epi32(x0, x1);
_mm_storel_epi64( (__m128i*)(dst + x), _mm_packus_epi16(x0, x0));
}
return x;
}
};
template<int shiftval> struct VResizeCubicVec_32f16
{
int operator()(const uchar** _src, uchar* _dst, const uchar* _beta, int width ) const
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
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const float** src = (const float**)_src;
const float* beta = (const float*)_beta;
const float *S0 = src[0], *S1 = src[1], *S2 = src[2], *S3 = src[3];
ushort* dst = (ushort*)_dst;
int x = 0;
__m128 b0 = _mm_set1_ps(beta[0]), b1 = _mm_set1_ps(beta[1]),
b2 = _mm_set1_ps(beta[2]), b3 = _mm_set1_ps(beta[3]);
__m128i preshift = _mm_set1_epi32(shiftval);
__m128i postshift = _mm_set1_epi16((short)shiftval);
for( ; x <= width - 8; x += 8 )
{
__m128 x0, x1, y0, y1, s0, s1;
__m128i t0, t1;
x0 = _mm_loadu_ps(S0 + x);
x1 = _mm_loadu_ps(S0 + x + 4);
y0 = _mm_loadu_ps(S1 + x);
y1 = _mm_loadu_ps(S1 + x + 4);
s0 = _mm_mul_ps(x0, b0);
s1 = _mm_mul_ps(x1, b0);
y0 = _mm_mul_ps(y0, b1);
y1 = _mm_mul_ps(y1, b1);
s0 = _mm_add_ps(s0, y0);
s1 = _mm_add_ps(s1, y1);
x0 = _mm_loadu_ps(S2 + x);
x1 = _mm_loadu_ps(S2 + x + 4);
y0 = _mm_loadu_ps(S3 + x);
y1 = _mm_loadu_ps(S3 + x + 4);
x0 = _mm_mul_ps(x0, b2);
x1 = _mm_mul_ps(x1, b2);
y0 = _mm_mul_ps(y0, b3);
y1 = _mm_mul_ps(y1, b3);
s0 = _mm_add_ps(s0, x0);
s1 = _mm_add_ps(s1, x1);
s0 = _mm_add_ps(s0, y0);
s1 = _mm_add_ps(s1, y1);
t0 = _mm_add_epi32(_mm_cvtps_epi32(s0), preshift);
t1 = _mm_add_epi32(_mm_cvtps_epi32(s1), preshift);
t0 = _mm_add_epi16(_mm_packs_epi32(t0, t1), postshift);
_mm_storeu_si128( (__m128i*)(dst + x), t0);
}
return x;
}
};
typedef VResizeCubicVec_32f16<SHRT_MIN> VResizeCubicVec_32f16u;
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typedef VResizeCubicVec_32f16<0> VResizeCubicVec_32f16s;
struct VResizeCubicVec_32f
{
int operator()(const uchar** _src, uchar* _dst, const uchar* _beta, int width ) const
{
if( !checkHardwareSupport(CV_CPU_SSE) )
return 0;
2012-05-30 23:56:53 +08:00
const float** src = (const float**)_src;
const float* beta = (const float*)_beta;
const float *S0 = src[0], *S1 = src[1], *S2 = src[2], *S3 = src[3];
float* dst = (float*)_dst;
int x = 0;
__m128 b0 = _mm_set1_ps(beta[0]), b1 = _mm_set1_ps(beta[1]),
b2 = _mm_set1_ps(beta[2]), b3 = _mm_set1_ps(beta[3]);
for( ; x <= width - 8; x += 8 )
{
__m128 x0, x1, y0, y1, s0, s1;
x0 = _mm_loadu_ps(S0 + x);
x1 = _mm_loadu_ps(S0 + x + 4);
y0 = _mm_loadu_ps(S1 + x);
y1 = _mm_loadu_ps(S1 + x + 4);
s0 = _mm_mul_ps(x0, b0);
s1 = _mm_mul_ps(x1, b0);
y0 = _mm_mul_ps(y0, b1);
y1 = _mm_mul_ps(y1, b1);
s0 = _mm_add_ps(s0, y0);
s1 = _mm_add_ps(s1, y1);
x0 = _mm_loadu_ps(S2 + x);
x1 = _mm_loadu_ps(S2 + x + 4);
y0 = _mm_loadu_ps(S3 + x);
y1 = _mm_loadu_ps(S3 + x + 4);
x0 = _mm_mul_ps(x0, b2);
x1 = _mm_mul_ps(x1, b2);
y0 = _mm_mul_ps(y0, b3);
y1 = _mm_mul_ps(y1, b3);
s0 = _mm_add_ps(s0, x0);
s1 = _mm_add_ps(s1, x1);
s0 = _mm_add_ps(s0, y0);
s1 = _mm_add_ps(s1, y1);
_mm_storeu_ps( dst + x, s0);
_mm_storeu_ps( dst + x + 4, s1);
}
return x;
}
};
#else
typedef VResizeNoVec VResizeLinearVec_32s8u;
typedef VResizeNoVec VResizeLinearVec_32f16u;
typedef VResizeNoVec VResizeLinearVec_32f16s;
typedef VResizeNoVec VResizeLinearVec_32f;
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typedef VResizeNoVec VResizeCubicVec_32s8u;
typedef VResizeNoVec VResizeCubicVec_32f16u;
typedef VResizeNoVec VResizeCubicVec_32f16s;
typedef VResizeNoVec VResizeCubicVec_32f;
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#endif
typedef HResizeNoVec HResizeLinearVec_8u32s;
typedef HResizeNoVec HResizeLinearVec_16u32f;
typedef HResizeNoVec HResizeLinearVec_16s32f;
typedef HResizeNoVec HResizeLinearVec_32f;
typedef HResizeNoVec HResizeLinearVec_64f;
template<typename T, typename WT, typename AT, int ONE, class VecOp>
struct HResizeLinear
{
typedef T value_type;
typedef WT buf_type;
typedef AT alpha_type;
void operator()(const T** src, WT** dst, int count,
const int* xofs, const AT* alpha,
int swidth, int dwidth, int cn, int xmin, int xmax ) const
{
int dx, k;
VecOp vecOp;
int dx0 = vecOp((const uchar**)src, (uchar**)dst, count,
xofs, (const uchar*)alpha, swidth, dwidth, cn, xmin, xmax );
for( k = 0; k <= count - 2; k++ )
{
const T *S0 = src[k], *S1 = src[k+1];
WT *D0 = dst[k], *D1 = dst[k+1];
for( dx = dx0; dx < xmax; dx++ )
{
int sx = xofs[dx];
WT a0 = alpha[dx*2], a1 = alpha[dx*2+1];
WT t0 = S0[sx]*a0 + S0[sx + cn]*a1;
WT t1 = S1[sx]*a0 + S1[sx + cn]*a1;
D0[dx] = t0; D1[dx] = t1;
}
for( ; dx < dwidth; dx++ )
{
int sx = xofs[dx];
D0[dx] = WT(S0[sx]*ONE); D1[dx] = WT(S1[sx]*ONE);
}
}
for( ; k < count; k++ )
{
const T *S = src[k];
WT *D = dst[k];
for( dx = 0; dx < xmax; dx++ )
{
int sx = xofs[dx];
D[dx] = S[sx]*alpha[dx*2] + S[sx+cn]*alpha[dx*2+1];
}
for( ; dx < dwidth; dx++ )
D[dx] = WT(S[xofs[dx]]*ONE);
}
}
};
template<typename T, typename WT, typename AT, class CastOp, class VecOp>
struct VResizeLinear
{
typedef T value_type;
typedef WT buf_type;
typedef AT alpha_type;
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void operator()(const WT** src, T* dst, const AT* beta, int width ) const
{
WT b0 = beta[0], b1 = beta[1];
const WT *S0 = src[0], *S1 = src[1];
CastOp castOp;
VecOp vecOp;
int x = vecOp((const uchar**)src, (uchar*)dst, (const uchar*)beta, width);
2012-06-06 18:39:42 +08:00
#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
{
WT t0, t1;
t0 = S0[x]*b0 + S1[x]*b1;
t1 = S0[x+1]*b0 + S1[x+1]*b1;
dst[x] = castOp(t0); dst[x+1] = castOp(t1);
t0 = S0[x+2]*b0 + S1[x+2]*b1;
t1 = S0[x+3]*b0 + S1[x+3]*b1;
dst[x+2] = castOp(t0); dst[x+3] = castOp(t1);
}
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#endif
for( ; x < width; x++ )
dst[x] = castOp(S0[x]*b0 + S1[x]*b1);
}
};
template<>
struct VResizeLinear<uchar, int, short, FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>, VResizeLinearVec_32s8u>
{
typedef uchar value_type;
typedef int buf_type;
typedef short alpha_type;
void operator()(const buf_type** src, value_type* dst, const alpha_type* beta, int width ) const
{
alpha_type b0 = beta[0], b1 = beta[1];
const buf_type *S0 = src[0], *S1 = src[1];
VResizeLinearVec_32s8u vecOp;
int x = vecOp((const uchar**)src, (uchar*)dst, (const uchar*)beta, width);
#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
{
dst[x+0] = uchar(( ((b0 * (S0[x+0] >> 4)) >> 16) + ((b1 * (S1[x+0] >> 4)) >> 16) + 2)>>2);
dst[x+1] = uchar(( ((b0 * (S0[x+1] >> 4)) >> 16) + ((b1 * (S1[x+1] >> 4)) >> 16) + 2)>>2);
dst[x+2] = uchar(( ((b0 * (S0[x+2] >> 4)) >> 16) + ((b1 * (S1[x+2] >> 4)) >> 16) + 2)>>2);
dst[x+3] = uchar(( ((b0 * (S0[x+3] >> 4)) >> 16) + ((b1 * (S1[x+3] >> 4)) >> 16) + 2)>>2);
}
#endif
for( ; x < width; x++ )
dst[x] = uchar(( ((b0 * (S0[x] >> 4)) >> 16) + ((b1 * (S1[x] >> 4)) >> 16) + 2)>>2);
}
};
template<typename T, typename WT, typename AT>
struct HResizeCubic
{
typedef T value_type;
typedef WT buf_type;
typedef AT alpha_type;
void operator()(const T** src, WT** dst, int count,
const int* xofs, const AT* alpha,
int swidth, int dwidth, int cn, int xmin, int xmax ) const
{
for( int k = 0; k < count; k++ )
{
const T *S = src[k];
WT *D = dst[k];
int dx = 0, limit = xmin;
for(;;)
{
for( ; dx < limit; dx++, alpha += 4 )
{
int j, sx = xofs[dx] - cn;
WT v = 0;
for( j = 0; j < 4; j++ )
{
int sxj = sx + j*cn;
if( (unsigned)sxj >= (unsigned)swidth )
{
while( sxj < 0 )
sxj += cn;
while( sxj >= swidth )
sxj -= cn;
}
v += S[sxj]*alpha[j];
}
D[dx] = v;
}
if( limit == dwidth )
break;
for( ; dx < xmax; dx++, alpha += 4 )
{
int sx = xofs[dx];
D[dx] = S[sx-cn]*alpha[0] + S[sx]*alpha[1] +
S[sx+cn]*alpha[2] + S[sx+cn*2]*alpha[3];
}
limit = dwidth;
}
alpha -= dwidth*4;
}
}
};
template<typename T, typename WT, typename AT, class CastOp, class VecOp>
struct VResizeCubic
{
typedef T value_type;
typedef WT buf_type;
typedef AT alpha_type;
void operator()(const WT** src, T* dst, const AT* beta, int width ) const
{
WT b0 = beta[0], b1 = beta[1], b2 = beta[2], b3 = beta[3];
const WT *S0 = src[0], *S1 = src[1], *S2 = src[2], *S3 = src[3];
CastOp castOp;
VecOp vecOp;
int x = vecOp((const uchar**)src, (uchar*)dst, (const uchar*)beta, width);
for( ; x < width; x++ )
dst[x] = castOp(S0[x]*b0 + S1[x]*b1 + S2[x]*b2 + S3[x]*b3);
}
};
template<typename T, typename WT, typename AT>
struct HResizeLanczos4
{
typedef T value_type;
typedef WT buf_type;
typedef AT alpha_type;
void operator()(const T** src, WT** dst, int count,
const int* xofs, const AT* alpha,
int swidth, int dwidth, int cn, int xmin, int xmax ) const
{
for( int k = 0; k < count; k++ )
{
const T *S = src[k];
WT *D = dst[k];
int dx = 0, limit = xmin;
for(;;)
{
for( ; dx < limit; dx++, alpha += 8 )
{
int j, sx = xofs[dx] - cn*3;
WT v = 0;
for( j = 0; j < 8; j++ )
{
int sxj = sx + j*cn;
if( (unsigned)sxj >= (unsigned)swidth )
{
while( sxj < 0 )
sxj += cn;
while( sxj >= swidth )
sxj -= cn;
}
v += S[sxj]*alpha[j];
}
D[dx] = v;
}
if( limit == dwidth )
break;
for( ; dx < xmax; dx++, alpha += 8 )
{
int sx = xofs[dx];
D[dx] = S[sx-cn*3]*alpha[0] + S[sx-cn*2]*alpha[1] +
S[sx-cn]*alpha[2] + S[sx]*alpha[3] +
S[sx+cn]*alpha[4] + S[sx+cn*2]*alpha[5] +
S[sx+cn*3]*alpha[6] + S[sx+cn*4]*alpha[7];
}
limit = dwidth;
}
alpha -= dwidth*8;
}
}
};
template<typename T, typename WT, typename AT, class CastOp, class VecOp>
struct VResizeLanczos4
{
typedef T value_type;
typedef WT buf_type;
typedef AT alpha_type;
void operator()(const WT** src, T* dst, const AT* beta, int width ) const
{
CastOp castOp;
VecOp vecOp;
int k, x = vecOp((const uchar**)src, (uchar*)dst, (const uchar*)beta, width);
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#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
{
WT b = beta[0];
const WT* S = src[0];
WT s0 = S[x]*b, s1 = S[x+1]*b, s2 = S[x+2]*b, s3 = S[x+3]*b;
for( k = 1; k < 8; k++ )
{
b = beta[k]; S = src[k];
s0 += S[x]*b; s1 += S[x+1]*b;
s2 += S[x+2]*b; s3 += S[x+3]*b;
}
dst[x] = castOp(s0); dst[x+1] = castOp(s1);
dst[x+2] = castOp(s2); dst[x+3] = castOp(s3);
}
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#endif
for( ; x < width; x++ )
{
dst[x] = castOp(src[0][x]*beta[0] + src[1][x]*beta[1] +
src[2][x]*beta[2] + src[3][x]*beta[3] + src[4][x]*beta[4] +
src[5][x]*beta[5] + src[6][x]*beta[6] + src[7][x]*beta[7]);
}
}
};
static inline int clip(int x, int a, int b)
{
return x >= a ? (x < b ? x : b-1) : a;
}
static const int MAX_ESIZE=16;
template <typename HResize, typename VResize>
class resizeGeneric_Invoker :
public ParallelLoopBody
{
public:
typedef typename HResize::value_type T;
typedef typename HResize::buf_type WT;
typedef typename HResize::alpha_type AT;
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resizeGeneric_Invoker(const Mat& _src, Mat &_dst, const int *_xofs, const int *_yofs,
const AT* _alpha, const AT* __beta, const Size& _ssize, const Size &_dsize,
int _ksize, int _xmin, int _xmax) :
ParallelLoopBody(), src(_src), dst(_dst), xofs(_xofs), yofs(_yofs),
alpha(_alpha), _beta(__beta), ssize(_ssize), dsize(_dsize),
ksize(_ksize), xmin(_xmin), xmax(_xmax)
{
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CV_Assert(ksize <= MAX_ESIZE);
}
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#if defined(__GNUC__) && (__GNUC__ == 4) && (__GNUC_MINOR__ == 8)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Warray-bounds"
#endif
virtual void operator() (const Range& range) const
{
int dy, cn = src.channels();
HResize hresize;
VResize vresize;
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int bufstep = (int)alignSize(dsize.width, 16);
AutoBuffer<WT> _buffer(bufstep*ksize);
const T* srows[MAX_ESIZE]={0};
WT* rows[MAX_ESIZE]={0};
int prev_sy[MAX_ESIZE];
for(int k = 0; k < ksize; k++ )
{
prev_sy[k] = -1;
rows[k] = (WT*)_buffer + bufstep*k;
}
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const AT* beta = _beta + ksize * range.start;
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for( dy = range.start; dy < range.end; dy++, beta += ksize )
{
int sy0 = yofs[dy], k0=ksize, k1=0, ksize2 = ksize/2;
for(int k = 0; k < ksize; k++ )
{
int sy = clip(sy0 - ksize2 + 1 + k, 0, ssize.height);
for( k1 = std::max(k1, k); k1 < ksize; k1++ )
{
if( sy == prev_sy[k1] ) // if the sy-th row has been computed already, reuse it.
{
if( k1 > k )
memcpy( rows[k], rows[k1], bufstep*sizeof(rows[0][0]) );
break;
}
}
if( k1 == ksize )
k0 = std::min(k0, k); // remember the first row that needs to be computed
srows[k] = (T*)(src.data + src.step*sy);
prev_sy[k] = sy;
}
if( k0 < ksize )
hresize( (const T**)(srows + k0), (WT**)(rows + k0), ksize - k0, xofs, (const AT*)(alpha),
ssize.width, dsize.width, cn, xmin, xmax );
vresize( (const WT**)rows, (T*)(dst.data + dst.step*dy), beta, dsize.width );
}
}
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#if defined(__GNUC__) && (__GNUC__ == 4) && (__GNUC_MINOR__ == 8)
# pragma GCC diagnostic pop
#endif
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private:
Mat src;
Mat dst;
const int* xofs, *yofs;
const AT* alpha, *_beta;
Size ssize, dsize;
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const int ksize, xmin, xmax;
resizeGeneric_Invoker& operator = (const resizeGeneric_Invoker&);
};
template<class HResize, class VResize>
static void resizeGeneric_( const Mat& src, Mat& dst,
const int* xofs, const void* _alpha,
const int* yofs, const void* _beta,
int xmin, int xmax, int ksize )
{
typedef typename HResize::alpha_type AT;
const AT* beta = (const AT*)_beta;
Size ssize = src.size(), dsize = dst.size();
int cn = src.channels();
ssize.width *= cn;
dsize.width *= cn;
xmin *= cn;
xmax *= cn;
// image resize is a separable operation. In case of not too strong
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Range range(0, dsize.height);
resizeGeneric_Invoker<HResize, VResize> invoker(src, dst, xofs, yofs, (const AT*)_alpha, beta,
ssize, dsize, ksize, xmin, xmax);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
}
template <typename T, typename WT>
struct ResizeAreaFastNoVec
{
ResizeAreaFastNoVec(int, int) { }
ResizeAreaFastNoVec(int, int, int, int) { }
int operator() (const T*, T*, int) const
{ return 0; }
};
#if CV_SSE2
class ResizeAreaFastVec_SIMD_8u
{
public:
ResizeAreaFastVec_SIMD_8u(int _cn, int _step) :
cn(_cn), step(_step)
{
use_simd = checkHardwareSupport(CV_CPU_SSE2);
}
int operator() (const uchar* S, uchar* D, int w) const
{
if (!use_simd)
return 0;
int dx = 0;
const uchar* S0 = S;
const uchar* S1 = S0 + step;
__m128i zero = _mm_setzero_si128();
__m128i delta2 = _mm_set1_epi16(2);
if (cn == 1)
{
__m128i masklow = _mm_set1_epi16(0x00ff);
for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i s0 = _mm_add_epi16(_mm_srli_epi16(r0, 8), _mm_and_si128(r0, masklow));
__m128i s1 = _mm_add_epi16(_mm_srli_epi16(r1, 8), _mm_and_si128(r1, masklow));
s0 = _mm_add_epi16(_mm_add_epi16(s0, s1), delta2);
s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
}
}
else if (cn == 3)
for ( ; dx <= w - 11; dx += 6, S0 += 12, S1 += 12, D += 6)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i r0_16l = _mm_unpacklo_epi8(r0, zero);
__m128i r0_16h = _mm_unpacklo_epi8(_mm_srli_si128(r0, 6), zero);
__m128i r1_16l = _mm_unpacklo_epi8(r1, zero);
__m128i r1_16h = _mm_unpacklo_epi8(_mm_srli_si128(r1, 6), zero);
__m128i s0 = _mm_add_epi16(r0_16l, _mm_srli_si128(r0_16l, 6));
__m128i s1 = _mm_add_epi16(r1_16l, _mm_srli_si128(r1_16l, 6));
s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
s0 = _mm_add_epi16(r0_16h, _mm_srli_si128(r0_16h, 6));
s1 = _mm_add_epi16(r1_16h, _mm_srli_si128(r1_16h, 6));
s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
_mm_storel_epi64((__m128i*)(D+3), s0);
}
else
{
CV_Assert(cn == 4);
int v[] = { 0, 0, -1, -1 };
__m128i mask = _mm_loadu_si128((const __m128i*)v);
for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i r0_16l = _mm_unpacklo_epi8(r0, zero);
__m128i r0_16h = _mm_unpackhi_epi8(r0, zero);
__m128i r1_16l = _mm_unpacklo_epi8(r1, zero);
__m128i r1_16h = _mm_unpackhi_epi8(r1, zero);
__m128i s0 = _mm_add_epi16(r0_16l, _mm_srli_si128(r0_16l, 8));
__m128i s1 = _mm_add_epi16(r1_16l, _mm_srli_si128(r1_16l, 8));
s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
__m128i res0 = _mm_srli_epi16(s0, 2);
s0 = _mm_add_epi16(r0_16h, _mm_srli_si128(r0_16h, 8));
s1 = _mm_add_epi16(r1_16h, _mm_srli_si128(r1_16h, 8));
s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
__m128i res1 = _mm_srli_epi16(s0, 2);
s0 = _mm_packus_epi16(_mm_or_si128(_mm_andnot_si128(mask, res0),
_mm_and_si128(mask, _mm_slli_si128(res1, 8))), zero);
_mm_storel_epi64((__m128i*)(D), s0);
}
}
return dx;
}
private:
int cn;
bool use_simd;
int step;
};
class ResizeAreaFastVec_SIMD_16u
{
public:
ResizeAreaFastVec_SIMD_16u(int _cn, int _step) :
cn(_cn), step(_step)
{
use_simd = checkHardwareSupport(CV_CPU_SSE2);
}
int operator() (const ushort* S, ushort* D, int w) const
{
if (!use_simd)
return 0;
int dx = 0;
const ushort* S0 = (const ushort*)S;
const ushort* S1 = (const ushort*)((const uchar*)(S) + step);
__m128i masklow = _mm_set1_epi32(0x0000ffff);
__m128i zero = _mm_setzero_si128();
__m128i delta2 = _mm_set1_epi32(2);
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#define _mm_packus_epi32(a, zero) _mm_packs_epi32(_mm_srai_epi32(_mm_slli_epi32(a, 16), 16), zero)
if (cn == 1)
{
for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i s0 = _mm_add_epi32(_mm_srli_epi32(r0, 16), _mm_and_si128(r0, masklow));
__m128i s1 = _mm_add_epi32(_mm_srli_epi32(r1, 16), _mm_and_si128(r1, masklow));
s0 = _mm_add_epi32(_mm_add_epi32(s0, s1), delta2);
s0 = _mm_srli_epi32(s0, 2);
s0 = _mm_packus_epi32(s0, zero);
_mm_storel_epi64((__m128i*)D, s0);
}
}
else if (cn == 3)
for ( ; dx <= w - 4; dx += 3, S0 += 6, S1 += 6, D += 3)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i r0_16l = _mm_unpacklo_epi16(r0, zero);
__m128i r0_16h = _mm_unpacklo_epi16(_mm_srli_si128(r0, 6), zero);
__m128i r1_16l = _mm_unpacklo_epi16(r1, zero);
__m128i r1_16h = _mm_unpacklo_epi16(_mm_srli_si128(r1, 6), zero);
__m128i s0 = _mm_add_epi32(r0_16l, r0_16h);
__m128i s1 = _mm_add_epi32(r1_16l, r1_16h);
s0 = _mm_add_epi32(delta2, _mm_add_epi32(s0, s1));
s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
}
else
{
CV_Assert(cn == 4);
for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i r0_32l = _mm_unpacklo_epi16(r0, zero);
__m128i r0_32h = _mm_unpackhi_epi16(r0, zero);
__m128i r1_32l = _mm_unpacklo_epi16(r1, zero);
__m128i r1_32h = _mm_unpackhi_epi16(r1, zero);
__m128i s0 = _mm_add_epi32(r0_32l, r0_32h);
__m128i s1 = _mm_add_epi32(r1_32l, r1_32h);
s0 = _mm_add_epi32(s1, _mm_add_epi32(s0, delta2));
s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
}
}
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#undef _mm_packus_epi32
return dx;
}
private:
int cn;
int step;
bool use_simd;
};
#else
typedef ResizeAreaFastNoVec<uchar, uchar> ResizeAreaFastVec_SIMD_8u;
typedef ResizeAreaFastNoVec<ushort, ushort> ResizeAreaFastVec_SIMD_16u;
#endif
template<typename T, typename SIMDVecOp>
struct ResizeAreaFastVec
{
ResizeAreaFastVec(int _scale_x, int _scale_y, int _cn, int _step) :
scale_x(_scale_x), scale_y(_scale_y), cn(_cn), step(_step), vecOp(_cn, _step)
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{
fast_mode = scale_x == 2 && scale_y == 2 && (cn == 1 || cn == 3 || cn == 4);
}
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int operator() (const T* S, T* D, int w) const
{
if (!fast_mode)
return 0;
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const T* nextS = (const T*)((const uchar*)S + step);
int dx = vecOp(S, D, w);
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if (cn == 1)
for( ; dx < w; ++dx )
{
int index = dx*2;
D[dx] = (T)((S[index] + S[index+1] + nextS[index] + nextS[index+1] + 2) >> 2);
}
else if (cn == 3)
for( ; dx < w; dx += 3 )
{
int index = dx*2;
D[dx] = (T)((S[index] + S[index+3] + nextS[index] + nextS[index+3] + 2) >> 2);
D[dx+1] = (T)((S[index+1] + S[index+4] + nextS[index+1] + nextS[index+4] + 2) >> 2);
D[dx+2] = (T)((S[index+2] + S[index+5] + nextS[index+2] + nextS[index+5] + 2) >> 2);
}
else
{
CV_Assert(cn == 4);
for( ; dx < w; dx += 4 )
{
int index = dx*2;
D[dx] = (T)((S[index] + S[index+4] + nextS[index] + nextS[index+4] + 2) >> 2);
D[dx+1] = (T)((S[index+1] + S[index+5] + nextS[index+1] + nextS[index+5] + 2) >> 2);
D[dx+2] = (T)((S[index+2] + S[index+6] + nextS[index+2] + nextS[index+6] + 2) >> 2);
D[dx+3] = (T)((S[index+3] + S[index+7] + nextS[index+3] + nextS[index+7] + 2) >> 2);
}
}
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return dx;
}
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private:
int scale_x, scale_y;
int cn;
bool fast_mode;
int step;
SIMDVecOp vecOp;
};
template <typename T, typename WT, typename VecOp>
class resizeAreaFast_Invoker :
public ParallelLoopBody
{
public:
resizeAreaFast_Invoker(const Mat &_src, Mat &_dst,
int _scale_x, int _scale_y, const int* _ofs, const int* _xofs) :
ParallelLoopBody(), src(_src), dst(_dst), scale_x(_scale_x),
scale_y(_scale_y), ofs(_ofs), xofs(_xofs)
{
}
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virtual void operator() (const Range& range) const
{
Size ssize = src.size(), dsize = dst.size();
int cn = src.channels();
int area = scale_x*scale_y;
float scale = 1.f/(area);
int dwidth1 = (ssize.width/scale_x)*cn;
dsize.width *= cn;
ssize.width *= cn;
int dy, dx, k = 0;
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VecOp vop(scale_x, scale_y, src.channels(), (int)src.step/*, area_ofs*/);
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for( dy = range.start; dy < range.end; dy++ )
{
T* D = (T*)(dst.data + dst.step*dy);
int sy0 = dy*scale_y;
int w = sy0 + scale_y <= ssize.height ? dwidth1 : 0;
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if( sy0 >= ssize.height )
{
for( dx = 0; dx < dsize.width; dx++ )
D[dx] = 0;
continue;
}
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dx = vop((const T*)(src.data + src.step * sy0), D, w);
for( ; dx < w; dx++ )
{
const T* S = (const T*)(src.data + src.step * sy0) + xofs[dx];
WT sum = 0;
k = 0;
#if CV_ENABLE_UNROLLED
for( ; k <= area - 4; k += 4 )
sum += S[ofs[k]] + S[ofs[k+1]] + S[ofs[k+2]] + S[ofs[k+3]];
#endif
for( ; k < area; k++ )
sum += S[ofs[k]];
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D[dx] = saturate_cast<T>(sum * scale);
}
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for( ; dx < dsize.width; dx++ )
{
WT sum = 0;
int count = 0, sx0 = xofs[dx];
if( sx0 >= ssize.width )
D[dx] = 0;
for( int sy = 0; sy < scale_y; sy++ )
{
if( sy0 + sy >= ssize.height )
break;
const T* S = (const T*)(src.data + src.step*(sy0 + sy)) + sx0;
for( int sx = 0; sx < scale_x*cn; sx += cn )
{
if( sx0 + sx >= ssize.width )
break;
sum += S[sx];
count++;
}
}
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D[dx] = saturate_cast<T>((float)sum/count);
}
}
}
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private:
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Mat src;
Mat dst;
int scale_x, scale_y;
const int *ofs, *xofs;
};
template<typename T, typename WT, typename VecOp>
static void resizeAreaFast_( const Mat& src, Mat& dst, const int* ofs, const int* xofs,
int scale_x, int scale_y )
{
Range range(0, dst.rows);
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resizeAreaFast_Invoker<T, WT, VecOp> invoker(src, dst, scale_x,
scale_y, ofs, xofs);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
}
struct DecimateAlpha
{
int si, di;
float alpha;
};
template<typename T, typename WT> class ResizeArea_Invoker :
public ParallelLoopBody
{
public:
ResizeArea_Invoker( const Mat& _src, Mat& _dst,
const DecimateAlpha* _xtab, int _xtab_size,
const DecimateAlpha* _ytab, int _ytab_size,
const int* _tabofs )
{
src = &_src;
dst = &_dst;
xtab0 = _xtab;
xtab_size0 = _xtab_size;
ytab = _ytab;
ytab_size = _ytab_size;
tabofs = _tabofs;
}
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virtual void operator() (const Range& range) const
{
Size dsize = dst->size();
int cn = dst->channels();
dsize.width *= cn;
AutoBuffer<WT> _buffer(dsize.width*2);
const DecimateAlpha* xtab = xtab0;
int xtab_size = xtab_size0;
WT *buf = _buffer, *sum = buf + dsize.width;
int j_start = tabofs[range.start], j_end = tabofs[range.end], j, k, dx, prev_dy = ytab[j_start].di;
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for( dx = 0; dx < dsize.width; dx++ )
sum[dx] = (WT)0;
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for( j = j_start; j < j_end; j++ )
{
WT beta = ytab[j].alpha;
int dy = ytab[j].di;
int sy = ytab[j].si;
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{
const T* S = (const T*)(src->data + src->step*sy);
for( dx = 0; dx < dsize.width; dx++ )
buf[dx] = (WT)0;
if( cn == 1 )
for( k = 0; k < xtab_size; k++ )
{
int dxn = xtab[k].di;
WT alpha = xtab[k].alpha;
buf[dxn] += S[xtab[k].si]*alpha;
}
else if( cn == 2 )
for( k = 0; k < xtab_size; k++ )
{
int sxn = xtab[k].si;
int dxn = xtab[k].di;
WT alpha = xtab[k].alpha;
WT t0 = buf[dxn] + S[sxn]*alpha;
WT t1 = buf[dxn+1] + S[sxn+1]*alpha;
buf[dxn] = t0; buf[dxn+1] = t1;
}
else if( cn == 3 )
for( k = 0; k < xtab_size; k++ )
{
int sxn = xtab[k].si;
int dxn = xtab[k].di;
WT alpha = xtab[k].alpha;
WT t0 = buf[dxn] + S[sxn]*alpha;
WT t1 = buf[dxn+1] + S[sxn+1]*alpha;
WT t2 = buf[dxn+2] + S[sxn+2]*alpha;
buf[dxn] = t0; buf[dxn+1] = t1; buf[dxn+2] = t2;
}
else if( cn == 4 )
{
for( k = 0; k < xtab_size; k++ )
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{
int sxn = xtab[k].si;
int dxn = xtab[k].di;
WT alpha = xtab[k].alpha;
WT t0 = buf[dxn] + S[sxn]*alpha;
WT t1 = buf[dxn+1] + S[sxn+1]*alpha;
buf[dxn] = t0; buf[dxn+1] = t1;
t0 = buf[dxn+2] + S[sxn+2]*alpha;
t1 = buf[dxn+3] + S[sxn+3]*alpha;
buf[dxn+2] = t0; buf[dxn+3] = t1;
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}
}
else
{
for( k = 0; k < xtab_size; k++ )
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{
int sxn = xtab[k].si;
int dxn = xtab[k].di;
WT alpha = xtab[k].alpha;
for( int c = 0; c < cn; c++ )
buf[dxn + c] += S[sxn + c]*alpha;
}
}
}
if( dy != prev_dy )
{
T* D = (T*)(dst->data + dst->step*prev_dy);
for( dx = 0; dx < dsize.width; dx++ )
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{
D[dx] = saturate_cast<T>(sum[dx]);
sum[dx] = beta*buf[dx];
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}
prev_dy = dy;
}
else
{
for( dx = 0; dx < dsize.width; dx++ )
sum[dx] += beta*buf[dx];
}
}
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{
T* D = (T*)(dst->data + dst->step*prev_dy);
for( dx = 0; dx < dsize.width; dx++ )
D[dx] = saturate_cast<T>(sum[dx]);
}
}
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private:
const Mat* src;
Mat* dst;
const DecimateAlpha* xtab0;
const DecimateAlpha* ytab;
int xtab_size0, ytab_size;
const int* tabofs;
};
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template <typename T, typename WT>
static void resizeArea_( const Mat& src, Mat& dst,
const DecimateAlpha* xtab, int xtab_size,
const DecimateAlpha* ytab, int ytab_size,
const int* tabofs )
{
parallel_for_(Range(0, dst.rows),
ResizeArea_Invoker<T, WT>(src, dst, xtab, xtab_size, ytab, ytab_size, tabofs),
dst.total()/((double)(1 << 16)));
}
typedef void (*ResizeFunc)( const Mat& src, Mat& dst,
const int* xofs, const void* alpha,
const int* yofs, const void* beta,
int xmin, int xmax, int ksize );
typedef void (*ResizeAreaFastFunc)( const Mat& src, Mat& dst,
const int* ofs, const int *xofs,
int scale_x, int scale_y );
typedef void (*ResizeAreaFunc)( const Mat& src, Mat& dst,
const DecimateAlpha* xtab, int xtab_size,
const DecimateAlpha* ytab, int ytab_size,
const int* yofs);
static int computeResizeAreaTab( int ssize, int dsize, int cn, double scale, DecimateAlpha* tab )
{
int k = 0;
for(int dx = 0; dx < dsize; dx++ )
{
double fsx1 = dx * scale;
double fsx2 = fsx1 + scale;
double cellWidth = std::min(scale, ssize - fsx1);
int sx1 = cvCeil(fsx1), sx2 = cvFloor(fsx2);
sx2 = std::min(sx2, ssize - 1);
sx1 = std::min(sx1, sx2);
if( sx1 - fsx1 > 1e-3 )
{
assert( k < ssize*2 );
tab[k].di = dx * cn;
tab[k].si = (sx1 - 1) * cn;
tab[k++].alpha = (float)((sx1 - fsx1) / cellWidth);
}
for(int sx = sx1; sx < sx2; sx++ )
{
assert( k < ssize*2 );
tab[k].di = dx * cn;
tab[k].si = sx * cn;
tab[k++].alpha = float(1.0 / cellWidth);
}
if( fsx2 - sx2 > 1e-3 )
{
assert( k < ssize*2 );
tab[k].di = dx * cn;
tab[k].si = sx2 * cn;
tab[k++].alpha = (float)(std::min(std::min(fsx2 - sx2, 1.), cellWidth) / cellWidth);
}
}
return k;
}
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#define CHECK_IPP_STATUS(STATUS) if (STATUS < 0) { *ok = false; return; }
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#define SET_IPP_RESIZE_LINEAR_FUNC_PTR(TYPE, CN) \
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func = (ippiResizeFunc)ippiResizeLinear_##TYPE##_##CN##R; \
CHECK_IPP_STATUS(ippiResizeGetSize_##TYPE(srcSize, dstSize, (IppiInterpolationType)mode, 0, &specSize, &initSize));\
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specBuf.allocate(specSize);\
pSpec = (uchar*)specBuf;\
CHECK_IPP_STATUS(ippiResizeLinearInit_##TYPE(srcSize, dstSize, (IppiResizeSpec_32f*)pSpec));
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#define SET_IPP_RESIZE_LINEAR_FUNC_64_PTR(TYPE, CN) \
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if (mode == (int)ippCubic) { *ok = false; return; } \
func = (ippiResizeFunc)ippiResizeLinear_##TYPE##_##CN##R; \
CHECK_IPP_STATUS(ippiResizeGetSize_##TYPE(srcSize, dstSize, (IppiInterpolationType)mode, 0, &specSize, &initSize));\
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specBuf.allocate(specSize);\
pSpec = (uchar*)specBuf;\
CHECK_IPP_STATUS(ippiResizeLinearInit_##TYPE(srcSize, dstSize, (IppiResizeSpec_64f*)pSpec));\
getBufferSizeFunc = (ippiResizeGetBufferSize)ippiResizeGetBufferSize_##TYPE;\
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getSrcOffsetFunc = (ippiResizeGetSrcOffset) ippiResizeGetSrcOffset_##TYPE;
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#define SET_IPP_RESIZE_CUBIC_FUNC_PTR(TYPE, CN) \
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func = (ippiResizeFunc)ippiResizeCubic_##TYPE##_##CN##R; \
CHECK_IPP_STATUS(ippiResizeGetSize_##TYPE(srcSize, dstSize, (IppiInterpolationType)mode, 0, &specSize, &initSize));\
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specBuf.allocate(specSize);\
pSpec = (uchar*)specBuf;\
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AutoBuffer<uchar> buf(initSize);\
uchar* pInit = (uchar*)buf;\
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CHECK_IPP_STATUS(ippiResizeCubicInit_##TYPE(srcSize, dstSize, 0.f, 0.75f, (IppiResizeSpec_32f*)pSpec, pInit));
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#define SET_IPP_RESIZE_PTR(TYPE, CN) \
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if (mode == (int)ippLinear) { SET_IPP_RESIZE_LINEAR_FUNC_PTR(TYPE, CN);} \
else if (mode == (int)ippCubic) { SET_IPP_RESIZE_CUBIC_FUNC_PTR(TYPE, CN);} \
else { *ok = false; return; } \
getBufferSizeFunc = (ippiResizeGetBufferSize)ippiResizeGetBufferSize_##TYPE; \
getSrcOffsetFunc = (ippiResizeGetSrcOffset)ippiResizeGetSrcOffset_##TYPE;
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#if IPP_VERSION_X100 >= 701
class IPPresizeInvoker :
public ParallelLoopBody
{
public:
IPPresizeInvoker(const Mat & _src, Mat & _dst, double _inv_scale_x, double _inv_scale_y, int _mode, bool *_ok) :
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ParallelLoopBody(), src(_src), dst(_dst), inv_scale_x(_inv_scale_x),
inv_scale_y(_inv_scale_y), pSpec(NULL), mode(_mode),
func(NULL), getBufferSizeFunc(NULL), getSrcOffsetFunc(NULL), ok(_ok)
{
*ok = true;
IppiSize srcSize, dstSize;
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int type = src.type(), specSize = 0, initSize = 0;
srcSize.width = src.cols;
srcSize.height = src.rows;
dstSize.width = dst.cols;
dstSize.height = dst.rows;
switch (type)
{
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#if 0 // disabled since it breaks tests for CascadeClassifier
case CV_8UC1: SET_IPP_RESIZE_PTR(8u,C1); break;
case CV_8UC3: SET_IPP_RESIZE_PTR(8u,C3); break;
case CV_8UC4: SET_IPP_RESIZE_PTR(8u,C4); break;
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#endif
case CV_16UC1: SET_IPP_RESIZE_PTR(16u,C1); break;
case CV_16UC3: SET_IPP_RESIZE_PTR(16u,C3); break;
case CV_16UC4: SET_IPP_RESIZE_PTR(16u,C4); break;
case CV_16SC1: SET_IPP_RESIZE_PTR(16s,C1); break;
case CV_16SC3: SET_IPP_RESIZE_PTR(16s,C3); break;
case CV_16SC4: SET_IPP_RESIZE_PTR(16s,C4); break;
case CV_32FC1: SET_IPP_RESIZE_PTR(32f,C1); break;
case CV_32FC3: SET_IPP_RESIZE_PTR(32f,C3); break;
case CV_32FC4: SET_IPP_RESIZE_PTR(32f,C4); break;
case CV_64FC1: SET_IPP_RESIZE_LINEAR_FUNC_64_PTR(64f,C1); break;
case CV_64FC3: SET_IPP_RESIZE_LINEAR_FUNC_64_PTR(64f,C3); break;
case CV_64FC4: SET_IPP_RESIZE_LINEAR_FUNC_64_PTR(64f,C4); break;
default: { *ok = false; return; } break;
}
}
~IPPresizeInvoker()
{
}
virtual void operator() (const Range& range) const
{
if (*ok == false)
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return;
int cn = src.channels();
int dsty = min(cvRound(range.start * inv_scale_y), dst.rows);
int dstwidth = min(cvRound(src.cols * inv_scale_x), dst.cols);
int dstheight = min(cvRound(range.end * inv_scale_y), dst.rows);
IppiPoint dstOffset = { 0, dsty }, srcOffset = {0, 0};
IppiSize dstSize = { dstwidth, dstheight - dsty };
int bufsize = 0, itemSize = (int)src.elemSize1();
CHECK_IPP_STATUS(getBufferSizeFunc(pSpec, dstSize, cn, &bufsize));
CHECK_IPP_STATUS(getSrcOffsetFunc(pSpec, dstOffset, &srcOffset));
const Ipp8u* pSrc = (const Ipp8u*)src.data + (int)src.step[0] * srcOffset.y + srcOffset.x * cn * itemSize;
Ipp8u* pDst = (Ipp8u*)dst.data + (int)dst.step[0] * dstOffset.y + dstOffset.x * cn * itemSize;
AutoBuffer<uchar> buf(bufsize + 64);
uchar* bufptr = alignPtr((uchar*)buf, 32);
if( func( pSrc, (int)src.step[0], pDst, (int)dst.step[0], dstOffset, dstSize, ippBorderRepl, 0, pSpec, bufptr ) < 0 )
*ok = false;
}
private:
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const Mat & src;
Mat & dst;
double inv_scale_x;
double inv_scale_y;
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void *pSpec;
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AutoBuffer<uchar> specBuf;
int mode;
ippiResizeFunc func;
ippiResizeGetBufferSize getBufferSizeFunc;
ippiResizeGetSrcOffset getSrcOffsetFunc;
bool *ok;
const IPPresizeInvoker& operator= (const IPPresizeInvoker&);
};
#endif
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#ifdef HAVE_OPENCL
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static void ocl_computeResizeAreaTabs(int ssize, int dsize, double scale, int * const map_tab,
float * const alpha_tab, int * const ofs_tab)
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{
int k = 0, dx = 0;
for ( ; dx < dsize; dx++)
{
ofs_tab[dx] = k;
double fsx1 = dx * scale;
double fsx2 = fsx1 + scale;
double cellWidth = std::min(scale, ssize - fsx1);
int sx1 = cvCeil(fsx1), sx2 = cvFloor(fsx2);
sx2 = std::min(sx2, ssize - 1);
sx1 = std::min(sx1, sx2);
if (sx1 - fsx1 > 1e-3)
{
map_tab[k] = sx1 - 1;
alpha_tab[k++] = (float)((sx1 - fsx1) / cellWidth);
}
for (int sx = sx1; sx < sx2; sx++)
{
map_tab[k] = sx;
alpha_tab[k++] = float(1.0 / cellWidth);
}
if (fsx2 - sx2 > 1e-3)
{
map_tab[k] = sx2;
alpha_tab[k++] = (float)(std::min(std::min(fsx2 - sx2, 1.), cellWidth) / cellWidth);
}
}
ofs_tab[dx] = k;
}
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static bool ocl_resize( InputArray _src, OutputArray _dst, Size dsize,
double fx, double fy, int interpolation)
{
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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double inv_fx = 1.0 / fx, inv_fy = 1.0 / fy;
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float inv_fxf = (float)inv_fx, inv_fyf = (float)inv_fy;
int iscale_x = saturate_cast<int>(inv_fx), iscale_y = saturate_cast<int>(inv_fx);
bool is_area_fast = std::abs(inv_fx - iscale_x) < DBL_EPSILON &&
std::abs(inv_fy - iscale_y) < DBL_EPSILON;
// in case of scale_x && scale_y is equal to 2
// INTER_AREA (fast) also is equal to INTER_LINEAR
if( interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 )
/*interpolation = INTER_AREA*/(void)0; // INTER_AREA is slower
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if( !(cn <= 4 &&
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(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR ||
(interpolation == INTER_AREA && inv_fx >= 1 && inv_fy >= 1) )) )
return false;
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UMat src = _src.getUMat();
_dst.create(dsize, type);
UMat dst = _dst.getUMat();
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Size ssize = src.size();
ocl::Kernel k;
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size_t globalsize[] = { dst.cols, dst.rows };
ocl::Image2D srcImage;
// See if this could be done with a sampler. We stick with integer
// datatypes because the observed error is low.
bool useSampler = (interpolation == INTER_LINEAR && ocl::Device::getDefault().imageSupport() &&
ocl::Image2D::canCreateAlias(src) && depth <= 4 &&
ocl::Image2D::isFormatSupported(depth, cn, true));
if (useSampler)
{
int wdepth = std::max(depth, CV_32S);
char buf[2][32];
cv::String compileOpts = format("-D USE_SAMPLER -D depth=%d -D T=%s -D T1=%s "
"-D convertToDT=%s -D cn=%d",
depth, ocl::typeToStr(type), ocl::typeToStr(depth),
ocl::convertTypeStr(wdepth, depth, cn, buf[1]),
cn);
k.create("resizeSampler", ocl::imgproc::resize_oclsrc, compileOpts);
if (k.empty())
useSampler = false;
else
{
// Convert the input into an OpenCL image type, using normalized channel data types
// and aliasing the UMat.
srcImage = ocl::Image2D(src, true, true);
k.args(srcImage, ocl::KernelArg::WriteOnly(dst),
(float)inv_fx, (float)inv_fy);
}
}
if (interpolation == INTER_LINEAR && !useSampler)
{
char buf[2][32];
// integer path is slower because of CPU part, so it's disabled
if (depth == CV_8U && ((void)0, 0))
{
AutoBuffer<uchar> _buffer((dsize.width + dsize.height)*(sizeof(int) + sizeof(short)*2));
int* xofs = (int*)(uchar*)_buffer, * yofs = xofs + dsize.width;
short* ialpha = (short*)(yofs + dsize.height), * ibeta = ialpha + dsize.width*2;
float fxx, fyy;
int sx, sy;
for (int dx = 0; dx < dsize.width; dx++)
{
fxx = (float)((dx+0.5)*inv_fx - 0.5);
sx = cvFloor(fxx);
fxx -= sx;
if (sx < 0)
fxx = 0, sx = 0;
if (sx >= ssize.width-1)
fxx = 0, sx = ssize.width-1;
xofs[dx] = sx;
ialpha[dx*2 + 0] = saturate_cast<short>((1.f - fxx) * INTER_RESIZE_COEF_SCALE);
ialpha[dx*2 + 1] = saturate_cast<short>(fxx * INTER_RESIZE_COEF_SCALE);
}
for (int dy = 0; dy < dsize.height; dy++)
{
fyy = (float)((dy+0.5)*inv_fy - 0.5);
sy = cvFloor(fyy);
fyy -= sy;
yofs[dy] = sy;
ibeta[dy*2 + 0] = saturate_cast<short>((1.f - fyy) * INTER_RESIZE_COEF_SCALE);
ibeta[dy*2 + 1] = saturate_cast<short>(fyy * INTER_RESIZE_COEF_SCALE);
}
int wdepth = std::max(depth, CV_32S), wtype = CV_MAKETYPE(wdepth, cn);
UMat coeffs;
Mat(1, static_cast<int>(_buffer.size()), CV_8UC1, (uchar *)_buffer).copyTo(coeffs);
k.create("resizeLN", ocl::imgproc::resize_oclsrc,
format("-D INTER_LINEAR_INTEGER -D depth=%d -D T=%s -D T1=%s "
"-D WT=%s -D convertToWT=%s -D convertToDT=%s -D cn=%d "
"-D INTER_RESIZE_COEF_BITS=%d",
depth, ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(wtype),
ocl::convertTypeStr(depth, wdepth, cn, buf[0]),
ocl::convertTypeStr(wdepth, depth, cn, buf[1]),
cn, INTER_RESIZE_COEF_BITS));
if (k.empty())
return false;
k.args(ocl::KernelArg::ReadOnly(src), ocl::KernelArg::WriteOnly(dst),
ocl::KernelArg::PtrReadOnly(coeffs));
}
else
{
int wdepth = std::max(depth, CV_32S), wtype = CV_MAKETYPE(wdepth, cn);
k.create("resizeLN", ocl::imgproc::resize_oclsrc,
format("-D INTER_LINEAR -D depth=%d -D T=%s -D T1=%s "
"-D WT=%s -D convertToWT=%s -D convertToDT=%s -D cn=%d "
"-D INTER_RESIZE_COEF_BITS=%d",
depth, ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(wtype),
ocl::convertTypeStr(depth, wdepth, cn, buf[0]),
ocl::convertTypeStr(wdepth, depth, cn, buf[1]),
cn, INTER_RESIZE_COEF_BITS));
if (k.empty())
return false;
k.args(ocl::KernelArg::ReadOnly(src), ocl::KernelArg::WriteOnly(dst),
(float)inv_fx, (float)inv_fy);
}
}
else if (interpolation == INTER_NEAREST)
{
k.create("resizeNN", ocl::imgproc::resize_oclsrc,
format("-D INTER_NEAREST -D T=%s -D T1=%s -D cn=%d",
ocl::memopTypeToStr(type), ocl::memopTypeToStr(depth), cn));
if (k.empty())
return false;
k.args(ocl::KernelArg::ReadOnly(src), ocl::KernelArg::WriteOnly(dst),
(float)inv_fx, (float)inv_fy);
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}
else if (interpolation == INTER_AREA)
{
int wdepth = std::max(depth, is_area_fast ? CV_32S : CV_32F);
int wtype = CV_MAKE_TYPE(wdepth, cn);
char cvt[2][40];
String buildOption = format("-D INTER_AREA -D T=%s -D T1=%s -D WTV=%s -D convertToWTV=%s -D cn=%d",
ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(wtype),
ocl::convertTypeStr(depth, wdepth, cn, cvt[0]), cn);
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UMat alphaOcl, tabofsOcl, mapOcl;
UMat dmap, smap;
if (is_area_fast)
{
int wdepth2 = std::max(CV_32F, depth), wtype2 = CV_MAKE_TYPE(wdepth2, cn);
buildOption = buildOption + format(" -D convertToT=%s -D WT2V=%s -D convertToWT2V=%s -D INTER_AREA_FAST"
" -D XSCALE=%d -D YSCALE=%d -D SCALE=%ff",
ocl::convertTypeStr(wdepth2, depth, cn, cvt[0]),
ocl::typeToStr(wtype2), ocl::convertTypeStr(wdepth, wdepth2, cn, cvt[1]),
iscale_x, iscale_y, 1.0f / (iscale_x * iscale_y));
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k.create("resizeAREA_FAST", ocl::imgproc::resize_oclsrc, buildOption);
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if (k.empty())
return false;
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}
else
{
buildOption = buildOption + format(" -D convertToT=%s", ocl::convertTypeStr(wdepth, depth, cn, cvt[0]));
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k.create("resizeAREA", ocl::imgproc::resize_oclsrc, buildOption);
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if (k.empty())
return false;
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int xytab_size = (ssize.width + ssize.height) << 1;
int tabofs_size = dsize.height + dsize.width + 2;
AutoBuffer<int> _xymap_tab(xytab_size), _xyofs_tab(tabofs_size);
AutoBuffer<float> _xyalpha_tab(xytab_size);
int * xmap_tab = _xymap_tab, * ymap_tab = _xymap_tab + (ssize.width << 1);
float * xalpha_tab = _xyalpha_tab, * yalpha_tab = _xyalpha_tab + (ssize.width << 1);
int * xofs_tab = _xyofs_tab, * yofs_tab = _xyofs_tab + dsize.width + 1;
ocl_computeResizeAreaTabs(ssize.width, dsize.width, inv_fx, xmap_tab, xalpha_tab, xofs_tab);
ocl_computeResizeAreaTabs(ssize.height, dsize.height, inv_fy, ymap_tab, yalpha_tab, yofs_tab);
// loading precomputed arrays to GPU
Mat(1, xytab_size, CV_32FC1, (void *)_xyalpha_tab).copyTo(alphaOcl);
Mat(1, xytab_size, CV_32SC1, (void *)_xymap_tab).copyTo(mapOcl);
Mat(1, tabofs_size, CV_32SC1, (void *)_xyofs_tab).copyTo(tabofsOcl);
}
ocl::KernelArg srcarg = ocl::KernelArg::ReadOnly(src), dstarg = ocl::KernelArg::WriteOnly(dst);
if (is_area_fast)
k.args(srcarg, dstarg);
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else
k.args(srcarg, dstarg, inv_fxf, inv_fyf, ocl::KernelArg::PtrReadOnly(tabofsOcl),
ocl::KernelArg::PtrReadOnly(mapOcl), ocl::KernelArg::PtrReadOnly(alphaOcl));
return k.run(2, globalsize, NULL, false);
}
return k.run(2, globalsize, 0, false);
}
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#endif
}
//////////////////////////////////////////////////////////////////////////////////////////
void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
double inv_scale_x, double inv_scale_y, int interpolation )
{
static ResizeFunc linear_tab[] =
{
resizeGeneric_<
HResizeLinear<uchar, int, short,
INTER_RESIZE_COEF_SCALE,
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HResizeLinearVec_8u32s>,
VResizeLinear<uchar, int, short,
FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
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VResizeLinearVec_32s8u> >,
0,
resizeGeneric_<
HResizeLinear<ushort, float, float, 1,
HResizeLinearVec_16u32f>,
VResizeLinear<ushort, float, float, Cast<float, ushort>,
VResizeLinearVec_32f16u> >,
resizeGeneric_<
HResizeLinear<short, float, float, 1,
HResizeLinearVec_16s32f>,
VResizeLinear<short, float, float, Cast<float, short>,
VResizeLinearVec_32f16s> >,
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0,
resizeGeneric_<
HResizeLinear<float, float, float, 1,
HResizeLinearVec_32f>,
VResizeLinear<float, float, float, Cast<float, float>,
VResizeLinearVec_32f> >,
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resizeGeneric_<
HResizeLinear<double, double, float, 1,
HResizeNoVec>,
VResizeLinear<double, double, float, Cast<double, double>,
VResizeNoVec> >,
0
};
static ResizeFunc cubic_tab[] =
{
resizeGeneric_<
HResizeCubic<uchar, int, short>,
VResizeCubic<uchar, int, short,
FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
VResizeCubicVec_32s8u> >,
0,
resizeGeneric_<
HResizeCubic<ushort, float, float>,
VResizeCubic<ushort, float, float, Cast<float, ushort>,
VResizeCubicVec_32f16u> >,
resizeGeneric_<
HResizeCubic<short, float, float>,
VResizeCubic<short, float, float, Cast<float, short>,
VResizeCubicVec_32f16s> >,
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0,
resizeGeneric_<
HResizeCubic<float, float, float>,
VResizeCubic<float, float, float, Cast<float, float>,
VResizeCubicVec_32f> >,
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resizeGeneric_<
HResizeCubic<double, double, float>,
VResizeCubic<double, double, float, Cast<double, double>,
VResizeNoVec> >,
0
};
static ResizeFunc lanczos4_tab[] =
{
resizeGeneric_<HResizeLanczos4<uchar, int, short>,
VResizeLanczos4<uchar, int, short,
FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
VResizeNoVec> >,
0,
resizeGeneric_<HResizeLanczos4<ushort, float, float>,
VResizeLanczos4<ushort, float, float, Cast<float, ushort>,
VResizeNoVec> >,
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resizeGeneric_<HResizeLanczos4<short, float, float>,
VResizeLanczos4<short, float, float, Cast<float, short>,
VResizeNoVec> >,
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0,
resizeGeneric_<HResizeLanczos4<float, float, float>,
VResizeLanczos4<float, float, float, Cast<float, float>,
VResizeNoVec> >,
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resizeGeneric_<HResizeLanczos4<double, double, float>,
VResizeLanczos4<double, double, float, Cast<double, double>,
VResizeNoVec> >,
0
};
static ResizeAreaFastFunc areafast_tab[] =
{
resizeAreaFast_<uchar, int, ResizeAreaFastVec<uchar, ResizeAreaFastVec_SIMD_8u> >,
0,
resizeAreaFast_<ushort, float, ResizeAreaFastVec<ushort, ResizeAreaFastVec_SIMD_16u> >,
resizeAreaFast_<short, float, ResizeAreaFastVec<short, ResizeAreaFastNoVec<short, float> > >,
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0,
resizeAreaFast_<float, float, ResizeAreaFastNoVec<float, float> >,
resizeAreaFast_<double, double, ResizeAreaFastNoVec<double, double> >,
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0
};
static ResizeAreaFunc area_tab[] =
{
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resizeArea_<uchar, float>, 0, resizeArea_<ushort, float>,
resizeArea_<short, float>, 0, resizeArea_<float, float>,
resizeArea_<double, double>, 0
};
Size ssize = _src.size();
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CV_Assert( ssize.area() > 0 );
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CV_Assert( dsize.area() > 0 || (inv_scale_x > 0 && inv_scale_y > 0) );
if( dsize.area() == 0 )
{
dsize = Size(saturate_cast<int>(ssize.width*inv_scale_x),
saturate_cast<int>(ssize.height*inv_scale_y));
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CV_Assert( dsize.area() > 0 );
}
else
{
inv_scale_x = (double)dsize.width/ssize.width;
inv_scale_y = (double)dsize.height/ssize.height;
}
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CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_resize(_src, _dst, dsize, inv_scale_x, inv_scale_y, interpolation))
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Mat src = _src.getMat();
_dst.create(dsize, src.type());
Mat dst = _dst.getMat();
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#ifdef HAVE_TEGRA_OPTIMIZATION
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if (tegra::resize(src, dst, (float)inv_scale_x, (float)inv_scale_y, interpolation))
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return;
#endif
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int type = src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
double scale_x = 1./inv_scale_x, scale_y = 1./inv_scale_y;
int k, sx, sy, dx, dy;
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int iscale_x = saturate_cast<int>(scale_x);
int iscale_y = saturate_cast<int>(scale_y);
bool is_area_fast = std::abs(scale_x - iscale_x) < DBL_EPSILON &&
std::abs(scale_y - iscale_y) < DBL_EPSILON;
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#if IPP_VERSION_X100 >= 701
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#define IPP_RESIZE_EPS 1e-10
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double ex = fabs((double)dsize.width / src.cols - inv_scale_x) / inv_scale_x;
double ey = fabs((double)dsize.height / src.rows - inv_scale_y) / inv_scale_y;
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if ( ((ex < IPP_RESIZE_EPS && ey < IPP_RESIZE_EPS && depth != CV_64F) || (ex == 0 && ey == 0 && depth == CV_64F)) &&
(interpolation == INTER_LINEAR || interpolation == INTER_CUBIC) &&
!(interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 && depth == CV_8U))
{
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int mode = -1;
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if (interpolation == INTER_LINEAR && src.rows >= 2 && src.cols >= 2)
mode = ippLinear;
else if (interpolation == INTER_CUBIC && src.rows >= 4 && src.cols >= 4)
mode = ippCubic;
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if( mode >= 0 && (cn == 1 || cn == 3 || cn == 4) &&
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(depth == CV_16U || depth == CV_16S || depth == CV_32F ||
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(depth == CV_64F && mode == ippLinear)))
{
bool ok = true;
Range range(0, src.rows);
IPPresizeInvoker invoker(src, dst, inv_scale_x, inv_scale_y, mode, &ok);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
if( ok )
return;
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setIppErrorStatus();
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}
}
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#undef IPP_RESIZE_EPS
#endif
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if( interpolation == INTER_NEAREST )
{
resizeNN( src, dst, inv_scale_x, inv_scale_y );
return;
}
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{
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// in case of scale_x && scale_y is equal to 2
// INTER_AREA (fast) also is equal to INTER_LINEAR
if( interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 )
interpolation = INTER_AREA;
// true "area" interpolation is only implemented for the case (scale_x <= 1 && scale_y <= 1).
// In other cases it is emulated using some variant of bilinear interpolation
if( interpolation == INTER_AREA && scale_x >= 1 && scale_y >= 1 )
{
if( is_area_fast )
{
int area = iscale_x*iscale_y;
size_t srcstep = src.step / src.elemSize1();
AutoBuffer<int> _ofs(area + dsize.width*cn);
int* ofs = _ofs;
int* xofs = ofs + area;
ResizeAreaFastFunc func = areafast_tab[depth];
CV_Assert( func != 0 );
for( sy = 0, k = 0; sy < iscale_y; sy++ )
for( sx = 0; sx < iscale_x; sx++ )
ofs[k++] = (int)(sy*srcstep + sx*cn);
for( dx = 0; dx < dsize.width; dx++ )
{
int j = dx * cn;
sx = iscale_x * j;
for( k = 0; k < cn; k++ )
xofs[j + k] = sx + k;
}
func( src, dst, ofs, xofs, iscale_x, iscale_y );
return;
}
ResizeAreaFunc func = area_tab[depth];
CV_Assert( func != 0 && cn <= 4 );
AutoBuffer<DecimateAlpha> _xytab((ssize.width + ssize.height)*2);
DecimateAlpha* xtab = _xytab, *ytab = xtab + ssize.width*2;
int xtab_size = computeResizeAreaTab(ssize.width, dsize.width, cn, scale_x, xtab);
int ytab_size = computeResizeAreaTab(ssize.height, dsize.height, 1, scale_y, ytab);
AutoBuffer<int> _tabofs(dsize.height + 1);
int* tabofs = _tabofs;
for( k = 0, dy = 0; k < ytab_size; k++ )
{
if( k == 0 || ytab[k].di != ytab[k-1].di )
{
assert( ytab[k].di == dy );
tabofs[dy++] = k;
}
}
tabofs[dy] = ytab_size;
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func( src, dst, xtab, xtab_size, ytab, ytab_size, tabofs );
return;
}
}
int xmin = 0, xmax = dsize.width, width = dsize.width*cn;
bool area_mode = interpolation == INTER_AREA;
bool fixpt = depth == CV_8U;
float fx, fy;
ResizeFunc func=0;
int ksize=0, ksize2;
if( interpolation == INTER_CUBIC )
ksize = 4, func = cubic_tab[depth];
else if( interpolation == INTER_LANCZOS4 )
ksize = 8, func = lanczos4_tab[depth];
else if( interpolation == INTER_LINEAR || interpolation == INTER_AREA )
ksize = 2, func = linear_tab[depth];
else
CV_Error( CV_StsBadArg, "Unknown interpolation method" );
ksize2 = ksize/2;
CV_Assert( func != 0 );
AutoBuffer<uchar> _buffer((width + dsize.height)*(sizeof(int) + sizeof(float)*ksize));
int* xofs = (int*)(uchar*)_buffer;
int* yofs = xofs + width;
float* alpha = (float*)(yofs + dsize.height);
short* ialpha = (short*)alpha;
float* beta = alpha + width*ksize;
short* ibeta = ialpha + width*ksize;
float cbuf[MAX_ESIZE];
for( dx = 0; dx < dsize.width; dx++ )
{
if( !area_mode )
{
fx = (float)((dx+0.5)*scale_x - 0.5);
sx = cvFloor(fx);
fx -= sx;
}
else
{
sx = cvFloor(dx*scale_x);
fx = (float)((dx+1) - (sx+1)*inv_scale_x);
fx = fx <= 0 ? 0.f : fx - cvFloor(fx);
}
if( sx < ksize2-1 )
{
xmin = dx+1;
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if( sx < 0 && (interpolation != INTER_CUBIC && interpolation != INTER_LANCZOS4))
fx = 0, sx = 0;
}
if( sx + ksize2 >= ssize.width )
{
xmax = std::min( xmax, dx );
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if( sx >= ssize.width-1 && (interpolation != INTER_CUBIC && interpolation != INTER_LANCZOS4))
fx = 0, sx = ssize.width-1;
}
for( k = 0, sx *= cn; k < cn; k++ )
xofs[dx*cn + k] = sx + k;
if( interpolation == INTER_CUBIC )
interpolateCubic( fx, cbuf );
else if( interpolation == INTER_LANCZOS4 )
interpolateLanczos4( fx, cbuf );
else
{
cbuf[0] = 1.f - fx;
cbuf[1] = fx;
}
if( fixpt )
{
for( k = 0; k < ksize; k++ )
ialpha[dx*cn*ksize + k] = saturate_cast<short>(cbuf[k]*INTER_RESIZE_COEF_SCALE);
for( ; k < cn*ksize; k++ )
ialpha[dx*cn*ksize + k] = ialpha[dx*cn*ksize + k - ksize];
}
else
{
for( k = 0; k < ksize; k++ )
alpha[dx*cn*ksize + k] = cbuf[k];
for( ; k < cn*ksize; k++ )
alpha[dx*cn*ksize + k] = alpha[dx*cn*ksize + k - ksize];
}
}
for( dy = 0; dy < dsize.height; dy++ )
{
if( !area_mode )
{
fy = (float)((dy+0.5)*scale_y - 0.5);
sy = cvFloor(fy);
fy -= sy;
}
else
{
sy = cvFloor(dy*scale_y);
fy = (float)((dy+1) - (sy+1)*inv_scale_y);
fy = fy <= 0 ? 0.f : fy - cvFloor(fy);
}
yofs[dy] = sy;
if( interpolation == INTER_CUBIC )
interpolateCubic( fy, cbuf );
else if( interpolation == INTER_LANCZOS4 )
interpolateLanczos4( fy, cbuf );
else
{
cbuf[0] = 1.f - fy;
cbuf[1] = fy;
}
if( fixpt )
{
for( k = 0; k < ksize; k++ )
ibeta[dy*ksize + k] = saturate_cast<short>(cbuf[k]*INTER_RESIZE_COEF_SCALE);
}
else
{
for( k = 0; k < ksize; k++ )
beta[dy*ksize + k] = cbuf[k];
}
}
func( src, dst, xofs, fixpt ? (void*)ialpha : (void*)alpha, yofs,
fixpt ? (void*)ibeta : (void*)beta, xmin, xmax, ksize );
}
/****************************************************************************************\
* General warping (affine, perspective, remap) *
\****************************************************************************************/
namespace cv
{
template<typename T>
static void remapNearest( const Mat& _src, Mat& _dst, const Mat& _xy,
int borderType, const Scalar& _borderValue )
{
Size ssize = _src.size(), dsize = _dst.size();
int cn = _src.channels();
const T* S0 = (const T*)_src.data;
size_t sstep = _src.step/sizeof(S0[0]);
Scalar_<T> cval(saturate_cast<T>(_borderValue[0]),
saturate_cast<T>(_borderValue[1]),
saturate_cast<T>(_borderValue[2]),
saturate_cast<T>(_borderValue[3]));
int dx, dy;
unsigned width1 = ssize.width, height1 = ssize.height;
if( _dst.isContinuous() && _xy.isContinuous() )
{
dsize.width *= dsize.height;
dsize.height = 1;
}
for( dy = 0; dy < dsize.height; dy++ )
{
T* D = (T*)(_dst.data + _dst.step*dy);
const short* XY = (const short*)(_xy.data + _xy.step*dy);
if( cn == 1 )
{
for( dx = 0; dx < dsize.width; dx++ )
{
int sx = XY[dx*2], sy = XY[dx*2+1];
if( (unsigned)sx < width1 && (unsigned)sy < height1 )
D[dx] = S0[sy*sstep + sx];
else
{
if( borderType == BORDER_REPLICATE )
{
sx = clip(sx, 0, ssize.width);
sy = clip(sy, 0, ssize.height);
D[dx] = S0[sy*sstep + sx];
}
else if( borderType == BORDER_CONSTANT )
D[dx] = cval[0];
else if( borderType != BORDER_TRANSPARENT )
{
sx = borderInterpolate(sx, ssize.width, borderType);
sy = borderInterpolate(sy, ssize.height, borderType);
D[dx] = S0[sy*sstep + sx];
}
}
}
}
else
{
for( dx = 0; dx < dsize.width; dx++, D += cn )
{
int sx = XY[dx*2], sy = XY[dx*2+1], k;
const T *S;
if( (unsigned)sx < width1 && (unsigned)sy < height1 )
{
if( cn == 3 )
{
S = S0 + sy*sstep + sx*3;
D[0] = S[0], D[1] = S[1], D[2] = S[2];
}
else if( cn == 4 )
{
S = S0 + sy*sstep + sx*4;
D[0] = S[0], D[1] = S[1], D[2] = S[2], D[3] = S[3];
}
else
{
S = S0 + sy*sstep + sx*cn;
for( k = 0; k < cn; k++ )
D[k] = S[k];
}
}
else if( borderType != BORDER_TRANSPARENT )
{
if( borderType == BORDER_REPLICATE )
{
sx = clip(sx, 0, ssize.width);
sy = clip(sy, 0, ssize.height);
S = S0 + sy*sstep + sx*cn;
}
else if( borderType == BORDER_CONSTANT )
S = &cval[0];
else
{
sx = borderInterpolate(sx, ssize.width, borderType);
sy = borderInterpolate(sy, ssize.height, borderType);
S = S0 + sy*sstep + sx*cn;
}
for( k = 0; k < cn; k++ )
D[k] = S[k];
}
}
}
}
}
struct RemapNoVec
{
int operator()( const Mat&, void*, const short*, const ushort*,
const void*, int ) const { return 0; }
};
#if CV_SSE2
struct RemapVec_8u
{
int operator()( const Mat& _src, void* _dst, const short* XY,
const ushort* FXY, const void* _wtab, int width ) const
{
int cn = _src.channels(), x = 0, sstep = (int)_src.step;
if( (cn != 1 && cn != 3 && cn != 4) || !checkHardwareSupport(CV_CPU_SSE2) ||
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sstep > 0x8000 )
return 0;
const uchar *S0 = _src.data, *S1 = _src.data + _src.step;
const short* wtab = cn == 1 ? (const short*)_wtab : &BilinearTab_iC4[0][0][0];
uchar* D = (uchar*)_dst;
__m128i delta = _mm_set1_epi32(INTER_REMAP_COEF_SCALE/2);
__m128i xy2ofs = _mm_set1_epi32(cn + (sstep << 16));
__m128i z = _mm_setzero_si128();
int CV_DECL_ALIGNED(16) iofs0[4], iofs1[4];
if( cn == 1 )
{
for( ; x <= width - 8; x += 8 )
{
__m128i xy0 = _mm_loadu_si128( (const __m128i*)(XY + x*2));
__m128i xy1 = _mm_loadu_si128( (const __m128i*)(XY + x*2 + 8));
__m128i v0, v1, v2, v3, a0, a1, b0, b1;
unsigned i0, i1;
xy0 = _mm_madd_epi16( xy0, xy2ofs );
xy1 = _mm_madd_epi16( xy1, xy2ofs );
_mm_store_si128( (__m128i*)iofs0, xy0 );
_mm_store_si128( (__m128i*)iofs1, xy1 );
i0 = *(ushort*)(S0 + iofs0[0]) + (*(ushort*)(S0 + iofs0[1]) << 16);
i1 = *(ushort*)(S0 + iofs0[2]) + (*(ushort*)(S0 + iofs0[3]) << 16);
v0 = _mm_unpacklo_epi32(_mm_cvtsi32_si128(i0), _mm_cvtsi32_si128(i1));
i0 = *(ushort*)(S1 + iofs0[0]) + (*(ushort*)(S1 + iofs0[1]) << 16);
i1 = *(ushort*)(S1 + iofs0[2]) + (*(ushort*)(S1 + iofs0[3]) << 16);
v1 = _mm_unpacklo_epi32(_mm_cvtsi32_si128(i0), _mm_cvtsi32_si128(i1));
v0 = _mm_unpacklo_epi8(v0, z);
v1 = _mm_unpacklo_epi8(v1, z);
a0 = _mm_unpacklo_epi32(_mm_loadl_epi64((__m128i*)(wtab+FXY[x]*4)),
_mm_loadl_epi64((__m128i*)(wtab+FXY[x+1]*4)));
a1 = _mm_unpacklo_epi32(_mm_loadl_epi64((__m128i*)(wtab+FXY[x+2]*4)),
_mm_loadl_epi64((__m128i*)(wtab+FXY[x+3]*4)));
b0 = _mm_unpacklo_epi64(a0, a1);
b1 = _mm_unpackhi_epi64(a0, a1);
v0 = _mm_madd_epi16(v0, b0);
v1 = _mm_madd_epi16(v1, b1);
v0 = _mm_add_epi32(_mm_add_epi32(v0, v1), delta);
i0 = *(ushort*)(S0 + iofs1[0]) + (*(ushort*)(S0 + iofs1[1]) << 16);
i1 = *(ushort*)(S0 + iofs1[2]) + (*(ushort*)(S0 + iofs1[3]) << 16);
v2 = _mm_unpacklo_epi32(_mm_cvtsi32_si128(i0), _mm_cvtsi32_si128(i1));
i0 = *(ushort*)(S1 + iofs1[0]) + (*(ushort*)(S1 + iofs1[1]) << 16);
i1 = *(ushort*)(S1 + iofs1[2]) + (*(ushort*)(S1 + iofs1[3]) << 16);
v3 = _mm_unpacklo_epi32(_mm_cvtsi32_si128(i0), _mm_cvtsi32_si128(i1));
v2 = _mm_unpacklo_epi8(v2, z);
v3 = _mm_unpacklo_epi8(v3, z);
a0 = _mm_unpacklo_epi32(_mm_loadl_epi64((__m128i*)(wtab+FXY[x+4]*4)),
_mm_loadl_epi64((__m128i*)(wtab+FXY[x+5]*4)));
a1 = _mm_unpacklo_epi32(_mm_loadl_epi64((__m128i*)(wtab+FXY[x+6]*4)),
_mm_loadl_epi64((__m128i*)(wtab+FXY[x+7]*4)));
b0 = _mm_unpacklo_epi64(a0, a1);
b1 = _mm_unpackhi_epi64(a0, a1);
v2 = _mm_madd_epi16(v2, b0);
v3 = _mm_madd_epi16(v3, b1);
v2 = _mm_add_epi32(_mm_add_epi32(v2, v3), delta);
v0 = _mm_srai_epi32(v0, INTER_REMAP_COEF_BITS);
v2 = _mm_srai_epi32(v2, INTER_REMAP_COEF_BITS);
v0 = _mm_packus_epi16(_mm_packs_epi32(v0, v2), z);
_mm_storel_epi64( (__m128i*)(D + x), v0 );
}
}
else if( cn == 3 )
{
for( ; x <= width - 5; x += 4, D += 12 )
{
__m128i xy0 = _mm_loadu_si128( (const __m128i*)(XY + x*2));
__m128i u0, v0, u1, v1;
xy0 = _mm_madd_epi16( xy0, xy2ofs );
_mm_store_si128( (__m128i*)iofs0, xy0 );
const __m128i *w0, *w1;
w0 = (const __m128i*)(wtab + FXY[x]*16);
w1 = (const __m128i*)(wtab + FXY[x+1]*16);
u0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[0])),
_mm_cvtsi32_si128(*(int*)(S0 + iofs0[0] + 3)));
v0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[0])),
_mm_cvtsi32_si128(*(int*)(S1 + iofs0[0] + 3)));
u1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[1])),
_mm_cvtsi32_si128(*(int*)(S0 + iofs0[1] + 3)));
v1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[1])),
_mm_cvtsi32_si128(*(int*)(S1 + iofs0[1] + 3)));
u0 = _mm_unpacklo_epi8(u0, z);
v0 = _mm_unpacklo_epi8(v0, z);
u1 = _mm_unpacklo_epi8(u1, z);
v1 = _mm_unpacklo_epi8(v1, z);
u0 = _mm_add_epi32(_mm_madd_epi16(u0, w0[0]), _mm_madd_epi16(v0, w0[1]));
u1 = _mm_add_epi32(_mm_madd_epi16(u1, w1[0]), _mm_madd_epi16(v1, w1[1]));
u0 = _mm_srai_epi32(_mm_add_epi32(u0, delta), INTER_REMAP_COEF_BITS);
u1 = _mm_srai_epi32(_mm_add_epi32(u1, delta), INTER_REMAP_COEF_BITS);
u0 = _mm_slli_si128(u0, 4);
u0 = _mm_packs_epi32(u0, u1);
u0 = _mm_packus_epi16(u0, u0);
_mm_storel_epi64((__m128i*)D, _mm_srli_si128(u0,1));
w0 = (const __m128i*)(wtab + FXY[x+2]*16);
w1 = (const __m128i*)(wtab + FXY[x+3]*16);
u0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[2])),
_mm_cvtsi32_si128(*(int*)(S0 + iofs0[2] + 3)));
v0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[2])),
_mm_cvtsi32_si128(*(int*)(S1 + iofs0[2] + 3)));
u1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[3])),
_mm_cvtsi32_si128(*(int*)(S0 + iofs0[3] + 3)));
v1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[3])),
_mm_cvtsi32_si128(*(int*)(S1 + iofs0[3] + 3)));
u0 = _mm_unpacklo_epi8(u0, z);
v0 = _mm_unpacklo_epi8(v0, z);
u1 = _mm_unpacklo_epi8(u1, z);
v1 = _mm_unpacklo_epi8(v1, z);
u0 = _mm_add_epi32(_mm_madd_epi16(u0, w0[0]), _mm_madd_epi16(v0, w0[1]));
u1 = _mm_add_epi32(_mm_madd_epi16(u1, w1[0]), _mm_madd_epi16(v1, w1[1]));
u0 = _mm_srai_epi32(_mm_add_epi32(u0, delta), INTER_REMAP_COEF_BITS);
u1 = _mm_srai_epi32(_mm_add_epi32(u1, delta), INTER_REMAP_COEF_BITS);
u0 = _mm_slli_si128(u0, 4);
u0 = _mm_packs_epi32(u0, u1);
u0 = _mm_packus_epi16(u0, u0);
_mm_storel_epi64((__m128i*)(D + 6), _mm_srli_si128(u0,1));
}
}
else if( cn == 4 )
{
for( ; x <= width - 4; x += 4, D += 16 )
{
__m128i xy0 = _mm_loadu_si128( (const __m128i*)(XY + x*2));
__m128i u0, v0, u1, v1;
xy0 = _mm_madd_epi16( xy0, xy2ofs );
_mm_store_si128( (__m128i*)iofs0, xy0 );
const __m128i *w0, *w1;
w0 = (const __m128i*)(wtab + FXY[x]*16);
w1 = (const __m128i*)(wtab + FXY[x+1]*16);
u0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[0])),
_mm_cvtsi32_si128(*(int*)(S0 + iofs0[0] + 4)));
v0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[0])),
_mm_cvtsi32_si128(*(int*)(S1 + iofs0[0] + 4)));
u1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[1])),
_mm_cvtsi32_si128(*(int*)(S0 + iofs0[1] + 4)));
v1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[1])),
_mm_cvtsi32_si128(*(int*)(S1 + iofs0[1] + 4)));
u0 = _mm_unpacklo_epi8(u0, z);
v0 = _mm_unpacklo_epi8(v0, z);
u1 = _mm_unpacklo_epi8(u1, z);
v1 = _mm_unpacklo_epi8(v1, z);
u0 = _mm_add_epi32(_mm_madd_epi16(u0, w0[0]), _mm_madd_epi16(v0, w0[1]));
u1 = _mm_add_epi32(_mm_madd_epi16(u1, w1[0]), _mm_madd_epi16(v1, w1[1]));
u0 = _mm_srai_epi32(_mm_add_epi32(u0, delta), INTER_REMAP_COEF_BITS);
u1 = _mm_srai_epi32(_mm_add_epi32(u1, delta), INTER_REMAP_COEF_BITS);
u0 = _mm_packs_epi32(u0, u1);
u0 = _mm_packus_epi16(u0, u0);
_mm_storel_epi64((__m128i*)D, u0);
w0 = (const __m128i*)(wtab + FXY[x+2]*16);
w1 = (const __m128i*)(wtab + FXY[x+3]*16);
u0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[2])),
_mm_cvtsi32_si128(*(int*)(S0 + iofs0[2] + 4)));
v0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[2])),
_mm_cvtsi32_si128(*(int*)(S1 + iofs0[2] + 4)));
u1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[3])),
_mm_cvtsi32_si128(*(int*)(S0 + iofs0[3] + 4)));
v1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[3])),
_mm_cvtsi32_si128(*(int*)(S1 + iofs0[3] + 4)));
u0 = _mm_unpacklo_epi8(u0, z);
v0 = _mm_unpacklo_epi8(v0, z);
u1 = _mm_unpacklo_epi8(u1, z);
v1 = _mm_unpacklo_epi8(v1, z);
u0 = _mm_add_epi32(_mm_madd_epi16(u0, w0[0]), _mm_madd_epi16(v0, w0[1]));
u1 = _mm_add_epi32(_mm_madd_epi16(u1, w1[0]), _mm_madd_epi16(v1, w1[1]));
u0 = _mm_srai_epi32(_mm_add_epi32(u0, delta), INTER_REMAP_COEF_BITS);
u1 = _mm_srai_epi32(_mm_add_epi32(u1, delta), INTER_REMAP_COEF_BITS);
u0 = _mm_packs_epi32(u0, u1);
u0 = _mm_packus_epi16(u0, u0);
_mm_storel_epi64((__m128i*)(D + 8), u0);
}
}
return x;
}
};
#else
typedef RemapNoVec RemapVec_8u;
#endif
template<class CastOp, class VecOp, typename AT>
static void remapBilinear( const Mat& _src, Mat& _dst, const Mat& _xy,
const Mat& _fxy, const void* _wtab,
int borderType, const Scalar& _borderValue )
{
typedef typename CastOp::rtype T;
typedef typename CastOp::type1 WT;
Size ssize = _src.size(), dsize = _dst.size();
int cn = _src.channels();
const AT* wtab = (const AT*)_wtab;
const T* S0 = (const T*)_src.data;
size_t sstep = _src.step/sizeof(S0[0]);
Scalar_<T> cval(saturate_cast<T>(_borderValue[0]),
saturate_cast<T>(_borderValue[1]),
saturate_cast<T>(_borderValue[2]),
saturate_cast<T>(_borderValue[3]));
int dx, dy;
CastOp castOp;
VecOp vecOp;
unsigned width1 = std::max(ssize.width-1, 0), height1 = std::max(ssize.height-1, 0);
CV_Assert( cn <= 4 && ssize.area() > 0 );
#if CV_SSE2
if( _src.type() == CV_8UC3 )
width1 = std::max(ssize.width-2, 0);
#endif
for( dy = 0; dy < dsize.height; dy++ )
{
T* D = (T*)(_dst.data + _dst.step*dy);
const short* XY = (const short*)(_xy.data + _xy.step*dy);
const ushort* FXY = (const ushort*)(_fxy.data + _fxy.step*dy);
int X0 = 0;
bool prevInlier = false;
for( dx = 0; dx <= dsize.width; dx++ )
{
bool curInlier = dx < dsize.width ?
(unsigned)XY[dx*2] < width1 &&
(unsigned)XY[dx*2+1] < height1 : !prevInlier;
if( curInlier == prevInlier )
continue;
int X1 = dx;
dx = X0;
X0 = X1;
prevInlier = curInlier;
if( !curInlier )
{
int len = vecOp( _src, D, XY + dx*2, FXY + dx, wtab, X1 - dx );
D += len*cn;
dx += len;
if( cn == 1 )
{
for( ; dx < X1; dx++, D++ )
{
int sx = XY[dx*2], sy = XY[dx*2+1];
const AT* w = wtab + FXY[dx]*4;
const T* S = S0 + sy*sstep + sx;
*D = castOp(WT(S[0]*w[0] + S[1]*w[1] + S[sstep]*w[2] + S[sstep+1]*w[3]));
}
}
else if( cn == 2 )
for( ; dx < X1; dx++, D += 2 )
{
int sx = XY[dx*2], sy = XY[dx*2+1];
const AT* w = wtab + FXY[dx]*4;
const T* S = S0 + sy*sstep + sx*2;
WT t0 = S[0]*w[0] + S[2]*w[1] + S[sstep]*w[2] + S[sstep+2]*w[3];
WT t1 = S[1]*w[0] + S[3]*w[1] + S[sstep+1]*w[2] + S[sstep+3]*w[3];
D[0] = castOp(t0); D[1] = castOp(t1);
}
else if( cn == 3 )
for( ; dx < X1; dx++, D += 3 )
{
int sx = XY[dx*2], sy = XY[dx*2+1];
const AT* w = wtab + FXY[dx]*4;
const T* S = S0 + sy*sstep + sx*3;
WT t0 = S[0]*w[0] + S[3]*w[1] + S[sstep]*w[2] + S[sstep+3]*w[3];
WT t1 = S[1]*w[0] + S[4]*w[1] + S[sstep+1]*w[2] + S[sstep+4]*w[3];
WT t2 = S[2]*w[0] + S[5]*w[1] + S[sstep+2]*w[2] + S[sstep+5]*w[3];
D[0] = castOp(t0); D[1] = castOp(t1); D[2] = castOp(t2);
}
else
for( ; dx < X1; dx++, D += 4 )
{
int sx = XY[dx*2], sy = XY[dx*2+1];
const AT* w = wtab + FXY[dx]*4;
const T* S = S0 + sy*sstep + sx*4;
WT t0 = S[0]*w[0] + S[4]*w[1] + S[sstep]*w[2] + S[sstep+4]*w[3];
WT t1 = S[1]*w[0] + S[5]*w[1] + S[sstep+1]*w[2] + S[sstep+5]*w[3];
D[0] = castOp(t0); D[1] = castOp(t1);
t0 = S[2]*w[0] + S[6]*w[1] + S[sstep+2]*w[2] + S[sstep+6]*w[3];
t1 = S[3]*w[0] + S[7]*w[1] + S[sstep+3]*w[2] + S[sstep+7]*w[3];
D[2] = castOp(t0); D[3] = castOp(t1);
}
}
else
{
if( borderType == BORDER_TRANSPARENT && cn != 3 )
{
D += (X1 - dx)*cn;
dx = X1;
continue;
}
if( cn == 1 )
for( ; dx < X1; dx++, D++ )
{
int sx = XY[dx*2], sy = XY[dx*2+1];
if( borderType == BORDER_CONSTANT &&
(sx >= ssize.width || sx+1 < 0 ||
sy >= ssize.height || sy+1 < 0) )
{
D[0] = cval[0];
}
else
{
int sx0, sx1, sy0, sy1;
T v0, v1, v2, v3;
const AT* w = wtab + FXY[dx]*4;
if( borderType == BORDER_REPLICATE )
{
sx0 = clip(sx, 0, ssize.width);
sx1 = clip(sx+1, 0, ssize.width);
sy0 = clip(sy, 0, ssize.height);
sy1 = clip(sy+1, 0, ssize.height);
v0 = S0[sy0*sstep + sx0];
v1 = S0[sy0*sstep + sx1];
v2 = S0[sy1*sstep + sx0];
v3 = S0[sy1*sstep + sx1];
}
else
{
sx0 = borderInterpolate(sx, ssize.width, borderType);
sx1 = borderInterpolate(sx+1, ssize.width, borderType);
sy0 = borderInterpolate(sy, ssize.height, borderType);
sy1 = borderInterpolate(sy+1, ssize.height, borderType);
v0 = sx0 >= 0 && sy0 >= 0 ? S0[sy0*sstep + sx0] : cval[0];
v1 = sx1 >= 0 && sy0 >= 0 ? S0[sy0*sstep + sx1] : cval[0];
v2 = sx0 >= 0 && sy1 >= 0 ? S0[sy1*sstep + sx0] : cval[0];
v3 = sx1 >= 0 && sy1 >= 0 ? S0[sy1*sstep + sx1] : cval[0];
}
D[0] = castOp(WT(v0*w[0] + v1*w[1] + v2*w[2] + v3*w[3]));
}
}
else
for( ; dx < X1; dx++, D += cn )
{
int sx = XY[dx*2], sy = XY[dx*2+1], k;
if( borderType == BORDER_CONSTANT &&
(sx >= ssize.width || sx+1 < 0 ||
sy >= ssize.height || sy+1 < 0) )
{
for( k = 0; k < cn; k++ )
D[k] = cval[k];
}
else
{
int sx0, sx1, sy0, sy1;
const T *v0, *v1, *v2, *v3;
const AT* w = wtab + FXY[dx]*4;
if( borderType == BORDER_REPLICATE )
{
sx0 = clip(sx, 0, ssize.width);
sx1 = clip(sx+1, 0, ssize.width);
sy0 = clip(sy, 0, ssize.height);
sy1 = clip(sy+1, 0, ssize.height);
v0 = S0 + sy0*sstep + sx0*cn;
v1 = S0 + sy0*sstep + sx1*cn;
v2 = S0 + sy1*sstep + sx0*cn;
v3 = S0 + sy1*sstep + sx1*cn;
}
else if( borderType == BORDER_TRANSPARENT &&
((unsigned)sx >= (unsigned)(ssize.width-1) ||
(unsigned)sy >= (unsigned)(ssize.height-1)))
continue;
else
{
sx0 = borderInterpolate(sx, ssize.width, borderType);
sx1 = borderInterpolate(sx+1, ssize.width, borderType);
sy0 = borderInterpolate(sy, ssize.height, borderType);
sy1 = borderInterpolate(sy+1, ssize.height, borderType);
v0 = sx0 >= 0 && sy0 >= 0 ? S0 + sy0*sstep + sx0*cn : &cval[0];
v1 = sx1 >= 0 && sy0 >= 0 ? S0 + sy0*sstep + sx1*cn : &cval[0];
v2 = sx0 >= 0 && sy1 >= 0 ? S0 + sy1*sstep + sx0*cn : &cval[0];
v3 = sx1 >= 0 && sy1 >= 0 ? S0 + sy1*sstep + sx1*cn : &cval[0];
}
for( k = 0; k < cn; k++ )
D[k] = castOp(WT(v0[k]*w[0] + v1[k]*w[1] + v2[k]*w[2] + v3[k]*w[3]));
}
}
}
}
}
}
template<class CastOp, typename AT, int ONE>
static void remapBicubic( const Mat& _src, Mat& _dst, const Mat& _xy,
const Mat& _fxy, const void* _wtab,
int borderType, const Scalar& _borderValue )
{
typedef typename CastOp::rtype T;
typedef typename CastOp::type1 WT;
Size ssize = _src.size(), dsize = _dst.size();
int cn = _src.channels();
const AT* wtab = (const AT*)_wtab;
const T* S0 = (const T*)_src.data;
size_t sstep = _src.step/sizeof(S0[0]);
Scalar_<T> cval(saturate_cast<T>(_borderValue[0]),
saturate_cast<T>(_borderValue[1]),
saturate_cast<T>(_borderValue[2]),
saturate_cast<T>(_borderValue[3]));
int dx, dy;
CastOp castOp;
int borderType1 = borderType != BORDER_TRANSPARENT ? borderType : BORDER_REFLECT_101;
unsigned width1 = std::max(ssize.width-3, 0), height1 = std::max(ssize.height-3, 0);
if( _dst.isContinuous() && _xy.isContinuous() && _fxy.isContinuous() )
{
dsize.width *= dsize.height;
dsize.height = 1;
}
for( dy = 0; dy < dsize.height; dy++ )
{
T* D = (T*)(_dst.data + _dst.step*dy);
const short* XY = (const short*)(_xy.data + _xy.step*dy);
const ushort* FXY = (const ushort*)(_fxy.data + _fxy.step*dy);
for( dx = 0; dx < dsize.width; dx++, D += cn )
{
int sx = XY[dx*2]-1, sy = XY[dx*2+1]-1;
const AT* w = wtab + FXY[dx]*16;
int i, k;
if( (unsigned)sx < width1 && (unsigned)sy < height1 )
{
const T* S = S0 + sy*sstep + sx*cn;
for( k = 0; k < cn; k++ )
{
WT sum = S[0]*w[0] + S[cn]*w[1] + S[cn*2]*w[2] + S[cn*3]*w[3];
S += sstep;
sum += S[0]*w[4] + S[cn]*w[5] + S[cn*2]*w[6] + S[cn*3]*w[7];
S += sstep;
sum += S[0]*w[8] + S[cn]*w[9] + S[cn*2]*w[10] + S[cn*3]*w[11];
S += sstep;
sum += S[0]*w[12] + S[cn]*w[13] + S[cn*2]*w[14] + S[cn*3]*w[15];
S += 1 - sstep*3;
D[k] = castOp(sum);
}
}
else
{
int x[4], y[4];
if( borderType == BORDER_TRANSPARENT &&
((unsigned)(sx+1) >= (unsigned)ssize.width ||
(unsigned)(sy+1) >= (unsigned)ssize.height) )
continue;
if( borderType1 == BORDER_CONSTANT &&
(sx >= ssize.width || sx+4 <= 0 ||
sy >= ssize.height || sy+4 <= 0))
{
for( k = 0; k < cn; k++ )
D[k] = cval[k];
continue;
}
for( i = 0; i < 4; i++ )
{
x[i] = borderInterpolate(sx + i, ssize.width, borderType1)*cn;
y[i] = borderInterpolate(sy + i, ssize.height, borderType1);
}
for( k = 0; k < cn; k++, S0++, w -= 16 )
{
WT cv = cval[k], sum = cv*ONE;
for( i = 0; i < 4; i++, w += 4 )
{
int yi = y[i];
const T* S = S0 + yi*sstep;
if( yi < 0 )
continue;
if( x[0] >= 0 )
sum += (S[x[0]] - cv)*w[0];
if( x[1] >= 0 )
sum += (S[x[1]] - cv)*w[1];
if( x[2] >= 0 )
sum += (S[x[2]] - cv)*w[2];
if( x[3] >= 0 )
sum += (S[x[3]] - cv)*w[3];
}
D[k] = castOp(sum);
}
S0 -= cn;
}
}
}
}
template<class CastOp, typename AT, int ONE>
static void remapLanczos4( const Mat& _src, Mat& _dst, const Mat& _xy,
const Mat& _fxy, const void* _wtab,
int borderType, const Scalar& _borderValue )
{
typedef typename CastOp::rtype T;
typedef typename CastOp::type1 WT;
Size ssize = _src.size(), dsize = _dst.size();
int cn = _src.channels();
const AT* wtab = (const AT*)_wtab;
const T* S0 = (const T*)_src.data;
size_t sstep = _src.step/sizeof(S0[0]);
Scalar_<T> cval(saturate_cast<T>(_borderValue[0]),
saturate_cast<T>(_borderValue[1]),
saturate_cast<T>(_borderValue[2]),
saturate_cast<T>(_borderValue[3]));
int dx, dy;
CastOp castOp;
int borderType1 = borderType != BORDER_TRANSPARENT ? borderType : BORDER_REFLECT_101;
2012-05-30 23:56:53 +08:00
unsigned width1 = std::max(ssize.width-7, 0), height1 = std::max(ssize.height-7, 0);
if( _dst.isContinuous() && _xy.isContinuous() && _fxy.isContinuous() )
{
dsize.width *= dsize.height;
dsize.height = 1;
}
for( dy = 0; dy < dsize.height; dy++ )
{
T* D = (T*)(_dst.data + _dst.step*dy);
const short* XY = (const short*)(_xy.data + _xy.step*dy);
const ushort* FXY = (const ushort*)(_fxy.data + _fxy.step*dy);
for( dx = 0; dx < dsize.width; dx++, D += cn )
{
int sx = XY[dx*2]-3, sy = XY[dx*2+1]-3;
const AT* w = wtab + FXY[dx]*64;
const T* S = S0 + sy*sstep + sx*cn;
int i, k;
if( (unsigned)sx < width1 && (unsigned)sy < height1 )
{
for( k = 0; k < cn; k++ )
{
WT sum = 0;
for( int r = 0; r < 8; r++, S += sstep, w += 8 )
sum += S[0]*w[0] + S[cn]*w[1] + S[cn*2]*w[2] + S[cn*3]*w[3] +
S[cn*4]*w[4] + S[cn*5]*w[5] + S[cn*6]*w[6] + S[cn*7]*w[7];
w -= 64;
S -= sstep*8 - 1;
D[k] = castOp(sum);
}
}
else
{
int x[8], y[8];
if( borderType == BORDER_TRANSPARENT &&
((unsigned)(sx+3) >= (unsigned)ssize.width ||
(unsigned)(sy+3) >= (unsigned)ssize.height) )
continue;
if( borderType1 == BORDER_CONSTANT &&
(sx >= ssize.width || sx+8 <= 0 ||
sy >= ssize.height || sy+8 <= 0))
{
for( k = 0; k < cn; k++ )
D[k] = cval[k];
continue;
}
for( i = 0; i < 8; i++ )
{
x[i] = borderInterpolate(sx + i, ssize.width, borderType1)*cn;
y[i] = borderInterpolate(sy + i, ssize.height, borderType1);
}
for( k = 0; k < cn; k++, S0++, w -= 64 )
{
WT cv = cval[k], sum = cv*ONE;
for( i = 0; i < 8; i++, w += 8 )
{
int yi = y[i];
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const T* S1 = S0 + yi*sstep;
if( yi < 0 )
continue;
if( x[0] >= 0 )
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sum += (S1[x[0]] - cv)*w[0];
if( x[1] >= 0 )
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sum += (S1[x[1]] - cv)*w[1];
if( x[2] >= 0 )
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sum += (S1[x[2]] - cv)*w[2];
if( x[3] >= 0 )
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sum += (S1[x[3]] - cv)*w[3];
if( x[4] >= 0 )
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sum += (S1[x[4]] - cv)*w[4];
if( x[5] >= 0 )
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sum += (S1[x[5]] - cv)*w[5];
if( x[6] >= 0 )
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sum += (S1[x[6]] - cv)*w[6];
if( x[7] >= 0 )
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sum += (S1[x[7]] - cv)*w[7];
}
D[k] = castOp(sum);
}
S0 -= cn;
}
}
}
}
typedef void (*RemapNNFunc)(const Mat& _src, Mat& _dst, const Mat& _xy,
int borderType, const Scalar& _borderValue );
typedef void (*RemapFunc)(const Mat& _src, Mat& _dst, const Mat& _xy,
const Mat& _fxy, const void* _wtab,
int borderType, const Scalar& _borderValue);
class RemapInvoker :
public ParallelLoopBody
{
public:
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RemapInvoker(const Mat& _src, Mat& _dst, const Mat *_m1,
const Mat *_m2, int _borderType, const Scalar &_borderValue,
int _planar_input, RemapNNFunc _nnfunc, RemapFunc _ifunc, const void *_ctab) :
ParallelLoopBody(), src(&_src), dst(&_dst), m1(_m1), m2(_m2),
borderType(_borderType), borderValue(_borderValue),
planar_input(_planar_input), nnfunc(_nnfunc), ifunc(_ifunc), ctab(_ctab)
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{
}
virtual void operator() (const Range& range) const
{
int x, y, x1, y1;
const int buf_size = 1 << 14;
int brows0 = std::min(128, dst->rows), map_depth = m1->depth();
int bcols0 = std::min(buf_size/brows0, dst->cols);
brows0 = std::min(buf_size/bcols0, dst->rows);
#if CV_SSE2
bool useSIMD = checkHardwareSupport(CV_CPU_SSE2);
#endif
Mat _bufxy(brows0, bcols0, CV_16SC2), _bufa;
if( !nnfunc )
_bufa.create(brows0, bcols0, CV_16UC1);
for( y = range.start; y < range.end; y += brows0 )
{
for( x = 0; x < dst->cols; x += bcols0 )
{
int brows = std::min(brows0, range.end - y);
int bcols = std::min(bcols0, dst->cols - x);
Mat dpart(*dst, Rect(x, y, bcols, brows));
Mat bufxy(_bufxy, Rect(0, 0, bcols, brows));
if( nnfunc )
{
if( m1->type() == CV_16SC2 && !m2->data ) // the data is already in the right format
bufxy = (*m1)(Rect(x, y, bcols, brows));
else if( map_depth != CV_32F )
{
for( y1 = 0; y1 < brows; y1++ )
{
short* XY = (short*)(bufxy.data + bufxy.step*y1);
const short* sXY = (const short*)(m1->data + m1->step*(y+y1)) + x*2;
const ushort* sA = (const ushort*)(m2->data + m2->step*(y+y1)) + x;
for( x1 = 0; x1 < bcols; x1++ )
{
int a = sA[x1] & (INTER_TAB_SIZE2-1);
XY[x1*2] = sXY[x1*2] + NNDeltaTab_i[a][0];
XY[x1*2+1] = sXY[x1*2+1] + NNDeltaTab_i[a][1];
}
}
}
else if( !planar_input )
(*m1)(Rect(x, y, bcols, brows)).convertTo(bufxy, bufxy.depth());
else
{
for( y1 = 0; y1 < brows; y1++ )
{
short* XY = (short*)(bufxy.data + bufxy.step*y1);
const float* sX = (const float*)(m1->data + m1->step*(y+y1)) + x;
const float* sY = (const float*)(m2->data + m2->step*(y+y1)) + x;
x1 = 0;
#if CV_SSE2
if( useSIMD )
{
for( ; x1 <= bcols - 8; x1 += 8 )
{
__m128 fx0 = _mm_loadu_ps(sX + x1);
__m128 fx1 = _mm_loadu_ps(sX + x1 + 4);
__m128 fy0 = _mm_loadu_ps(sY + x1);
__m128 fy1 = _mm_loadu_ps(sY + x1 + 4);
__m128i ix0 = _mm_cvtps_epi32(fx0);
__m128i ix1 = _mm_cvtps_epi32(fx1);
__m128i iy0 = _mm_cvtps_epi32(fy0);
__m128i iy1 = _mm_cvtps_epi32(fy1);
ix0 = _mm_packs_epi32(ix0, ix1);
iy0 = _mm_packs_epi32(iy0, iy1);
ix1 = _mm_unpacklo_epi16(ix0, iy0);
iy1 = _mm_unpackhi_epi16(ix0, iy0);
_mm_storeu_si128((__m128i*)(XY + x1*2), ix1);
_mm_storeu_si128((__m128i*)(XY + x1*2 + 8), iy1);
}
}
#endif
for( ; x1 < bcols; x1++ )
{
XY[x1*2] = saturate_cast<short>(sX[x1]);
XY[x1*2+1] = saturate_cast<short>(sY[x1]);
}
}
}
nnfunc( *src, dpart, bufxy, borderType, borderValue );
continue;
}
Mat bufa(_bufa, Rect(0, 0, bcols, brows));
for( y1 = 0; y1 < brows; y1++ )
{
short* XY = (short*)(bufxy.data + bufxy.step*y1);
ushort* A = (ushort*)(bufa.data + bufa.step*y1);
if( m1->type() == CV_16SC2 && (m2->type() == CV_16UC1 || m2->type() == CV_16SC1) )
{
bufxy = (*m1)(Rect(x, y, bcols, brows));
const ushort* sA = (const ushort*)(m2->data + m2->step*(y+y1)) + x;
for( x1 = 0; x1 < bcols; x1++ )
A[x1] = (ushort)(sA[x1] & (INTER_TAB_SIZE2-1));
}
else if( planar_input )
{
const float* sX = (const float*)(m1->data + m1->step*(y+y1)) + x;
const float* sY = (const float*)(m2->data + m2->step*(y+y1)) + x;
x1 = 0;
#if CV_SSE2
if( useSIMD )
{
__m128 scale = _mm_set1_ps((float)INTER_TAB_SIZE);
__m128i mask = _mm_set1_epi32(INTER_TAB_SIZE-1);
for( ; x1 <= bcols - 8; x1 += 8 )
{
__m128 fx0 = _mm_loadu_ps(sX + x1);
__m128 fx1 = _mm_loadu_ps(sX + x1 + 4);
__m128 fy0 = _mm_loadu_ps(sY + x1);
__m128 fy1 = _mm_loadu_ps(sY + x1 + 4);
__m128i ix0 = _mm_cvtps_epi32(_mm_mul_ps(fx0, scale));
__m128i ix1 = _mm_cvtps_epi32(_mm_mul_ps(fx1, scale));
__m128i iy0 = _mm_cvtps_epi32(_mm_mul_ps(fy0, scale));
__m128i iy1 = _mm_cvtps_epi32(_mm_mul_ps(fy1, scale));
__m128i mx0 = _mm_and_si128(ix0, mask);
__m128i mx1 = _mm_and_si128(ix1, mask);
__m128i my0 = _mm_and_si128(iy0, mask);
__m128i my1 = _mm_and_si128(iy1, mask);
mx0 = _mm_packs_epi32(mx0, mx1);
my0 = _mm_packs_epi32(my0, my1);
my0 = _mm_slli_epi16(my0, INTER_BITS);
mx0 = _mm_or_si128(mx0, my0);
_mm_storeu_si128((__m128i*)(A + x1), mx0);
ix0 = _mm_srai_epi32(ix0, INTER_BITS);
ix1 = _mm_srai_epi32(ix1, INTER_BITS);
iy0 = _mm_srai_epi32(iy0, INTER_BITS);
iy1 = _mm_srai_epi32(iy1, INTER_BITS);
ix0 = _mm_packs_epi32(ix0, ix1);
iy0 = _mm_packs_epi32(iy0, iy1);
ix1 = _mm_unpacklo_epi16(ix0, iy0);
iy1 = _mm_unpackhi_epi16(ix0, iy0);
_mm_storeu_si128((__m128i*)(XY + x1*2), ix1);
_mm_storeu_si128((__m128i*)(XY + x1*2 + 8), iy1);
}
}
#endif
for( ; x1 < bcols; x1++ )
{
int sx = cvRound(sX[x1]*INTER_TAB_SIZE);
int sy = cvRound(sY[x1]*INTER_TAB_SIZE);
int v = (sy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (sx & (INTER_TAB_SIZE-1));
XY[x1*2] = saturate_cast<short>(sx >> INTER_BITS);
XY[x1*2+1] = saturate_cast<short>(sy >> INTER_BITS);
A[x1] = (ushort)v;
}
}
else
{
const float* sXY = (const float*)(m1->data + m1->step*(y+y1)) + x*2;
for( x1 = 0; x1 < bcols; x1++ )
{
int sx = cvRound(sXY[x1*2]*INTER_TAB_SIZE);
int sy = cvRound(sXY[x1*2+1]*INTER_TAB_SIZE);
int v = (sy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (sx & (INTER_TAB_SIZE-1));
XY[x1*2] = saturate_cast<short>(sx >> INTER_BITS);
XY[x1*2+1] = saturate_cast<short>(sy >> INTER_BITS);
A[x1] = (ushort)v;
}
}
}
ifunc(*src, dpart, bufxy, bufa, ctab, borderType, borderValue);
}
}
}
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private:
const Mat* src;
Mat* dst;
const Mat *m1, *m2;
int borderType;
Scalar borderValue;
int planar_input;
RemapNNFunc nnfunc;
RemapFunc ifunc;
const void *ctab;
};
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#ifdef HAVE_OPENCL
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static bool ocl_remap(InputArray _src, OutputArray _dst, InputArray _map1, InputArray _map2,
int interpolation, int borderType, const Scalar& borderValue)
{
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const ocl::Device & dev = ocl::Device::getDefault();
int cn = _src.channels(), type = _src.type(), depth = _src.depth(),
rowsPerWI = dev.isIntel() ? 4 : 1;
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if (borderType == BORDER_TRANSPARENT || !(interpolation == INTER_LINEAR || interpolation == INTER_NEAREST)
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|| _map1.type() == CV_16SC1 || _map2.type() == CV_16SC1)
return false;
UMat src = _src.getUMat(), map1 = _map1.getUMat(), map2 = _map2.getUMat();
if( (map1.type() == CV_16SC2 && (map2.type() == CV_16UC1 || map2.empty())) ||
(map2.type() == CV_16SC2 && (map1.type() == CV_16UC1 || map1.empty())) )
{
if (map1.type() != CV_16SC2)
std::swap(map1, map2);
}
else
CV_Assert( map1.type() == CV_32FC2 || (map1.type() == CV_32FC1 && map2.type() == CV_32FC1) );
_dst.create(map1.size(), type);
UMat dst = _dst.getUMat();
String kernelName = "remap";
if (map1.type() == CV_32FC2 && map2.empty())
kernelName += "_32FC2";
else if (map1.type() == CV_16SC2)
{
kernelName += "_16SC2";
if (!map2.empty())
kernelName += "_16UC1";
}
else if (map1.type() == CV_32FC1 && map2.type() == CV_32FC1)
kernelName += "_2_32FC1";
else
CV_Error(Error::StsBadArg, "Unsupported map types");
static const char * const interMap[] = { "INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_LINEAR", "INTER_LANCZOS" };
static const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP",
"BORDER_REFLECT_101", "BORDER_TRANSPARENT" };
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String buildOptions = format("-D %s -D %s -D T=%s -D rowsPerWI=%d",
interMap[interpolation], borderMap[borderType],
ocl::typeToStr(type), rowsPerWI);
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if (interpolation != INTER_NEAREST)
{
char cvt[3][40];
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int wdepth = std::max(CV_32F, depth);
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buildOptions = buildOptions
+ format(" -D WT=%s -D convertToT=%s -D convertToWT=%s"
" -D convertToWT2=%s -D WT2=%s",
ocl::typeToStr(CV_MAKE_TYPE(wdepth, cn)),
ocl::convertTypeStr(wdepth, depth, cn, cvt[0]),
ocl::convertTypeStr(depth, wdepth, cn, cvt[1]),
ocl::convertTypeStr(CV_32S, wdepth, 2, cvt[2]),
ocl::typeToStr(CV_MAKE_TYPE(wdepth, 2)));
}
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int scalarcn = cn == 3 ? 4 : cn;
int sctype = CV_MAKETYPE(depth, scalarcn);
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buildOptions += format(" -D T=%s -D T1=%s -D cn=%d -D ST=%s -D depth=%d",
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ocl::typeToStr(type), ocl::typeToStr(depth),
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cn, ocl::typeToStr(sctype), depth);
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ocl::Kernel k(kernelName.c_str(), ocl::imgproc::remap_oclsrc, buildOptions);
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Mat scalar(1, 1, sctype, borderValue);
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ocl::KernelArg srcarg = ocl::KernelArg::ReadOnly(src), dstarg = ocl::KernelArg::WriteOnly(dst),
map1arg = ocl::KernelArg::ReadOnlyNoSize(map1),
scalararg = ocl::KernelArg::Constant((void*)scalar.data, scalar.elemSize());
if (map2.empty())
k.args(srcarg, dstarg, map1arg, scalararg);
else
k.args(srcarg, dstarg, map1arg, ocl::KernelArg::ReadOnlyNoSize(map2), scalararg);
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size_t globalThreads[2] = { dst.cols, (dst.rows + rowsPerWI - 1) / rowsPerWI };
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return k.run(2, globalThreads, NULL, false);
}
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#endif
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#if IPP_VERSION_X100 >= 0 && !defined HAVE_IPP_ICV_ONLY && 0
typedef IppStatus (CV_STDCALL * ippiRemap)(const void * pSrc, IppiSize srcSize, int srcStep, IppiRect srcRoi,
const Ipp32f* pxMap, int xMapStep, const Ipp32f* pyMap, int yMapStep,
void * pDst, int dstStep, IppiSize dstRoiSize, int interpolation);
class IPPRemapInvoker :
public ParallelLoopBody
{
public:
IPPRemapInvoker(Mat & _src, Mat & _dst, Mat & _xmap, Mat & _ymap, ippiRemap _ippFunc,
int _ippInterpolation, int _borderType, const Scalar & _borderValue, bool * _ok) :
ParallelLoopBody(), src(_src), dst(_dst), map1(_xmap), map2(_ymap), ippFunc(_ippFunc),
ippInterpolation(_ippInterpolation), borderType(_borderType), borderValue(_borderValue), ok(_ok)
{
*ok = true;
}
virtual void operator() (const Range & range) const
{
IppiRect srcRoiRect = { 0, 0, src.cols, src.rows };
Mat dstRoi = dst.rowRange(range);
IppiSize dstRoiSize = ippiSize(dstRoi.size());
int type = dst.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if (borderType == BORDER_CONSTANT &&
!IPPSet(borderValue, dstRoi.data, (int)dstRoi.step, dstRoiSize, cn, depth))
{
*ok = false;
return;
}
if (ippFunc(src.data, ippiSize(src.size()), (int)src.step, srcRoiRect,
(const Ipp32f *)map1.data, (int)map1.step, (const Ipp32f *)map2.data, (int)map2.step,
dstRoi.data, (int)dstRoi.step, dstRoiSize, ippInterpolation) < 0)
*ok = false;
}
private:
Mat & src, & dst, & map1, & map2;
ippiRemap ippFunc;
int ippInterpolation, borderType;
Scalar borderValue;
bool * ok;
};
#endif
}
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void cv::remap( InputArray _src, OutputArray _dst,
InputArray _map1, InputArray _map2,
int interpolation, int borderType, const Scalar& borderValue )
{
static RemapNNFunc nn_tab[] =
{
remapNearest<uchar>, remapNearest<schar>, remapNearest<ushort>, remapNearest<short>,
remapNearest<int>, remapNearest<float>, remapNearest<double>, 0
};
static RemapFunc linear_tab[] =
{
remapBilinear<FixedPtCast<int, uchar, INTER_REMAP_COEF_BITS>, RemapVec_8u, short>, 0,
remapBilinear<Cast<float, ushort>, RemapNoVec, float>,
remapBilinear<Cast<float, short>, RemapNoVec, float>, 0,
remapBilinear<Cast<float, float>, RemapNoVec, float>,
remapBilinear<Cast<double, double>, RemapNoVec, float>, 0
};
static RemapFunc cubic_tab[] =
{
remapBicubic<FixedPtCast<int, uchar, INTER_REMAP_COEF_BITS>, short, INTER_REMAP_COEF_SCALE>, 0,
remapBicubic<Cast<float, ushort>, float, 1>,
remapBicubic<Cast<float, short>, float, 1>, 0,
remapBicubic<Cast<float, float>, float, 1>,
remapBicubic<Cast<double, double>, float, 1>, 0
};
static RemapFunc lanczos4_tab[] =
{
remapLanczos4<FixedPtCast<int, uchar, INTER_REMAP_COEF_BITS>, short, INTER_REMAP_COEF_SCALE>, 0,
remapLanczos4<Cast<float, ushort>, float, 1>,
remapLanczos4<Cast<float, short>, float, 1>, 0,
remapLanczos4<Cast<float, float>, float, 1>,
remapLanczos4<Cast<double, double>, float, 1>, 0
};
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CV_Assert( _map1.size().area() > 0 );
CV_Assert( _map2.empty() || (_map2.size() == _map1.size()));
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CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_remap(_src, _dst, _map1, _map2, interpolation, borderType, borderValue))
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Mat src = _src.getMat(), map1 = _map1.getMat(), map2 = _map2.getMat();
_dst.create( map1.size(), src.type() );
Mat dst = _dst.getMat();
if( dst.data == src.data )
src = src.clone();
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if( interpolation == INTER_AREA )
interpolation = INTER_LINEAR;
int type = src.type(), depth = CV_MAT_DEPTH(type);
#if IPP_VERSION_X100 >= 0 && !defined HAVE_IPP_ICV_ONLY && 0
if ((interpolation == INTER_LINEAR || interpolation == INTER_CUBIC || interpolation == INTER_NEAREST) &&
map1.type() == CV_32FC1 && map2.type() == CV_32FC1 &&
(borderType == BORDER_CONSTANT || borderType == BORDER_TRANSPARENT))
{
int ippInterpolation =
interpolation == INTER_NEAREST ? IPPI_INTER_NN :
interpolation == INTER_LINEAR ? IPPI_INTER_LINEAR : IPPI_INTER_CUBIC;
ippiRemap ippFunc =
type == CV_8UC1 ? (ippiRemap)ippiRemap_8u_C1R :
type == CV_8UC3 ? (ippiRemap)ippiRemap_8u_C3R :
type == CV_8UC4 ? (ippiRemap)ippiRemap_8u_C4R :
type == CV_16UC1 ? (ippiRemap)ippiRemap_16u_C1R :
type == CV_16UC3 ? (ippiRemap)ippiRemap_16u_C3R :
type == CV_16UC4 ? (ippiRemap)ippiRemap_16u_C4R :
type == CV_32FC1 ? (ippiRemap)ippiRemap_32f_C1R :
type == CV_32FC3 ? (ippiRemap)ippiRemap_32f_C3R :
type == CV_32FC4 ? (ippiRemap)ippiRemap_32f_C4R : 0;
if (ippFunc)
{
bool ok;
IPPRemapInvoker invoker(src, dst, map1, map2, ippFunc, ippInterpolation,
borderType, borderValue, &ok);
Range range(0, dst.rows);
parallel_for_(range, invoker, dst.total() / (double)(1 << 16));
if (ok)
return;
setIppErrorStatus();
}
}
#endif
RemapNNFunc nnfunc = 0;
RemapFunc ifunc = 0;
const void* ctab = 0;
bool fixpt = depth == CV_8U;
bool planar_input = false;
if( interpolation == INTER_NEAREST )
{
nnfunc = nn_tab[depth];
CV_Assert( nnfunc != 0 );
}
else
{
if( interpolation == INTER_LINEAR )
ifunc = linear_tab[depth];
else if( interpolation == INTER_CUBIC )
ifunc = cubic_tab[depth];
else if( interpolation == INTER_LANCZOS4 )
ifunc = lanczos4_tab[depth];
else
CV_Error( CV_StsBadArg, "Unknown interpolation method" );
CV_Assert( ifunc != 0 );
ctab = initInterTab2D( interpolation, fixpt );
}
const Mat *m1 = &map1, *m2 = &map2;
if( (map1.type() == CV_16SC2 && (map2.type() == CV_16UC1 || map2.type() == CV_16SC1 || !map2.data)) ||
(map2.type() == CV_16SC2 && (map1.type() == CV_16UC1 || map1.type() == CV_16SC1 || !map1.data)) )
{
if( map1.type() != CV_16SC2 )
std::swap(m1, m2);
}
else
{
CV_Assert( ((map1.type() == CV_32FC2 || map1.type() == CV_16SC2) && !map2.data) ||
(map1.type() == CV_32FC1 && map2.type() == CV_32FC1) );
planar_input = map1.channels() == 1;
}
RemapInvoker invoker(src, dst, m1, m2,
borderType, borderValue, planar_input, nnfunc, ifunc,
ctab);
parallel_for_(Range(0, dst.rows), invoker, dst.total()/(double)(1<<16));
}
void cv::convertMaps( InputArray _map1, InputArray _map2,
OutputArray _dstmap1, OutputArray _dstmap2,
int dstm1type, bool nninterpolate )
{
Mat map1 = _map1.getMat(), map2 = _map2.getMat(), dstmap1, dstmap2;
Size size = map1.size();
const Mat *m1 = &map1, *m2 = &map2;
int m1type = m1->type(), m2type = m2->type();
CV_Assert( (m1type == CV_16SC2 && (nninterpolate || m2type == CV_16UC1 || m2type == CV_16SC1)) ||
(m2type == CV_16SC2 && (nninterpolate || m1type == CV_16UC1 || m1type == CV_16SC1)) ||
(m1type == CV_32FC1 && m2type == CV_32FC1) ||
(m1type == CV_32FC2 && !m2->data) );
if( m2type == CV_16SC2 )
{
std::swap( m1, m2 );
std::swap( m1type, m2type );
}
if( dstm1type <= 0 )
dstm1type = m1type == CV_16SC2 ? CV_32FC2 : CV_16SC2;
CV_Assert( dstm1type == CV_16SC2 || dstm1type == CV_32FC1 || dstm1type == CV_32FC2 );
_dstmap1.create( size, dstm1type );
dstmap1 = _dstmap1.getMat();
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if( !nninterpolate && dstm1type != CV_32FC2 )
{
_dstmap2.create( size, dstm1type == CV_16SC2 ? CV_16UC1 : CV_32FC1 );
dstmap2 = _dstmap2.getMat();
}
else
_dstmap2.release();
if( m1type == dstm1type || (nninterpolate &&
((m1type == CV_16SC2 && dstm1type == CV_32FC2) ||
(m1type == CV_32FC2 && dstm1type == CV_16SC2))) )
{
m1->convertTo( dstmap1, dstmap1.type() );
if( dstmap2.data && dstmap2.type() == m2->type() )
m2->copyTo( dstmap2 );
return;
}
if( m1type == CV_32FC1 && dstm1type == CV_32FC2 )
{
Mat vdata[] = { *m1, *m2 };
merge( vdata, 2, dstmap1 );
return;
}
if( m1type == CV_32FC2 && dstm1type == CV_32FC1 )
{
Mat mv[] = { dstmap1, dstmap2 };
split( *m1, mv );
return;
}
if( m1->isContinuous() && (!m2->data || m2->isContinuous()) &&
dstmap1.isContinuous() && (!dstmap2.data || dstmap2.isContinuous()) )
{
size.width *= size.height;
size.height = 1;
}
const float scale = 1.f/INTER_TAB_SIZE;
int x, y;
for( y = 0; y < size.height; y++ )
{
const float* src1f = (const float*)(m1->data + m1->step*y);
const float* src2f = (const float*)(m2->data + m2->step*y);
const short* src1 = (const short*)src1f;
const ushort* src2 = (const ushort*)src2f;
float* dst1f = (float*)(dstmap1.data + dstmap1.step*y);
float* dst2f = (float*)(dstmap2.data + dstmap2.step*y);
short* dst1 = (short*)dst1f;
ushort* dst2 = (ushort*)dst2f;
if( m1type == CV_32FC1 && dstm1type == CV_16SC2 )
{
if( nninterpolate )
for( x = 0; x < size.width; x++ )
{
dst1[x*2] = saturate_cast<short>(src1f[x]);
dst1[x*2+1] = saturate_cast<short>(src2f[x]);
}
else
for( x = 0; x < size.width; x++ )
{
int ix = saturate_cast<int>(src1f[x]*INTER_TAB_SIZE);
int iy = saturate_cast<int>(src2f[x]*INTER_TAB_SIZE);
dst1[x*2] = saturate_cast<short>(ix >> INTER_BITS);
dst1[x*2+1] = saturate_cast<short>(iy >> INTER_BITS);
dst2[x] = (ushort)((iy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (ix & (INTER_TAB_SIZE-1)));
}
}
else if( m1type == CV_32FC2 && dstm1type == CV_16SC2 )
{
if( nninterpolate )
for( x = 0; x < size.width; x++ )
{
dst1[x*2] = saturate_cast<short>(src1f[x*2]);
dst1[x*2+1] = saturate_cast<short>(src1f[x*2+1]);
}
else
for( x = 0; x < size.width; x++ )
{
int ix = saturate_cast<int>(src1f[x*2]*INTER_TAB_SIZE);
int iy = saturate_cast<int>(src1f[x*2+1]*INTER_TAB_SIZE);
dst1[x*2] = saturate_cast<short>(ix >> INTER_BITS);
dst1[x*2+1] = saturate_cast<short>(iy >> INTER_BITS);
dst2[x] = (ushort)((iy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (ix & (INTER_TAB_SIZE-1)));
}
}
else if( m1type == CV_16SC2 && dstm1type == CV_32FC1 )
{
for( x = 0; x < size.width; x++ )
{
int fxy = src2 ? src2[x] & (INTER_TAB_SIZE2-1) : 0;
dst1f[x] = src1[x*2] + (fxy & (INTER_TAB_SIZE-1))*scale;
dst2f[x] = src1[x*2+1] + (fxy >> INTER_BITS)*scale;
}
}
else if( m1type == CV_16SC2 && dstm1type == CV_32FC2 )
{
for( x = 0; x < size.width; x++ )
{
int fxy = src2 ? src2[x] & (INTER_TAB_SIZE2-1): 0;
dst1f[x*2] = src1[x*2] + (fxy & (INTER_TAB_SIZE-1))*scale;
dst1f[x*2+1] = src1[x*2+1] + (fxy >> INTER_BITS)*scale;
}
}
else
CV_Error( CV_StsNotImplemented, "Unsupported combination of input/output matrices" );
}
}
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namespace cv
{
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class WarpAffineInvoker :
public ParallelLoopBody
{
public:
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WarpAffineInvoker(const Mat &_src, Mat &_dst, int _interpolation, int _borderType,
const Scalar &_borderValue, int *_adelta, int *_bdelta, double *_M) :
ParallelLoopBody(), src(_src), dst(_dst), interpolation(_interpolation),
borderType(_borderType), borderValue(_borderValue), adelta(_adelta), bdelta(_bdelta),
M(_M)
{
}
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virtual void operator() (const Range& range) const
{
const int BLOCK_SZ = 64;
short XY[BLOCK_SZ*BLOCK_SZ*2], A[BLOCK_SZ*BLOCK_SZ];
const int AB_BITS = MAX(10, (int)INTER_BITS);
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const int AB_SCALE = 1 << AB_BITS;
int round_delta = interpolation == INTER_NEAREST ? AB_SCALE/2 : AB_SCALE/INTER_TAB_SIZE/2, x, y, x1, y1;
#if CV_SSE2
bool useSIMD = checkHardwareSupport(CV_CPU_SSE2);
#endif
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int bh0 = std::min(BLOCK_SZ/2, dst.rows);
int bw0 = std::min(BLOCK_SZ*BLOCK_SZ/bh0, dst.cols);
bh0 = std::min(BLOCK_SZ*BLOCK_SZ/bw0, dst.rows);
for( y = range.start; y < range.end; y += bh0 )
{
for( x = 0; x < dst.cols; x += bw0 )
{
int bw = std::min( bw0, dst.cols - x);
int bh = std::min( bh0, range.end - y);
Mat _XY(bh, bw, CV_16SC2, XY), matA;
Mat dpart(dst, Rect(x, y, bw, bh));
for( y1 = 0; y1 < bh; y1++ )
{
short* xy = XY + y1*bw*2;
int X0 = saturate_cast<int>((M[1]*(y + y1) + M[2])*AB_SCALE) + round_delta;
int Y0 = saturate_cast<int>((M[4]*(y + y1) + M[5])*AB_SCALE) + round_delta;
if( interpolation == INTER_NEAREST )
for( x1 = 0; x1 < bw; x1++ )
{
int X = (X0 + adelta[x+x1]) >> AB_BITS;
int Y = (Y0 + bdelta[x+x1]) >> AB_BITS;
xy[x1*2] = saturate_cast<short>(X);
xy[x1*2+1] = saturate_cast<short>(Y);
}
else
{
short* alpha = A + y1*bw;
x1 = 0;
#if CV_SSE2
if( useSIMD )
{
__m128i fxy_mask = _mm_set1_epi32(INTER_TAB_SIZE - 1);
__m128i XX = _mm_set1_epi32(X0), YY = _mm_set1_epi32(Y0);
for( ; x1 <= bw - 8; x1 += 8 )
{
__m128i tx0, tx1, ty0, ty1;
tx0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(adelta + x + x1)), XX);
ty0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(bdelta + x + x1)), YY);
tx1 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(adelta + x + x1 + 4)), XX);
ty1 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(bdelta + x + x1 + 4)), YY);
tx0 = _mm_srai_epi32(tx0, AB_BITS - INTER_BITS);
ty0 = _mm_srai_epi32(ty0, AB_BITS - INTER_BITS);
tx1 = _mm_srai_epi32(tx1, AB_BITS - INTER_BITS);
ty1 = _mm_srai_epi32(ty1, AB_BITS - INTER_BITS);
__m128i fx_ = _mm_packs_epi32(_mm_and_si128(tx0, fxy_mask),
_mm_and_si128(tx1, fxy_mask));
__m128i fy_ = _mm_packs_epi32(_mm_and_si128(ty0, fxy_mask),
_mm_and_si128(ty1, fxy_mask));
tx0 = _mm_packs_epi32(_mm_srai_epi32(tx0, INTER_BITS),
_mm_srai_epi32(tx1, INTER_BITS));
ty0 = _mm_packs_epi32(_mm_srai_epi32(ty0, INTER_BITS),
_mm_srai_epi32(ty1, INTER_BITS));
fx_ = _mm_adds_epi16(fx_, _mm_slli_epi16(fy_, INTER_BITS));
_mm_storeu_si128((__m128i*)(xy + x1*2), _mm_unpacklo_epi16(tx0, ty0));
_mm_storeu_si128((__m128i*)(xy + x1*2 + 8), _mm_unpackhi_epi16(tx0, ty0));
_mm_storeu_si128((__m128i*)(alpha + x1), fx_);
}
}
#endif
for( ; x1 < bw; x1++ )
{
int X = (X0 + adelta[x+x1]) >> (AB_BITS - INTER_BITS);
int Y = (Y0 + bdelta[x+x1]) >> (AB_BITS - INTER_BITS);
xy[x1*2] = saturate_cast<short>(X >> INTER_BITS);
xy[x1*2+1] = saturate_cast<short>(Y >> INTER_BITS);
alpha[x1] = (short)((Y & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE +
(X & (INTER_TAB_SIZE-1)));
}
}
}
if( interpolation == INTER_NEAREST )
remap( src, dpart, _XY, Mat(), interpolation, borderType, borderValue );
else
{
Mat _matA(bh, bw, CV_16U, A);
remap( src, dpart, _XY, _matA, interpolation, borderType, borderValue );
}
}
}
}
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private:
Mat src;
Mat dst;
int interpolation, borderType;
Scalar borderValue;
int *adelta, *bdelta;
double *M;
};
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#if defined (HAVE_IPP) && IPP_VERSION_MAJOR * 100 + IPP_VERSION_MINOR >= 801 && 0
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class IPPWarpAffineInvoker :
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public ParallelLoopBody
{
public:
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IPPWarpAffineInvoker(Mat &_src, Mat &_dst, double (&_coeffs)[2][3], int &_interpolation, int _borderType,
const Scalar &_borderValue, ippiWarpAffineBackFunc _func, bool *_ok) :
ParallelLoopBody(), src(_src), dst(_dst), mode(_interpolation), coeffs(_coeffs),
borderType(_borderType), borderValue(_borderValue), func(_func), ok(_ok)
{
*ok = true;
}
virtual void operator() (const Range& range) const
{
IppiSize srcsize = { src.cols, src.rows };
IppiRect srcroi = { 0, 0, src.cols, src.rows };
IppiRect dstroi = { 0, range.start, dst.cols, range.end - range.start };
int cnn = src.channels();
if( borderType == BORDER_CONSTANT )
{
IppiSize setSize = { dst.cols, range.end - range.start };
void *dataPointer = dst.data + dst.step[0] * range.start;
if( !IPPSet( borderValue, dataPointer, (int)dst.step[0], setSize, cnn, src.depth() ) )
{
*ok = false;
return;
}
}
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// Aug 2013: problem in IPP 7.1, 8.0 : sometimes function return ippStsCoeffErr
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IppStatus status = func( src.data, srcsize, (int)src.step[0], srcroi, dst.data,
(int)dst.step[0], dstroi, coeffs, mode );
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if( status < 0)
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*ok = false;
}
private:
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Mat &src;
Mat &dst;
int mode;
double (&coeffs)[2][3];
int borderType;
Scalar borderValue;
ippiWarpAffineBackFunc func;
bool *ok;
const IPPWarpAffineInvoker& operator= (const IPPWarpAffineInvoker&);
};
#endif
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#ifdef HAVE_OPENCL
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enum { OCL_OP_PERSPECTIVE = 1, OCL_OP_AFFINE = 0 };
static bool ocl_warpTransform(InputArray _src, OutputArray _dst, InputArray _M0,
Size dsize, int flags, int borderType, const Scalar& borderValue,
int op_type)
{
CV_Assert(op_type == OCL_OP_AFFINE || op_type == OCL_OP_PERSPECTIVE);
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const ocl::Device & dev = ocl::Device::getDefault();
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int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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double doubleSupport = dev.doubleFPConfig() > 0;
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int interpolation = flags & INTER_MAX;
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if( interpolation == INTER_AREA )
interpolation = INTER_LINEAR;
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int rowsPerWI = dev.isIntel() && op_type == OCL_OP_AFFINE && interpolation <= INTER_LINEAR ? 4 : 1;
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if ( !(borderType == cv::BORDER_CONSTANT &&
(interpolation == cv::INTER_NEAREST || interpolation == cv::INTER_LINEAR || interpolation == cv::INTER_CUBIC)) ||
(!doubleSupport && depth == CV_64F) || cn > 4)
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return false;
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const char * const interpolationMap[3] = { "NEAREST", "LINEAR", "CUBIC" };
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ocl::ProgramSource program = op_type == OCL_OP_AFFINE ?
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ocl::imgproc::warp_affine_oclsrc : ocl::imgproc::warp_perspective_oclsrc;
const char * const kernelName = op_type == OCL_OP_AFFINE ? "warpAffine" : "warpPerspective";
int scalarcn = cn == 3 ? 4 : cn;
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bool is32f = !dev.isAMD() && (interpolation == INTER_CUBIC || interpolation == INTER_LINEAR) && op_type == OCL_OP_AFFINE;
int wdepth = interpolation == INTER_NEAREST ? depth : std::max(is32f ? CV_32F : CV_32S, depth);
int sctype = CV_MAKETYPE(wdepth, scalarcn);
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ocl::Kernel k;
String opts;
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if (interpolation == INTER_NEAREST)
{
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opts = format("-D INTER_NEAREST -D T=%s%s -D T1=%s -D ST=%s -D cn=%d -D rowsPerWI=%d",
ocl::typeToStr(type), doubleSupport ? " -D DOUBLE_SUPPORT" : "",
ocl::typeToStr(CV_MAT_DEPTH(type)),
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ocl::typeToStr(sctype), cn, rowsPerWI);
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}
else
{
char cvt[2][50];
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opts = format("-D INTER_%s -D T=%s -D T1=%s -D ST=%s -D WT=%s -D depth=%d"
" -D convertToWT=%s -D convertToT=%s%s -D cn=%d -D rowsPerWI=%d",
interpolationMap[interpolation], ocl::typeToStr(type),
ocl::typeToStr(CV_MAT_DEPTH(type)),
ocl::typeToStr(sctype),
ocl::typeToStr(CV_MAKE_TYPE(wdepth, cn)), depth,
ocl::convertTypeStr(depth, wdepth, cn, cvt[0]),
ocl::convertTypeStr(wdepth, depth, cn, cvt[1]),
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doubleSupport ? " -D DOUBLE_SUPPORT" : "", cn, rowsPerWI);
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}
k.create(kernelName, program, opts);
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if (k.empty())
return false;
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double borderBuf[] = { 0, 0, 0, 0 };
scalarToRawData(borderValue, borderBuf, sctype);
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UMat src = _src.getUMat(), M0;
_dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
UMat dst = _dst.getUMat();
double M[9];
int matRows = (op_type == OCL_OP_AFFINE ? 2 : 3);
Mat matM(matRows, 3, CV_64F, M), M1 = _M0.getMat();
CV_Assert( (M1.type() == CV_32F || M1.type() == CV_64F) &&
M1.rows == matRows && M1.cols == 3 );
M1.convertTo(matM, matM.type());
if( !(flags & WARP_INVERSE_MAP) )
{
if (op_type == OCL_OP_PERSPECTIVE)
invert(matM, matM);
else
{
double D = M[0]*M[4] - M[1]*M[3];
D = D != 0 ? 1./D : 0;
double A11 = M[4]*D, A22=M[0]*D;
M[0] = A11; M[1] *= -D;
M[3] *= -D; M[4] = A22;
double b1 = -M[0]*M[2] - M[1]*M[5];
double b2 = -M[3]*M[2] - M[4]*M[5];
M[2] = b1; M[5] = b2;
}
}
matM.convertTo(M0, doubleSupport ? CV_64F : CV_32F);
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k.args(ocl::KernelArg::ReadOnly(src), ocl::KernelArg::WriteOnly(dst), ocl::KernelArg::PtrReadOnly(M0),
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ocl::KernelArg(0, 0, 0, 0, borderBuf, CV_ELEM_SIZE(sctype)));
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size_t globalThreads[2] = { dst.cols, (dst.rows + rowsPerWI - 1) / rowsPerWI };
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return k.run(2, globalThreads, NULL, false);
}
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#endif
}
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void cv::warpAffine( InputArray _src, OutputArray _dst,
InputArray _M0, Size dsize,
int flags, int borderType, const Scalar& borderValue )
{
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CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_warpTransform(_src, _dst, _M0, dsize, flags, borderType,
borderValue, OCL_OP_AFFINE))
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Mat src = _src.getMat(), M0 = _M0.getMat();
_dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
Mat dst = _dst.getMat();
CV_Assert( src.cols > 0 && src.rows > 0 );
if( dst.data == src.data )
src = src.clone();
double M[6];
Mat matM(2, 3, CV_64F, M);
int interpolation = flags & INTER_MAX;
if( interpolation == INTER_AREA )
interpolation = INTER_LINEAR;
CV_Assert( (M0.type() == CV_32F || M0.type() == CV_64F) && M0.rows == 2 && M0.cols == 3 );
M0.convertTo(matM, matM.type());
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#ifdef HAVE_TEGRA_OPTIMIZATION
if( tegra::warpAffine(src, dst, M, flags, borderType, borderValue) )
return;
#endif
if( !(flags & WARP_INVERSE_MAP) )
{
double D = M[0]*M[4] - M[1]*M[3];
D = D != 0 ? 1./D : 0;
double A11 = M[4]*D, A22=M[0]*D;
M[0] = A11; M[1] *= -D;
M[3] *= -D; M[4] = A22;
double b1 = -M[0]*M[2] - M[1]*M[5];
double b2 = -M[3]*M[2] - M[4]*M[5];
M[2] = b1; M[5] = b2;
}
int x;
AutoBuffer<int> _abdelta(dst.cols*2);
int* adelta = &_abdelta[0], *bdelta = adelta + dst.cols;
const int AB_BITS = MAX(10, (int)INTER_BITS);
const int AB_SCALE = 1 << AB_BITS;
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#if defined (HAVE_IPP) && IPP_VERSION_MAJOR * 100 + IPP_VERSION_MINOR >= 801 && 0
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int type = src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if( ( depth == CV_8U || depth == CV_16U || depth == CV_32F ) &&
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( cn == 1 || cn == 3 || cn == 4 ) &&
( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC) &&
( borderType == cv::BORDER_TRANSPARENT || borderType == cv::BORDER_CONSTANT) )
{
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ippiWarpAffineBackFunc ippFunc = 0;
if ((flags & WARP_INVERSE_MAP) != 0)
{
ippFunc =
type == CV_8UC1 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_8u_C1R :
type == CV_8UC3 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_8u_C3R :
type == CV_8UC4 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_8u_C4R :
type == CV_16UC1 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_16u_C1R :
type == CV_16UC3 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_16u_C3R :
type == CV_16UC4 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_16u_C4R :
type == CV_32FC1 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_32f_C1R :
type == CV_32FC3 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_32f_C3R :
type == CV_32FC4 ? (ippiWarpAffineBackFunc)ippiWarpAffineBack_32f_C4R :
0;
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}
else
{
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ippFunc =
type == CV_8UC1 ? (ippiWarpAffineBackFunc)ippiWarpAffine_8u_C1R :
type == CV_8UC3 ? (ippiWarpAffineBackFunc)ippiWarpAffine_8u_C3R :
type == CV_8UC4 ? (ippiWarpAffineBackFunc)ippiWarpAffine_8u_C4R :
type == CV_16UC1 ? (ippiWarpAffineBackFunc)ippiWarpAffine_16u_C1R :
type == CV_16UC3 ? (ippiWarpAffineBackFunc)ippiWarpAffine_16u_C3R :
type == CV_16UC4 ? (ippiWarpAffineBackFunc)ippiWarpAffine_16u_C4R :
type == CV_32FC1 ? (ippiWarpAffineBackFunc)ippiWarpAffine_32f_C1R :
type == CV_32FC3 ? (ippiWarpAffineBackFunc)ippiWarpAffine_32f_C3R :
type == CV_32FC4 ? (ippiWarpAffineBackFunc)ippiWarpAffine_32f_C4R :
0;
}
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int mode =
interpolation == INTER_LINEAR ? IPPI_INTER_LINEAR :
interpolation == INTER_NEAREST ? IPPI_INTER_NN :
interpolation == INTER_CUBIC ? IPPI_INTER_CUBIC :
0;
CV_Assert(mode && ippFunc);
double coeffs[2][3];
for( int i = 0; i < 2; i++ )
for( int j = 0; j < 3; j++ )
coeffs[i][j] = matM.at<double>(i, j);
bool ok;
Range range(0, dst.rows);
IPPWarpAffineInvoker invoker(src, dst, coeffs, mode, borderType, borderValue, ippFunc, &ok);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
if( ok )
return;
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setIppErrorStatus();
}
#endif
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for( x = 0; x < dst.cols; x++ )
{
adelta[x] = saturate_cast<int>(M[0]*x*AB_SCALE);
bdelta[x] = saturate_cast<int>(M[3]*x*AB_SCALE);
}
Range range(0, dst.rows);
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WarpAffineInvoker invoker(src, dst, interpolation, borderType,
borderValue, adelta, bdelta, M);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
}
namespace cv
{
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class WarpPerspectiveInvoker :
public ParallelLoopBody
{
public:
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WarpPerspectiveInvoker(const Mat &_src, Mat &_dst, double *_M, int _interpolation,
int _borderType, const Scalar &_borderValue) :
ParallelLoopBody(), src(_src), dst(_dst), M(_M), interpolation(_interpolation),
borderType(_borderType), borderValue(_borderValue)
{
}
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virtual void operator() (const Range& range) const
{
const int BLOCK_SZ = 32;
short XY[BLOCK_SZ*BLOCK_SZ*2], A[BLOCK_SZ*BLOCK_SZ];
int x, y, x1, y1, width = dst.cols, height = dst.rows;
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int bh0 = std::min(BLOCK_SZ/2, height);
int bw0 = std::min(BLOCK_SZ*BLOCK_SZ/bh0, width);
bh0 = std::min(BLOCK_SZ*BLOCK_SZ/bw0, height);
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for( y = range.start; y < range.end; y += bh0 )
{
for( x = 0; x < width; x += bw0 )
{
int bw = std::min( bw0, width - x);
int bh = std::min( bh0, range.end - y); // height
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Mat _XY(bh, bw, CV_16SC2, XY), matA;
Mat dpart(dst, Rect(x, y, bw, bh));
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for( y1 = 0; y1 < bh; y1++ )
{
short* xy = XY + y1*bw*2;
double X0 = M[0]*x + M[1]*(y + y1) + M[2];
double Y0 = M[3]*x + M[4]*(y + y1) + M[5];
double W0 = M[6]*x + M[7]*(y + y1) + M[8];
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if( interpolation == INTER_NEAREST )
for( x1 = 0; x1 < bw; x1++ )
{
double W = W0 + M[6]*x1;
W = W ? 1./W : 0;
double fX = std::max((double)INT_MIN, std::min((double)INT_MAX, (X0 + M[0]*x1)*W));
double fY = std::max((double)INT_MIN, std::min((double)INT_MAX, (Y0 + M[3]*x1)*W));
int X = saturate_cast<int>(fX);
int Y = saturate_cast<int>(fY);
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xy[x1*2] = saturate_cast<short>(X);
xy[x1*2+1] = saturate_cast<short>(Y);
}
else
{
short* alpha = A + y1*bw;
for( x1 = 0; x1 < bw; x1++ )
{
double W = W0 + M[6]*x1;
W = W ? INTER_TAB_SIZE/W : 0;
double fX = std::max((double)INT_MIN, std::min((double)INT_MAX, (X0 + M[0]*x1)*W));
double fY = std::max((double)INT_MIN, std::min((double)INT_MAX, (Y0 + M[3]*x1)*W));
int X = saturate_cast<int>(fX);
int Y = saturate_cast<int>(fY);
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xy[x1*2] = saturate_cast<short>(X >> INTER_BITS);
xy[x1*2+1] = saturate_cast<short>(Y >> INTER_BITS);
alpha[x1] = (short)((Y & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE +
(X & (INTER_TAB_SIZE-1)));
}
}
}
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if( interpolation == INTER_NEAREST )
remap( src, dpart, _XY, Mat(), interpolation, borderType, borderValue );
else
{
Mat _matA(bh, bw, CV_16U, A);
remap( src, dpart, _XY, _matA, interpolation, borderType, borderValue );
}
}
}
}
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private:
Mat src;
Mat dst;
double* M;
int interpolation, borderType;
Scalar borderValue;
};
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#if defined (HAVE_IPP) && IPP_VERSION_MAJOR * 100 + IPP_VERSION_MINOR >= 801 && 0
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class IPPWarpPerspectiveInvoker :
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public ParallelLoopBody
{
public:
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IPPWarpPerspectiveInvoker(Mat &_src, Mat &_dst, double (&_coeffs)[3][3], int &_interpolation,
int &_borderType, const Scalar &_borderValue, ippiWarpPerspectiveFunc _func, bool *_ok) :
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ParallelLoopBody(), src(_src), dst(_dst), mode(_interpolation), coeffs(_coeffs),
borderType(_borderType), borderValue(_borderValue), func(_func), ok(_ok)
{
*ok = true;
}
virtual void operator() (const Range& range) const
{
IppiSize srcsize = {src.cols, src.rows};
IppiRect srcroi = {0, 0, src.cols, src.rows};
IppiRect dstroi = {0, range.start, dst.cols, range.end - range.start};
int cnn = src.channels();
if( borderType == BORDER_CONSTANT )
{
IppiSize setSize = {dst.cols, range.end - range.start};
void *dataPointer = dst.data + dst.step[0] * range.start;
if( !IPPSet( borderValue, dataPointer, (int)dst.step[0], setSize, cnn, src.depth() ) )
{
*ok = false;
return;
}
}
IppStatus status = func(src.data, srcsize, (int)src.step[0], srcroi, dst.data, (int)dst.step[0], dstroi, coeffs, mode);
if (status != ippStsNoErr)
*ok = false;
}
private:
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Mat &src;
Mat &dst;
int mode;
double (&coeffs)[3][3];
int borderType;
const Scalar borderValue;
ippiWarpPerspectiveFunc func;
bool *ok;
const IPPWarpPerspectiveInvoker& operator= (const IPPWarpPerspectiveInvoker&);
};
#endif
}
void cv::warpPerspective( InputArray _src, OutputArray _dst, InputArray _M0,
Size dsize, int flags, int borderType, const Scalar& borderValue )
{
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CV_Assert( _src.total() > 0 );
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CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_warpTransform(_src, _dst, _M0, dsize, flags, borderType, borderValue,
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OCL_OP_PERSPECTIVE))
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Mat src = _src.getMat(), M0 = _M0.getMat();
_dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
Mat dst = _dst.getMat();
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if( dst.data == src.data )
src = src.clone();
double M[9];
Mat matM(3, 3, CV_64F, M);
int interpolation = flags & INTER_MAX;
if( interpolation == INTER_AREA )
interpolation = INTER_LINEAR;
CV_Assert( (M0.type() == CV_32F || M0.type() == CV_64F) && M0.rows == 3 && M0.cols == 3 );
M0.convertTo(matM, matM.type());
#ifdef HAVE_TEGRA_OPTIMIZATION
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if( tegra::warpPerspective(src, dst, M, flags, borderType, borderValue) )
return;
#endif
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#if defined (HAVE_IPP) && IPP_VERSION_MAJOR * 100 + IPP_VERSION_MINOR >= 801 && 0
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int type = src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if( (depth == CV_8U || depth == CV_16U || depth == CV_32F) &&
(cn == 1 || cn == 3 || cn == 4) &&
( borderType == cv::BORDER_TRANSPARENT || borderType == cv::BORDER_CONSTANT ) &&
(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC))
{
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ippiWarpPerspectiveFunc ippFunc = 0;
if ((flags & WARP_INVERSE_MAP) != 0)
{
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ippFunc = type == CV_8UC1 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_8u_C1R :
type == CV_8UC3 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_8u_C3R :
type == CV_8UC4 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_8u_C4R :
type == CV_16UC1 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_16u_C1R :
type == CV_16UC3 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_16u_C3R :
type == CV_16UC4 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_16u_C4R :
type == CV_32FC1 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_32f_C1R :
type == CV_32FC3 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_32f_C3R :
type == CV_32FC4 ? (ippiWarpPerspectiveFunc)ippiWarpPerspectiveBack_32f_C4R : 0;
}
else
{
ippFunc = type == CV_8UC1 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_8u_C1R :
type == CV_8UC3 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_8u_C3R :
type == CV_8UC4 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_8u_C4R :
type == CV_16UC1 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_16u_C1R :
type == CV_16UC3 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_16u_C3R :
type == CV_16UC4 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_16u_C4R :
type == CV_32FC1 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_32f_C1R :
type == CV_32FC3 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_32f_C3R :
type == CV_32FC4 ? (ippiWarpPerspectiveFunc)ippiWarpPerspective_32f_C4R : 0;
}
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int mode =
interpolation == INTER_NEAREST ? IPPI_INTER_NN :
interpolation == INTER_LINEAR ? IPPI_INTER_LINEAR :
interpolation == INTER_CUBIC ? IPPI_INTER_CUBIC : 0;
CV_Assert(mode && ippFunc);
double coeffs[3][3];
for( int i = 0; i < 3; i++ )
for( int j = 0; j < 3; j++ )
coeffs[i][j] = matM.at<double>(i, j);
bool ok;
Range range(0, dst.rows);
IPPWarpPerspectiveInvoker invoker(src, dst, coeffs, mode, borderType, borderValue, ippFunc, &ok);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
if( ok )
return;
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setIppErrorStatus();
}
#endif
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if( !(flags & WARP_INVERSE_MAP) )
invert(matM, matM);
Range range(0, dst.rows);
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WarpPerspectiveInvoker invoker(src, dst, M, interpolation, borderType, borderValue);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
}
cv::Mat cv::getRotationMatrix2D( Point2f center, double angle, double scale )
{
angle *= CV_PI/180;
double alpha = cos(angle)*scale;
double beta = sin(angle)*scale;
Mat M(2, 3, CV_64F);
double* m = (double*)M.data;
m[0] = alpha;
m[1] = beta;
m[2] = (1-alpha)*center.x - beta*center.y;
m[3] = -beta;
m[4] = alpha;
m[5] = beta*center.x + (1-alpha)*center.y;
return M;
}
/* Calculates coefficients of perspective transformation
* which maps (xi,yi) to (ui,vi), (i=1,2,3,4):
*
* c00*xi + c01*yi + c02
* ui = ---------------------
* c20*xi + c21*yi + c22
*
* c10*xi + c11*yi + c12
* vi = ---------------------
* c20*xi + c21*yi + c22
*
* Coefficients are calculated by solving linear system:
* / x0 y0 1 0 0 0 -x0*u0 -y0*u0 \ /c00\ /u0\
* | x1 y1 1 0 0 0 -x1*u1 -y1*u1 | |c01| |u1|
* | x2 y2 1 0 0 0 -x2*u2 -y2*u2 | |c02| |u2|
* | x3 y3 1 0 0 0 -x3*u3 -y3*u3 |.|c10|=|u3|,
* | 0 0 0 x0 y0 1 -x0*v0 -y0*v0 | |c11| |v0|
* | 0 0 0 x1 y1 1 -x1*v1 -y1*v1 | |c12| |v1|
* | 0 0 0 x2 y2 1 -x2*v2 -y2*v2 | |c20| |v2|
* \ 0 0 0 x3 y3 1 -x3*v3 -y3*v3 / \c21/ \v3/
*
* where:
* cij - matrix coefficients, c22 = 1
*/
cv::Mat cv::getPerspectiveTransform( const Point2f src[], const Point2f dst[] )
{
Mat M(3, 3, CV_64F), X(8, 1, CV_64F, M.data);
double a[8][8], b[8];
Mat A(8, 8, CV_64F, a), B(8, 1, CV_64F, b);
for( int i = 0; i < 4; ++i )
{
a[i][0] = a[i+4][3] = src[i].x;
a[i][1] = a[i+4][4] = src[i].y;
a[i][2] = a[i+4][5] = 1;
a[i][3] = a[i][4] = a[i][5] =
a[i+4][0] = a[i+4][1] = a[i+4][2] = 0;
a[i][6] = -src[i].x*dst[i].x;
a[i][7] = -src[i].y*dst[i].x;
a[i+4][6] = -src[i].x*dst[i].y;
a[i+4][7] = -src[i].y*dst[i].y;
b[i] = dst[i].x;
b[i+4] = dst[i].y;
}
solve( A, B, X, DECOMP_SVD );
((double*)M.data)[8] = 1.;
return M;
}
/* Calculates coefficients of affine transformation
* which maps (xi,yi) to (ui,vi), (i=1,2,3):
*
* ui = c00*xi + c01*yi + c02
*
* vi = c10*xi + c11*yi + c12
*
* Coefficients are calculated by solving linear system:
* / x0 y0 1 0 0 0 \ /c00\ /u0\
* | x1 y1 1 0 0 0 | |c01| |u1|
* | x2 y2 1 0 0 0 | |c02| |u2|
* | 0 0 0 x0 y0 1 | |c10| |v0|
* | 0 0 0 x1 y1 1 | |c11| |v1|
* \ 0 0 0 x2 y2 1 / |c12| |v2|
*
* where:
* cij - matrix coefficients
*/
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cv::Mat cv::getAffineTransform( const Point2f src[], const Point2f dst[] )
{
Mat M(2, 3, CV_64F), X(6, 1, CV_64F, M.data);
double a[6*6], b[6];
Mat A(6, 6, CV_64F, a), B(6, 1, CV_64F, b);
for( int i = 0; i < 3; i++ )
{
int j = i*12;
int k = i*12+6;
a[j] = a[k+3] = src[i].x;
a[j+1] = a[k+4] = src[i].y;
a[j+2] = a[k+5] = 1;
a[j+3] = a[j+4] = a[j+5] = 0;
a[k] = a[k+1] = a[k+2] = 0;
b[i*2] = dst[i].x;
b[i*2+1] = dst[i].y;
}
solve( A, B, X );
return M;
}
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void cv::invertAffineTransform(InputArray _matM, OutputArray __iM)
{
Mat matM = _matM.getMat();
CV_Assert(matM.rows == 2 && matM.cols == 3);
__iM.create(2, 3, matM.type());
Mat _iM = __iM.getMat();
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if( matM.type() == CV_32F )
{
const float* M = (const float*)matM.data;
float* iM = (float*)_iM.data;
int step = (int)(matM.step/sizeof(M[0])), istep = (int)(_iM.step/sizeof(iM[0]));
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double D = M[0]*M[step+1] - M[1]*M[step];
D = D != 0 ? 1./D : 0;
double A11 = M[step+1]*D, A22 = M[0]*D, A12 = -M[1]*D, A21 = -M[step]*D;
double b1 = -A11*M[2] - A12*M[step+2];
double b2 = -A21*M[2] - A22*M[step+2];
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iM[0] = (float)A11; iM[1] = (float)A12; iM[2] = (float)b1;
iM[istep] = (float)A21; iM[istep+1] = (float)A22; iM[istep+2] = (float)b2;
}
else if( matM.type() == CV_64F )
{
const double* M = (const double*)matM.data;
double* iM = (double*)_iM.data;
int step = (int)(matM.step/sizeof(M[0])), istep = (int)(_iM.step/sizeof(iM[0]));
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double D = M[0]*M[step+1] - M[1]*M[step];
D = D != 0 ? 1./D : 0;
double A11 = M[step+1]*D, A22 = M[0]*D, A12 = -M[1]*D, A21 = -M[step]*D;
double b1 = -A11*M[2] - A12*M[step+2];
double b2 = -A21*M[2] - A22*M[step+2];
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iM[0] = A11; iM[1] = A12; iM[2] = b1;
iM[istep] = A21; iM[istep+1] = A22; iM[istep+2] = b2;
}
else
CV_Error( CV_StsUnsupportedFormat, "" );
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}
cv::Mat cv::getPerspectiveTransform(InputArray _src, InputArray _dst)
{
Mat src = _src.getMat(), dst = _dst.getMat();
CV_Assert(src.checkVector(2, CV_32F) == 4 && dst.checkVector(2, CV_32F) == 4);
return getPerspectiveTransform((const Point2f*)src.data, (const Point2f*)dst.data);
}
cv::Mat cv::getAffineTransform(InputArray _src, InputArray _dst)
{
Mat src = _src.getMat(), dst = _dst.getMat();
CV_Assert(src.checkVector(2, CV_32F) == 3 && dst.checkVector(2, CV_32F) == 3);
return getAffineTransform((const Point2f*)src.data, (const Point2f*)dst.data);
}
CV_IMPL void
cvResize( const CvArr* srcarr, CvArr* dstarr, int method )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( src.type() == dst.type() );
cv::resize( src, dst, dst.size(), (double)dst.cols/src.cols,
(double)dst.rows/src.rows, method );
}
CV_IMPL void
cvWarpAffine( const CvArr* srcarr, CvArr* dstarr, const CvMat* marr,
int flags, CvScalar fillval )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
cv::Mat matrix = cv::cvarrToMat(marr);
CV_Assert( src.type() == dst.type() );
cv::warpAffine( src, dst, matrix, dst.size(), flags,
(flags & CV_WARP_FILL_OUTLIERS) ? cv::BORDER_CONSTANT : cv::BORDER_TRANSPARENT,
fillval );
}
CV_IMPL void
cvWarpPerspective( const CvArr* srcarr, CvArr* dstarr, const CvMat* marr,
int flags, CvScalar fillval )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
cv::Mat matrix = cv::cvarrToMat(marr);
CV_Assert( src.type() == dst.type() );
cv::warpPerspective( src, dst, matrix, dst.size(), flags,
(flags & CV_WARP_FILL_OUTLIERS) ? cv::BORDER_CONSTANT : cv::BORDER_TRANSPARENT,
fillval );
}
CV_IMPL void
cvRemap( const CvArr* srcarr, CvArr* dstarr,
const CvArr* _mapx, const CvArr* _mapy,
int flags, CvScalar fillval )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), dst0 = dst;
cv::Mat mapx = cv::cvarrToMat(_mapx), mapy = cv::cvarrToMat(_mapy);
CV_Assert( src.type() == dst.type() && dst.size() == mapx.size() );
cv::remap( src, dst, mapx, mapy, flags & cv::INTER_MAX,
(flags & CV_WARP_FILL_OUTLIERS) ? cv::BORDER_CONSTANT : cv::BORDER_TRANSPARENT,
fillval );
CV_Assert( dst0.data == dst.data );
}
CV_IMPL CvMat*
cv2DRotationMatrix( CvPoint2D32f center, double angle,
double scale, CvMat* matrix )
{
cv::Mat M0 = cv::cvarrToMat(matrix), M = cv::getRotationMatrix2D(center, angle, scale);
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CV_Assert( M.size() == M0.size() );
M.convertTo(M0, M0.type());
return matrix;
}
CV_IMPL CvMat*
cvGetPerspectiveTransform( const CvPoint2D32f* src,
const CvPoint2D32f* dst,
CvMat* matrix )
{
cv::Mat M0 = cv::cvarrToMat(matrix),
M = cv::getPerspectiveTransform((const cv::Point2f*)src, (const cv::Point2f*)dst);
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CV_Assert( M.size() == M0.size() );
M.convertTo(M0, M0.type());
return matrix;
}
CV_IMPL CvMat*
cvGetAffineTransform( const CvPoint2D32f* src,
const CvPoint2D32f* dst,
CvMat* matrix )
{
cv::Mat M0 = cv::cvarrToMat(matrix),
M = cv::getAffineTransform((const cv::Point2f*)src, (const cv::Point2f*)dst);
CV_Assert( M.size() == M0.size() );
M.convertTo(M0, M0.type());
return matrix;
}
CV_IMPL void
cvConvertMaps( const CvArr* arr1, const CvArr* arr2, CvArr* dstarr1, CvArr* dstarr2 )
{
cv::Mat map1 = cv::cvarrToMat(arr1), map2;
cv::Mat dstmap1 = cv::cvarrToMat(dstarr1), dstmap2;
if( arr2 )
map2 = cv::cvarrToMat(arr2);
if( dstarr2 )
{
dstmap2 = cv::cvarrToMat(dstarr2);
if( dstmap2.type() == CV_16SC1 )
dstmap2 = cv::Mat(dstmap2.size(), CV_16UC1, dstmap2.data, dstmap2.step);
}
cv::convertMaps( map1, map2, dstmap1, dstmap2, dstmap1.type(), false );
}
/****************************************************************************************\
* Log-Polar Transform *
\****************************************************************************************/
/* now it is done via Remap; more correct implementation should use
some super-sampling technique outside of the "fovea" circle */
CV_IMPL void
cvLogPolar( const CvArr* srcarr, CvArr* dstarr,
CvPoint2D32f center, double M, int flags )
{
cv::Ptr<CvMat> mapx, mapy;
CvMat srcstub, *src = cvGetMat(srcarr, &srcstub);
CvMat dststub, *dst = cvGetMat(dstarr, &dststub);
CvSize ssize, dsize;
if( !CV_ARE_TYPES_EQ( src, dst ))
CV_Error( CV_StsUnmatchedFormats, "" );
if( M <= 0 )
CV_Error( CV_StsOutOfRange, "M should be >0" );
ssize = cvGetMatSize(src);
dsize = cvGetMatSize(dst);
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mapx.reset(cvCreateMat( dsize.height, dsize.width, CV_32F ));
mapy.reset(cvCreateMat( dsize.height, dsize.width, CV_32F ));
if( !(flags & CV_WARP_INVERSE_MAP) )
{
int phi, rho;
cv::AutoBuffer<double> _exp_tab(dsize.width);
double* exp_tab = _exp_tab;
for( rho = 0; rho < dst->width; rho++ )
exp_tab[rho] = std::exp(rho/M);
for( phi = 0; phi < dsize.height; phi++ )
{
double cp = cos(phi*2*CV_PI/dsize.height);
double sp = sin(phi*2*CV_PI/dsize.height);
float* mx = (float*)(mapx->data.ptr + phi*mapx->step);
float* my = (float*)(mapy->data.ptr + phi*mapy->step);
for( rho = 0; rho < dsize.width; rho++ )
{
double r = exp_tab[rho];
double x = r*cp + center.x;
double y = r*sp + center.y;
mx[rho] = (float)x;
my[rho] = (float)y;
}
}
}
else
{
int x, y;
CvMat bufx, bufy, bufp, bufa;
double ascale = ssize.height/(2*CV_PI);
cv::AutoBuffer<float> _buf(4*dsize.width);
float* buf = _buf;
bufx = cvMat( 1, dsize.width, CV_32F, buf );
bufy = cvMat( 1, dsize.width, CV_32F, buf + dsize.width );
bufp = cvMat( 1, dsize.width, CV_32F, buf + dsize.width*2 );
bufa = cvMat( 1, dsize.width, CV_32F, buf + dsize.width*3 );
for( x = 0; x < dsize.width; x++ )
bufx.data.fl[x] = (float)x - center.x;
for( y = 0; y < dsize.height; y++ )
{
float* mx = (float*)(mapx->data.ptr + y*mapx->step);
float* my = (float*)(mapy->data.ptr + y*mapy->step);
for( x = 0; x < dsize.width; x++ )
bufy.data.fl[x] = (float)y - center.y;
#if 1
cvCartToPolar( &bufx, &bufy, &bufp, &bufa );
for( x = 0; x < dsize.width; x++ )
bufp.data.fl[x] += 1.f;
cvLog( &bufp, &bufp );
for( x = 0; x < dsize.width; x++ )
{
double rho = bufp.data.fl[x]*M;
double phi = bufa.data.fl[x]*ascale;
mx[x] = (float)rho;
my[x] = (float)phi;
}
#else
for( x = 0; x < dsize.width; x++ )
{
double xx = bufx.data.fl[x];
double yy = bufy.data.fl[x];
double p = log(std::sqrt(xx*xx + yy*yy) + 1.)*M;
double a = atan2(yy,xx);
if( a < 0 )
a = 2*CV_PI + a;
a *= ascale;
mx[x] = (float)p;
my[x] = (float)a;
}
#endif
}
}
cvRemap( src, dst, mapx, mapy, flags, cvScalarAll(0) );
}
void cv::logPolar( InputArray _src, OutputArray _dst,
Point2f center, double M, int flags )
{
Mat src = _src.getMat();
_dst.create( src.size(), src.type() );
CvMat c_src = src, c_dst = _dst.getMat();
cvLogPolar( &c_src, &c_dst, center, M, flags );
}
/****************************************************************************************
Linear-Polar Transform
J.L. Blanco, Apr 2009
****************************************************************************************/
CV_IMPL
void cvLinearPolar( const CvArr* srcarr, CvArr* dstarr,
CvPoint2D32f center, double maxRadius, int flags )
{
cv::Ptr<CvMat> mapx, mapy;
CvMat srcstub, *src = (CvMat*)srcarr;
CvMat dststub, *dst = (CvMat*)dstarr;
CvSize ssize, dsize;
src = cvGetMat( srcarr, &srcstub,0,0 );
dst = cvGetMat( dstarr, &dststub,0,0 );
if( !CV_ARE_TYPES_EQ( src, dst ))
CV_Error( CV_StsUnmatchedFormats, "" );
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ssize.width = src->cols;
ssize.height = src->rows;
dsize.width = dst->cols;
dsize.height = dst->rows;
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mapx.reset(cvCreateMat( dsize.height, dsize.width, CV_32F ));
mapy.reset(cvCreateMat( dsize.height, dsize.width, CV_32F ));
if( !(flags & CV_WARP_INVERSE_MAP) )
{
int phi, rho;
for( phi = 0; phi < dsize.height; phi++ )
{
double cp = cos(phi*2*CV_PI/dsize.height);
double sp = sin(phi*2*CV_PI/dsize.height);
float* mx = (float*)(mapx->data.ptr + phi*mapx->step);
float* my = (float*)(mapy->data.ptr + phi*mapy->step);
for( rho = 0; rho < dsize.width; rho++ )
{
double r = maxRadius*(rho+1)/dsize.width;
double x = r*cp + center.x;
double y = r*sp + center.y;
mx[rho] = (float)x;
my[rho] = (float)y;
}
}
}
else
{
int x, y;
CvMat bufx, bufy, bufp, bufa;
const double ascale = ssize.height/(2*CV_PI);
const double pscale = ssize.width/maxRadius;
cv::AutoBuffer<float> _buf(4*dsize.width);
float* buf = _buf;
bufx = cvMat( 1, dsize.width, CV_32F, buf );
bufy = cvMat( 1, dsize.width, CV_32F, buf + dsize.width );
bufp = cvMat( 1, dsize.width, CV_32F, buf + dsize.width*2 );
bufa = cvMat( 1, dsize.width, CV_32F, buf + dsize.width*3 );
for( x = 0; x < dsize.width; x++ )
bufx.data.fl[x] = (float)x - center.x;
for( y = 0; y < dsize.height; y++ )
{
float* mx = (float*)(mapx->data.ptr + y*mapx->step);
float* my = (float*)(mapy->data.ptr + y*mapy->step);
for( x = 0; x < dsize.width; x++ )
bufy.data.fl[x] = (float)y - center.y;
cvCartToPolar( &bufx, &bufy, &bufp, &bufa, 0 );
for( x = 0; x < dsize.width; x++ )
bufp.data.fl[x] += 1.f;
for( x = 0; x < dsize.width; x++ )
{
double rho = bufp.data.fl[x]*pscale;
double phi = bufa.data.fl[x]*ascale;
mx[x] = (float)rho;
my[x] = (float)phi;
}
}
}
cvRemap( src, dst, mapx, mapy, flags, cvScalarAll(0) );
}
void cv::linearPolar( InputArray _src, OutputArray _dst,
Point2f center, double maxRadius, int flags )
{
Mat src = _src.getMat();
_dst.create( src.size(), src.type() );
CvMat c_src = src, c_dst = _dst.getMat();
cvLinearPolar( &c_src, &c_dst, center, maxRadius, flags );
}
/* End of file. */