imgwarp.cpp 162.3 KB
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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 <iostream>
#include <vector>
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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
static IppStatus sts = ippInit();
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#endif
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namespace cv
{

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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
    typedef IppStatus (CV_STDCALL* ippiSetFunc)(const void*, void *, int, IppiSize);
    typedef IppStatus (CV_STDCALL* ippiWarpPerspectiveBackFunc)(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);
    typedef IppStatus (CV_STDCALL* ippiResizeSqrPixelFunc)(const void*, IppiSize, int, IppiRect, void*, int, IppiRect, double, double, double, double, int, Ipp8u *);

    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++ )
            values[i] = (Type)value[i];
        return func(values, dataPointer, step, size) >= 0;
    }

    bool IPPSet(const cv::Scalar &value, void *dataPointer, int step, IppiSize &size, int channels, int depth)
    {
        if( channels == 1 )
        {
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            switch( depth )
            {
            case CV_8U:
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                return ippiSet_8u_C1R((Ipp8u)value[0], (Ipp8u *)dataPointer, step, size) >= 0;
            case CV_16U:
                return ippiSet_16u_C1R((Ipp16u)value[0], (Ipp16u *)dataPointer, step, size) >= 0;
            case CV_32F:
                return ippiSet_32f_C1R((Ipp32f)value[0], (Ipp32f *)dataPointer, step, size) >= 0;
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            }
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        }
        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);
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                }
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            }
            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);
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                }
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            }
        }
        return false;
    }
#endif

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/************** 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);
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#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++ )
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    {
        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++ )
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        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] )
    {
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        AutoBuffer<float> _tab(8*INTER_TAB_SIZE);
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        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;
}

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#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();
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#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                                         *
\****************************************************************************************/

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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;
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    resizeNNInvoker(const resizeNNInvoker&);
    resizeNNInvoker& operator=(const resizeNNInvoker&);
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};

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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;
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    int x;
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    for( x = 0; x < dsize.width; x++ )
    {
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        int sx = cvFloor(x*ifx);
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        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);
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    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
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}


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;
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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;
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struct VResizeCubicVec_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], *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

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typedef HResizeNoVec HResizeLinearVec_8u32s;
typedef HResizeNoVec HResizeLinearVec_16u32f;
typedef HResizeNoVec HResizeLinearVec_16s32f;
typedef HResizeNoVec HResizeLinearVec_32f;
typedef HResizeNoVec HResizeLinearVec_64f;

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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);
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        #if CV_ENABLE_UNROLLED
        for( ; x <= width - 4; x += 4 )
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        {
            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
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        for( ; x < width; x++ )
            dst[x] = castOp(S0[x]*b0 + S1[x]*b1);
    }
};

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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);
    }
};

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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
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        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
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        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;

1204 1205 1206 1207 1208 1209 1210 1211
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;
1212

1213 1214 1215 1216 1217 1218 1219 1220
    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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1222 1223 1224 1225 1226
    virtual void operator() (const Range& range) const
    {
        int dy, cn = src.channels();
        HResize hresize;
        VResize vresize;
1227

1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238
        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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1240
        const AT* beta = _beta + ksize * range.start;
1241

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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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1271
private:
1272
    Mat src;
1273 1274 1275
    Mat dst;
    const int* xofs, *yofs;
    const AT* alpha, *_beta;
1276 1277
    Size ssize, dsize;
    int ksize, xmin, xmax;
1278 1279
};

1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294
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;
1295
    // image resize is a separable operation. In case of not too strong
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1297 1298 1299
    Range range(0, dsize.height);
    resizeGeneric_Invoker<HResize, VResize> invoker(src, dst, xofs, yofs, (const AT*)_alpha, beta,
        ssize, dsize, ksize, xmin, xmax);
1300
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
1301
}
1302

1303 1304 1305
template <typename T, typename WT>
struct ResizeAreaFastNoVec
{
1306 1307 1308 1309
    ResizeAreaFastNoVec(int, int) { }
    ResizeAreaFastNoVec(int, int, int, int) { }
    int operator() (const T*, T*, int) const
    { return 0; }
1310
};
1311

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#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();
1331
        __m128i delta2 = _mm_set1_epi16(2);
1332 1333 1334

        if (cn == 1)
        {
1335
            __m128i masklow = _mm_set1_epi16(0x00ff);
1336
            for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
1337
            {
1338 1339
                __m128i r0 = _mm_loadu_si128((const __m128i*)S0);
                __m128i r1 = _mm_loadu_si128((const __m128i*)S1);
1340

1341 1342 1343 1344
                __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);
1345

1346
                _mm_storel_epi64((__m128i*)D, s0);
1347 1348 1349
            }
        }
        else if (cn == 3)
1350
            for ( ; dx <= w - 6; dx += 6, S0 += 12, S1 += 12, D += 6)
1351
            {
1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370
                __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);
1371 1372 1373 1374
            }
        else
        {
            CV_Assert(cn == 4);
1375
            for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
1376
            {
1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395
                __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));
                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, 8));
                s1 = _mm_add_epi16(r1_16h, _mm_srli_si128(r1_16h, 8));
                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+4), s0);
1396 1397 1398 1399 1400 1401 1402 1403 1404
            }
        }

        return dx;
    }

private:
    int cn;
    bool use_simd;
1405
    int step;
1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417 1418 1419 1420 1421 1422 1423
};

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;
1424
        const ushort* S1 = (const ushort*)((const uchar*)(S) + step);
1425 1426
        __m128i masklow = _mm_set1_epi32(0x0000ffff);
        __m128i zero = _mm_setzero_si128();
1427
        __m128i delta2 = _mm_set1_epi32(2);
1428

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#define _mm_packus_epi32(a, zero) _mm_packs_epi32(_mm_srai_epi32(_mm_slli_epi32(a, 16), 16), zero)
1430

1431 1432
        if (cn == 1)
        {
1433
            for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
1434
            {
1435 1436
                __m128i r0 = _mm_loadu_si128((const __m128i*)S0);
                __m128i r1 = _mm_loadu_si128((const __m128i*)S1);
1437

1438 1439 1440
                __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);
1441 1442
                s0 = _mm_srli_epi32(s0, 2);
                s0 = _mm_packus_epi32(s0, zero);
1443

1444
                _mm_storel_epi64((__m128i*)D, s0);
1445 1446 1447
            }
        }
        else if (cn == 3)
1448
            for ( ; dx <= w - 3; dx += 3, S0 += 6, S1 += 6, D += 3)
1449
            {
1450 1451 1452 1453 1454 1455 1456 1457
                __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);

1458 1459 1460
                __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));
1461
                s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
1462
                _mm_storel_epi64((__m128i*)D, s0);
1463 1464 1465 1466
            }
        else
        {
            CV_Assert(cn == 4);
1467
            for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
1468
            {
1469 1470 1471 1472 1473 1474 1475 1476 1477 1478 1479
                __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));
1480
                s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
1481
                _mm_storel_epi64((__m128i*)D, s0);
1482 1483 1484
            }
        }

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1485 1486
#undef _mm_packus_epi32

1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497 1498 1499 1500 1501
        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>
1502
struct ResizeAreaFastVec
1503
{
1504 1505
    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)
1506 1507
    {
        fast_mode = scale_x == 2 && scale_y == 2 && (cn == 1 || cn == 3 || cn == 4);
1508
    }
1509

1510
    int operator() (const T* S, T* D, int w) const
1511
    {
1512
        if (!fast_mode)
1513
            return 0;
1514

1515
        const T* nextS = (const T*)((const uchar*)S + step);
1516
        int dx = vecOp(S, D, w);
1517

1518
        if (cn == 1)
1519 1520 1521 1522 1523
            for( ; dx < w; ++dx )
            {
                int index = dx*2;
                D[dx] = (T)((S[index] + S[index+1] + nextS[index] + nextS[index+1] + 2) >> 2);
            }
1524
        else if (cn == 3)
1525
            for( ; dx < w; dx += 3 )
1526
            {
1527
                int index = dx*2;
1528 1529 1530 1531 1532 1533
                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
            {
1534
                CV_Assert(cn == 4);
1535 1536 1537 1538 1539 1540 1541 1542
                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);
                }
1543
            }
1544

1545
        return dx;
1546
    }
1547

1548
private:
1549 1550
    int scale_x, scale_y;
    int cn;
1551
    bool fast_mode;
1552
    int step;
1553
    SIMDVecOp vecOp;
1554
};
1555

1556 1557 1558
template <typename T, typename WT, typename VecOp>
class resizeAreaFast_Invoker :
    public ParallelLoopBody
1559
{
1560 1561 1562 1563 1564
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)
1565
    {
1566
    }
1567

1568 1569 1570 1571 1572 1573 1574 1575 1576 1577
    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;
1578

1579
        VecOp vop(scale_x, scale_y, src.channels(), (int)src.step/*, area_ofs*/);
1580

1581
        for( dy = range.start; dy < range.end; dy++ )
1582
        {
1583 1584 1585
            T* D = (T*)(dst.data + dst.step*dy);
            int sy0 = dy*scale_y;
            int w = sy0 + scale_y <= ssize.height ? dwidth1 : 0;
1586

1587 1588 1589 1590 1591 1592
            if( sy0 >= ssize.height )
            {
                for( dx = 0; dx < dsize.width; dx++ )
                    D[dx] = 0;
                continue;
            }
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1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604 1605
            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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1607 1608
                D[dx] = saturate_cast<T>(sum * scale);
            }
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1609

1610
            for( ; dx < dsize.width; dx++ )
1611
            {
1612 1613 1614 1615 1616 1617
                WT sum = 0;
                int count = 0, sx0 = xofs[dx];
                if( sx0 >= ssize.width )
                    D[dx] = 0;

                for( int sy = 0; sy < scale_y; sy++ )
1618
                {
1619
                    if( sy0 + sy >= ssize.height )
1620
                        break;
1621 1622 1623 1624 1625 1626 1627 1628
                    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++;
                    }
1629
                }
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1630

1631
                D[dx] = saturate_cast<T>((float)sum/count);
1632
            }
1633
        }
1634
    }
1635

1636
private:
1637
    Mat src;
1638
    Mat dst;
1639
    int scale_x, scale_y;
1640 1641 1642 1643 1644 1645 1646 1647
    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);
1648
    resizeAreaFast_Invoker<T, WT, VecOp> invoker(src, dst, scale_x,
1649
        scale_y, ofs, xofs);
1650
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
1651 1652 1653 1654 1655 1656 1657 1658
}

struct DecimateAlpha
{
    int si, di;
    float alpha;
};

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template<typename T, typename WT> class ResizeArea_Invoker :
1661
    public ParallelLoopBody
1662
{
1663
public:
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1664 1665 1666 1667
    ResizeArea_Invoker( const Mat& _src, Mat& _dst,
                        const DecimateAlpha* _xtab, int _xtab_size,
                        const DecimateAlpha* _ytab, int _ytab_size,
                        const int* _tabofs )
1668
    {
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1669 1670 1671 1672 1673 1674 1675
        src = &_src;
        dst = &_dst;
        xtab0 = _xtab;
        xtab_size0 = _xtab_size;
        ytab = _ytab;
        ytab_size = _ytab_size;
        tabofs = _tabofs;
1676
    }
1677

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1678
    virtual void operator() (const Range& range) const
1679
    {
V
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1680 1681
        Size dsize = dst->size();
        int cn = dst->channels();
1682 1683
        dsize.width *= cn;
        AutoBuffer<WT> _buffer(dsize.width*2);
V
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1684 1685
        const DecimateAlpha* xtab = xtab0;
        int xtab_size = xtab_size0;
1686
        WT *buf = _buffer, *sum = buf + dsize.width;
1687
        int j_start = tabofs[range.start], j_end = tabofs[range.end], j, k, dx, prev_dy = ytab[j_start].di;
1688

I
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1689
        for( dx = 0; dx < dsize.width; dx++ )
V
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1690
            sum[dx] = (WT)0;
1691

V
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1692
        for( j = j_start; j < j_end; j++ )
1693
        {
V
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1694 1695 1696
            WT beta = ytab[j].alpha;
            int dy = ytab[j].di;
            int sy = ytab[j].si;
1697

1698
            {
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1699 1700 1701 1702 1703 1704 1705 1706 1707 1708 1709 1710 1711 1712 1713 1714 1715 1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731
                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 )
1732
                {
V
Vadim Pisarevsky 已提交
1733
                    for( k = 0; k < xtab_size; k++ )
I
attempt  
Ilya Lavrenov 已提交
1734
                    {
V
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1735 1736 1737 1738 1739 1740 1741 1742 1743
                        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;
I
attempt  
Ilya Lavrenov 已提交
1744
                    }
1745 1746
                }
                else
V
Vadim Pisarevsky 已提交
1747 1748
                {
                    for( k = 0; k < xtab_size; k++ )
1749
                    {
V
Vadim Pisarevsky 已提交
1750 1751 1752 1753 1754
                        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;
1755
                    }
V
Vadim Pisarevsky 已提交
1756
                }
1757
            }
V
Vadim Pisarevsky 已提交
1758 1759

            if( dy != prev_dy )
1760
            {
V
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1761 1762 1763
                T* D = (T*)(dst->data + dst->step*prev_dy);

                for( dx = 0; dx < dsize.width; dx++ )
I
attempt  
Ilya Lavrenov 已提交
1764
                {
V
Vadim Pisarevsky 已提交
1765 1766
                    D[dx] = saturate_cast<T>(sum[dx]);
                    sum[dx] = beta*buf[dx];
I
attempt  
Ilya Lavrenov 已提交
1767
                }
V
Vadim Pisarevsky 已提交
1768 1769 1770 1771 1772 1773
                prev_dy = dy;
            }
            else
            {
                for( dx = 0; dx < dsize.width; dx++ )
                    sum[dx] += beta*buf[dx];
1774 1775
            }
        }
1776

1777
        {
V
Vadim Pisarevsky 已提交
1778 1779 1780
        T* D = (T*)(dst->data + dst->step*prev_dy);
        for( dx = 0; dx < dsize.width; dx++ )
            D[dx] = saturate_cast<T>(sum[dx]);
1781 1782
        }
    }
1783

1784
private:
V
Vadim Pisarevsky 已提交
1785 1786 1787 1788 1789 1790
    const Mat* src;
    Mat* dst;
    const DecimateAlpha* xtab0;
    const DecimateAlpha* ytab;
    int xtab_size0, ytab_size;
    const int* tabofs;
1791 1792
};

V
Vadim Pisarevsky 已提交
1793

I
attempt  
Ilya Lavrenov 已提交
1794
template <typename T, typename WT>
V
Vadim Pisarevsky 已提交
1795 1796 1797 1798
static void resizeArea_( const Mat& src, Mat& dst,
                         const DecimateAlpha* xtab, int xtab_size,
                         const DecimateAlpha* ytab, int ytab_size,
                         const int* tabofs )
1799
{
V
Vadim Pisarevsky 已提交
1800 1801 1802
    parallel_for_(Range(0, dst.rows),
                 ResizeArea_Invoker<T, WT>(src, dst, xtab, xtab_size, ytab, ytab_size, tabofs),
                 dst.total()/((double)(1 << 16)));
1803
}
1804 1805 1806 1807 1808 1809 1810 1811


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,
1812 1813
                                    const int* ofs, const int *xofs,
                                    int scale_x, int scale_y );
1814 1815

typedef void (*ResizeAreaFunc)( const Mat& src, Mat& dst,
V
Vadim Pisarevsky 已提交
1816 1817 1818 1819 1820 1821 1822
                                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 )
{
1823 1824
    int k = 0;
    for(int dx = 0; dx < dsize; dx++ )
V
Vadim Pisarevsky 已提交
1825
    {
1826
        double fsx1 = dx * scale;
V
Vadim Pisarevsky 已提交
1827
        double fsx2 = fsx1 + scale;
1828
        double cellWidth = std::min(scale, ssize - fsx1);
1829

V
Vadim Pisarevsky 已提交
1830 1831
        int sx1 = cvCeil(fsx1), sx2 = cvFloor(fsx2);

1832 1833 1834 1835
        sx2 = std::min(sx2, ssize - 1);
        sx1 = std::min(sx1, sx2);

        if( sx1 - fsx1 > 1e-3 )
V
Vadim Pisarevsky 已提交
1836 1837
        {
            assert( k < ssize*2 );
1838 1839 1840
            tab[k].di = dx * cn;
            tab[k].si = (sx1 - 1) * cn;
            tab[k++].alpha = (float)((sx1 - fsx1) / cellWidth);
V
Vadim Pisarevsky 已提交
1841 1842
        }

1843
        for(int sx = sx1; sx < sx2; sx++ )
V
Vadim Pisarevsky 已提交
1844 1845
        {
            assert( k < ssize*2 );
1846 1847 1848
            tab[k].di = dx * cn;
            tab[k].si = sx * cn;
            tab[k++].alpha = float(1.0 / cellWidth);
V
Vadim Pisarevsky 已提交
1849 1850 1851 1852 1853
        }

        if( fsx2 - sx2 > 1e-3 )
        {
            assert( k < ssize*2 );
1854 1855
            tab[k].di = dx * cn;
            tab[k].si = sx2 * cn;
1856
            tab[k++].alpha = (float)(std::min(std::min(fsx2 - sx2, 1.), cellWidth) / cellWidth);
V
Vadim Pisarevsky 已提交
1857 1858 1859 1860 1861
        }
    }
    return k;
}

1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
class IPPresizeInvoker :
    public ParallelLoopBody
{
public:
    IPPresizeInvoker(Mat &_src, Mat &_dst, double &_inv_scale_x, double &_inv_scale_y, int _mode, ippiResizeSqrPixelFunc _func, bool *_ok) :
      ParallelLoopBody(), src(_src), dst(_dst), inv_scale_x(_inv_scale_x), inv_scale_y(_inv_scale_y), mode(_mode), func(_func), ok(_ok)
      {
          *ok = true;
      }

      virtual void operator() (const Range& range) const
      {
          int cn = src.channels();
          IppiRect srcroi = { 0, range.start, src.cols, range.end - range.start };
          int dsty = CV_IMIN(cvRound(range.start * inv_scale_y), dst.rows);
          int dstwidth = CV_IMIN(cvRound(src.cols * inv_scale_x), dst.cols);
          int dstheight = CV_IMIN(cvRound(range.end * inv_scale_y), dst.rows);
          IppiRect dstroi = { 0, dsty, dstwidth, dstheight - dsty };
          int bufsize;
          ippiResizeGetBufSize( srcroi, dstroi, cn, mode, &bufsize );
          Ipp8u *buf;
          buf = ippsMalloc_8u( bufsize );
          IppStatus sts;
          if( func( src.data, ippiSize(src.cols, src.rows), (int)src.step[0], srcroi, dst.data, (int)dst.step[0], dstroi, inv_scale_x, inv_scale_y, 0, 0, mode, buf ) < 0 )
              *ok = false;
          ippsFree(buf);
      }
private:
    Mat &src;
    Mat &dst;
    double inv_scale_x;
    double inv_scale_y;
    int mode;
    ippiResizeSqrPixelFunc func;
    bool *ok;
    const IPPresizeInvoker& operator= (const IPPresizeInvoker&);
};
#endif
1901

1902
}
M
Marina Kolpakova 已提交
1903

1904

1905 1906
//////////////////////////////////////////////////////////////////////////////////////////

1907
void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
1908
                 double inv_scale_x, double inv_scale_y, int interpolation )
1909 1910 1911 1912 1913 1914
{
    static ResizeFunc linear_tab[] =
    {
        resizeGeneric_<
            HResizeLinear<uchar, int, short,
                INTER_RESIZE_COEF_SCALE,
M
Marina Kolpakova 已提交
1915
                HResizeLinearVec_8u32s>,
1916 1917
            VResizeLinear<uchar, int, short,
                FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
M
Marina Kolpakova 已提交
1918 1919
                VResizeLinearVec_32s8u> >,
        0,
1920 1921 1922 1923 1924 1925 1926 1927 1928 1929
        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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Marina Kolpakova 已提交
1930
        0,
1931 1932 1933 1934 1935
        resizeGeneric_<
            HResizeLinear<float, float, float, 1,
                HResizeLinearVec_32f>,
            VResizeLinear<float, float, float, Cast<float, float>,
                VResizeLinearVec_32f> >,
V
Vadim Pisarevsky 已提交
1936 1937 1938 1939 1940 1941
        resizeGeneric_<
            HResizeLinear<double, double, float, 1,
                HResizeNoVec>,
            VResizeLinear<double, double, float, Cast<double, double>,
                VResizeNoVec> >,
        0
1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959
    };

    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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Marina Kolpakova 已提交
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        0,
1961 1962 1963 1964
        resizeGeneric_<
            HResizeCubic<float, float, float>,
            VResizeCubic<float, float, float, Cast<float, float>,
            VResizeCubicVec_32f> >,
V
Vadim Pisarevsky 已提交
1965 1966 1967 1968 1969
        resizeGeneric_<
            HResizeCubic<double, double, float>,
            VResizeCubic<double, double, float, Cast<double, double>,
            VResizeNoVec> >,
        0
1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981
    };

    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>,
1983 1984
            VResizeLanczos4<short, float, float, Cast<float, short>,
            VResizeNoVec> >,
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        0,
1986 1987 1988
        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
1993 1994 1995 1996
    };

    static ResizeAreaFastFunc areafast_tab[] =
    {
1997
        resizeAreaFast_<uchar, int, ResizeAreaFastVec<uchar, ResizeAreaFastVec_SIMD_8u> >,
1998
        0,
1999 2000
        resizeAreaFast_<ushort, float, ResizeAreaFastVec<ushort, ResizeAreaFastVec_SIMD_16u> >,
        resizeAreaFast_<short, float, ResizeAreaFastVec<short, ResizeAreaFastNoVec<short, float> > >,
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        0,
2002 2003
        resizeAreaFast_<float, float, ResizeAreaFastNoVec<float, float> >,
        resizeAreaFast_<double, double, ResizeAreaFastNoVec<double, double> >,
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        0
2005 2006 2007 2008
    };

    static ResizeAreaFunc area_tab[] =
    {
2009
        resizeArea_<uchar, float>, 0, resizeArea_<ushort, float>,
2010 2011
        resizeArea_<short, float>, 0, resizeArea_<float, float>,
        resizeArea_<double, double>, 0
2012 2013
    };

2014
    Mat src = _src.getMat();
2015
    Size ssize = src.size();
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Marina Kolpakova 已提交
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2017
    CV_Assert( ssize.area() > 0 );
2018 2019
    CV_Assert( dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0) );
    if( !dsize.area() )
2020 2021 2022
    {
        dsize = Size(saturate_cast<int>(src.cols*inv_scale_x),
            saturate_cast<int>(src.rows*inv_scale_y));
2023
        CV_Assert( dsize.area() );
2024 2025 2026 2027 2028 2029
    }
    else
    {
        inv_scale_x = (double)dsize.width/src.cols;
        inv_scale_y = (double)dsize.height/src.rows;
    }
2030 2031
    _dst.create(dsize, src.type());
    Mat dst = _dst.getMat();
2032

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2033 2034

#ifdef HAVE_TEGRA_OPTIMIZATION
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2035
    if (tegra::resize(src, dst, (float)inv_scale_x, (float)inv_scale_y, interpolation))
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        return;
#endif

2039 2040 2041 2042
    int depth = src.depth(), cn = src.channels();
    double scale_x = 1./inv_scale_x, scale_y = 1./inv_scale_y;
    int k, sx, sy, dx, dy;

2043
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
2044
    int mode = interpolation == INTER_LINEAR ? IPPI_INTER_LINEAR : 0;
2045
    int type = src.type();
2046 2047
    ippiResizeSqrPixelFunc ippFunc =
        type == CV_8UC1 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_8u_C1R :
2048 2049 2050 2051 2052 2053 2054 2055 2056 2057
        type == CV_8UC3 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_8u_C3R :
        type == CV_8UC4 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_8u_C4R :
        type == CV_16UC1 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_16u_C1R :
        type == CV_16UC3 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_16u_C3R :
        type == CV_16UC4 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_16u_C4R :
        type == CV_16SC1 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_16s_C1R :
        type == CV_16SC3 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_16s_C3R :
        type == CV_16SC4 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_16s_C4R :
        type == CV_32FC1 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_32f_C1R :
        type == CV_32FC3 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_32f_C3R :
2058
        type == CV_32FC4 ? (ippiResizeSqrPixelFunc)ippiResizeSqrPixel_32f_C4R :
2059
        0;
2060
    if( ippFunc && mode != 0 )
2061 2062 2063 2064 2065 2066 2067 2068 2069
    {
        bool ok;
        Range range(0, src.rows);
        IPPresizeInvoker invoker(src, dst, inv_scale_x, inv_scale_y, mode, ippFunc, &ok);
        parallel_for_(range, invoker, dst.total()/(double)(1<<16));
        if( ok )
            return;
    }
#endif
2070 2071 2072 2073 2074 2075

    if( interpolation == INTER_NEAREST )
    {
        resizeNN( src, dst, inv_scale_x, inv_scale_y );
        return;
    }
2076

2077 2078 2079
    {
        int iscale_x = saturate_cast<int>(scale_x);
        int iscale_y = saturate_cast<int>(scale_y);
2080

2081 2082
        bool is_area_fast = std::abs(scale_x - iscale_x) < DBL_EPSILON &&
                std::abs(scale_y - iscale_y) < DBL_EPSILON;
2083 2084

        // in case of scale_x && scale_y is equal to 2
2085
        // INTER_AREA (fast) also is equal to INTER_LINEAR
2086
        if( interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 )
2087 2088 2089 2090 2091
            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 )
2092
        {
2093
            if( is_area_fast )
2094
            {
2095 2096 2097 2098 2099 2100 2101 2102 2103 2104 2105
                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);
2106

2107 2108 2109 2110 2111 2112 2113
                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;
                }
2114

2115 2116 2117
                func( src, dst, ofs, xofs, iscale_x, iscale_y );
                return;
            }
2118

2119 2120
            ResizeAreaFunc func = area_tab[depth];
            CV_Assert( func != 0 && cn <= 4 );
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            AutoBuffer<DecimateAlpha> _xytab((ssize.width + ssize.height)*2);
            DecimateAlpha* xtab = _xytab, *ytab = xtab + ssize.width*2;
2124

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            int xtab_size = computeResizeAreaTab(ssize.width, dsize.width, cn, scale_x, xtab);
            int ytab_size = computeResizeAreaTab(ssize.height, dsize.height, 1, scale_y, ytab);
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            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 )
2133
                {
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                    assert( ytab[k].di == dy );
                    tabofs[dy++] = k;
2136
                }
2137
            }
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            tabofs[dy] = ytab_size;
2139

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            func( src, dst, xtab, xtab_size, ytab, ytab_size, tabofs );
2141
            return;
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        }
    }

    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;
            if( sx < 0 )
                fx = 0, sx = 0;
        }

        if( sx + ksize2 >= ssize.width )
        {
            xmax = std::min( xmax, dx );
            if( sx >= ssize.width-1 )
                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)                     *
\****************************************************************************************/

2276 2277 2278
namespace cv
{

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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();

        if( (cn != 1 && cn != 3 && cn != 4) || !checkHardwareSupport(CV_CPU_SSE2) )
            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;
        int x = 0, sstep = (int)_src.step;
        __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;
2813
    int borderType1 = borderType != BORDER_TRANSPARENT ? borderType : BORDER_REFLECT_101;
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    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];
2853 2854 2855
                if( borderType == BORDER_TRANSPARENT &&
                    ((unsigned)(sx+1) >= (unsigned)ssize.width ||
                    (unsigned)(sy+1) >= (unsigned)ssize.height) )
2856 2857
                    continue;

2858
                if( borderType1 == BORDER_CONSTANT &&
2859 2860 2861 2862 2863 2864 2865 2866 2867 2868
                    (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++ )
                {
2869 2870
                    x[i] = borderInterpolate(sx + i, ssize.width, borderType1)*cn;
                    y[i] = borderInterpolate(sy + i, ssize.height, borderType1);
2871 2872 2873 2874 2875 2876 2877 2878 2879 2880 2881 2882 2883 2884 2885 2886 2887 2888 2889 2890 2891 2892 2893 2894 2895 2896 2897 2898 2899 2900 2901 2902 2903 2904 2905 2906 2907 2908 2909 2910 2911 2912 2913 2914 2915 2916 2917
                }

                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;
2918
    int borderType1 = borderType != BORDER_TRANSPARENT ? borderType : BORDER_REFLECT_101;
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Marina Kolpakova 已提交
2919

2920 2921 2922 2923 2924 2925 2926 2927 2928 2929 2930 2931 2932 2933 2934 2935 2936 2937 2938 2939 2940 2941 2942 2943 2944 2945 2946 2947 2948 2949 2950 2951 2952 2953 2954 2955
    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];
2956 2957 2958
                if( borderType == BORDER_TRANSPARENT &&
                    ((unsigned)(sx+3) >= (unsigned)ssize.width ||
                    (unsigned)(sy+3) >= (unsigned)ssize.height) )
2959 2960
                    continue;

2961
                if( borderType1 == BORDER_CONSTANT &&
2962 2963 2964 2965 2966 2967 2968 2969 2970 2971
                    (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++ )
                {
2972 2973
                    x[i] = borderInterpolate(sx + i, ssize.width, borderType1)*cn;
                    y[i] = borderInterpolate(sy + i, ssize.height, borderType1);
2974 2975 2976 2977 2978 2979 2980 2981
                }

                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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Andrey Kamaev 已提交
2982
                        const T* S1 = S0 + yi*sstep;
2983 2984 2985
                        if( yi < 0 )
                            continue;
                        if( x[0] >= 0 )
A
Andrey Kamaev 已提交
2986
                            sum += (S1[x[0]] - cv)*w[0];
2987
                        if( x[1] >= 0 )
A
Andrey Kamaev 已提交
2988
                            sum += (S1[x[1]] - cv)*w[1];
2989
                        if( x[2] >= 0 )
A
Andrey Kamaev 已提交
2990
                            sum += (S1[x[2]] - cv)*w[2];
2991
                        if( x[3] >= 0 )
A
Andrey Kamaev 已提交
2992
                            sum += (S1[x[3]] - cv)*w[3];
2993
                        if( x[4] >= 0 )
A
Andrey Kamaev 已提交
2994
                            sum += (S1[x[4]] - cv)*w[4];
2995
                        if( x[5] >= 0 )
A
Andrey Kamaev 已提交
2996
                            sum += (S1[x[5]] - cv)*w[5];
2997
                        if( x[6] >= 0 )
A
Andrey Kamaev 已提交
2998
                            sum += (S1[x[6]] - cv)*w[6];
2999
                        if( x[7] >= 0 )
A
Andrey Kamaev 已提交
3000
                            sum += (S1[x[7]] - cv)*w[7];
3001 3002 3003 3004 3005 3006 3007 3008 3009 3010 3011 3012 3013 3014 3015 3016 3017
                    }
                    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);

3018
class RemapInvoker :
3019 3020 3021
    public ParallelLoopBody
{
public:
3022
    RemapInvoker(const Mat& _src, Mat& _dst, const Mat *_m1,
3023
                 const Mat *_m2, int _borderType, const Scalar &_borderValue,
3024
                 int _planar_input, RemapNNFunc _nnfunc, RemapFunc _ifunc, const void *_ctab) :
3025
        ParallelLoopBody(), src(&_src), dst(&_dst), m1(_m1), m2(_m2),
3026
        borderType(_borderType), borderValue(_borderValue),
3027
        planar_input(_planar_input), nnfunc(_nnfunc), ifunc(_ifunc), ctab(_ctab)
3028 3029 3030
    {
    }

3031 3032 3033 3034
    virtual void operator() (const Range& range) const
    {
        int x, y, x1, y1;
        const int buf_size = 1 << 14;
3035 3036 3037
        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);
3038 3039 3040 3041 3042 3043 3044 3045 3046 3047
    #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 )
        {
3048
            for( x = 0; x < dst->cols; x += bcols0 )
3049 3050
            {
                int brows = std::min(brows0, range.end - y);
3051 3052
                int bcols = std::min(bcols0, dst->cols - x);
                Mat dpart(*dst, Rect(x, y, bcols, brows));
3053 3054 3055 3056
                Mat bufxy(_bufxy, Rect(0, 0, bcols, brows));

                if( nnfunc )
                {
3057 3058
                    if( m1->type() == CV_16SC2 && !m2->data ) // the data is already in the right format
                        bufxy = (*m1)(Rect(x, y, bcols, brows));
3059 3060 3061 3062 3063 3064 3065 3066 3067 3068 3069 3070 3071 3072 3073 3074 3075
                    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 )
3076
                        (*m1)(Rect(x, y, bcols, brows)).convertTo(bufxy, bufxy.depth());
3077 3078 3079 3080 3081
                    else
                    {
                        for( y1 = 0; y1 < brows; y1++ )
                        {
                            short* XY = (short*)(bufxy.data + bufxy.step*y1);
3082 3083
                            const float* sX = (const float*)(m1->data + m1->step*(y+y1)) + x;
                            const float* sY = (const float*)(m2->data + m2->step*(y+y1)) + x;
3084 3085 3086 3087 3088 3089 3090 3091 3092 3093 3094 3095 3096 3097 3098 3099 3100 3101 3102 3103 3104 3105 3106 3107 3108 3109 3110 3111 3112 3113 3114 3115
                            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]);
                            }
                        }
                    }
3116
                    nnfunc( *src, dpart, bufxy, borderType, borderValue );
3117 3118 3119 3120 3121 3122 3123 3124 3125
                    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);

3126
                    if( m1->type() == CV_16SC2 && (m2->type() == CV_16UC1 || m2->type() == CV_16SC1) )
3127
                    {
3128 3129
                        bufxy = (*m1)(Rect(x, y, bcols, brows));
                        bufa = (*m2)(Rect(x, y, bcols, brows));
3130 3131 3132
                    }
                    else if( planar_input )
                    {
3133 3134
                        const float* sX = (const float*)(m1->data + m1->step*(y+y1)) + x;
                        const float* sY = (const float*)(m2->data + m2->step*(y+y1)) + x;
3135 3136 3137 3138 3139 3140 3141 3142 3143 3144 3145 3146 3147 3148 3149 3150 3151 3152 3153 3154 3155 3156 3157 3158 3159 3160 3161 3162 3163 3164 3165 3166 3167 3168 3169 3170 3171 3172 3173 3174 3175 3176 3177 3178 3179 3180 3181 3182 3183 3184 3185 3186

                        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] = (short)(sx >> INTER_BITS);
                            XY[x1*2+1] = (short)(sy >> INTER_BITS);
                            A[x1] = (ushort)v;
                        }
                    }
                    else
                    {
3187
                        const float* sXY = (const float*)(m1->data + m1->step*(y+y1)) + x*2;
3188 3189 3190 3191 3192 3193 3194 3195 3196 3197 3198 3199

                        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] = (short)(sx >> INTER_BITS);
                            XY[x1*2+1] = (short)(sy >> INTER_BITS);
                            A[x1] = (ushort)v;
                        }
                    }
                }
3200
                ifunc(*src, dpart, bufxy, bufa, ctab, borderType, borderValue);
3201 3202 3203
            }
        }
    }
3204

3205
private:
3206 3207
    const Mat* src;
    Mat* dst;
3208
    const Mat *m1, *m2;
3209
    int borderType;
3210
    Scalar borderValue;
3211 3212 3213 3214 3215 3216
    int planar_input;
    RemapNNFunc nnfunc;
    RemapFunc ifunc;
    const void *ctab;
};

3217
}
M
Marina Kolpakova 已提交
3218

3219 3220
void cv::remap( InputArray _src, OutputArray _dst,
                InputArray _map1, InputArray _map2,
3221
                int interpolation, int borderType, const Scalar& borderValue )
3222 3223 3224
{
    static RemapNNFunc nn_tab[] =
    {
3225 3226
        remapNearest<uchar>, remapNearest<schar>, remapNearest<ushort>, remapNearest<short>,
        remapNearest<int>, remapNearest<float>, remapNearest<double>, 0
3227 3228 3229 3230 3231 3232 3233
    };

    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,
3234 3235
        remapBilinear<Cast<float, float>, RemapNoVec, float>,
        remapBilinear<Cast<double, double>, RemapNoVec, float>, 0
3236 3237 3238 3239 3240 3241 3242
    };

    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,
3243 3244
        remapBicubic<Cast<float, float>, float, 1>,
        remapBicubic<Cast<double, double>, float, 1>, 0
3245 3246 3247 3248 3249 3250 3251
    };

    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,
3252 3253
        remapLanczos4<Cast<float, float>, float, 1>,
        remapLanczos4<Cast<double, double>, float, 1>, 0
3254 3255
    };

3256
    Mat src = _src.getMat(), map1 = _map1.getMat(), map2 = _map2.getMat();
M
Marina Kolpakova 已提交
3257

3258 3259
    CV_Assert( map1.size().area() > 0 );
    CV_Assert( !map2.data || (map2.size() == map1.size()));
M
Marina Kolpakova 已提交
3260

3261 3262
    _dst.create( map1.size(), src.type() );
    Mat dst = _dst.getMat();
3263 3264
    if( dst.data == src.data )
        src = src.clone();
3265

3266
    int depth = src.depth();
3267 3268 3269 3270 3271 3272 3273 3274 3275 3276 3277 3278 3279 3280 3281 3282 3283 3284 3285 3286 3287 3288 3289 3290 3291 3292 3293 3294 3295 3296
    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_AREA )
            interpolation = INTER_LINEAR;

        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;

3297 3298
    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)) )
3299 3300 3301 3302 3303 3304
    {
        if( map1.type() != CV_16SC2 )
            std::swap(m1, m2);
    }
    else
    {
3305
        CV_Assert( ((map1.type() == CV_32FC2 || map1.type() == CV_16SC2) && !map2.data) ||
3306 3307 3308 3309
            (map1.type() == CV_32FC1 && map2.type() == CV_32FC1) );
        planar_input = map1.channels() == 1;
    }

3310
    RemapInvoker invoker(src, dst, m1, m2,
3311 3312
                         borderType, borderValue, planar_input, nnfunc, ifunc,
                         ctab);
3313
    parallel_for_(Range(0, dst.rows), invoker, dst.total()/(double)(1<<16));
3314 3315 3316
}


3317
void cv::convertMaps( InputArray _map1, InputArray _map2,
3318 3319
                      OutputArray _dstmap1, OutputArray _dstmap2,
                      int dstm1type, bool nninterpolate )
3320
{
3321
    Mat map1 = _map1.getMat(), map2 = _map2.getMat(), dstmap1, dstmap2;
3322 3323 3324 3325 3326 3327 3328 3329 3330 3331 3332 3333 3334 3335 3336 3337 3338 3339
    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 );
3340 3341
    _dstmap1.create( size, dstm1type );
    dstmap1 = _dstmap1.getMat();
M
Marina Kolpakova 已提交
3342

3343
    if( !nninterpolate && dstm1type != CV_32FC2 )
3344 3345 3346 3347
    {
        _dstmap2.create( size, dstm1type == CV_16SC2 ? CV_16UC1 : CV_32FC1 );
        dstmap2 = _dstmap2.getMat();
    }
3348
    else
3349
        _dstmap2.release();
3350 3351 3352 3353 3354 3355 3356 3357 3358 3359 3360 3361 3362 3363 3364 3365 3366 3367 3368 3369 3370 3371 3372 3373 3374 3375 3376 3377 3378 3379 3380 3381 3382 3383 3384 3385 3386 3387 3388 3389 3390 3391 3392 3393 3394 3395 3396 3397 3398 3399 3400 3401 3402 3403 3404 3405 3406 3407 3408 3409 3410 3411 3412 3413 3414 3415 3416 3417 3418 3419 3420 3421 3422 3423 3424 3425 3426 3427 3428 3429 3430 3431 3432 3433 3434 3435 3436 3437 3438 3439 3440 3441 3442 3443 3444 3445 3446 3447 3448 3449 3450 3451 3452 3453 3454

    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] = (short)(ix >> INTER_BITS);
                    dst1[x*2+1] = (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] = (short)(ix >> INTER_BITS);
                    dst1[x*2+1] = (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] : 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] : 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" );
    }
}

3455

3456 3457 3458
namespace cv
{

3459
class warpAffineInvoker :
3460 3461 3462
    public ParallelLoopBody
{
public:
3463
    warpAffineInvoker(const Mat &_src, Mat &_dst, int _interpolation, int _borderType,
3464 3465 3466 3467 3468 3469
                      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)
    {
    }
3470

3471 3472 3473 3474 3475
    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);
3476
        const int AB_SCALE = 1 << AB_BITS;
3477 3478 3479 3480
        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
3481

3482 3483 3484 3485 3486 3487 3488 3489 3490 3491 3492 3493 3494 3495 3496 3497 3498 3499 3500 3501 3502 3503 3504 3505 3506 3507 3508 3509 3510 3511 3512 3513 3514 3515 3516 3517 3518 3519 3520 3521 3522 3523 3524 3525 3526 3527 3528 3529 3530 3531 3532 3533 3534 3535 3536 3537 3538 3539 3540 3541 3542 3543 3544 3545 3546 3547 3548 3549 3550 3551 3552 3553 3554 3555 3556 3557 3558
        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)));
                        }
                    }
                }
3559

3560 3561 3562 3563 3564 3565 3566 3567 3568 3569
                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 );
                }
            }
        }
    }
3570

3571
private:
3572
    Mat src;
3573 3574
    Mat dst;
    int interpolation, borderType;
3575
    Scalar borderValue;
3576 3577 3578
    int *adelta, *bdelta;
    double *M;
};
3579

3580 3581 3582 3583 3584 3585 3586 3587 3588 3589 3590 3591 3592 3593 3594 3595 3596 3597 3598 3599 3600 3601 3602 3603 3604 3605 3606 3607 3608 3609 3610 3611 3612 3613 3614 3615 3616 3617 3618 3619 3620 3621 3622
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
class IPPwarpAffineInvoker :
    public ParallelLoopBody
{
public:
    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;
              }
          }
          if( func( src.data, srcsize, (int)src.step[0], srcroi, dst.data, (int)dst.step[0], dstroi, coeffs, mode ) < 0) ////Aug 2013: problem in IPP 7.1, 8.0 : sometimes function return ippStsCoeffErr
              *ok = false;
      }
private:
    Mat &src;
    Mat &dst;
    double (&coeffs)[2][3];
    int mode;
    int borderType;
    Scalar borderValue;
    ippiWarpAffineBackFunc func;
    bool *ok;
    const IPPwarpAffineInvoker& operator= (const IPPwarpAffineInvoker&);
};
#endif

3623
}
3624 3625


3626 3627
void cv::warpAffine( InputArray _src, OutputArray _dst,
                     InputArray _M0, Size dsize,
3628
                     int flags, int borderType, const Scalar& borderValue )
3629
{
3630
    Mat src = _src.getMat(), M0 = _M0.getMat();
3631
    _dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
3632
    Mat dst = _dst.getMat();
3633 3634 3635
    CV_Assert( src.cols > 0 && src.rows > 0 );
    if( dst.data == src.data )
        src = src.clone();
3636 3637 3638 3639 3640 3641 3642 3643 3644 3645

    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());

A
Andrey Kamaev 已提交
3646 3647 3648 3649 3650
#ifdef HAVE_TEGRA_OPTIMIZATION
    if( tegra::warpAffine(src, dst, M, flags, borderType, borderValue) )
        return;
#endif

3651 3652 3653 3654 3655 3656 3657 3658 3659 3660 3661 3662
    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;
    }

3663 3664 3665
    int x;
    AutoBuffer<int> _abdelta(dst.cols*2);
    int* adelta = &_abdelta[0], *bdelta = adelta + dst.cols;
3666 3667 3668
    const int AB_BITS = MAX(10, (int)INTER_BITS);
    const int AB_SCALE = 1 << AB_BITS;

3669 3670 3671
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
    int depth = src.depth();
    int channels = src.channels();
3672 3673
    if( ( depth == CV_8U || depth == CV_16U || depth == CV_32F ) &&
        ( channels == 1 || channels == 3 || channels == 4 ) &&
3674 3675 3676
        ( borderType == cv::BORDER_TRANSPARENT || ( borderType == cv::BORDER_CONSTANT ) ) )
    {
        int type = src.type();
3677
        ippiWarpAffineBackFunc ippFunc =
3678 3679 3680 3681 3682 3683 3684 3685 3686 3687
            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;
3688
        int mode =
3689 3690
            flags == INTER_LINEAR ? IPPI_INTER_LINEAR :
            flags == INTER_NEAREST ? IPPI_INTER_NN :
3691
            flags == INTER_CUBIC ? IPPI_INTER_CUBIC :
3692 3693 3694 3695 3696 3697 3698 3699 3700 3701 3702 3703 3704 3705 3706 3707 3708 3709 3710 3711
            0;
        if( 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;
        }
    }
#endif
3712

3713
    for( x = 0; x < dst.cols; x++ )
3714 3715 3716 3717 3718
    {
        adelta[x] = saturate_cast<int>(M[0]*x*AB_SCALE);
        bdelta[x] = saturate_cast<int>(M[3]*x*AB_SCALE);
    }

3719 3720 3721
    Range range(0, dst.rows);
    warpAffineInvoker invoker(src, dst, interpolation, borderType,
                              borderValue, adelta, bdelta, M);
3722
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
3723
}
3724 3725


3726 3727
namespace cv
{
3728

3729 3730 3731 3732
class warpPerspectiveInvoker :
    public ParallelLoopBody
{
public:
3733

3734 3735 3736 3737 3738 3739
    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)
    {
    }
3740

3741 3742 3743 3744 3745
    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;
3746

3747 3748 3749
        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);
3750

3751 3752 3753
        for( y = range.start; y < range.end; y += bh0 )
        {
            for( x = 0; x < width; x += bw0 )
3754
            {
3755 3756
                int bw = std::min( bw0, width - x);
                int bh = std::min( bh0, range.end - y); // height
3757

3758 3759
                Mat _XY(bh, bw, CV_16SC2, XY), matA;
                Mat dpart(dst, Rect(x, y, bw, bh));
3760

3761
                for( y1 = 0; y1 < bh; y1++ )
3762
                {
3763 3764 3765 3766
                    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];
3767

3768 3769
                    if( interpolation == INTER_NEAREST )
                        for( x1 = 0; x1 < bw; x1++ )
3770
                        {
3771 3772 3773 3774 3775 3776
                            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);
3777

3778 3779
                            xy[x1*2] = saturate_cast<short>(X);
                            xy[x1*2+1] = saturate_cast<short>(Y);
3780
                        }
3781
                    else
3782
                    {
3783 3784 3785 3786 3787 3788 3789 3790 3791
                        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);
3792

3793 3794 3795 3796 3797
                            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)));
                        }
3798 3799
                    }
                }
3800

3801 3802 3803 3804 3805 3806 3807
                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 );
                }
3808 3809 3810
            }
        }
    }
3811

3812
private:
3813
    Mat src;
3814 3815 3816
    Mat dst;
    double* M;
    int interpolation, borderType;
3817
    Scalar borderValue;
3818
};
3819

3820 3821 3822 3823 3824
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
class IPPwarpPerspectiveInvoker :
    public ParallelLoopBody
{
public:
3825
    IPPwarpPerspectiveInvoker(Mat &_src, Mat &_dst, double (&_coeffs)[3][3], int &_interpolation, int &_borderType, const Scalar &_borderValue, ippiWarpPerspectiveBackFunc _func, bool *_ok) :
3826 3827 3828 3829 3830 3831 3832 3833 3834 3835 3836 3837 3838 3839 3840 3841 3842 3843 3844 3845 3846 3847 3848 3849 3850 3851 3852 3853 3854 3855 3856 3857 3858 3859 3860 3861 3862 3863
      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;
              }
          }
          if( func(src.data, srcsize, (int)src.step[0], srcroi, dst.data, (int)dst.step[0], dstroi, coeffs, mode) < 0)
              *ok = false;
      }
private:
    Mat &src;
    Mat &dst;
    double (&coeffs)[3][3];
    int mode;
    int borderType;
    const Scalar borderValue;
    ippiWarpPerspectiveBackFunc func;
    bool *ok;
    const IPPwarpPerspectiveInvoker& operator= (const IPPwarpPerspectiveInvoker&);
};
#endif

3864 3865
}

3866
void cv::warpPerspective( InputArray _src, OutputArray _dst, InputArray _M0,
3867
                          Size dsize, int flags, int borderType, const Scalar& borderValue )
3868
{
3869
    Mat src = _src.getMat(), M0 = _M0.getMat();
3870
    _dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
3871
    Mat dst = _dst.getMat();
M
Marina Kolpakova 已提交
3872

3873 3874 3875
    CV_Assert( src.cols > 0 && src.rows > 0 );
    if( dst.data == src.data )
        src = src.clone();
3876 3877 3878 3879 3880 3881 3882 3883 3884 3885

    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());

3886
#ifdef HAVE_TEGRA_OPTIMIZATION
A
Andrey Kamaev 已提交
3887
    if( tegra::warpPerspective(src, dst, M, flags, borderType, borderValue) )
3888 3889 3890
        return;
#endif

A
Andrey Kamaev 已提交
3891 3892 3893
    if( !(flags & WARP_INVERSE_MAP) )
         invert(matM, matM);

3894 3895 3896
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
    int depth = src.depth();
    int channels = src.channels();
3897 3898
    if( ( depth == CV_8U || depth == CV_16U || depth == CV_32F ) &&
        ( channels == 1 || channels == 3 || channels == 4 ) &&
3899 3900 3901
        ( borderType == cv::BORDER_TRANSPARENT || borderType == cv::BORDER_CONSTANT ) )
    {
        int type = src.type();
3902
        ippiWarpPerspectiveBackFunc ippFunc =
3903 3904 3905 3906 3907 3908 3909 3910 3911 3912
            type == CV_8UC1 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_8u_C1R :
            type == CV_8UC3 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_8u_C3R :
            type == CV_8UC4 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_8u_C4R :
            type == CV_16UC1 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_16u_C1R :
            type == CV_16UC3 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_16u_C3R :
            type == CV_16UC4 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_16u_C4R :
            type == CV_32FC1 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_32f_C1R :
            type == CV_32FC3 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_32f_C3R :
            type == CV_32FC4 ? (ippiWarpPerspectiveBackFunc)ippiWarpPerspectiveBack_32f_C4R :
            0;
3913
        int mode =
3914 3915
            flags == INTER_LINEAR ? IPPI_INTER_LINEAR :
            flags == INTER_NEAREST ? IPPI_INTER_NN :
3916
            flags == INTER_CUBIC ? IPPI_INTER_CUBIC :
3917 3918 3919 3920 3921 3922 3923 3924 3925 3926 3927 3928 3929 3930 3931 3932 3933 3934 3935 3936
            0;
        if( 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;
        }
    }
#endif
A
Andrey Kamaev 已提交
3937

3938 3939
    Range range(0, dst.rows);
    warpPerspectiveInvoker invoker(src, dst, M, interpolation, borderType, borderValue);
3940
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
3941 3942 3943
}


3944
cv::Mat cv::getRotationMatrix2D( Point2f center, double angle, double scale )
3945 3946 3947 3948 3949 3950 3951 3952 3953 3954 3955 3956 3957 3958 3959 3960 3961 3962 3963 3964 3965 3966 3967 3968 3969 3970 3971 3972 3973 3974 3975 3976 3977 3978 3979 3980 3981 3982 3983 3984 3985 3986
{
    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
 */
3987
cv::Mat cv::getPerspectiveTransform( const Point2f src[], const Point2f dst[] )
3988 3989 3990 3991 3992 3993 3994 3995 3996 3997 3998 3999 4000 4001 4002 4003 4004 4005 4006 4007 4008 4009 4010 4011 4012 4013 4014 4015 4016 4017 4018 4019 4020 4021 4022 4023 4024 4025 4026 4027 4028 4029 4030 4031
{
    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
 */
K
Kirill Kornyakov 已提交
4032

4033
cv::Mat cv::getAffineTransform( const Point2f src[], const Point2f dst[] )
4034 4035 4036 4037 4038 4039 4040 4041 4042 4043 4044 4045 4046 4047 4048 4049 4050 4051 4052 4053 4054
{
    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;
}
M
Marina Kolpakova 已提交
4055

4056
void cv::invertAffineTransform(InputArray _matM, OutputArray __iM)
4057
{
4058
    Mat matM = _matM.getMat();
4059
    CV_Assert(matM.rows == 2 && matM.cols == 3);
4060 4061
    __iM.create(2, 3, matM.type());
    Mat _iM = __iM.getMat();
M
Marina Kolpakova 已提交
4062

4063 4064 4065 4066
    if( matM.type() == CV_32F )
    {
        const float* M = (const float*)matM.data;
        float* iM = (float*)_iM.data;
4067
        int step = (int)(matM.step/sizeof(M[0])), istep = (int)(_iM.step/sizeof(iM[0]));
M
Marina Kolpakova 已提交
4068

4069 4070 4071 4072 4073
        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];
M
Marina Kolpakova 已提交
4074

4075 4076 4077 4078 4079 4080 4081
        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;
4082
        int step = (int)(matM.step/sizeof(M[0])), istep = (int)(_iM.step/sizeof(iM[0]));
M
Marina Kolpakova 已提交
4083

4084 4085 4086 4087 4088
        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];
M
Marina Kolpakova 已提交
4089

4090 4091 4092 4093 4094
        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, "" );
M
Marina Kolpakova 已提交
4095
}
4096

4097 4098 4099 4100 4101 4102 4103 4104 4105 4106 4107 4108 4109 4110
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);
}

4111 4112 4113 4114 4115 4116 4117 4118 4119 4120 4121 4122 4123 4124 4125 4126 4127 4128 4129 4130 4131 4132 4133 4134 4135 4136 4137 4138 4139 4140 4141 4142 4143 4144 4145 4146 4147 4148 4149 4150 4151 4152 4153 4154 4155 4156 4157 4158 4159 4160 4161 4162 4163 4164
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);
4165
    CV_Assert( M.size() == M0.size() );
4166 4167 4168 4169 4170 4171 4172 4173 4174 4175 4176 4177
    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);
4178
    CV_Assert( M.size() == M0.size() );
4179 4180 4181 4182 4183 4184 4185 4186 4187 4188 4189 4190 4191 4192 4193 4194 4195 4196 4197 4198 4199 4200 4201 4202 4203 4204 4205 4206 4207 4208 4209 4210 4211 4212 4213 4214 4215 4216 4217 4218 4219 4220 4221 4222 4223 4224 4225 4226 4227 4228 4229 4230 4231 4232 4233 4234 4235 4236 4237 4238 4239
    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);

R
Roman Donchenko 已提交
4240 4241
    mapx.reset(cvCreateMat( dsize.height, dsize.width, CV_32F ));
    mapy.reset(cvCreateMat( dsize.height, dsize.width, CV_32F ));
4242 4243 4244 4245 4246 4247 4248 4249 4250 4251 4252 4253 4254 4255 4256 4257 4258 4259 4260 4261 4262 4263 4264 4265 4266 4267 4268 4269 4270 4271 4272 4273 4274 4275 4276 4277 4278 4279 4280 4281 4282 4283 4284 4285 4286 4287 4288 4289 4290 4291 4292 4293 4294 4295 4296 4297 4298 4299 4300 4301 4302 4303 4304 4305 4306 4307 4308 4309 4310 4311 4312 4313 4314 4315

    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];

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                double p = log(std::sqrt(xx*xx + yy*yy) + 1.)*M;
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                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) );
}


/****************************************************************************************
                                   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;
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    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 ));
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    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) );
}


/* End of file. */