imgwarp.cpp 187.0 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 "opencl_kernels.hpp"
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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
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static IppStatus sts = ippicvInit();
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#endif
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namespace cv
{
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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR*100 + IPP_VERSION_MINOR >= 701)
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    typedef IppStatus (CV_STDCALL* ippicviResizeFunc)(const void*, int, const void*, int, IppiPoint, IppiSize, IppiBorderType, void*, void*, Ipp8u*);
    typedef IppStatus (CV_STDCALL* ippicviResizeGetBufferSize)(void*, IppiSize, Ipp32u, int*);
    typedef IppStatus (CV_STDCALL* ippicviResizeGetSrcOffset)(void*, IppiPoint, IppiPoint*);
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#endif
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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
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    typedef IppStatus (CV_STDCALL* ippicviSetFunc)(const void*, void *, int, IppiSize);
    typedef IppStatus (CV_STDCALL* ippicviWarpPerspectiveBackFunc)(const void*, IppiSize, int, IppiRect, void *, int, IppiRect, double [3][3], int);
    typedef IppStatus (CV_STDCALL* ippicviWarpAffineBackFunc)(const void*, IppiSize, int, IppiRect, void *, int, IppiRect, double [2][3], int);
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    template <int channels, typename Type>
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    bool IPPSetSimple(cv::Scalar value, void *dataPointer, int step, IppiSize &size, ippicviSetFunc func)
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    {
        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 ippicviSet_8u_C1R((Ipp8u)value[0], (Ipp8u *)dataPointer, step, size) >= 0;
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            case CV_16U:
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                return ippicviSet_16u_C1R((Ipp16u)value[0], (Ipp16u *)dataPointer, step, size) >= 0;
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            case CV_32F:
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                return ippicviSet_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:
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                    return IPPSetSimple<3, Ipp8u>(value, dataPointer, step, size, (ippicviSetFunc)ippicviSet_8u_C3R);
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                case CV_16U:
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                    return IPPSetSimple<3, Ipp16u>(value, dataPointer, step, size, (ippicviSetFunc)ippicviSet_16u_C3R);
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                case CV_32F:
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                    return IPPSetSimple<3, Ipp32f>(value, dataPointer, step, size, (ippicviSetFunc)ippicviSet_32f_C3R);
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                }
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            }
            else if( channels == 4 )
            {
                switch( depth )
                {
                case CV_8U:
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                    return IPPSetSimple<4, Ipp8u>(value, dataPointer, step, size, (ippicviSetFunc)ippicviSet_8u_C4R);
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                case CV_16U:
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                    return IPPSetSimple<4, Ipp16u>(value, dataPointer, step, size, (ippicviSetFunc)ippicviSet_16u_C4R);
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                case CV_32F:
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                    return IPPSetSimple<4, Ipp32f>(value, dataPointer, step, size, (ippicviSetFunc)ippicviSet_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;

1207 1208 1209 1210 1211 1212 1213 1214
template <typename HResize, typename VResize>
class resizeGeneric_Invoker :
    public ParallelLoopBody
{
public:
    typedef typename HResize::value_type T;
    typedef typename HResize::buf_type WT;
    typedef typename HResize::alpha_type AT;
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    resizeGeneric_Invoker(const Mat& _src, Mat &_dst, const int *_xofs, const int *_yofs,
        const AT* _alpha, const AT* __beta, const Size& _ssize, const Size &_dsize,
        int _ksize, int _xmin, int _xmax) :
        ParallelLoopBody(), src(_src), dst(_dst), xofs(_xofs), yofs(_yofs),
        alpha(_alpha), _beta(__beta), ssize(_ssize), dsize(_dsize),
        ksize(_ksize), xmin(_xmin), xmax(_xmax)
    {
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        CV_Assert(ksize <= MAX_ESIZE);
1224
    }
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#if defined(__GNUC__) && (__GNUC__ == 4) && (__GNUC_MINOR__ == 8)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Warray-bounds"
#endif
1230 1231 1232 1233 1234
    virtual void operator() (const Range& range) const
    {
        int dy, cn = src.channels();
        HResize hresize;
        VResize vresize;
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        int bufstep = (int)alignSize(dsize.width, 16);
        AutoBuffer<WT> _buffer(bufstep*ksize);
        const T* srows[MAX_ESIZE]={0};
        WT* rows[MAX_ESIZE]={0};
        int prev_sy[MAX_ESIZE];

        for(int k = 0; k < ksize; k++ )
        {
            prev_sy[k] = -1;
            rows[k] = (WT*)_buffer + bufstep*k;
        }
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1248
        const AT* beta = _beta + ksize * range.start;
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        for( dy = range.start; dy < range.end; dy++, beta += ksize )
        {
            int sy0 = yofs[dy], k0=ksize, k1=0, ksize2 = ksize/2;

            for(int k = 0; k < ksize; k++ )
            {
                int sy = clip(sy0 - ksize2 + 1 + k, 0, ssize.height);
                for( k1 = std::max(k1, k); k1 < ksize; k1++ )
                {
                    if( sy == prev_sy[k1] ) // if the sy-th row has been computed already, reuse it.
                    {
                        if( k1 > k )
                            memcpy( rows[k], rows[k1], bufstep*sizeof(rows[0][0]) );
                        break;
                    }
                }
                if( k1 == ksize )
                    k0 = std::min(k0, k); // remember the first row that needs to be computed
                srows[k] = (T*)(src.data + src.step*sy);
                prev_sy[k] = sy;
            }

            if( k0 < ksize )
                hresize( (const T**)(srows + k0), (WT**)(rows + k0), ksize - k0, xofs, (const AT*)(alpha),
                        ssize.width, dsize.width, cn, xmin, xmax );
            vresize( (const WT**)rows, (T*)(dst.data + dst.step*dy), beta, dsize.width );
        }
    }
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#if defined(__GNUC__) && (__GNUC__ == 4) && (__GNUC_MINOR__ == 8)
# pragma GCC diagnostic pop
#endif
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1282
private:
1283
    Mat src;
1284 1285 1286
    Mat dst;
    const int* xofs, *yofs;
    const AT* alpha, *_beta;
1287
    Size ssize, dsize;
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    const int ksize, xmin, xmax;

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

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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;
1308
    // image resize is a separable operation. In case of not too strong
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    Range range(0, dsize.height);
    resizeGeneric_Invoker<HResize, VResize> invoker(src, dst, xofs, yofs, (const AT*)_alpha, beta,
        ssize, dsize, ksize, xmin, xmax);
1313
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
1314
}
1315

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template <typename T, typename WT>
struct ResizeAreaFastNoVec
{
1319 1320 1321 1322
    ResizeAreaFastNoVec(int, int) { }
    ResizeAreaFastNoVec(int, int, int, int) { }
    int operator() (const T*, T*, int) const
    { return 0; }
1323
};
1324

1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343
#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();
1344
        __m128i delta2 = _mm_set1_epi16(2);
1345 1346 1347

        if (cn == 1)
        {
1348
            __m128i masklow = _mm_set1_epi16(0x00ff);
1349
            for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
1350
            {
1351 1352
                __m128i r0 = _mm_loadu_si128((const __m128i*)S0);
                __m128i r1 = _mm_loadu_si128((const __m128i*)S1);
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1354 1355 1356 1357
                __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);
1358

1359
                _mm_storel_epi64((__m128i*)D, s0);
1360 1361 1362
            }
        }
        else if (cn == 3)
1363
            for ( ; dx <= w - 11; dx += 6, S0 += 12, S1 += 12, D += 6)
1364
            {
1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383
                __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);
1384 1385 1386 1387
            }
        else
        {
            CV_Assert(cn == 4);
1388 1389 1390
            int v[] = { 0, 0, -1, -1 };
            __m128i mask = _mm_loadu_si128((const __m128i*)v);

1391
            for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
1392
            {
1393 1394 1395 1396 1397 1398 1399 1400 1401 1402 1403
                __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));
1404
                __m128i res0 = _mm_srli_epi16(s0, 2);
1405 1406 1407 1408

                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));
1409 1410 1411 1412
                __m128i res1 = _mm_srli_epi16(s0, 2);
                s0 = _mm_packus_epi16(_mm_or_si128(_mm_andnot_si128(mask, res0),
                                                   _mm_and_si128(mask, _mm_slli_si128(res1, 8))), zero);
                _mm_storel_epi64((__m128i*)(D), s0);
1413 1414 1415 1416 1417 1418 1419 1420 1421
            }
        }

        return dx;
    }

private:
    int cn;
    bool use_simd;
1422
    int step;
1423 1424 1425 1426 1427 1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440
};

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;
1441
        const ushort* S1 = (const ushort*)((const uchar*)(S) + step);
1442 1443
        __m128i masklow = _mm_set1_epi32(0x0000ffff);
        __m128i zero = _mm_setzero_si128();
1444
        __m128i delta2 = _mm_set1_epi32(2);
1445

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#define _mm_packus_epi32(a, zero) _mm_packs_epi32(_mm_srai_epi32(_mm_slli_epi32(a, 16), 16), zero)
1447

1448 1449
        if (cn == 1)
        {
1450
            for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
1451
            {
1452 1453
                __m128i r0 = _mm_loadu_si128((const __m128i*)S0);
                __m128i r1 = _mm_loadu_si128((const __m128i*)S1);
1454

1455 1456 1457
                __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);
1458 1459
                s0 = _mm_srli_epi32(s0, 2);
                s0 = _mm_packus_epi32(s0, zero);
1460

1461
                _mm_storel_epi64((__m128i*)D, s0);
1462 1463 1464
            }
        }
        else if (cn == 3)
1465
            for ( ; dx <= w - 4; dx += 3, S0 += 6, S1 += 6, D += 3)
1466
            {
1467 1468 1469 1470 1471 1472 1473 1474
                __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);

1475 1476 1477
                __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));
1478
                s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
1479
                _mm_storel_epi64((__m128i*)D, s0);
1480 1481 1482 1483
            }
        else
        {
            CV_Assert(cn == 4);
1484
            for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
1485
            {
1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496
                __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));
1497
                s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
1498
                _mm_storel_epi64((__m128i*)D, s0);
1499 1500 1501
            }
        }

I
Ilya Lavrenov 已提交
1502 1503
#undef _mm_packus_epi32

1504 1505 1506 1507 1508 1509 1510 1511 1512 1513 1514 1515 1516 1517 1518
        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>
1519
struct ResizeAreaFastVec
1520
{
1521 1522
    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)
1523 1524
    {
        fast_mode = scale_x == 2 && scale_y == 2 && (cn == 1 || cn == 3 || cn == 4);
1525
    }
1526

1527
    int operator() (const T* S, T* D, int w) const
1528
    {
1529
        if (!fast_mode)
1530
            return 0;
1531

1532
        const T* nextS = (const T*)((const uchar*)S + step);
1533
        int dx = vecOp(S, D, w);
1534

1535
        if (cn == 1)
1536 1537 1538 1539 1540
            for( ; dx < w; ++dx )
            {
                int index = dx*2;
                D[dx] = (T)((S[index] + S[index+1] + nextS[index] + nextS[index+1] + 2) >> 2);
            }
1541
        else if (cn == 3)
1542
            for( ; dx < w; dx += 3 )
1543
            {
1544
                int index = dx*2;
1545 1546 1547 1548 1549 1550
                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
            {
1551
                CV_Assert(cn == 4);
1552 1553 1554 1555 1556 1557 1558 1559
                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);
                }
1560
            }
1561

1562
        return dx;
1563
    }
1564

1565
private:
1566 1567
    int scale_x, scale_y;
    int cn;
1568
    bool fast_mode;
1569
    int step;
1570
    SIMDVecOp vecOp;
1571
};
1572

1573 1574 1575
template <typename T, typename WT, typename VecOp>
class resizeAreaFast_Invoker :
    public ParallelLoopBody
1576
{
1577 1578 1579 1580 1581
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)
1582
    {
1583
    }
1584

1585 1586 1587 1588 1589 1590 1591 1592 1593 1594
    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;
1595

1596
        VecOp vop(scale_x, scale_y, src.channels(), (int)src.step/*, area_ofs*/);
1597

1598
        for( dy = range.start; dy < range.end; dy++ )
1599
        {
1600 1601 1602
            T* D = (T*)(dst.data + dst.step*dy);
            int sy0 = dy*scale_y;
            int w = sy0 + scale_y <= ssize.height ? dwidth1 : 0;
1603

1604 1605 1606 1607 1608 1609
            if( sy0 >= ssize.height )
            {
                for( dx = 0; dx < dsize.width; dx++ )
                    D[dx] = 0;
                continue;
            }
M
Marina Kolpakova 已提交
1610

1611 1612 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622
            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]];
M
Marina Kolpakova 已提交
1623

1624 1625
                D[dx] = saturate_cast<T>(sum * scale);
            }
M
Marina Kolpakova 已提交
1626

1627
            for( ; dx < dsize.width; dx++ )
1628
            {
1629 1630 1631 1632 1633 1634
                WT sum = 0;
                int count = 0, sx0 = xofs[dx];
                if( sx0 >= ssize.width )
                    D[dx] = 0;

                for( int sy = 0; sy < scale_y; sy++ )
1635
                {
1636
                    if( sy0 + sy >= ssize.height )
1637
                        break;
1638 1639 1640 1641 1642 1643 1644 1645
                    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++;
                    }
1646
                }
M
Marina Kolpakova 已提交
1647

1648
                D[dx] = saturate_cast<T>((float)sum/count);
1649
            }
1650
        }
1651
    }
1652

1653
private:
1654
    Mat src;
1655
    Mat dst;
1656
    int scale_x, scale_y;
1657 1658 1659 1660 1661 1662 1663 1664
    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);
1665
    resizeAreaFast_Invoker<T, WT, VecOp> invoker(src, dst, scale_x,
1666
        scale_y, ofs, xofs);
1667
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
1668 1669 1670 1671 1672 1673 1674 1675
}

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

V
Vadim Pisarevsky 已提交
1676 1677

template<typename T, typename WT> class ResizeArea_Invoker :
1678
    public ParallelLoopBody
1679
{
1680
public:
V
Vadim Pisarevsky 已提交
1681 1682 1683 1684
    ResizeArea_Invoker( const Mat& _src, Mat& _dst,
                        const DecimateAlpha* _xtab, int _xtab_size,
                        const DecimateAlpha* _ytab, int _ytab_size,
                        const int* _tabofs )
1685
    {
V
Vadim Pisarevsky 已提交
1686 1687 1688 1689 1690 1691 1692
        src = &_src;
        dst = &_dst;
        xtab0 = _xtab;
        xtab_size0 = _xtab_size;
        ytab = _ytab;
        ytab_size = _ytab_size;
        tabofs = _tabofs;
1693
    }
1694

V
Vadim Pisarevsky 已提交
1695
    virtual void operator() (const Range& range) const
1696
    {
V
Vadim Pisarevsky 已提交
1697 1698
        Size dsize = dst->size();
        int cn = dst->channels();
1699 1700
        dsize.width *= cn;
        AutoBuffer<WT> _buffer(dsize.width*2);
V
Vadim Pisarevsky 已提交
1701 1702
        const DecimateAlpha* xtab = xtab0;
        int xtab_size = xtab_size0;
1703
        WT *buf = _buffer, *sum = buf + dsize.width;
1704
        int j_start = tabofs[range.start], j_end = tabofs[range.end], j, k, dx, prev_dy = ytab[j_start].di;
1705

I
attempt  
Ilya Lavrenov 已提交
1706
        for( dx = 0; dx < dsize.width; dx++ )
V
Vadim Pisarevsky 已提交
1707
            sum[dx] = (WT)0;
1708

V
Vadim Pisarevsky 已提交
1709
        for( j = j_start; j < j_end; j++ )
1710
        {
V
Vadim Pisarevsky 已提交
1711 1712 1713
            WT beta = ytab[j].alpha;
            int dy = ytab[j].di;
            int sy = ytab[j].si;
1714

1715
            {
V
Vadim Pisarevsky 已提交
1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748
                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 )
1749
                {
V
Vadim Pisarevsky 已提交
1750
                    for( k = 0; k < xtab_size; k++ )
I
attempt  
Ilya Lavrenov 已提交
1751
                    {
V
Vadim Pisarevsky 已提交
1752 1753 1754 1755 1756 1757 1758 1759 1760
                        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
1761
                    }
1762 1763
                }
                else
V
Vadim Pisarevsky 已提交
1764 1765
                {
                    for( k = 0; k < xtab_size; k++ )
1766
                    {
V
Vadim Pisarevsky 已提交
1767 1768 1769 1770 1771
                        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;
1772
                    }
V
Vadim Pisarevsky 已提交
1773
                }
1774
            }
V
Vadim Pisarevsky 已提交
1775 1776

            if( dy != prev_dy )
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++ )
I
attempt  
Ilya Lavrenov 已提交
1781
                {
V
Vadim Pisarevsky 已提交
1782 1783
                    D[dx] = saturate_cast<T>(sum[dx]);
                    sum[dx] = beta*buf[dx];
I
attempt  
Ilya Lavrenov 已提交
1784
                }
V
Vadim Pisarevsky 已提交
1785 1786 1787 1788 1789 1790
                prev_dy = dy;
            }
            else
            {
                for( dx = 0; dx < dsize.width; dx++ )
                    sum[dx] += beta*buf[dx];
1791 1792
            }
        }
1793

1794
        {
V
Vadim Pisarevsky 已提交
1795 1796 1797
        T* D = (T*)(dst->data + dst->step*prev_dy);
        for( dx = 0; dx < dsize.width; dx++ )
            D[dx] = saturate_cast<T>(sum[dx]);
1798 1799
        }
    }
1800

1801
private:
V
Vadim Pisarevsky 已提交
1802 1803 1804 1805 1806 1807
    const Mat* src;
    Mat* dst;
    const DecimateAlpha* xtab0;
    const DecimateAlpha* ytab;
    int xtab_size0, ytab_size;
    const int* tabofs;
1808 1809
};

V
Vadim Pisarevsky 已提交
1810

I
attempt  
Ilya Lavrenov 已提交
1811
template <typename T, typename WT>
V
Vadim Pisarevsky 已提交
1812 1813 1814 1815
static void resizeArea_( const Mat& src, Mat& dst,
                         const DecimateAlpha* xtab, int xtab_size,
                         const DecimateAlpha* ytab, int ytab_size,
                         const int* tabofs )
1816
{
V
Vadim Pisarevsky 已提交
1817 1818 1819
    parallel_for_(Range(0, dst.rows),
                 ResizeArea_Invoker<T, WT>(src, dst, xtab, xtab_size, ytab, ytab_size, tabofs),
                 dst.total()/((double)(1 << 16)));
1820
}
1821 1822 1823 1824 1825 1826 1827 1828


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,
1829 1830
                                    const int* ofs, const int *xofs,
                                    int scale_x, int scale_y );
1831 1832

typedef void (*ResizeAreaFunc)( const Mat& src, Mat& dst,
V
Vadim Pisarevsky 已提交
1833 1834 1835 1836 1837 1838 1839
                                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 )
{
1840 1841
    int k = 0;
    for(int dx = 0; dx < dsize; dx++ )
V
Vadim Pisarevsky 已提交
1842
    {
1843
        double fsx1 = dx * scale;
V
Vadim Pisarevsky 已提交
1844
        double fsx2 = fsx1 + scale;
1845
        double cellWidth = std::min(scale, ssize - fsx1);
1846

V
Vadim Pisarevsky 已提交
1847 1848
        int sx1 = cvCeil(fsx1), sx2 = cvFloor(fsx2);

1849 1850 1851 1852
        sx2 = std::min(sx2, ssize - 1);
        sx1 = std::min(sx1, sx2);

        if( sx1 - fsx1 > 1e-3 )
V
Vadim Pisarevsky 已提交
1853 1854
        {
            assert( k < ssize*2 );
1855 1856 1857
            tab[k].di = dx * cn;
            tab[k].si = (sx1 - 1) * cn;
            tab[k++].alpha = (float)((sx1 - fsx1) / cellWidth);
V
Vadim Pisarevsky 已提交
1858 1859
        }

1860
        for(int sx = sx1; sx < sx2; sx++ )
V
Vadim Pisarevsky 已提交
1861 1862
        {
            assert( k < ssize*2 );
1863 1864 1865
            tab[k].di = dx * cn;
            tab[k].si = sx * cn;
            tab[k++].alpha = float(1.0 / cellWidth);
V
Vadim Pisarevsky 已提交
1866 1867 1868 1869 1870
        }

        if( fsx2 - sx2 > 1e-3 )
        {
            assert( k < ssize*2 );
1871 1872
            tab[k].di = dx * cn;
            tab[k].si = sx2 * cn;
1873
            tab[k++].alpha = (float)(std::min(std::min(fsx2 - sx2, 1.), cellWidth) / cellWidth);
V
Vadim Pisarevsky 已提交
1874 1875 1876 1877 1878
        }
    }
    return k;
}

E
fixed  
Elena Gvozdeva 已提交
1879 1880
#define CHECK_IPP_FUNC(FUNC) if( FUNC==0 ) { *ok = false; return;}
#define CHECK_IPP_STATUS(STATUS) if( STATUS!=ippStsNoErr ) { *ok = false; return;}
E
fixed  
Elena Gvozdeva 已提交
1881 1882

#define SET_IPP_RESIZE_LINEAR_FUNC_PTR(TYPE, CN) \
V
vbystricky 已提交
1883 1884
    func = (ippicviResizeFunc)ippicviResizeLinear_##TYPE##_##CN##R; CHECK_IPP_FUNC(func);\
    CHECK_IPP_STATUS(ippicviResizeGetSize_##TYPE(srcSize, dstSize, (IppiInterpolationType)mode, 0, &specSize, &initSize));\
E
fixed  
Elena Gvozdeva 已提交
1885 1886
    specBuf.allocate(specSize);\
    pSpec = (uchar*)specBuf;\
V
vbystricky 已提交
1887
    CHECK_IPP_STATUS(ippicviResizeLinearInit_##TYPE(srcSize, dstSize, (IppiResizeSpec_32f*)pSpec));
E
fixed  
Elena Gvozdeva 已提交
1888 1889

#define SET_IPP_RESIZE_LINEAR_FUNC_64_PTR(TYPE, CN) \
E
fixed  
Elena Gvozdeva 已提交
1890
    if (mode==(int)ippCubic) { *ok = false; return;}\
V
vbystricky 已提交
1891 1892
    func = (ippicviResizeFunc)ippicviResizeLinear_##TYPE##_##CN##R; CHECK_IPP_FUNC(func);\
    CHECK_IPP_STATUS(ippicviResizeGetSize_##TYPE(srcSize, dstSize, (IppiInterpolationType)mode, 0, &specSize, &initSize));\
E
fixed  
Elena Gvozdeva 已提交
1893 1894
    specBuf.allocate(specSize);\
    pSpec = (uchar*)specBuf;\
V
vbystricky 已提交
1895 1896 1897
    CHECK_IPP_STATUS(ippicviResizeLinearInit_##TYPE(srcSize, dstSize, (IppiResizeSpec_64f*)pSpec));\
    getBufferSizeFunc = (ippicviResizeGetBufferSize)ippicviResizeGetBufferSize_##TYPE;\
    getSrcOffsetFunc =  (ippicviResizeGetSrcOffset) ippicviResizeGetBufferSize_##TYPE;
E
fixed  
Elena Gvozdeva 已提交
1898 1899

#define SET_IPP_RESIZE_CUBIC_FUNC_PTR(TYPE, CN) \
V
vbystricky 已提交
1900 1901
    func = (ippicviResizeFunc)ippicviResizeCubic_##TYPE##_##CN##R; CHECK_IPP_FUNC(func);\
    CHECK_IPP_STATUS(ippicviResizeGetSize_##TYPE(srcSize, dstSize, (IppiInterpolationType)mode, 0, &specSize, &initSize));\
E
fixed  
Elena Gvozdeva 已提交
1902 1903
    specBuf.allocate(specSize);\
    pSpec = (uchar*)specBuf;\
E
fixed  
Elena Gvozdeva 已提交
1904 1905
    AutoBuffer<uchar> buf(initSize);\
    uchar* pInit = (uchar*)buf;\
V
vbystricky 已提交
1906
    CHECK_IPP_STATUS(ippicviResizeCubicInit_##TYPE(srcSize, dstSize,  0.f, 0.75f, (IppiResizeSpec_32f*)pSpec, pInit));
E
fixed  
Elena Gvozdeva 已提交
1907 1908 1909 1910 1911

#define SET_IPP_RESIZE_PTR(TYPE, CN) \
    if (mode == (int)ippLinear)     { SET_IPP_RESIZE_LINEAR_FUNC_PTR(TYPE, CN);}\
    else if (mode == (int)ippCubic) { SET_IPP_RESIZE_CUBIC_FUNC_PTR(TYPE, CN);}\
    else { *ok = false; return;}\
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    getBufferSizeFunc = (ippicviResizeGetBufferSize)ippicviResizeGetBufferSize_##TYPE;\
    getSrcOffsetFunc =  (ippicviResizeGetSrcOffset)ippicviResizeGetSrcOffset_##TYPE;
E
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E
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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR*100 + IPP_VERSION_MINOR >= 701)
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class IPPresizeInvoker :
    public ParallelLoopBody
{
public:
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    IPPresizeInvoker(const Mat & _src, Mat & _dst, double _inv_scale_x, double _inv_scale_y, int _mode, bool *_ok) :
        ParallelLoopBody(), src(_src), dst(_dst), inv_scale_x(_inv_scale_x), inv_scale_y(_inv_scale_y), mode(_mode), ok(_ok)
    {
        *ok = true;
        IppiSize srcSize, dstSize;
        int type = src.type();
        int specSize = 0, initSize = 0;
        srcSize.width  = src.cols;
        srcSize.height = src.rows;
        dstSize.width  = dst.cols;
        dstSize.height = dst.rows;

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<<<<<<< HEAD
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        switch (type)
        {
            case CV_8UC1:  SET_IPP_RESIZE_PTR(8u,C1);  break;
            case CV_8UC3:  SET_IPP_RESIZE_PTR(8u,C3);  break;
            case CV_8UC4:  SET_IPP_RESIZE_PTR(8u,C4);  break;
            case CV_16UC1: SET_IPP_RESIZE_PTR(16u,C1); break;
            case CV_16UC3: SET_IPP_RESIZE_PTR(16u,C3); break;
            case CV_16UC4: SET_IPP_RESIZE_PTR(16u,C4); break;
            case CV_16SC1: SET_IPP_RESIZE_PTR(16s,C1); break;
            case CV_16SC3: SET_IPP_RESIZE_PTR(16s,C3); break;
            case CV_16SC4: SET_IPP_RESIZE_PTR(16s,C4); break;
            case CV_32FC1: SET_IPP_RESIZE_PTR(32f,C1); break;
            case CV_32FC3: SET_IPP_RESIZE_PTR(32f,C3); break;
            case CV_32FC4: SET_IPP_RESIZE_PTR(32f,C4); break;
            case CV_64FC1: SET_IPP_RESIZE_LINEAR_FUNC_64_PTR(64f,C1); break;
            case CV_64FC3: SET_IPP_RESIZE_LINEAR_FUNC_64_PTR(64f,C3); break;
            case CV_64FC4: SET_IPP_RESIZE_LINEAR_FUNC_64_PTR(64f,C4); break;
            default: { *ok = false; return; } break;
        }
    }

    ~IPPresizeInvoker()
    {
    }

    virtual void operator() (const Range& range) const
    {
        if (*ok == false)
          return;

        int cn = src.channels();
        int dsty = min(cvRound(range.start * inv_scale_y), dst.rows);
        int dstwidth  = min(cvRound(src.cols * inv_scale_x), dst.cols);
        int dstheight = min(cvRound(range.end * inv_scale_y), dst.rows);

        IppiPoint dstOffset = { 0, dsty }, srcOffset = {0, 0};
        IppiSize  dstSize   = { dstwidth, dstheight - dsty };
        int bufsize = 0, itemSize = (int)src.elemSize1();

        CHECK_IPP_STATUS(getBufferSizeFunc(pSpec, dstSize, cn, &bufsize));
        CHECK_IPP_STATUS(getSrcOffsetFunc(pSpec, dstOffset, &srcOffset));

        Ipp8u* pSrc = (Ipp8u*)src.data + (int)src.step[0] * srcOffset.y + srcOffset.x * cn * itemSize;
        Ipp8u* pDst = (Ipp8u*)dst.data + (int)dst.step[0] * dstOffset.y + dstOffset.x * cn * itemSize;

        AutoBuffer<uchar> buf(bufsize + 64);
        uchar* bufptr = alignPtr((uchar*)buf, 32);

        if( func( pSrc, (int)src.step[0], pDst, (int)dst.step[0], dstOffset, dstSize, ippBorderRepl, 0, pSpec, bufptr ) < 0 )
            *ok = false;
    }

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=======
    ~IPPresizeInvoker()
    {
    }

    virtual void operator() (const Range& range) const
    {
        if (*ok == false) return;

        int cn = src.channels();
        int dsty = min(cvRound(range.start * inv_scale_y), dst.rows);
        int dstwidth  = min(cvRound(src.cols * inv_scale_x), dst.cols);
        int dstheight = min(cvRound(range.end * inv_scale_y), dst.rows);

        IppiPoint dstOffset = { 0, dsty }, srcOffset = {0, 0};
        IppiSize  dstSize   = { dstwidth, dstheight - dsty };
        int bufsize = 0, itemSize = (int)src.elemSize1();

        CHECK_IPP_STATUS(getBufferSizeFunc(pSpec, dstSize, cn, &bufsize));
        CHECK_IPP_STATUS(getSrcOffsetFunc(pSpec, dstOffset, &srcOffset));

        Ipp8u* pSrc = (Ipp8u*)src.data + (int)src.step[0] * srcOffset.y + srcOffset.x * cn * itemSize;
        Ipp8u* pDst = (Ipp8u*)dst.data + (int)dst.step[0] * dstOffset.y + dstOffset.x * cn * itemSize;

        AutoBuffer<uchar> buf(bufsize + 64);
        uchar* bufptr = alignPtr((uchar*)buf, 32);

        if( func( pSrc, (int)src.step[0], pDst, (int)dst.step[0], dstOffset, dstSize, ippBorderRepl, 0, pSpec, bufptr ) < 0 )
            *ok = false;
    }
>>>>>>> Prepare codes for ippicv library
2016
private:
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    const Mat & src;
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    Mat & dst;
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    double inv_scale_x;
    double inv_scale_y;
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    void *pSpec;
    AutoBuffer<uchar>   specBuf;
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    int mode;
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    ippicviResizeFunc func;
    ippicviResizeGetBufferSize getBufferSizeFunc;
    ippicviResizeGetSrcOffset getSrcOffsetFunc;
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    bool *ok;
    const IPPresizeInvoker& operator= (const IPPresizeInvoker&);
};
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2031
#endif
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#ifdef HAVE_OPENCL

2035
static void ocl_computeResizeAreaTabs(int ssize, int dsize, double scale, int * const map_tab,
2036
                                      float * const alpha_tab, int * const ofs_tab)
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{
    int k = 0, dx = 0;
    for ( ; dx < dsize; dx++)
    {
        ofs_tab[dx] = k;

        double fsx1 = dx * scale;
        double fsx2 = fsx1 + scale;
        double cellWidth = std::min(scale, ssize - fsx1);

        int sx1 = cvCeil(fsx1), sx2 = cvFloor(fsx2);

        sx2 = std::min(sx2, ssize - 1);
        sx1 = std::min(sx1, sx2);

        if (sx1 - fsx1 > 1e-3)
        {
            map_tab[k] = sx1 - 1;
            alpha_tab[k++] = (float)((sx1 - fsx1) / cellWidth);
        }

        for (int sx = sx1; sx < sx2; sx++)
        {
            map_tab[k] = sx;
            alpha_tab[k++] = float(1.0 / cellWidth);
        }

        if (fsx2 - sx2 > 1e-3)
        {
            map_tab[k] = sx2;
            alpha_tab[k++] = (float)(std::min(std::min(fsx2 - sx2, 1.), cellWidth) / cellWidth);
        }
    }
    ofs_tab[dx] = k;
}

static void ocl_computeResizeAreaFastTabs(int * dmap_tab, int * smap_tab, int scale, int dcols, int scol)
{
    for (int i = 0; i < dcols; ++i)
        dmap_tab[i] = scale * i;

    for (int i = 0, size = dcols * scale; i < size; ++i)
        smap_tab[i] = std::min(scol - 1, i);
}

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static bool ocl_resize( InputArray _src, OutputArray _dst, Size dsize,
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                        double fx, double fy, int interpolation)
{
    int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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2087
    double inv_fx = 1.0 / fx, inv_fy = 1.0 / fy;
2088
    float inv_fxf = (float)inv_fx, inv_fyf = (float)inv_fy;
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    int iscale_x = saturate_cast<int>(inv_fx), iscale_y = saturate_cast<int>(inv_fx);
    bool is_area_fast = std::abs(inv_fx - iscale_x) < DBL_EPSILON &&
        std::abs(inv_fy - iscale_y) < DBL_EPSILON;

    // in case of scale_x && scale_y is equal to 2
    // INTER_AREA (fast) also is equal to INTER_LINEAR
    if( interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 )
        /*interpolation = INTER_AREA*/(void)0; // INTER_AREA is slower
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2098
    if( !(cn <= 4 &&
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           (interpolation == INTER_NEAREST || interpolation == INTER_LINEAR ||
            (interpolation == INTER_AREA && inv_fx >= 1 && inv_fy >= 1) )) )
2101
        return false;
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    UMat src = _src.getUMat();
    _dst.create(dsize, type);
    UMat dst = _dst.getUMat();
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2107
    Size ssize = src.size();
2108
    ocl::Kernel k;
2109
    size_t globalsize[] = { dst.cols, dst.rows };
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    if (interpolation == INTER_LINEAR)
    {
        char buf[2][32];
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        // integer path is slower because of CPU part, so it's disabled
        if (depth == CV_8U && ((void)0, 0))
        {
            AutoBuffer<uchar> _buffer((dsize.width + dsize.height)*(sizeof(int) + sizeof(short)*2));
            int* xofs = (int*)(uchar*)_buffer, * yofs = xofs + dsize.width;
            short* ialpha = (short*)(yofs + dsize.height), * ibeta = ialpha + dsize.width*2;
            float fxx, fyy;
            int sx, sy;

            for (int dx = 0; dx < dsize.width; dx++)
            {
                fxx = (float)((dx+0.5)*inv_fx - 0.5);
                sx = cvFloor(fxx);
                fxx -= sx;

                if (sx < 0)
                    fxx = 0, sx = 0;

                if (sx >= ssize.width-1)
                    fxx = 0, sx = ssize.width-1;

                xofs[dx] = sx;
                ialpha[dx*2 + 0] = saturate_cast<short>((1.f - fxx) * INTER_RESIZE_COEF_SCALE);
                ialpha[dx*2 + 1] = saturate_cast<short>(fxx         * INTER_RESIZE_COEF_SCALE);
            }

            for (int dy = 0; dy < dsize.height; dy++)
            {
                fyy = (float)((dy+0.5)*inv_fy - 0.5);
                sy = cvFloor(fyy);
                fyy -= sy;

                yofs[dy] = sy;
                ibeta[dy*2 + 0] = saturate_cast<short>((1.f - fyy) * INTER_RESIZE_COEF_SCALE);
                ibeta[dy*2 + 1] = saturate_cast<short>(fyy         * INTER_RESIZE_COEF_SCALE);
            }

            int wdepth = std::max(depth, CV_32S), wtype = CV_MAKETYPE(wdepth, cn);
            UMat coeffs;
            Mat(1, static_cast<int>(_buffer.size()), CV_8UC1, (uchar *)_buffer).copyTo(coeffs);

            k.create("resizeLN", ocl::imgproc::resize_oclsrc,
                     format("-D INTER_LINEAR_INTEGER -D depth=%d -D T=%s -D T1=%s "
                            "-D WT=%s -D convertToWT=%s -D convertToDT=%s -D cn=%d "
                            "-D INTER_RESIZE_COEF_BITS=%d",
                            depth, ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(wtype),
                            ocl::convertTypeStr(depth, wdepth, cn, buf[0]),
                            ocl::convertTypeStr(wdepth, depth, cn, buf[1]),
                            cn, INTER_RESIZE_COEF_BITS));
            if (k.empty())
                return false;

            k.args(ocl::KernelArg::ReadOnly(src), ocl::KernelArg::WriteOnly(dst),
                   ocl::KernelArg::PtrReadOnly(coeffs));
        }
        else
        {
            int wdepth = std::max(depth, CV_32S), wtype = CV_MAKETYPE(wdepth, cn);
            k.create("resizeLN", ocl::imgproc::resize_oclsrc,
                     format("-D INTER_LINEAR -D depth=%d -D T=%s -D T1=%s "
                            "-D WT=%s -D convertToWT=%s -D convertToDT=%s -D cn=%d "
                            "-D INTER_RESIZE_COEF_BITS=%d",
                            depth, ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(wtype),
                            ocl::convertTypeStr(depth, wdepth, cn, buf[0]),
                            ocl::convertTypeStr(wdepth, depth, cn, buf[1]),
                            cn, INTER_RESIZE_COEF_BITS));
            if (k.empty())
                return false;

            k.args(ocl::KernelArg::ReadOnly(src), ocl::KernelArg::WriteOnly(dst),
                   (float)inv_fx, (float)inv_fy);
        }
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    }
    else if (interpolation == INTER_NEAREST)
    {
        k.create("resizeNN", ocl::imgproc::resize_oclsrc,
2191
                 format("-D INTER_NEAREST -D T=%s -D T1=%s -D cn=%d",
2192
                        ocl::memopTypeToStr(type), ocl::memopTypeToStr(depth), cn));
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        if (k.empty())
            return false;

        k.args(ocl::KernelArg::ReadOnly(src), ocl::KernelArg::WriteOnly(dst),
               (float)inv_fx, (float)inv_fy);
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    }
    else if (interpolation == INTER_AREA)
    {
        int wdepth = std::max(depth, is_area_fast ? CV_32S : CV_32F);
        int wtype = CV_MAKE_TYPE(wdepth, cn);

        char cvt[2][40];
2205
        String buildOption = format("-D INTER_AREA -D T=%s -D T1=%s -D WTV=%s -D convertToWTV=%s -D cn=%d",
2206 2207
                                    ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(wtype),
                                    ocl::convertTypeStr(depth, wdepth, cn, cvt[0]), cn);
2208 2209 2210 2211 2212 2213 2214

        UMat alphaOcl, tabofsOcl, mapOcl;
        UMat dmap, smap;

        if (is_area_fast)
        {
            int wdepth2 = std::max(CV_32F, depth), wtype2 = CV_MAKE_TYPE(wdepth2, cn);
2215
            buildOption = buildOption + format(" -D convertToT=%s -D WT2V=%s -D convertToWT2V=%s -D INTER_AREA_FAST"
2216
                                               " -D XSCALE=%d -D YSCALE=%d -D SCALE=%ff",
2217 2218 2219 2220 2221
                                               ocl::convertTypeStr(wdepth2, depth, cn, cvt[0]),
                                               ocl::typeToStr(wtype2), ocl::convertTypeStr(wdepth, wdepth2, cn, cvt[1]),
                                  iscale_x, iscale_y, 1.0f / (iscale_x * iscale_y));

            k.create("resizeAREA_FAST", ocl::imgproc::resize_oclsrc, buildOption);
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            if (k.empty())
                return false;
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            int smap_tab_size = dst.cols * iscale_x + dst.rows * iscale_y;
            AutoBuffer<int> dmap_tab(dst.cols + dst.rows), smap_tab(smap_tab_size);
            int * dxmap_tab = dmap_tab, * dymap_tab = dxmap_tab + dst.cols;
            int * sxmap_tab = smap_tab, * symap_tab = smap_tab + dst.cols * iscale_y;

            ocl_computeResizeAreaFastTabs(dxmap_tab, sxmap_tab, iscale_x, dst.cols, src.cols);
            ocl_computeResizeAreaFastTabs(dymap_tab, symap_tab, iscale_y, dst.rows, src.rows);

            Mat(1, dst.cols + dst.rows, CV_32SC1, (void *)dmap_tab).copyTo(dmap);
            Mat(1, smap_tab_size, CV_32SC1, (void *)smap_tab).copyTo(smap);
        }
        else
        {
2238
            buildOption = buildOption + format(" -D convertToT=%s", ocl::convertTypeStr(wdepth, depth, cn, cvt[0]));
2239
            k.create("resizeAREA", ocl::imgproc::resize_oclsrc, buildOption);
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            if (k.empty())
                return false;
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            int xytab_size = (ssize.width + ssize.height) << 1;
            int tabofs_size = dsize.height + dsize.width + 2;

            AutoBuffer<int> _xymap_tab(xytab_size), _xyofs_tab(tabofs_size);
            AutoBuffer<float> _xyalpha_tab(xytab_size);
            int * xmap_tab = _xymap_tab, * ymap_tab = _xymap_tab + (ssize.width << 1);
            float * xalpha_tab = _xyalpha_tab, * yalpha_tab = _xyalpha_tab + (ssize.width << 1);
            int * xofs_tab = _xyofs_tab, * yofs_tab = _xyofs_tab + dsize.width + 1;

            ocl_computeResizeAreaTabs(ssize.width, dsize.width, inv_fx, xmap_tab, xalpha_tab, xofs_tab);
            ocl_computeResizeAreaTabs(ssize.height, dsize.height, inv_fy, ymap_tab, yalpha_tab, yofs_tab);

            // loading precomputed arrays to GPU
            Mat(1, xytab_size, CV_32FC1, (void *)_xyalpha_tab).copyTo(alphaOcl);
            Mat(1, xytab_size, CV_32SC1, (void *)_xymap_tab).copyTo(mapOcl);
            Mat(1, tabofs_size, CV_32SC1, (void *)_xyofs_tab).copyTo(tabofsOcl);
        }

        ocl::KernelArg srcarg = ocl::KernelArg::ReadOnly(src), dstarg = ocl::KernelArg::WriteOnly(dst);

        if (is_area_fast)
            k.args(srcarg, dstarg, ocl::KernelArg::PtrReadOnly(dmap), ocl::KernelArg::PtrReadOnly(smap));
        else
            k.args(srcarg, dstarg, inv_fxf, inv_fyf, ocl::KernelArg::PtrReadOnly(tabofsOcl),
                   ocl::KernelArg::PtrReadOnly(mapOcl), ocl::KernelArg::PtrReadOnly(alphaOcl));

        return k.run(2, globalsize, NULL, false);
2270 2271 2272
    }

    return k.run(2, globalsize, 0, false);
2273
}
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#endif

2277
}
2278

2279 2280
//////////////////////////////////////////////////////////////////////////////////////////

2281
void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
2282
                 double inv_scale_x, double inv_scale_y, int interpolation )
2283 2284 2285 2286 2287 2288
{
    static ResizeFunc linear_tab[] =
    {
        resizeGeneric_<
            HResizeLinear<uchar, int, short,
                INTER_RESIZE_COEF_SCALE,
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                HResizeLinearVec_8u32s>,
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            VResizeLinear<uchar, int, short,
                FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
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                VResizeLinearVec_32s8u> >,
        0,
2294 2295 2296 2297 2298 2299 2300 2301 2302 2303
        resizeGeneric_<
            HResizeLinear<ushort, float, float, 1,
                HResizeLinearVec_16u32f>,
            VResizeLinear<ushort, float, float, Cast<float, ushort>,
                VResizeLinearVec_32f16u> >,
        resizeGeneric_<
            HResizeLinear<short, float, float, 1,
                HResizeLinearVec_16s32f>,
            VResizeLinear<short, float, float, Cast<float, short>,
                VResizeLinearVec_32f16s> >,
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        0,
2305 2306 2307 2308 2309
        resizeGeneric_<
            HResizeLinear<float, float, float, 1,
                HResizeLinearVec_32f>,
            VResizeLinear<float, float, float, Cast<float, float>,
                VResizeLinearVec_32f> >,
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        resizeGeneric_<
            HResizeLinear<double, double, float, 1,
                HResizeNoVec>,
            VResizeLinear<double, double, float, Cast<double, double>,
                VResizeNoVec> >,
        0
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    };

    static ResizeFunc cubic_tab[] =
    {
        resizeGeneric_<
            HResizeCubic<uchar, int, short>,
            VResizeCubic<uchar, int, short,
                FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
                VResizeCubicVec_32s8u> >,
        0,
        resizeGeneric_<
            HResizeCubic<ushort, float, float>,
            VResizeCubic<ushort, float, float, Cast<float, ushort>,
            VResizeCubicVec_32f16u> >,
        resizeGeneric_<
            HResizeCubic<short, float, float>,
            VResizeCubic<short, float, float, Cast<float, short>,
            VResizeCubicVec_32f16s> >,
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        0,
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        resizeGeneric_<
            HResizeCubic<float, float, float>,
            VResizeCubic<float, float, float, Cast<float, float>,
            VResizeCubicVec_32f> >,
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        resizeGeneric_<
            HResizeCubic<double, double, float>,
            VResizeCubic<double, double, float, Cast<double, double>,
            VResizeNoVec> >,
        0
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    };

    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>,
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            VResizeLanczos4<short, float, float, Cast<float, short>,
            VResizeNoVec> >,
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        0,
2360 2361 2362
        resizeGeneric_<HResizeLanczos4<float, float, float>,
            VResizeLanczos4<float, float, float, Cast<float, float>,
            VResizeNoVec> >,
V
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2363 2364 2365 2366
        resizeGeneric_<HResizeLanczos4<double, double, float>,
            VResizeLanczos4<double, double, float, Cast<double, double>,
            VResizeNoVec> >,
        0
2367 2368 2369 2370
    };

    static ResizeAreaFastFunc areafast_tab[] =
    {
2371
        resizeAreaFast_<uchar, int, ResizeAreaFastVec<uchar, ResizeAreaFastVec_SIMD_8u> >,
2372
        0,
2373 2374
        resizeAreaFast_<ushort, float, ResizeAreaFastVec<ushort, ResizeAreaFastVec_SIMD_16u> >,
        resizeAreaFast_<short, float, ResizeAreaFastVec<short, ResizeAreaFastNoVec<short, float> > >,
V
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2375
        0,
2376 2377
        resizeAreaFast_<float, float, ResizeAreaFastNoVec<float, float> >,
        resizeAreaFast_<double, double, ResizeAreaFastNoVec<double, double> >,
V
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2378
        0
2379 2380 2381 2382
    };

    static ResizeAreaFunc area_tab[] =
    {
2383
        resizeArea_<uchar, float>, 0, resizeArea_<ushort, float>,
2384 2385
        resizeArea_<short, float>, 0, resizeArea_<float, float>,
        resizeArea_<double, double>, 0
2386 2387
    };

2388
    Size ssize = _src.size();
M
Marina Kolpakova 已提交
2389

2390
    CV_Assert( ssize.area() > 0 );
V
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2391 2392
    CV_Assert( dsize.area() > 0 || (inv_scale_x > 0 && inv_scale_y > 0) );
    if( dsize.area() == 0 )
2393
    {
2394 2395
        dsize = Size(saturate_cast<int>(ssize.width*inv_scale_x),
                     saturate_cast<int>(ssize.height*inv_scale_y));
V
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2396
        CV_Assert( dsize.area() > 0 );
2397 2398 2399
    }
    else
    {
2400 2401
        inv_scale_x = (double)dsize.width/ssize.width;
        inv_scale_y = (double)dsize.height/ssize.height;
2402
    }
2403

I
Ilya Lavrenov 已提交
2404 2405
    CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
               ocl_resize(_src, _dst, dsize, inv_scale_x, inv_scale_y, interpolation))
2406

V
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2407 2408 2409
    Mat src = _src.getMat();
    _dst.create(dsize, src.type());
    Mat dst = _dst.getMat();
A
Andrey Kamaev 已提交
2410 2411

#ifdef HAVE_TEGRA_OPTIMIZATION
A
Alexander Smorkalov 已提交
2412
    if (tegra::resize(src, dst, (float)inv_scale_x, (float)inv_scale_y, interpolation))
A
Andrey Kamaev 已提交
2413 2414 2415
        return;
#endif

2416 2417 2418
    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;
E
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2419

E
fixed  
Elena Gvozdeva 已提交
2420
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR*100 + IPP_VERSION_MINOR >= 701)
E
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2421 2422 2423 2424 2425 2426 2427
#define IPP_RESIZE_EPS    1.e-10

    double ex = fabs((double)dsize.width/src.cols  - inv_scale_x)/inv_scale_x;
    double ey = fabs((double)dsize.height/src.rows - inv_scale_y)/inv_scale_y;

    if ((ex < IPP_RESIZE_EPS && ey < IPP_RESIZE_EPS && depth != CV_64F) ||
        (ex == 0 && ey == 0 && depth == CV_64F))
2428
    {
E
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2429 2430 2431 2432 2433 2434 2435 2436 2437 2438 2439 2440 2441 2442 2443 2444 2445 2446 2447 2448
        int mode = 0;
        if (interpolation == INTER_LINEAR && src.rows >= 2 && src.cols >= 2)
        {
            mode = ippLinear;
        }
        else if (interpolation == INTER_CUBIC && src.rows >= 4 && src.cols >= 4)
        {
            mode = ippCubic;
        }
        if( mode != 0 && (cn == 1 || cn ==3 || cn == 4) &&
            (depth == CV_8U || depth == CV_16U || depth == CV_16S || depth == CV_32F ||
            (depth == CV_64F && mode == ippLinear)))
        {
            bool ok = true;
            Range range(0, src.rows);
            IPPresizeInvoker invoker(src, dst, inv_scale_x, inv_scale_y, mode, &ok);
            parallel_for_(range, invoker, dst.total()/(double)(1<<16));
            if( ok )
                return;
        }
2449
    }
E
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2450
#undef IPP_RESIZE_EPS
2451
#endif
E
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2452

2453 2454 2455 2456 2457
    if( interpolation == INTER_NEAREST )
    {
        resizeNN( src, dst, inv_scale_x, inv_scale_y );
        return;
    }
2458

2459 2460 2461
    {
        int iscale_x = saturate_cast<int>(scale_x);
        int iscale_y = saturate_cast<int>(scale_y);
2462

2463 2464
        bool is_area_fast = std::abs(scale_x - iscale_x) < DBL_EPSILON &&
                std::abs(scale_y - iscale_y) < DBL_EPSILON;
2465 2466

        // in case of scale_x && scale_y is equal to 2
2467
        // INTER_AREA (fast) also is equal to INTER_LINEAR
2468
        if( interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 )
2469 2470 2471 2472 2473
            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 )
2474
        {
2475
            if( is_area_fast )
2476
            {
2477 2478 2479 2480 2481 2482 2483 2484 2485 2486 2487
                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);
2488

2489 2490 2491 2492 2493 2494 2495
                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;
                }
2496

2497 2498 2499
                func( src, dst, ofs, xofs, iscale_x, iscale_y );
                return;
            }
2500

2501 2502
            ResizeAreaFunc func = area_tab[depth];
            CV_Assert( func != 0 && cn <= 4 );
2503

V
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            AutoBuffer<DecimateAlpha> _xytab((ssize.width + ssize.height)*2);
            DecimateAlpha* xtab = _xytab, *ytab = xtab + ssize.width*2;
2506

V
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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);
2509

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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 )
2515
                {
V
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                    assert( ytab[k].di == dy );
                    tabofs[dy++] = k;
2518
                }
2519
            }
V
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2520
            tabofs[dy] = ytab_size;
2521

V
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2522
            func( src, dst, xtab, xtab_size, ytab, ytab_size, tabofs );
2523
            return;
2524 2525 2526 2527 2528 2529 2530 2531 2532 2533 2534 2535 2536 2537 2538 2539 2540 2541 2542 2543 2544 2545 2546 2547 2548 2549 2550 2551 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 2562 2563 2564 2565 2566 2567 2568 2569 2570 2571
        }
    }

    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;
E
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2572
            if( sx < 0 && (interpolation != INTER_CUBIC && interpolation != INTER_LANCZOS4))
2573 2574 2575 2576 2577 2578
                fx = 0, sx = 0;
        }

        if( sx + ksize2 >= ssize.width )
        {
            xmax = std::min( xmax, dx );
E
Elena Gvozdeva 已提交
2579
            if( sx >= ssize.width-1 && (interpolation != INTER_CUBIC && interpolation != INTER_LANCZOS4))
2580 2581 2582 2583 2584 2585 2586 2587 2588 2589 2590 2591 2592 2593 2594 2595 2596 2597 2598 2599 2600 2601 2602 2603 2604 2605 2606 2607 2608 2609 2610 2611 2612 2613 2614 2615 2616 2617 2618 2619 2620 2621 2622 2623 2624 2625 2626 2627 2628 2629 2630 2631 2632 2633 2634 2635 2636 2637 2638 2639 2640 2641 2642 2643 2644 2645 2646 2647 2648 2649 2650 2651 2652 2653 2654 2655 2656 2657
                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)                     *
\****************************************************************************************/

2658 2659 2660
namespace cv
{

2661 2662 2663 2664 2665 2666 2667 2668 2669 2670 2671 2672 2673 2674 2675 2676 2677 2678 2679 2680 2681 2682 2683 2684 2685 2686 2687 2688 2689 2690 2691 2692 2693 2694 2695 2696 2697 2698 2699 2700 2701 2702 2703 2704 2705 2706 2707 2708 2709 2710 2711 2712 2713 2714 2715 2716 2717 2718 2719 2720 2721 2722 2723 2724 2725 2726 2727 2728 2729 2730 2731 2732 2733 2734 2735 2736 2737 2738 2739 2740 2741 2742 2743 2744 2745 2746 2747 2748 2749 2750 2751 2752 2753 2754 2755 2756 2757 2758 2759 2760 2761 2762 2763 2764 2765 2766 2767 2768 2769 2770 2771 2772 2773 2774 2775 2776
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
    {
2777
        int cn = _src.channels(), x = 0, sstep = (int)_src.step;
2778

2779
        if( (cn != 1 && cn != 3 && cn != 4) || !checkHardwareSupport(CV_CPU_SSE2) ||
E
Fixed  
Elena Gvozdeva 已提交
2780
            sstep > 0x8000 )
2781 2782 2783 2784 2785 2786 2787 2788 2789 2790 2791 2792 2793 2794 2795 2796 2797 2798 2799 2800 2801 2802 2803 2804 2805 2806 2807 2808 2809 2810 2811 2812 2813 2814 2815 2816 2817 2818 2819 2820 2821 2822 2823 2824 2825 2826 2827 2828 2829 2830 2831 2832 2833 2834 2835 2836 2837 2838 2839 2840 2841 2842 2843 2844 2845 2846 2847 2848 2849 2850 2851 2852 2853 2854 2855 2856 2857 2858 2859 2860 2861 2862 2863 2864 2865 2866 2867 2868 2869 2870 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 2918 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 2956 2957 2958 2959 2960 2961 2962 2963 2964 2965 2966 2967 2968 2969 2970 2971 2972 2973 2974 2975 2976 2977 2978 2979 2980 2981 2982 2983 2984 2985 2986 2987 2988 2989 2990 2991 2992 2993 2994 2995 2996 2997 2998 2999 3000 3001 3002 3003 3004 3005 3006 3007 3008 3009 3010 3011 3012 3013 3014 3015 3016 3017 3018 3019 3020 3021 3022 3023 3024 3025 3026 3027 3028 3029 3030 3031 3032 3033 3034 3035 3036 3037 3038 3039 3040 3041 3042 3043 3044 3045 3046 3047 3048 3049 3050 3051 3052 3053 3054 3055 3056 3057 3058 3059 3060 3061 3062 3063 3064 3065 3066 3067 3068 3069 3070 3071 3072 3073 3074 3075 3076 3077 3078 3079 3080 3081 3082 3083 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 3116 3117 3118 3119 3120 3121 3122 3123 3124 3125 3126 3127 3128 3129 3130 3131 3132 3133 3134 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 3187 3188 3189 3190 3191 3192 3193 3194
            return 0;

        const uchar *S0 = _src.data, *S1 = _src.data + _src.step;
        const short* wtab = cn == 1 ? (const short*)_wtab : &BilinearTab_iC4[0][0][0];
        uchar* D = (uchar*)_dst;
        __m128i delta = _mm_set1_epi32(INTER_REMAP_COEF_SCALE/2);
        __m128i xy2ofs = _mm_set1_epi32(cn + (sstep << 16));
        __m128i z = _mm_setzero_si128();
        int CV_DECL_ALIGNED(16) iofs0[4], iofs1[4];

        if( cn == 1 )
        {
            for( ; x <= width - 8; x += 8 )
            {
                __m128i xy0 = _mm_loadu_si128( (const __m128i*)(XY + x*2));
                __m128i xy1 = _mm_loadu_si128( (const __m128i*)(XY + x*2 + 8));
                __m128i v0, v1, v2, v3, a0, a1, b0, b1;
                unsigned i0, i1;

                xy0 = _mm_madd_epi16( xy0, xy2ofs );
                xy1 = _mm_madd_epi16( xy1, xy2ofs );
                _mm_store_si128( (__m128i*)iofs0, xy0 );
                _mm_store_si128( (__m128i*)iofs1, xy1 );

                i0 = *(ushort*)(S0 + iofs0[0]) + (*(ushort*)(S0 + iofs0[1]) << 16);
                i1 = *(ushort*)(S0 + iofs0[2]) + (*(ushort*)(S0 + iofs0[3]) << 16);
                v0 = _mm_unpacklo_epi32(_mm_cvtsi32_si128(i0), _mm_cvtsi32_si128(i1));
                i0 = *(ushort*)(S1 + iofs0[0]) + (*(ushort*)(S1 + iofs0[1]) << 16);
                i1 = *(ushort*)(S1 + iofs0[2]) + (*(ushort*)(S1 + iofs0[3]) << 16);
                v1 = _mm_unpacklo_epi32(_mm_cvtsi32_si128(i0), _mm_cvtsi32_si128(i1));
                v0 = _mm_unpacklo_epi8(v0, z);
                v1 = _mm_unpacklo_epi8(v1, z);

                a0 = _mm_unpacklo_epi32(_mm_loadl_epi64((__m128i*)(wtab+FXY[x]*4)),
                                        _mm_loadl_epi64((__m128i*)(wtab+FXY[x+1]*4)));
                a1 = _mm_unpacklo_epi32(_mm_loadl_epi64((__m128i*)(wtab+FXY[x+2]*4)),
                                        _mm_loadl_epi64((__m128i*)(wtab+FXY[x+3]*4)));
                b0 = _mm_unpacklo_epi64(a0, a1);
                b1 = _mm_unpackhi_epi64(a0, a1);
                v0 = _mm_madd_epi16(v0, b0);
                v1 = _mm_madd_epi16(v1, b1);
                v0 = _mm_add_epi32(_mm_add_epi32(v0, v1), delta);

                i0 = *(ushort*)(S0 + iofs1[0]) + (*(ushort*)(S0 + iofs1[1]) << 16);
                i1 = *(ushort*)(S0 + iofs1[2]) + (*(ushort*)(S0 + iofs1[3]) << 16);
                v2 = _mm_unpacklo_epi32(_mm_cvtsi32_si128(i0), _mm_cvtsi32_si128(i1));
                i0 = *(ushort*)(S1 + iofs1[0]) + (*(ushort*)(S1 + iofs1[1]) << 16);
                i1 = *(ushort*)(S1 + iofs1[2]) + (*(ushort*)(S1 + iofs1[3]) << 16);
                v3 = _mm_unpacklo_epi32(_mm_cvtsi32_si128(i0), _mm_cvtsi32_si128(i1));
                v2 = _mm_unpacklo_epi8(v2, z);
                v3 = _mm_unpacklo_epi8(v3, z);

                a0 = _mm_unpacklo_epi32(_mm_loadl_epi64((__m128i*)(wtab+FXY[x+4]*4)),
                                        _mm_loadl_epi64((__m128i*)(wtab+FXY[x+5]*4)));
                a1 = _mm_unpacklo_epi32(_mm_loadl_epi64((__m128i*)(wtab+FXY[x+6]*4)),
                                        _mm_loadl_epi64((__m128i*)(wtab+FXY[x+7]*4)));
                b0 = _mm_unpacklo_epi64(a0, a1);
                b1 = _mm_unpackhi_epi64(a0, a1);
                v2 = _mm_madd_epi16(v2, b0);
                v3 = _mm_madd_epi16(v3, b1);
                v2 = _mm_add_epi32(_mm_add_epi32(v2, v3), delta);

                v0 = _mm_srai_epi32(v0, INTER_REMAP_COEF_BITS);
                v2 = _mm_srai_epi32(v2, INTER_REMAP_COEF_BITS);
                v0 = _mm_packus_epi16(_mm_packs_epi32(v0, v2), z);
                _mm_storel_epi64( (__m128i*)(D + x), v0 );
            }
        }
        else if( cn == 3 )
        {
            for( ; x <= width - 5; x += 4, D += 12 )
            {
                __m128i xy0 = _mm_loadu_si128( (const __m128i*)(XY + x*2));
                __m128i u0, v0, u1, v1;

                xy0 = _mm_madd_epi16( xy0, xy2ofs );
                _mm_store_si128( (__m128i*)iofs0, xy0 );
                const __m128i *w0, *w1;
                w0 = (const __m128i*)(wtab + FXY[x]*16);
                w1 = (const __m128i*)(wtab + FXY[x+1]*16);

                u0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[0])),
                                       _mm_cvtsi32_si128(*(int*)(S0 + iofs0[0] + 3)));
                v0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[0])),
                                       _mm_cvtsi32_si128(*(int*)(S1 + iofs0[0] + 3)));
                u1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[1])),
                                       _mm_cvtsi32_si128(*(int*)(S0 + iofs0[1] + 3)));
                v1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[1])),
                                       _mm_cvtsi32_si128(*(int*)(S1 + iofs0[1] + 3)));
                u0 = _mm_unpacklo_epi8(u0, z);
                v0 = _mm_unpacklo_epi8(v0, z);
                u1 = _mm_unpacklo_epi8(u1, z);
                v1 = _mm_unpacklo_epi8(v1, z);
                u0 = _mm_add_epi32(_mm_madd_epi16(u0, w0[0]), _mm_madd_epi16(v0, w0[1]));
                u1 = _mm_add_epi32(_mm_madd_epi16(u1, w1[0]), _mm_madd_epi16(v1, w1[1]));
                u0 = _mm_srai_epi32(_mm_add_epi32(u0, delta), INTER_REMAP_COEF_BITS);
                u1 = _mm_srai_epi32(_mm_add_epi32(u1, delta), INTER_REMAP_COEF_BITS);
                u0 = _mm_slli_si128(u0, 4);
                u0 = _mm_packs_epi32(u0, u1);
                u0 = _mm_packus_epi16(u0, u0);
                _mm_storel_epi64((__m128i*)D, _mm_srli_si128(u0,1));

                w0 = (const __m128i*)(wtab + FXY[x+2]*16);
                w1 = (const __m128i*)(wtab + FXY[x+3]*16);

                u0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[2])),
                                       _mm_cvtsi32_si128(*(int*)(S0 + iofs0[2] + 3)));
                v0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[2])),
                                       _mm_cvtsi32_si128(*(int*)(S1 + iofs0[2] + 3)));
                u1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[3])),
                                       _mm_cvtsi32_si128(*(int*)(S0 + iofs0[3] + 3)));
                v1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[3])),
                                       _mm_cvtsi32_si128(*(int*)(S1 + iofs0[3] + 3)));
                u0 = _mm_unpacklo_epi8(u0, z);
                v0 = _mm_unpacklo_epi8(v0, z);
                u1 = _mm_unpacklo_epi8(u1, z);
                v1 = _mm_unpacklo_epi8(v1, z);
                u0 = _mm_add_epi32(_mm_madd_epi16(u0, w0[0]), _mm_madd_epi16(v0, w0[1]));
                u1 = _mm_add_epi32(_mm_madd_epi16(u1, w1[0]), _mm_madd_epi16(v1, w1[1]));
                u0 = _mm_srai_epi32(_mm_add_epi32(u0, delta), INTER_REMAP_COEF_BITS);
                u1 = _mm_srai_epi32(_mm_add_epi32(u1, delta), INTER_REMAP_COEF_BITS);
                u0 = _mm_slli_si128(u0, 4);
                u0 = _mm_packs_epi32(u0, u1);
                u0 = _mm_packus_epi16(u0, u0);
                _mm_storel_epi64((__m128i*)(D + 6), _mm_srli_si128(u0,1));
            }
        }
        else if( cn == 4 )
        {
            for( ; x <= width - 4; x += 4, D += 16 )
            {
                __m128i xy0 = _mm_loadu_si128( (const __m128i*)(XY + x*2));
                __m128i u0, v0, u1, v1;

                xy0 = _mm_madd_epi16( xy0, xy2ofs );
                _mm_store_si128( (__m128i*)iofs0, xy0 );
                const __m128i *w0, *w1;
                w0 = (const __m128i*)(wtab + FXY[x]*16);
                w1 = (const __m128i*)(wtab + FXY[x+1]*16);

                u0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[0])),
                                       _mm_cvtsi32_si128(*(int*)(S0 + iofs0[0] + 4)));
                v0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[0])),
                                       _mm_cvtsi32_si128(*(int*)(S1 + iofs0[0] + 4)));
                u1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[1])),
                                       _mm_cvtsi32_si128(*(int*)(S0 + iofs0[1] + 4)));
                v1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[1])),
                                       _mm_cvtsi32_si128(*(int*)(S1 + iofs0[1] + 4)));
                u0 = _mm_unpacklo_epi8(u0, z);
                v0 = _mm_unpacklo_epi8(v0, z);
                u1 = _mm_unpacklo_epi8(u1, z);
                v1 = _mm_unpacklo_epi8(v1, z);
                u0 = _mm_add_epi32(_mm_madd_epi16(u0, w0[0]), _mm_madd_epi16(v0, w0[1]));
                u1 = _mm_add_epi32(_mm_madd_epi16(u1, w1[0]), _mm_madd_epi16(v1, w1[1]));
                u0 = _mm_srai_epi32(_mm_add_epi32(u0, delta), INTER_REMAP_COEF_BITS);
                u1 = _mm_srai_epi32(_mm_add_epi32(u1, delta), INTER_REMAP_COEF_BITS);
                u0 = _mm_packs_epi32(u0, u1);
                u0 = _mm_packus_epi16(u0, u0);
                _mm_storel_epi64((__m128i*)D, u0);

                w0 = (const __m128i*)(wtab + FXY[x+2]*16);
                w1 = (const __m128i*)(wtab + FXY[x+3]*16);

                u0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[2])),
                                       _mm_cvtsi32_si128(*(int*)(S0 + iofs0[2] + 4)));
                v0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[2])),
                                       _mm_cvtsi32_si128(*(int*)(S1 + iofs0[2] + 4)));
                u1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S0 + iofs0[3])),
                                       _mm_cvtsi32_si128(*(int*)(S0 + iofs0[3] + 4)));
                v1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(*(int*)(S1 + iofs0[3])),
                                       _mm_cvtsi32_si128(*(int*)(S1 + iofs0[3] + 4)));
                u0 = _mm_unpacklo_epi8(u0, z);
                v0 = _mm_unpacklo_epi8(v0, z);
                u1 = _mm_unpacklo_epi8(u1, z);
                v1 = _mm_unpacklo_epi8(v1, z);
                u0 = _mm_add_epi32(_mm_madd_epi16(u0, w0[0]), _mm_madd_epi16(v0, w0[1]));
                u1 = _mm_add_epi32(_mm_madd_epi16(u1, w1[0]), _mm_madd_epi16(v1, w1[1]));
                u0 = _mm_srai_epi32(_mm_add_epi32(u0, delta), INTER_REMAP_COEF_BITS);
                u1 = _mm_srai_epi32(_mm_add_epi32(u1, delta), INTER_REMAP_COEF_BITS);
                u0 = _mm_packs_epi32(u0, u1);
                u0 = _mm_packus_epi16(u0, u0);
                _mm_storel_epi64((__m128i*)(D + 8), u0);
            }
        }

        return x;
    }
};

#else

typedef RemapNoVec RemapVec_8u;

#endif


template<class CastOp, class VecOp, typename AT>
static void remapBilinear( const Mat& _src, Mat& _dst, const Mat& _xy,
                           const Mat& _fxy, const void* _wtab,
                           int borderType, const Scalar& _borderValue )
{
    typedef typename CastOp::rtype T;
    typedef typename CastOp::type1 WT;
    Size ssize = _src.size(), dsize = _dst.size();
    int cn = _src.channels();
    const AT* wtab = (const AT*)_wtab;
    const T* S0 = (const T*)_src.data;
    size_t sstep = _src.step/sizeof(S0[0]);
    Scalar_<T> cval(saturate_cast<T>(_borderValue[0]),
        saturate_cast<T>(_borderValue[1]),
        saturate_cast<T>(_borderValue[2]),
        saturate_cast<T>(_borderValue[3]));
    int dx, dy;
    CastOp castOp;
    VecOp vecOp;

    unsigned width1 = std::max(ssize.width-1, 0), height1 = std::max(ssize.height-1, 0);
    CV_Assert( cn <= 4 && ssize.area() > 0 );
#if CV_SSE2
    if( _src.type() == CV_8UC3 )
        width1 = std::max(ssize.width-2, 0);
#endif

    for( dy = 0; dy < dsize.height; dy++ )
    {
        T* D = (T*)(_dst.data + _dst.step*dy);
        const short* XY = (const short*)(_xy.data + _xy.step*dy);
        const ushort* FXY = (const ushort*)(_fxy.data + _fxy.step*dy);
        int X0 = 0;
        bool prevInlier = false;

        for( dx = 0; dx <= dsize.width; dx++ )
        {
            bool curInlier = dx < dsize.width ?
                (unsigned)XY[dx*2] < width1 &&
                (unsigned)XY[dx*2+1] < height1 : !prevInlier;
            if( curInlier == prevInlier )
                continue;

            int X1 = dx;
            dx = X0;
            X0 = X1;
            prevInlier = curInlier;

            if( !curInlier )
            {
                int len = vecOp( _src, D, XY + dx*2, FXY + dx, wtab, X1 - dx );
                D += len*cn;
                dx += len;

                if( cn == 1 )
                {
                    for( ; dx < X1; dx++, D++ )
                    {
                        int sx = XY[dx*2], sy = XY[dx*2+1];
                        const AT* w = wtab + FXY[dx]*4;
                        const T* S = S0 + sy*sstep + sx;
                        *D = castOp(WT(S[0]*w[0] + S[1]*w[1] + S[sstep]*w[2] + S[sstep+1]*w[3]));
                    }
                }
                else if( cn == 2 )
                    for( ; dx < X1; dx++, D += 2 )
                    {
                        int sx = XY[dx*2], sy = XY[dx*2+1];
                        const AT* w = wtab + FXY[dx]*4;
                        const T* S = S0 + sy*sstep + sx*2;
                        WT t0 = S[0]*w[0] + S[2]*w[1] + S[sstep]*w[2] + S[sstep+2]*w[3];
                        WT t1 = S[1]*w[0] + S[3]*w[1] + S[sstep+1]*w[2] + S[sstep+3]*w[3];
                        D[0] = castOp(t0); D[1] = castOp(t1);
                    }
                else if( cn == 3 )
                    for( ; dx < X1; dx++, D += 3 )
                    {
                        int sx = XY[dx*2], sy = XY[dx*2+1];
                        const AT* w = wtab + FXY[dx]*4;
                        const T* S = S0 + sy*sstep + sx*3;
                        WT t0 = S[0]*w[0] + S[3]*w[1] + S[sstep]*w[2] + S[sstep+3]*w[3];
                        WT t1 = S[1]*w[0] + S[4]*w[1] + S[sstep+1]*w[2] + S[sstep+4]*w[3];
                        WT t2 = S[2]*w[0] + S[5]*w[1] + S[sstep+2]*w[2] + S[sstep+5]*w[3];
                        D[0] = castOp(t0); D[1] = castOp(t1); D[2] = castOp(t2);
                    }
                else
                    for( ; dx < X1; dx++, D += 4 )
                    {
                        int sx = XY[dx*2], sy = XY[dx*2+1];
                        const AT* w = wtab + FXY[dx]*4;
                        const T* S = S0 + sy*sstep + sx*4;
                        WT t0 = S[0]*w[0] + S[4]*w[1] + S[sstep]*w[2] + S[sstep+4]*w[3];
                        WT t1 = S[1]*w[0] + S[5]*w[1] + S[sstep+1]*w[2] + S[sstep+5]*w[3];
                        D[0] = castOp(t0); D[1] = castOp(t1);
                        t0 = S[2]*w[0] + S[6]*w[1] + S[sstep+2]*w[2] + S[sstep+6]*w[3];
                        t1 = S[3]*w[0] + S[7]*w[1] + S[sstep+3]*w[2] + S[sstep+7]*w[3];
                        D[2] = castOp(t0); D[3] = castOp(t1);
                    }
            }
            else
            {
                if( borderType == BORDER_TRANSPARENT && cn != 3 )
                {
                    D += (X1 - dx)*cn;
                    dx = X1;
                    continue;
                }

                if( cn == 1 )
                    for( ; dx < X1; dx++, D++ )
                    {
                        int sx = XY[dx*2], sy = XY[dx*2+1];
                        if( borderType == BORDER_CONSTANT &&
                            (sx >= ssize.width || sx+1 < 0 ||
                             sy >= ssize.height || sy+1 < 0) )
                        {
                            D[0] = cval[0];
                        }
                        else
                        {
                            int sx0, sx1, sy0, sy1;
                            T v0, v1, v2, v3;
                            const AT* w = wtab + FXY[dx]*4;
                            if( borderType == BORDER_REPLICATE )
                            {
                                sx0 = clip(sx, 0, ssize.width);
                                sx1 = clip(sx+1, 0, ssize.width);
                                sy0 = clip(sy, 0, ssize.height);
                                sy1 = clip(sy+1, 0, ssize.height);
                                v0 = S0[sy0*sstep + sx0];
                                v1 = S0[sy0*sstep + sx1];
                                v2 = S0[sy1*sstep + sx0];
                                v3 = S0[sy1*sstep + sx1];
                            }
                            else
                            {
                                sx0 = borderInterpolate(sx, ssize.width, borderType);
                                sx1 = borderInterpolate(sx+1, ssize.width, borderType);
                                sy0 = borderInterpolate(sy, ssize.height, borderType);
                                sy1 = borderInterpolate(sy+1, ssize.height, borderType);
                                v0 = sx0 >= 0 && sy0 >= 0 ? S0[sy0*sstep + sx0] : cval[0];
                                v1 = sx1 >= 0 && sy0 >= 0 ? S0[sy0*sstep + sx1] : cval[0];
                                v2 = sx0 >= 0 && sy1 >= 0 ? S0[sy1*sstep + sx0] : cval[0];
                                v3 = sx1 >= 0 && sy1 >= 0 ? S0[sy1*sstep + sx1] : cval[0];
                            }
                            D[0] = castOp(WT(v0*w[0] + v1*w[1] + v2*w[2] + v3*w[3]));
                        }
                    }
                else
                    for( ; dx < X1; dx++, D += cn )
                    {
                        int sx = XY[dx*2], sy = XY[dx*2+1], k;
                        if( borderType == BORDER_CONSTANT &&
                            (sx >= ssize.width || sx+1 < 0 ||
                             sy >= ssize.height || sy+1 < 0) )
                        {
                            for( k = 0; k < cn; k++ )
                                D[k] = cval[k];
                        }
                        else
                        {
                            int sx0, sx1, sy0, sy1;
                            const T *v0, *v1, *v2, *v3;
                            const AT* w = wtab + FXY[dx]*4;
                            if( borderType == BORDER_REPLICATE )
                            {
                                sx0 = clip(sx, 0, ssize.width);
                                sx1 = clip(sx+1, 0, ssize.width);
                                sy0 = clip(sy, 0, ssize.height);
                                sy1 = clip(sy+1, 0, ssize.height);
                                v0 = S0 + sy0*sstep + sx0*cn;
                                v1 = S0 + sy0*sstep + sx1*cn;
                                v2 = S0 + sy1*sstep + sx0*cn;
                                v3 = S0 + sy1*sstep + sx1*cn;
                            }
                            else if( borderType == BORDER_TRANSPARENT &&
                                ((unsigned)sx >= (unsigned)(ssize.width-1) ||
                                (unsigned)sy >= (unsigned)(ssize.height-1)))
                                continue;
                            else
                            {
                                sx0 = borderInterpolate(sx, ssize.width, borderType);
                                sx1 = borderInterpolate(sx+1, ssize.width, borderType);
                                sy0 = borderInterpolate(sy, ssize.height, borderType);
                                sy1 = borderInterpolate(sy+1, ssize.height, borderType);
                                v0 = sx0 >= 0 && sy0 >= 0 ? S0 + sy0*sstep + sx0*cn : &cval[0];
                                v1 = sx1 >= 0 && sy0 >= 0 ? S0 + sy0*sstep + sx1*cn : &cval[0];
                                v2 = sx0 >= 0 && sy1 >= 0 ? S0 + sy1*sstep + sx0*cn : &cval[0];
                                v3 = sx1 >= 0 && sy1 >= 0 ? S0 + sy1*sstep + sx1*cn : &cval[0];
                            }
                            for( k = 0; k < cn; k++ )
                                D[k] = castOp(WT(v0[k]*w[0] + v1[k]*w[1] + v2[k]*w[2] + v3[k]*w[3]));
                        }
                    }
            }
        }
    }
}


template<class CastOp, typename AT, int ONE>
static void remapBicubic( const Mat& _src, Mat& _dst, const Mat& _xy,
                          const Mat& _fxy, const void* _wtab,
                          int borderType, const Scalar& _borderValue )
{
    typedef typename CastOp::rtype T;
    typedef typename CastOp::type1 WT;
    Size ssize = _src.size(), dsize = _dst.size();
    int cn = _src.channels();
    const AT* wtab = (const AT*)_wtab;
    const T* S0 = (const T*)_src.data;
    size_t sstep = _src.step/sizeof(S0[0]);
    Scalar_<T> cval(saturate_cast<T>(_borderValue[0]),
        saturate_cast<T>(_borderValue[1]),
        saturate_cast<T>(_borderValue[2]),
        saturate_cast<T>(_borderValue[3]));
    int dx, dy;
    CastOp castOp;
3195
    int borderType1 = borderType != BORDER_TRANSPARENT ? borderType : BORDER_REFLECT_101;
3196 3197 3198 3199 3200 3201 3202 3203 3204 3205 3206 3207 3208 3209 3210 3211 3212 3213 3214 3215 3216 3217 3218 3219 3220 3221 3222 3223 3224 3225 3226 3227 3228 3229 3230 3231 3232 3233 3234

    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];
3235 3236 3237
                if( borderType == BORDER_TRANSPARENT &&
                    ((unsigned)(sx+1) >= (unsigned)ssize.width ||
                    (unsigned)(sy+1) >= (unsigned)ssize.height) )
3238 3239
                    continue;

3240
                if( borderType1 == BORDER_CONSTANT &&
3241 3242 3243 3244 3245 3246 3247 3248 3249 3250
                    (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++ )
                {
3251 3252
                    x[i] = borderInterpolate(sx + i, ssize.width, borderType1)*cn;
                    y[i] = borderInterpolate(sy + i, ssize.height, borderType1);
3253 3254 3255 3256 3257 3258 3259 3260 3261 3262 3263 3264 3265 3266 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 3297 3298 3299
                }

                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;
3300
    int borderType1 = borderType != BORDER_TRANSPARENT ? borderType : BORDER_REFLECT_101;
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3302 3303 3304 3305 3306 3307 3308 3309 3310 3311 3312 3313 3314 3315 3316 3317 3318 3319 3320 3321 3322 3323 3324 3325 3326 3327 3328 3329 3330 3331 3332 3333 3334 3335 3336 3337
    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];
3338 3339 3340
                if( borderType == BORDER_TRANSPARENT &&
                    ((unsigned)(sx+3) >= (unsigned)ssize.width ||
                    (unsigned)(sy+3) >= (unsigned)ssize.height) )
3341 3342
                    continue;

3343
                if( borderType1 == BORDER_CONSTANT &&
3344 3345 3346 3347 3348 3349 3350 3351 3352 3353
                    (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++ )
                {
3354 3355
                    x[i] = borderInterpolate(sx + i, ssize.width, borderType1)*cn;
                    y[i] = borderInterpolate(sy + i, ssize.height, borderType1);
3356 3357 3358 3359 3360 3361 3362 3363
                }

                for( k = 0; k < cn; k++, S0++, w -= 64 )
                {
                    WT cv = cval[k], sum = cv*ONE;
                    for( i = 0; i < 8; i++, w += 8 )
                    {
                        int yi = y[i];
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                        const T* S1 = S0 + yi*sstep;
3365 3366 3367
                        if( yi < 0 )
                            continue;
                        if( x[0] >= 0 )
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                            sum += (S1[x[0]] - cv)*w[0];
3369
                        if( x[1] >= 0 )
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                            sum += (S1[x[1]] - cv)*w[1];
3371
                        if( x[2] >= 0 )
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                            sum += (S1[x[2]] - cv)*w[2];
3373
                        if( x[3] >= 0 )
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3374
                            sum += (S1[x[3]] - cv)*w[3];
3375
                        if( x[4] >= 0 )
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                            sum += (S1[x[4]] - cv)*w[4];
3377
                        if( x[5] >= 0 )
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3378
                            sum += (S1[x[5]] - cv)*w[5];
3379
                        if( x[6] >= 0 )
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Andrey Kamaev 已提交
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                            sum += (S1[x[6]] - cv)*w[6];
3381
                        if( x[7] >= 0 )
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                            sum += (S1[x[7]] - cv)*w[7];
3383 3384 3385 3386 3387 3388 3389 3390 3391 3392 3393 3394 3395 3396 3397 3398 3399
                    }
                    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);

3400
class RemapInvoker :
3401 3402 3403
    public ParallelLoopBody
{
public:
3404
    RemapInvoker(const Mat& _src, Mat& _dst, const Mat *_m1,
3405
                 const Mat *_m2, int _borderType, const Scalar &_borderValue,
3406
                 int _planar_input, RemapNNFunc _nnfunc, RemapFunc _ifunc, const void *_ctab) :
3407
        ParallelLoopBody(), src(&_src), dst(&_dst), m1(_m1), m2(_m2),
3408
        borderType(_borderType), borderValue(_borderValue),
3409
        planar_input(_planar_input), nnfunc(_nnfunc), ifunc(_ifunc), ctab(_ctab)
3410 3411 3412
    {
    }

3413 3414 3415 3416
    virtual void operator() (const Range& range) const
    {
        int x, y, x1, y1;
        const int buf_size = 1 << 14;
3417 3418 3419
        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);
3420 3421 3422 3423 3424 3425 3426 3427 3428 3429
    #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 )
        {
3430
            for( x = 0; x < dst->cols; x += bcols0 )
3431 3432
            {
                int brows = std::min(brows0, range.end - y);
3433 3434
                int bcols = std::min(bcols0, dst->cols - x);
                Mat dpart(*dst, Rect(x, y, bcols, brows));
3435 3436 3437 3438
                Mat bufxy(_bufxy, Rect(0, 0, bcols, brows));

                if( nnfunc )
                {
3439 3440
                    if( m1->type() == CV_16SC2 && !m2->data ) // the data is already in the right format
                        bufxy = (*m1)(Rect(x, y, bcols, brows));
3441 3442 3443 3444 3445 3446 3447 3448 3449 3450 3451 3452 3453 3454 3455 3456 3457
                    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 )
3458
                        (*m1)(Rect(x, y, bcols, brows)).convertTo(bufxy, bufxy.depth());
3459 3460 3461 3462 3463
                    else
                    {
                        for( y1 = 0; y1 < brows; y1++ )
                        {
                            short* XY = (short*)(bufxy.data + bufxy.step*y1);
3464 3465
                            const float* sX = (const float*)(m1->data + m1->step*(y+y1)) + x;
                            const float* sY = (const float*)(m2->data + m2->step*(y+y1)) + x;
3466 3467 3468 3469 3470 3471 3472 3473 3474 3475 3476 3477 3478 3479 3480 3481 3482 3483 3484 3485 3486 3487 3488 3489 3490 3491 3492 3493 3494 3495 3496 3497
                            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]);
                            }
                        }
                    }
3498
                    nnfunc( *src, dpart, bufxy, borderType, borderValue );
3499 3500 3501 3502 3503 3504 3505 3506 3507
                    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);

3508
                    if( m1->type() == CV_16SC2 && (m2->type() == CV_16UC1 || m2->type() == CV_16SC1) )
3509
                    {
3510
                        bufxy = (*m1)(Rect(x, y, bcols, brows));
3511 3512 3513 3514

                        const ushort* sA = (const ushort*)(m2->data + m2->step*(y+y1)) + x;
                        for( x1 = 0; x1 < bcols; x1++ )
                            A[x1] = (ushort)(sA[x1] & (INTER_TAB_SIZE2-1));
3515 3516 3517
                    }
                    else if( planar_input )
                    {
3518 3519
                        const float* sX = (const float*)(m1->data + m1->step*(y+y1)) + x;
                        const float* sY = (const float*)(m2->data + m2->step*(y+y1)) + x;
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 3559 3560 3561 3562 3563 3564

                        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));
3565 3566
                            XY[x1*2] = saturate_cast<short>(sx >> INTER_BITS);
                            XY[x1*2+1] = saturate_cast<short>(sy >> INTER_BITS);
3567 3568 3569 3570 3571
                            A[x1] = (ushort)v;
                        }
                    }
                    else
                    {
3572
                        const float* sXY = (const float*)(m1->data + m1->step*(y+y1)) + x*2;
3573 3574 3575 3576 3577 3578

                        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));
3579 3580
                            XY[x1*2] = saturate_cast<short>(sx >> INTER_BITS);
                            XY[x1*2+1] = saturate_cast<short>(sy >> INTER_BITS);
3581 3582 3583 3584
                            A[x1] = (ushort)v;
                        }
                    }
                }
3585
                ifunc(*src, dpart, bufxy, bufa, ctab, borderType, borderValue);
3586 3587 3588
            }
        }
    }
3589

3590
private:
3591 3592
    const Mat* src;
    Mat* dst;
3593
    const Mat *m1, *m2;
3594
    int borderType;
3595
    Scalar borderValue;
3596 3597 3598 3599 3600 3601
    int planar_input;
    RemapNNFunc nnfunc;
    RemapFunc ifunc;
    const void *ctab;
};

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Ilya Lavrenov 已提交
3602 3603
#ifdef HAVE_OPENCL

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3604 3605 3606 3607 3608
static bool ocl_remap(InputArray _src, OutputArray _dst, InputArray _map1, InputArray _map2,
                      int interpolation, int borderType, const Scalar& borderValue)
{
    int cn = _src.channels(), type = _src.type(), depth = _src.depth();

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3609
    if (borderType == BORDER_TRANSPARENT || !(interpolation == INTER_LINEAR || interpolation == INTER_NEAREST)
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Ilya Lavrenov 已提交
3610 3611 3612 3613 3614 3615 3616 3617 3618 3619 3620 3621 3622 3623 3624 3625 3626 3627 3628 3629 3630 3631 3632 3633 3634 3635 3636 3637 3638 3639 3640 3641 3642 3643 3644 3645 3646 3647 3648 3649 3650 3651 3652 3653 3654 3655 3656 3657 3658
            || _map1.type() == CV_16SC1 || _map2.type() == CV_16SC1)
        return false;

    UMat src = _src.getUMat(), map1 = _map1.getUMat(), map2 = _map2.getUMat();

    if( (map1.type() == CV_16SC2 && (map2.type() == CV_16UC1 || map2.empty())) ||
        (map2.type() == CV_16SC2 && (map1.type() == CV_16UC1 || map1.empty())) )
    {
        if (map1.type() != CV_16SC2)
            std::swap(map1, map2);
    }
    else
        CV_Assert( map1.type() == CV_32FC2 || (map1.type() == CV_32FC1 && map2.type() == CV_32FC1) );

    _dst.create(map1.size(), type);
    UMat dst = _dst.getUMat();

    String kernelName = "remap";
    if (map1.type() == CV_32FC2 && map2.empty())
        kernelName += "_32FC2";
    else if (map1.type() == CV_16SC2)
    {
        kernelName += "_16SC2";
        if (!map2.empty())
            kernelName += "_16UC1";
    }
    else if (map1.type() == CV_32FC1 && map2.type() == CV_32FC1)
        kernelName += "_2_32FC1";
    else
        CV_Error(Error::StsBadArg, "Unsupported map types");

    static const char * const interMap[] = { "INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_LINEAR", "INTER_LANCZOS" };
    static const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP",
                           "BORDER_REFLECT_101", "BORDER_TRANSPARENT" };
    String buildOptions = format("-D %s -D %s -D T=%s", interMap[interpolation], borderMap[borderType], ocl::typeToStr(type));

    if (interpolation != INTER_NEAREST)
    {
        char cvt[3][40];
        int wdepth = std::max(CV_32F, dst.depth());
        buildOptions = buildOptions
                      + format(" -D WT=%s -D convertToT=%s -D convertToWT=%s"
                               " -D convertToWT2=%s -D WT2=%s",
                               ocl::typeToStr(CV_MAKE_TYPE(wdepth, cn)),
                               ocl::convertTypeStr(wdepth, depth, cn, cvt[0]),
                               ocl::convertTypeStr(depth, wdepth, cn, cvt[1]),
                               ocl::convertTypeStr(CV_32S, wdepth, 2, cvt[2]),
                               ocl::typeToStr(CV_MAKE_TYPE(wdepth, 2)));
    }
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3659 3660 3661 3662 3663 3664
    int scalarcn = cn == 3 ? 4 : cn;
    int sctype = CV_MAKETYPE(depth, scalarcn);
    buildOptions += format(" -D T=%s -D T1=%s"
                           " -D cn=%d -D ST=%s",
                           ocl::typeToStr(type), ocl::typeToStr(depth),
                           cn, ocl::typeToStr(sctype));
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Ilya Lavrenov 已提交
3665 3666 3667

    ocl::Kernel k(kernelName.c_str(), ocl::imgproc::remap_oclsrc, buildOptions);

A
Alexander Alekhin 已提交
3668
    Mat scalar(1, 1, sctype, borderValue);
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Ilya Lavrenov 已提交
3669 3670 3671 3672 3673 3674 3675 3676 3677 3678 3679 3680 3681
    ocl::KernelArg srcarg = ocl::KernelArg::ReadOnly(src), dstarg = ocl::KernelArg::WriteOnly(dst),
            map1arg = ocl::KernelArg::ReadOnlyNoSize(map1),
            scalararg = ocl::KernelArg::Constant((void*)scalar.data, scalar.elemSize());

    if (map2.empty())
        k.args(srcarg, dstarg, map1arg, scalararg);
    else
        k.args(srcarg, dstarg, map1arg, ocl::KernelArg::ReadOnlyNoSize(map2), scalararg);

    size_t globalThreads[2] = { dst.cols, dst.rows };
    return k.run(2, globalThreads, NULL, false);
}

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3682 3683
#endif

3684
}
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3685

3686 3687
void cv::remap( InputArray _src, OutputArray _dst,
                InputArray _map1, InputArray _map2,
3688
                int interpolation, int borderType, const Scalar& borderValue )
3689 3690 3691
{
    static RemapNNFunc nn_tab[] =
    {
3692 3693
        remapNearest<uchar>, remapNearest<schar>, remapNearest<ushort>, remapNearest<short>,
        remapNearest<int>, remapNearest<float>, remapNearest<double>, 0
3694 3695 3696 3697 3698 3699 3700
    };

    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,
3701 3702
        remapBilinear<Cast<float, float>, RemapNoVec, float>,
        remapBilinear<Cast<double, double>, RemapNoVec, float>, 0
3703 3704 3705 3706 3707 3708 3709
    };

    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,
3710 3711
        remapBicubic<Cast<float, float>, float, 1>,
        remapBicubic<Cast<double, double>, float, 1>, 0
3712 3713 3714 3715 3716 3717 3718
    };

    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,
3719 3720
        remapLanczos4<Cast<float, float>, float, 1>,
        remapLanczos4<Cast<double, double>, float, 1>, 0
3721 3722
    };

I
Ilya Lavrenov 已提交
3723 3724
    CV_Assert( _map1.size().area() > 0 );
    CV_Assert( _map2.empty() || (_map2.size() == _map1.size()));
M
Marina Kolpakova 已提交
3725

I
Ilya Lavrenov 已提交
3726 3727
    CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
               ocl_remap(_src, _dst, _map1, _map2, interpolation, borderType, borderValue))
M
Marina Kolpakova 已提交
3728

I
Ilya Lavrenov 已提交
3729
    Mat src = _src.getMat(), map1 = _map1.getMat(), map2 = _map2.getMat();
3730 3731
    _dst.create( map1.size(), src.type() );
    Mat dst = _dst.getMat();
3732 3733
    if( dst.data == src.data )
        src = src.clone();
3734

3735
    int depth = src.depth();
3736 3737 3738 3739 3740 3741 3742 3743 3744 3745 3746 3747 3748 3749 3750 3751 3752 3753 3754 3755 3756 3757 3758 3759 3760 3761 3762 3763 3764 3765
    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;

3766 3767
    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)) )
3768 3769 3770 3771 3772 3773
    {
        if( map1.type() != CV_16SC2 )
            std::swap(m1, m2);
    }
    else
    {
3774
        CV_Assert( ((map1.type() == CV_32FC2 || map1.type() == CV_16SC2) && !map2.data) ||
3775 3776 3777 3778
            (map1.type() == CV_32FC1 && map2.type() == CV_32FC1) );
        planar_input = map1.channels() == 1;
    }

3779
    RemapInvoker invoker(src, dst, m1, m2,
3780 3781
                         borderType, borderValue, planar_input, nnfunc, ifunc,
                         ctab);
3782
    parallel_for_(Range(0, dst.rows), invoker, dst.total()/(double)(1<<16));
3783 3784 3785
}


3786
void cv::convertMaps( InputArray _map1, InputArray _map2,
3787 3788
                      OutputArray _dstmap1, OutputArray _dstmap2,
                      int dstm1type, bool nninterpolate )
3789
{
3790
    Mat map1 = _map1.getMat(), map2 = _map2.getMat(), dstmap1, dstmap2;
3791 3792 3793 3794 3795 3796 3797 3798 3799 3800 3801 3802 3803 3804 3805 3806 3807 3808
    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 );
3809 3810
    _dstmap1.create( size, dstm1type );
    dstmap1 = _dstmap1.getMat();
M
Marina Kolpakova 已提交
3811

3812
    if( !nninterpolate && dstm1type != CV_32FC2 )
3813 3814 3815 3816
    {
        _dstmap2.create( size, dstm1type == CV_16SC2 ? CV_16UC1 : CV_32FC1 );
        dstmap2 = _dstmap2.getMat();
    }
3817
    else
3818
        _dstmap2.release();
3819 3820 3821 3822 3823 3824 3825 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 3864 3865 3866 3867 3868 3869 3870 3871 3872 3873 3874 3875 3876 3877

    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);
3878 3879
                    dst1[x*2] = saturate_cast<short>(ix >> INTER_BITS);
                    dst1[x*2+1] = saturate_cast<short>(iy >> INTER_BITS);
3880 3881 3882 3883 3884 3885 3886 3887 3888 3889 3890 3891 3892 3893 3894 3895
                    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);
3896 3897
                    dst1[x*2] = saturate_cast<short>(ix >> INTER_BITS);
                    dst1[x*2+1] = saturate_cast<short>(iy >> INTER_BITS);
3898 3899 3900 3901 3902 3903 3904
                    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++ )
            {
3905
                int fxy = src2 ? src2[x] & (INTER_TAB_SIZE2-1) : 0;
3906 3907 3908 3909 3910 3911 3912 3913
                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++ )
            {
3914
                int fxy = src2 ? src2[x] & (INTER_TAB_SIZE2-1): 0;
3915 3916 3917 3918 3919 3920 3921 3922 3923
                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" );
    }
}

3924

3925 3926 3927
namespace cv
{

3928
class warpAffineInvoker :
3929 3930 3931
    public ParallelLoopBody
{
public:
3932
    warpAffineInvoker(const Mat &_src, Mat &_dst, int _interpolation, int _borderType,
3933 3934 3935 3936 3937 3938
                      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)
    {
    }
3939

3940 3941 3942 3943 3944
    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);
3945
        const int AB_SCALE = 1 << AB_BITS;
3946 3947 3948 3949
        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
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 3987 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
        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)));
                        }
                    }
                }
4028

4029 4030 4031 4032 4033 4034 4035 4036 4037 4038
                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 );
                }
            }
        }
    }
4039

4040
private:
4041
    Mat src;
4042 4043
    Mat dst;
    int interpolation, borderType;
4044
    Scalar borderValue;
4045 4046 4047
    int *adelta, *bdelta;
    double *M;
};
4048

4049 4050 4051 4052 4053
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
class IPPwarpAffineInvoker :
    public ParallelLoopBody
{
public:
V
vbystricky 已提交
4054
    IPPwarpAffineInvoker(Mat &_src, Mat &_dst, double (&_coeffs)[2][3], int &_interpolation, int &_borderType, const Scalar &_borderValue, ippicviWarpAffineBackFunc _func, bool *_ok) :
4055 4056 4057 4058 4059
      ParallelLoopBody(), src(_src), dst(_dst), mode(_interpolation), coeffs(_coeffs), borderType(_borderType), borderValue(_borderValue), func(_func), ok(_ok)
      {
          *ok = true;
      }

V
vbystricky 已提交
4060 4061 4062 4063 4064 4065 4066 4067 4068 4069 4070 4071 4072 4073 4074 4075 4076 4077 4078
    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;
    }
4079 4080 4081 4082 4083 4084 4085
private:
    Mat &src;
    Mat &dst;
    double (&coeffs)[2][3];
    int mode;
    int borderType;
    Scalar borderValue;
V
vbystricky 已提交
4086
    ippicviWarpAffineBackFunc func;
4087 4088 4089 4090 4091
    bool *ok;
    const IPPwarpAffineInvoker& operator= (const IPPwarpAffineInvoker&);
};
#endif

I
Ilya Lavrenov 已提交
4092 4093
#ifdef HAVE_OPENCL

I
Ilya Lavrenov 已提交
4094 4095 4096 4097 4098 4099 4100 4101
enum { OCL_OP_PERSPECTIVE = 1, OCL_OP_AFFINE = 0 };

static bool ocl_warpTransform(InputArray _src, OutputArray _dst, InputArray _M0,
                              Size dsize, int flags, int borderType, const Scalar& borderValue,
                              int op_type)
{
    CV_Assert(op_type == OCL_OP_AFFINE || op_type == OCL_OP_PERSPECTIVE);

4102
    int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
I
Ilya Lavrenov 已提交
4103 4104 4105 4106 4107 4108 4109 4110
    double doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;

    int interpolation = flags & INTER_MAX;
    if( interpolation == INTER_AREA )
        interpolation = INTER_LINEAR;

    if ( !(borderType == cv::BORDER_CONSTANT &&
           (interpolation == cv::INTER_NEAREST || interpolation == cv::INTER_LINEAR || interpolation == cv::INTER_CUBIC)) ||
4111
         (!doubleSupport && depth == CV_64F) || cn > 4)
I
Ilya Lavrenov 已提交
4112 4113
        return false;

I
Ilya Lavrenov 已提交
4114
    const char * const interpolationMap[3] = { "NEAREST", "LINEAR", "CUBIC" };
I
Ilya Lavrenov 已提交
4115
    ocl::ProgramSource program = op_type == OCL_OP_AFFINE ?
I
Ilya Lavrenov 已提交
4116 4117 4118
                ocl::imgproc::warp_affine_oclsrc : ocl::imgproc::warp_perspective_oclsrc;
    const char * const kernelName = op_type == OCL_OP_AFFINE ? "warpAffine" : "warpPerspective";

4119 4120 4121 4122
    int scalarcn = cn == 3 ? 4 : cn;
    int wdepth = interpolation == INTER_NEAREST ? depth : std::max(CV_32S, depth);
    int sctype = CV_MAKETYPE(wdepth, scalarcn);

I
Ilya Lavrenov 已提交
4123
    ocl::Kernel k;
4124
    String opts;
I
Ilya Lavrenov 已提交
4125 4126
    if (interpolation == INTER_NEAREST)
    {
4127 4128 4129 4130 4131
        opts = format("-D INTER_NEAREST -D T=%s%s -D T1=%s -D ST=%s -D cn=%d", ocl::typeToStr(type),
                      doubleSupport ? " -D DOUBLE_SUPPORT" : "",
                      ocl::typeToStr(CV_MAT_DEPTH(type)),
                      ocl::typeToStr(sctype),
                      cn);
I
Ilya Lavrenov 已提交
4132 4133 4134 4135
    }
    else
    {
        char cvt[2][50];
4136
        opts = format("-D INTER_%s -D T=%s -D T1=%s -D ST=%s -D WT=%s -D depth=%d -D convertToWT=%s -D convertToT=%s%s -D cn=%d",
4137 4138 4139 4140 4141 4142 4143
                      interpolationMap[interpolation], ocl::typeToStr(type),
                      ocl::typeToStr(CV_MAT_DEPTH(type)),
                      ocl::typeToStr(sctype),
                      ocl::typeToStr(CV_MAKE_TYPE(wdepth, cn)), depth,
                      ocl::convertTypeStr(depth, wdepth, cn, cvt[0]),
                      ocl::convertTypeStr(wdepth, depth, cn, cvt[1]),
                      doubleSupport ? " -D DOUBLE_SUPPORT" : "", cn);
I
Ilya Lavrenov 已提交
4144
    }
4145 4146

    k.create(kernelName, program, opts);
I
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4147 4148 4149
    if (k.empty())
        return false;

4150 4151 4152
    double borderBuf[] = {0, 0, 0, 0};
    scalarToRawData(borderValue, borderBuf, sctype);

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4153 4154 4155 4156 4157 4158 4159 4160 4161 4162 4163 4164 4165 4166 4167 4168 4169 4170 4171 4172 4173 4174 4175 4176 4177 4178 4179 4180 4181
    UMat src = _src.getUMat(), M0;
    _dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
    UMat dst = _dst.getUMat();

    double M[9];
    int matRows = (op_type == OCL_OP_AFFINE ? 2 : 3);
    Mat matM(matRows, 3, CV_64F, M), M1 = _M0.getMat();
    CV_Assert( (M1.type() == CV_32F || M1.type() == CV_64F) &&
               M1.rows == matRows && M1.cols == 3 );
    M1.convertTo(matM, matM.type());

    if( !(flags & WARP_INVERSE_MAP) )
    {
        if (op_type == OCL_OP_PERSPECTIVE)
            invert(matM, matM);
        else
        {
            double D = M[0]*M[4] - M[1]*M[3];
            D = D != 0 ? 1./D : 0;
            double A11 = M[4]*D, A22=M[0]*D;
            M[0] = A11; M[1] *= -D;
            M[3] *= -D; M[4] = A22;
            double b1 = -M[0]*M[2] - M[1]*M[5];
            double b2 = -M[3]*M[2] - M[4]*M[5];
            M[2] = b1; M[5] = b2;
        }
    }
    matM.convertTo(M0, doubleSupport ? CV_64F : CV_32F);

I
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4182
    k.args(ocl::KernelArg::ReadOnly(src), ocl::KernelArg::WriteOnly(dst), ocl::KernelArg::PtrReadOnly(M0),
I
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4183
           ocl::KernelArg(0, 0, 0, 0, borderBuf, CV_ELEM_SIZE(sctype)));
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4184 4185 4186 4187 4188

    size_t globalThreads[2] = { dst.cols, dst.rows };
    return k.run(2, globalThreads, NULL, false);
}

I
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4189 4190
#endif

4191
}
4192 4193


4194 4195
void cv::warpAffine( InputArray _src, OutputArray _dst,
                     InputArray _M0, Size dsize,
4196
                     int flags, int borderType, const Scalar& borderValue )
4197
{
I
Ilya Lavrenov 已提交
4198 4199 4200
    CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
               ocl_warpTransform(_src, _dst, _M0, dsize, flags, borderType,
                                 borderValue, OCL_OP_AFFINE))
I
Ilya Lavrenov 已提交
4201

4202
    Mat src = _src.getMat(), M0 = _M0.getMat();
4203
    _dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
4204
    Mat dst = _dst.getMat();
4205 4206 4207
    CV_Assert( src.cols > 0 && src.rows > 0 );
    if( dst.data == src.data )
        src = src.clone();
4208 4209 4210 4211 4212 4213 4214 4215 4216 4217

    double M[6];
    Mat matM(2, 3, CV_64F, M);
    int interpolation = flags & INTER_MAX;
    if( interpolation == INTER_AREA )
        interpolation = INTER_LINEAR;

    CV_Assert( (M0.type() == CV_32F || M0.type() == CV_64F) && M0.rows == 2 && M0.cols == 3 );
    M0.convertTo(matM, matM.type());

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Andrey Kamaev 已提交
4218 4219 4220 4221 4222
#ifdef HAVE_TEGRA_OPTIMIZATION
    if( tegra::warpAffine(src, dst, M, flags, borderType, borderValue) )
        return;
#endif

4223 4224 4225 4226 4227 4228 4229 4230 4231 4232 4233 4234
    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;
    }

4235 4236 4237
    int x;
    AutoBuffer<int> _abdelta(dst.cols*2);
    int* adelta = &_abdelta[0], *bdelta = adelta + dst.cols;
4238 4239
    const int AB_BITS = MAX(10, (int)INTER_BITS);
    const int AB_SCALE = 1 << AB_BITS;
4240
/*
4241 4242 4243
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
    int depth = src.depth();
    int channels = src.channels();
4244 4245
    if( ( depth == CV_8U || depth == CV_16U || depth == CV_32F ) &&
        ( channels == 1 || channels == 3 || channels == 4 ) &&
4246 4247 4248
        ( borderType == cv::BORDER_TRANSPARENT || ( borderType == cv::BORDER_CONSTANT ) ) )
    {
        int type = src.type();
V
vbystricky 已提交
4249 4250 4251 4252 4253 4254 4255 4256 4257 4258
        ippicviWarpAffineBackFunc ippFunc =
            type == CV_8UC1 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_8u_C1R :
            type == CV_8UC3 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_8u_C3R :
            type == CV_8UC4 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_8u_C4R :
            type == CV_16UC1 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_16u_C1R :
            type == CV_16UC3 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_16u_C3R :
            type == CV_16UC4 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_16u_C4R :
            type == CV_32FC1 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_32f_C1R :
            type == CV_32FC3 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_32f_C3R :
            type == CV_32FC4 ? (ippicviWarpAffineBackFunc)ippicviWarpAffineBack_32f_C4R :
4259
            0;
4260
        int mode =
4261 4262
            flags == INTER_LINEAR ? IPPI_INTER_LINEAR :
            flags == INTER_NEAREST ? IPPI_INTER_NN :
4263
            flags == INTER_CUBIC ? IPPI_INTER_CUBIC :
4264 4265 4266 4267 4268 4269 4270 4271 4272 4273 4274 4275 4276 4277 4278 4279 4280 4281 4282 4283
            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
4284
*/
4285
    for( x = 0; x < dst.cols; x++ )
4286 4287 4288 4289 4290
    {
        adelta[x] = saturate_cast<int>(M[0]*x*AB_SCALE);
        bdelta[x] = saturate_cast<int>(M[3]*x*AB_SCALE);
    }

4291 4292 4293
    Range range(0, dst.rows);
    warpAffineInvoker invoker(src, dst, interpolation, borderType,
                              borderValue, adelta, bdelta, M);
4294
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
4295
}
4296 4297


4298 4299
namespace cv
{
4300

4301 4302 4303 4304
class warpPerspectiveInvoker :
    public ParallelLoopBody
{
public:
4305

4306 4307 4308 4309 4310 4311
    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)
    {
    }
4312

4313 4314 4315 4316 4317
    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;
4318

4319 4320 4321
        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);
4322

4323 4324 4325
        for( y = range.start; y < range.end; y += bh0 )
        {
            for( x = 0; x < width; x += bw0 )
4326
            {
4327 4328
                int bw = std::min( bw0, width - x);
                int bh = std::min( bh0, range.end - y); // height
4329

4330 4331
                Mat _XY(bh, bw, CV_16SC2, XY), matA;
                Mat dpart(dst, Rect(x, y, bw, bh));
4332

4333
                for( y1 = 0; y1 < bh; y1++ )
4334
                {
4335 4336 4337 4338
                    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];
4339

4340 4341
                    if( interpolation == INTER_NEAREST )
                        for( x1 = 0; x1 < bw; x1++ )
4342
                        {
4343 4344 4345 4346 4347 4348
                            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);
4349

4350 4351
                            xy[x1*2] = saturate_cast<short>(X);
                            xy[x1*2+1] = saturate_cast<short>(Y);
4352
                        }
4353
                    else
4354
                    {
4355 4356 4357 4358 4359 4360 4361 4362 4363
                        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);
4364

4365 4366 4367 4368 4369
                            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)));
                        }
4370 4371
                    }
                }
4372

4373 4374 4375 4376 4377 4378 4379
                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 );
                }
4380 4381 4382
            }
        }
    }
4383

4384
private:
4385
    Mat src;
4386 4387 4388
    Mat dst;
    double* M;
    int interpolation, borderType;
4389
    Scalar borderValue;
4390
};
4391

4392 4393 4394 4395 4396
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
class IPPwarpPerspectiveInvoker :
    public ParallelLoopBody
{
public:
V
vbystricky 已提交
4397
    IPPwarpPerspectiveInvoker(Mat &_src, Mat &_dst, double (&_coeffs)[3][3], int &_interpolation, int &_borderType, const Scalar &_borderValue, ippicviWarpPerspectiveBackFunc _func, bool *_ok) :
4398 4399 4400 4401 4402
      ParallelLoopBody(), src(_src), dst(_dst), mode(_interpolation), coeffs(_coeffs), borderType(_borderType), borderValue(_borderValue), func(_func), ok(_ok)
      {
          *ok = true;
      }

V
vbystricky 已提交
4403 4404 4405 4406 4407 4408 4409 4410 4411 4412 4413 4414 4415 4416 4417 4418 4419 4420 4421 4422
    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;
    }
4423 4424 4425 4426 4427 4428 4429
private:
    Mat &src;
    Mat &dst;
    double (&coeffs)[3][3];
    int mode;
    int borderType;
    const Scalar borderValue;
V
vbystricky 已提交
4430
    ippicviWarpPerspectiveBackFunc func;
4431 4432 4433 4434 4435
    bool *ok;
    const IPPwarpPerspectiveInvoker& operator= (const IPPwarpPerspectiveInvoker&);
};
#endif

4436 4437
}

4438
void cv::warpPerspective( InputArray _src, OutputArray _dst, InputArray _M0,
4439
                          Size dsize, int flags, int borderType, const Scalar& borderValue )
4440
{
I
Ilya Lavrenov 已提交
4441 4442
    CV_Assert( _src.total() > 0 );

I
Ilya Lavrenov 已提交
4443 4444
    CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
               ocl_warpTransform(_src, _dst, _M0, dsize, flags, borderType, borderValue,
I
Ilya Lavrenov 已提交
4445
                              OCL_OP_PERSPECTIVE))
I
Ilya Lavrenov 已提交
4446

4447
    Mat src = _src.getMat(), M0 = _M0.getMat();
4448
    _dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
4449
    Mat dst = _dst.getMat();
M
Marina Kolpakova 已提交
4450

4451 4452
    if( dst.data == src.data )
        src = src.clone();
4453 4454 4455 4456 4457 4458 4459 4460 4461 4462

    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());

4463
#ifdef HAVE_TEGRA_OPTIMIZATION
A
Andrey Kamaev 已提交
4464
    if( tegra::warpPerspective(src, dst, M, flags, borderType, borderValue) )
4465 4466 4467
        return;
#endif

A
Andrey Kamaev 已提交
4468 4469
    if( !(flags & WARP_INVERSE_MAP) )
         invert(matM, matM);
4470
/*
4471 4472 4473
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
    int depth = src.depth();
    int channels = src.channels();
4474 4475
    if( ( depth == CV_8U || depth == CV_16U || depth == CV_32F ) &&
        ( channels == 1 || channels == 3 || channels == 4 ) &&
4476 4477 4478
        ( borderType == cv::BORDER_TRANSPARENT || borderType == cv::BORDER_CONSTANT ) )
    {
        int type = src.type();
V
vbystricky 已提交
4479 4480 4481 4482 4483 4484 4485 4486 4487 4488
        ippicviWarpPerspectiveBackFunc ippFunc =
            type == CV_8UC1 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_8u_C1R :
            type == CV_8UC3 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_8u_C3R :
            type == CV_8UC4 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_8u_C4R :
            type == CV_16UC1 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_16u_C1R :
            type == CV_16UC3 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_16u_C3R :
            type == CV_16UC4 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_16u_C4R :
            type == CV_32FC1 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_32f_C1R :
            type == CV_32FC3 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_32f_C3R :
            type == CV_32FC4 ? (ippicviWarpPerspectiveBackFunc)ippicviWarpPerspectiveBack_32f_C4R :
4489
            0;
4490
        int mode =
4491 4492
            flags == INTER_LINEAR ? IPPI_INTER_LINEAR :
            flags == INTER_NEAREST ? IPPI_INTER_NN :
4493
            flags == INTER_CUBIC ? IPPI_INTER_CUBIC :
4494 4495 4496 4497 4498 4499 4500 4501 4502 4503 4504 4505 4506 4507 4508 4509 4510 4511 4512 4513
            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
4514
*/
4515 4516
    Range range(0, dst.rows);
    warpPerspectiveInvoker invoker(src, dst, M, interpolation, borderType, borderValue);
4517
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
4518 4519 4520
}


4521
cv::Mat cv::getRotationMatrix2D( Point2f center, double angle, double scale )
4522 4523 4524 4525 4526 4527 4528 4529 4530 4531 4532 4533 4534 4535 4536 4537 4538 4539 4540 4541 4542 4543 4544 4545 4546 4547 4548 4549 4550 4551 4552 4553 4554 4555 4556 4557 4558 4559 4560 4561 4562 4563
{
    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
 */
4564
cv::Mat cv::getPerspectiveTransform( const Point2f src[], const Point2f dst[] )
4565 4566 4567 4568 4569 4570 4571 4572 4573 4574 4575 4576 4577 4578 4579 4580 4581 4582 4583 4584 4585 4586 4587 4588 4589 4590 4591 4592 4593 4594 4595 4596 4597 4598 4599 4600 4601 4602 4603 4604 4605 4606 4607 4608
{
    Mat M(3, 3, CV_64F), X(8, 1, CV_64F, M.data);
    double a[8][8], b[8];
    Mat A(8, 8, CV_64F, a), B(8, 1, CV_64F, b);

    for( int i = 0; i < 4; ++i )
    {
        a[i][0] = a[i+4][3] = src[i].x;
        a[i][1] = a[i+4][4] = src[i].y;
        a[i][2] = a[i+4][5] = 1;
        a[i][3] = a[i][4] = a[i][5] =
        a[i+4][0] = a[i+4][1] = a[i+4][2] = 0;
        a[i][6] = -src[i].x*dst[i].x;
        a[i][7] = -src[i].y*dst[i].x;
        a[i+4][6] = -src[i].x*dst[i].y;
        a[i+4][7] = -src[i].y*dst[i].y;
        b[i] = dst[i].x;
        b[i+4] = dst[i].y;
    }

    solve( A, B, X, DECOMP_SVD );
    ((double*)M.data)[8] = 1.;

    return M;
}

/* Calculates coefficients of affine transformation
 * which maps (xi,yi) to (ui,vi), (i=1,2,3):
 *
 * ui = c00*xi + c01*yi + c02
 *
 * vi = c10*xi + c11*yi + c12
 *
 * Coefficients are calculated by solving linear system:
 * / x0 y0  1  0  0  0 \ /c00\ /u0\
 * | x1 y1  1  0  0  0 | |c01| |u1|
 * | x2 y2  1  0  0  0 | |c02| |u2|
 * |  0  0  0 x0 y0  1 | |c10| |v0|
 * |  0  0  0 x1 y1  1 | |c11| |v1|
 * \  0  0  0 x2 y2  1 / |c12| |v2|
 *
 * where:
 *   cij - matrix coefficients
 */
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Kirill Kornyakov 已提交
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4610
cv::Mat cv::getAffineTransform( const Point2f src[], const Point2f dst[] )
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{
    Mat M(2, 3, CV_64F), X(6, 1, CV_64F, M.data);
    double a[6*6], b[6];
    Mat A(6, 6, CV_64F, a), B(6, 1, CV_64F, b);

    for( int i = 0; i < 3; i++ )
    {
        int j = i*12;
        int k = i*12+6;
        a[j] = a[k+3] = src[i].x;
        a[j+1] = a[k+4] = src[i].y;
        a[j+2] = a[k+5] = 1;
        a[j+3] = a[j+4] = a[j+5] = 0;
        a[k] = a[k+1] = a[k+2] = 0;
        b[i*2] = dst[i].x;
        b[i*2+1] = dst[i].y;
    }

    solve( A, B, X );
    return M;
}
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Marina Kolpakova 已提交
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4633
void cv::invertAffineTransform(InputArray _matM, OutputArray __iM)
4634
{
4635
    Mat matM = _matM.getMat();
4636
    CV_Assert(matM.rows == 2 && matM.cols == 3);
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    __iM.create(2, 3, matM.type());
    Mat _iM = __iM.getMat();
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Marina Kolpakova 已提交
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    if( matM.type() == CV_32F )
    {
        const float* M = (const float*)matM.data;
        float* iM = (float*)_iM.data;
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        int step = (int)(matM.step/sizeof(M[0])), istep = (int)(_iM.step/sizeof(iM[0]));
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Marina Kolpakova 已提交
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        double D = M[0]*M[step+1] - M[1]*M[step];
        D = D != 0 ? 1./D : 0;
        double A11 = M[step+1]*D, A22 = M[0]*D, A12 = -M[1]*D, A21 = -M[step]*D;
        double b1 = -A11*M[2] - A12*M[step+2];
        double b2 = -A21*M[2] - A22*M[step+2];
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Marina Kolpakova 已提交
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        iM[0] = (float)A11; iM[1] = (float)A12; iM[2] = (float)b1;
        iM[istep] = (float)A21; iM[istep+1] = (float)A22; iM[istep+2] = (float)b2;
    }
    else if( matM.type() == CV_64F )
    {
        const double* M = (const double*)matM.data;
        double* iM = (double*)_iM.data;
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        int step = (int)(matM.step/sizeof(M[0])), istep = (int)(_iM.step/sizeof(iM[0]));
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        double D = M[0]*M[step+1] - M[1]*M[step];
        D = D != 0 ? 1./D : 0;
        double A11 = M[step+1]*D, A22 = M[0]*D, A12 = -M[1]*D, A21 = -M[step]*D;
        double b1 = -A11*M[2] - A12*M[step+2];
        double b2 = -A21*M[2] - A22*M[step+2];
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Marina Kolpakova 已提交
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        iM[0] = A11; iM[1] = A12; iM[2] = b1;
        iM[istep] = A21; iM[istep+1] = A22; iM[istep+2] = b2;
    }
    else
        CV_Error( CV_StsUnsupportedFormat, "" );
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Marina Kolpakova 已提交
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}
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cv::Mat cv::getPerspectiveTransform(InputArray _src, InputArray _dst)
{
    Mat src = _src.getMat(), dst = _dst.getMat();
    CV_Assert(src.checkVector(2, CV_32F) == 4 && dst.checkVector(2, CV_32F) == 4);
    return getPerspectiveTransform((const Point2f*)src.data, (const Point2f*)dst.data);
}

cv::Mat cv::getAffineTransform(InputArray _src, InputArray _dst)
{
    Mat src = _src.getMat(), dst = _dst.getMat();
    CV_Assert(src.checkVector(2, CV_32F) == 3 && dst.checkVector(2, CV_32F) == 3);
    return getAffineTransform((const Point2f*)src.data, (const Point2f*)dst.data);
}

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CV_IMPL void
cvResize( const CvArr* srcarr, CvArr* dstarr, int method )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
    CV_Assert( src.type() == dst.type() );
    cv::resize( src, dst, dst.size(), (double)dst.cols/src.cols,
        (double)dst.rows/src.rows, method );
}


CV_IMPL void
cvWarpAffine( const CvArr* srcarr, CvArr* dstarr, const CvMat* marr,
              int flags, CvScalar fillval )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
    cv::Mat matrix = cv::cvarrToMat(marr);
    CV_Assert( src.type() == dst.type() );
    cv::warpAffine( src, dst, matrix, dst.size(), flags,
        (flags & CV_WARP_FILL_OUTLIERS) ? cv::BORDER_CONSTANT : cv::BORDER_TRANSPARENT,
        fillval );
}

CV_IMPL void
cvWarpPerspective( const CvArr* srcarr, CvArr* dstarr, const CvMat* marr,
                   int flags, CvScalar fillval )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
    cv::Mat matrix = cv::cvarrToMat(marr);
    CV_Assert( src.type() == dst.type() );
    cv::warpPerspective( src, dst, matrix, dst.size(), flags,
        (flags & CV_WARP_FILL_OUTLIERS) ? cv::BORDER_CONSTANT : cv::BORDER_TRANSPARENT,
        fillval );
}

CV_IMPL void
cvRemap( const CvArr* srcarr, CvArr* dstarr,
         const CvArr* _mapx, const CvArr* _mapy,
         int flags, CvScalar fillval )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), dst0 = dst;
    cv::Mat mapx = cv::cvarrToMat(_mapx), mapy = cv::cvarrToMat(_mapy);
    CV_Assert( src.type() == dst.type() && dst.size() == mapx.size() );
    cv::remap( src, dst, mapx, mapy, flags & cv::INTER_MAX,
        (flags & CV_WARP_FILL_OUTLIERS) ? cv::BORDER_CONSTANT : cv::BORDER_TRANSPARENT,
        fillval );
    CV_Assert( dst0.data == dst.data );
}


CV_IMPL CvMat*
cv2DRotationMatrix( CvPoint2D32f center, double angle,
                    double scale, CvMat* matrix )
{
    cv::Mat M0 = cv::cvarrToMat(matrix), M = cv::getRotationMatrix2D(center, angle, scale);
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    CV_Assert( M.size() == M0.size() );
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    M.convertTo(M0, M0.type());
    return matrix;
}


CV_IMPL CvMat*
cvGetPerspectiveTransform( const CvPoint2D32f* src,
                          const CvPoint2D32f* dst,
                          CvMat* matrix )
{
    cv::Mat M0 = cv::cvarrToMat(matrix),
        M = cv::getPerspectiveTransform((const cv::Point2f*)src, (const cv::Point2f*)dst);
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    CV_Assert( M.size() == M0.size() );
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    M.convertTo(M0, M0.type());
    return matrix;
}


CV_IMPL CvMat*
cvGetAffineTransform( const CvPoint2D32f* src,
                          const CvPoint2D32f* dst,
                          CvMat* matrix )
{
    cv::Mat M0 = cv::cvarrToMat(matrix),
        M = cv::getAffineTransform((const cv::Point2f*)src, (const cv::Point2f*)dst);
    CV_Assert( M.size() == M0.size() );
    M.convertTo(M0, M0.type());
    return matrix;
}


CV_IMPL void
cvConvertMaps( const CvArr* arr1, const CvArr* arr2, CvArr* dstarr1, CvArr* dstarr2 )
{
    cv::Mat map1 = cv::cvarrToMat(arr1), map2;
    cv::Mat dstmap1 = cv::cvarrToMat(dstarr1), dstmap2;

    if( arr2 )
        map2 = cv::cvarrToMat(arr2);
    if( dstarr2 )
    {
        dstmap2 = cv::cvarrToMat(dstarr2);
        if( dstmap2.type() == CV_16SC1 )
            dstmap2 = cv::Mat(dstmap2.size(), CV_16UC1, dstmap2.data, dstmap2.step);
    }

    cv::convertMaps( map1, map2, dstmap1, dstmap2, dstmap1.type(), false );
}

/****************************************************************************************\
*                                   Log-Polar Transform                                  *
\****************************************************************************************/

/* now it is done via Remap; more correct implementation should use
   some super-sampling technique outside of the "fovea" circle */
CV_IMPL void
cvLogPolar( const CvArr* srcarr, CvArr* dstarr,
            CvPoint2D32f center, double M, int flags )
{
    cv::Ptr<CvMat> mapx, mapy;

    CvMat srcstub, *src = cvGetMat(srcarr, &srcstub);
    CvMat dststub, *dst = cvGetMat(dstarr, &dststub);
    CvSize ssize, dsize;

    if( !CV_ARE_TYPES_EQ( src, dst ))
        CV_Error( CV_StsUnmatchedFormats, "" );

    if( M <= 0 )
        CV_Error( CV_StsOutOfRange, "M should be >0" );

    ssize = cvGetMatSize(src);
    dsize = cvGetMatSize(dst);

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Roman Donchenko 已提交
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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;
        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) );
}

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void cv::logPolar( InputArray _src, OutputArray _dst,
                   Point2f center, double M, int flags )
{
    Mat src = _src.getMat();
    _dst.create( src.size(), src.type() );
    CvMat c_src = src, c_dst = _dst.getMat();
    cvLogPolar( &c_src, &c_dst, center, M, flags );
}
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/****************************************************************************************
                                   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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Marina Kolpakova 已提交
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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) );
}

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void cv::linearPolar( InputArray _src, OutputArray _dst,
                      Point2f center, double maxRadius, int flags )
{
    Mat src = _src.getMat();
    _dst.create( src.size(), src.type() );
    CvMat c_src = src, c_dst = _dst.getMat();
    cvLinearPolar( &c_src, &c_dst, center, maxRadius, flags );
}
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/* End of file. */