imgwarp.cpp 149.6 KB
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
//  By downloading, copying, installing or using the software you agree to this license.
//  If you do not agree to this license, do not download, install,
//  copy or use the software.
//
//
//                           License Agreement
//                For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
//   * Redistribution's of source code must retain the above copyright notice,
//     this list of conditions and the following disclaimer.
//
//   * Redistribution's in binary form must reproduce the above copyright notice,
//     this list of conditions and the following disclaimer in the documentation
//     and/or other materials provided with the distribution.
//
//   * The name of the copyright holders may not be used to endorse or promote products
//     derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/

/* ////////////////////////////////////////////////////////////////////
//
//  Geometrical transforms on images and matrices: rotation, zoom etc.
//
// */

#include "precomp.hpp"
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#include <iostream>
#include <vector>
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namespace cv
{

/************** 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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Marina Kolpakova 已提交
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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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Victoria Zhislina 已提交
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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;

1140 1141 1142 1143 1144 1145 1146 1147
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;
1148

1149 1150 1151 1152 1153 1154 1155 1156
    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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1158 1159 1160 1161 1162
    virtual void operator() (const Range& range) const
    {
        int dy, cn = src.channels();
        HResize hresize;
        VResize vresize;
1163

1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174
        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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1176
        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 );
        }
    }
1206

1207
private:
1208
    Mat src;
1209 1210 1211
    Mat dst;
    const int* xofs, *yofs;
    const AT* alpha, *_beta;
1212 1213
    Size ssize, dsize;
    int ksize, xmin, xmax;
1214 1215
};

1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232
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::value_type T;
    typedef typename HResize::buf_type WT;
    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;
1233
    // image resize is a separable operation. In case of not too strong
1234

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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);
1238
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
1239
}
1240

1241 1242 1243
template <typename T, typename WT>
struct ResizeAreaFastNoVec
{
1244 1245 1246 1247
    ResizeAreaFastNoVec(int, int) { }
    ResizeAreaFastNoVec(int, int, int, int) { }
    int operator() (const T*, T*, int) const
    { return 0; }
1248
};
1249

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#if CV_SSE2
class ResizeAreaFastVec_SIMD_8u
{
public:
    ResizeAreaFastVec_SIMD_8u(int _cn, int _step) :
        cn(_cn), step(_step)
    {
        use_simd = checkHardwareSupport(CV_CPU_SSE2);
    }

    int operator() (const uchar* S, uchar* D, int w) const
    {
        if (!use_simd)
            return 0;

        int dx = 0;
        const uchar* S0 = S;
        const uchar* S1 = S0 + step;
        __m128i zero = _mm_setzero_si128();
1269
        __m128i delta2 = _mm_set1_epi16(2);
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        if (cn == 1)
        {
1273
            __m128i masklow = _mm_set1_epi16(0x00ff);
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Ilya Lavrenov 已提交
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            for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
1275
            {
1276 1277
                __m128i r0 = _mm_loadu_si128((const __m128i*)S0);
                __m128i r1 = _mm_loadu_si128((const __m128i*)S1);
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                __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);
1283

1284
                _mm_storel_epi64((__m128i*)D, s0);
1285 1286 1287
            }
        }
        else if (cn == 3)
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            for ( ; dx <= w - 6; dx += 6, S0 += 12, S1 += 12, D += 6)
1289
            {
1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308
                __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);
1309 1310 1311 1312
            }
        else
        {
            CV_Assert(cn == 4);
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Ilya Lavrenov 已提交
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            for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
1314
            {
1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333
                __m128i r0 = _mm_loadu_si128((const __m128i*)S0);
                __m128i r1 = _mm_loadu_si128((const __m128i*)S1);

                __m128i r0_16l = _mm_unpacklo_epi8(r0, zero);
                __m128i r0_16h = _mm_unpackhi_epi8(r0, zero);
                __m128i r1_16l = _mm_unpacklo_epi8(r1, zero);
                __m128i r1_16h = _mm_unpackhi_epi8(r1, zero);

                __m128i s0 = _mm_add_epi16(r0_16l, _mm_srli_si128(r0_16l, 8));
                __m128i s1 = _mm_add_epi16(r1_16l, _mm_srli_si128(r1_16l, 8));
                s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
                s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
                _mm_storel_epi64((__m128i*)D, s0);

                s0 = _mm_add_epi16(r0_16h, _mm_srli_si128(r0_16h, 8));
                s1 = _mm_add_epi16(r1_16h, _mm_srli_si128(r1_16h, 8));
                s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
                s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
                _mm_storel_epi64((__m128i*)(D+4), s0);
1334 1335 1336 1337 1338 1339 1340 1341 1342
            }
        }

        return dx;
    }

private:
    int cn;
    bool use_simd;
1343
    int step;
1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361
};

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;
1362
        const ushort* S1 = (const ushort*)((const uchar*)(S) + step);
1363 1364
        __m128i masklow = _mm_set1_epi32(0x0000ffff);
        __m128i zero = _mm_setzero_si128();
1365
        __m128i delta2 = _mm_set1_epi32(2);
1366

1367 1368
#define _mm_packus_epi32(a, zero) _mm_packs_epi32(_mm_srai_epi32(_mm_slli_epi32(a, 16), 16), zero);

1369 1370
        if (cn == 1)
        {
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            for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
1372
            {
1373 1374
                __m128i r0 = _mm_loadu_si128((const __m128i*)S0);
                __m128i r1 = _mm_loadu_si128((const __m128i*)S1);
1375

1376 1377 1378
                __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);
1379 1380
                s0 = _mm_srli_epi32(s0, 2);
                s0 = _mm_packus_epi32(s0, zero);
1381

1382
                _mm_storel_epi64((__m128i*)D, s0);
1383 1384 1385
            }
        }
        else if (cn == 3)
I
Ilya Lavrenov 已提交
1386
            for ( ; dx <= w - 3; dx += 3, S0 += 6, S1 += 6, D += 3)
1387
            {
1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398
                __m128i r0 = _mm_loadu_si128((const __m128i*)S0);
                __m128i r1 = _mm_loadu_si128((const __m128i*)S1);

                __m128i r0_16l = _mm_unpacklo_epi16(r0, zero);
                __m128i r0_16h = _mm_unpacklo_epi16(_mm_srli_si128(r0, 6), zero);
                __m128i r1_16l = _mm_unpacklo_epi16(r1, zero);
                __m128i r1_16h = _mm_unpacklo_epi16(_mm_srli_si128(r1, 6), zero);

                __m128i s0 = _mm_add_epi16(r0_16l, r0_16h);
                __m128i s1 = _mm_add_epi16(r1_16l, r1_16h);
                s0 = _mm_add_epi32(s1, _mm_add_epi32(s0, delta2));
1399
                s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
1400
                _mm_storel_epi64((__m128i*)D, s0);
1401 1402 1403 1404
            }
        else
        {
            CV_Assert(cn == 4);
I
Ilya Lavrenov 已提交
1405
            for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
1406
            {
1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417
                __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));
1418
                s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
1419
                _mm_storel_epi64((__m128i*)D, s0);
1420 1421 1422 1423 1424 1425 1426 1427 1428 1429 1430 1431 1432 1433 1434 1435 1436 1437
            }
        }

        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>
1438
struct ResizeAreaFastVec
1439
{
1440 1441
    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)
1442 1443
    {
        fast_mode = scale_x == 2 && scale_y == 2 && (cn == 1 || cn == 3 || cn == 4);
1444
    }
1445

1446
    int operator() (const T* S, T* D, int w) const
1447
    {
1448
        if (!fast_mode)
1449
            return 0;
1450

1451
        const T* nextS = (const T*)((const uchar*)S + step);
1452
        int dx = vecOp(S, D, w);
1453

1454
        if (cn == 1)
1455 1456 1457 1458 1459
            for( ; dx < w; ++dx )
            {
                int index = dx*2;
                D[dx] = (T)((S[index] + S[index+1] + nextS[index] + nextS[index+1] + 2) >> 2);
            }
1460
        else if (cn == 3)
1461
            for( ; dx < w; dx += 3 )
1462
            {
1463
                int index = dx*2;
1464 1465 1466 1467 1468 1469
                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
            {
1470
                CV_Assert(cn == 4);
1471 1472 1473 1474 1475 1476 1477 1478
                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);
                }
1479
            }
1480

1481
        return dx;
1482
    }
1483

1484
private:
1485 1486
    int scale_x, scale_y;
    int cn;
1487
    bool fast_mode;
1488
    int step;
1489
    SIMDVecOp vecOp;
1490
};
1491

1492 1493 1494
template <typename T, typename WT, typename VecOp>
class resizeAreaFast_Invoker :
    public ParallelLoopBody
1495
{
1496 1497 1498 1499 1500
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)
1501
    {
1502
    }
1503

1504 1505 1506 1507 1508 1509 1510 1511 1512 1513
    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;
1514

1515
        VecOp vop(scale_x, scale_y, src.channels(), (int)src.step/*, area_ofs*/);
1516

1517
        for( dy = range.start; dy < range.end; dy++ )
1518
        {
1519 1520 1521
            T* D = (T*)(dst.data + dst.step*dy);
            int sy0 = dy*scale_y;
            int w = sy0 + scale_y <= ssize.height ? dwidth1 : 0;
1522

1523 1524 1525 1526 1527 1528
            if( sy0 >= ssize.height )
            {
                for( dx = 0; dx < dsize.width; dx++ )
                    D[dx] = 0;
                continue;
            }
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Marina Kolpakova 已提交
1529

1530 1531 1532 1533 1534 1535 1536 1537 1538 1539 1540 1541
            dx = vop((const T*)(src.data + src.step * sy0), D, w);
            for( ; dx < w; dx++ )
            {
                const T* S = (const T*)(src.data + src.step * sy0) + xofs[dx];
                WT sum = 0;
                k = 0;
                #if CV_ENABLE_UNROLLED
                for( ; k <= area - 4; k += 4 )
                    sum += S[ofs[k]] + S[ofs[k+1]] + S[ofs[k+2]] + S[ofs[k+3]];
                #endif
                for( ; k < area; k++ )
                    sum += S[ofs[k]];
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Marina Kolpakova 已提交
1542

1543 1544
                D[dx] = saturate_cast<T>(sum * scale);
            }
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1545

1546
            for( ; dx < dsize.width; dx++ )
1547
            {
1548 1549 1550 1551 1552 1553
                WT sum = 0;
                int count = 0, sx0 = xofs[dx];
                if( sx0 >= ssize.width )
                    D[dx] = 0;

                for( int sy = 0; sy < scale_y; sy++ )
1554
                {
1555
                    if( sy0 + sy >= ssize.height )
1556
                        break;
1557 1558 1559 1560 1561 1562 1563 1564
                    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++;
                    }
1565
                }
M
Marina Kolpakova 已提交
1566

1567
                D[dx] = saturate_cast<T>((float)sum/count);
1568
            }
1569
        }
1570
    }
1571

1572
private:
1573
    Mat src;
1574
    Mat dst;
1575
    int scale_x, scale_y;
1576 1577 1578 1579 1580 1581 1582 1583
    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);
1584
    resizeAreaFast_Invoker<T, WT, VecOp> invoker(src, dst, scale_x,
1585
        scale_y, ofs, xofs);
1586
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
1587 1588 1589 1590 1591 1592 1593 1594
}

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

V
Vadim Pisarevsky 已提交
1595 1596

template<typename T, typename WT> class ResizeArea_Invoker :
1597
    public ParallelLoopBody
1598
{
1599
public:
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1600 1601 1602 1603
    ResizeArea_Invoker( const Mat& _src, Mat& _dst,
                        const DecimateAlpha* _xtab, int _xtab_size,
                        const DecimateAlpha* _ytab, int _ytab_size,
                        const int* _tabofs )
1604
    {
V
Vadim Pisarevsky 已提交
1605 1606 1607 1608 1609 1610 1611
        src = &_src;
        dst = &_dst;
        xtab0 = _xtab;
        xtab_size0 = _xtab_size;
        ytab = _ytab;
        ytab_size = _ytab_size;
        tabofs = _tabofs;
1612
    }
1613

V
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1614
    virtual void operator() (const Range& range) const
1615
    {
V
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1616 1617
        Size dsize = dst->size();
        int cn = dst->channels();
1618 1619
        dsize.width *= cn;
        AutoBuffer<WT> _buffer(dsize.width*2);
V
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1620 1621
        const DecimateAlpha* xtab = xtab0;
        int xtab_size = xtab_size0;
1622
        WT *buf = _buffer, *sum = buf + dsize.width;
1623
        int j_start = tabofs[range.start], j_end = tabofs[range.end], j, k, dx, prev_dy = ytab[j_start].di;
1624

I
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Ilya Lavrenov 已提交
1625
        for( dx = 0; dx < dsize.width; dx++ )
V
Vadim Pisarevsky 已提交
1626
            sum[dx] = (WT)0;
1627

V
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1628
        for( j = j_start; j < j_end; j++ )
1629
        {
V
Vadim Pisarevsky 已提交
1630 1631 1632
            WT beta = ytab[j].alpha;
            int dy = ytab[j].di;
            int sy = ytab[j].si;
1633

1634
            {
V
Vadim Pisarevsky 已提交
1635 1636 1637 1638 1639 1640 1641 1642 1643 1644 1645 1646 1647 1648 1649 1650 1651 1652 1653 1654 1655 1656 1657 1658 1659 1660 1661 1662 1663 1664 1665 1666 1667
                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 )
1668
                {
V
Vadim Pisarevsky 已提交
1669
                    for( k = 0; k < xtab_size; k++ )
I
attempt  
Ilya Lavrenov 已提交
1670
                    {
V
Vadim Pisarevsky 已提交
1671 1672 1673 1674 1675 1676 1677 1678 1679
                        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
1680
                    }
1681 1682
                }
                else
V
Vadim Pisarevsky 已提交
1683 1684
                {
                    for( k = 0; k < xtab_size; k++ )
1685
                    {
V
Vadim Pisarevsky 已提交
1686 1687 1688 1689 1690
                        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;
1691
                    }
V
Vadim Pisarevsky 已提交
1692
                }
1693
            }
V
Vadim Pisarevsky 已提交
1694 1695

            if( dy != prev_dy )
1696
            {
V
Vadim Pisarevsky 已提交
1697 1698 1699
                T* D = (T*)(dst->data + dst->step*prev_dy);

                for( dx = 0; dx < dsize.width; dx++ )
I
attempt  
Ilya Lavrenov 已提交
1700
                {
V
Vadim Pisarevsky 已提交
1701 1702
                    D[dx] = saturate_cast<T>(sum[dx]);
                    sum[dx] = beta*buf[dx];
I
attempt  
Ilya Lavrenov 已提交
1703
                }
V
Vadim Pisarevsky 已提交
1704 1705 1706 1707 1708 1709
                prev_dy = dy;
            }
            else
            {
                for( dx = 0; dx < dsize.width; dx++ )
                    sum[dx] += beta*buf[dx];
1710 1711
            }
        }
1712

1713
        {
V
Vadim Pisarevsky 已提交
1714 1715 1716
        T* D = (T*)(dst->data + dst->step*prev_dy);
        for( dx = 0; dx < dsize.width; dx++ )
            D[dx] = saturate_cast<T>(sum[dx]);
1717 1718
        }
    }
1719

1720
private:
V
Vadim Pisarevsky 已提交
1721 1722 1723 1724 1725 1726
    const Mat* src;
    Mat* dst;
    const DecimateAlpha* xtab0;
    const DecimateAlpha* ytab;
    int xtab_size0, ytab_size;
    const int* tabofs;
1727 1728
};

V
Vadim Pisarevsky 已提交
1729

I
attempt  
Ilya Lavrenov 已提交
1730
template <typename T, typename WT>
V
Vadim Pisarevsky 已提交
1731 1732 1733 1734
static void resizeArea_( const Mat& src, Mat& dst,
                         const DecimateAlpha* xtab, int xtab_size,
                         const DecimateAlpha* ytab, int ytab_size,
                         const int* tabofs )
1735
{
V
Vadim Pisarevsky 已提交
1736 1737 1738
    parallel_for_(Range(0, dst.rows),
                 ResizeArea_Invoker<T, WT>(src, dst, xtab, xtab_size, ytab, ytab_size, tabofs),
                 dst.total()/((double)(1 << 16)));
1739
}
1740 1741 1742 1743 1744 1745 1746 1747


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,
1748 1749
                                    const int* ofs, const int *xofs,
                                    int scale_x, int scale_y );
1750 1751

typedef void (*ResizeAreaFunc)( const Mat& src, Mat& dst,
V
Vadim Pisarevsky 已提交
1752 1753 1754 1755 1756 1757 1758
                                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 )
{
1759 1760
    int k = 0;
    for(int dx = 0; dx < dsize; dx++ )
V
Vadim Pisarevsky 已提交
1761
    {
1762
        double fsx1 = dx * scale;
V
Vadim Pisarevsky 已提交
1763
        double fsx2 = fsx1 + scale;
1764 1765
        double cellWidth = min(scale, ssize - fsx1);

V
Vadim Pisarevsky 已提交
1766 1767
        int sx1 = cvCeil(fsx1), sx2 = cvFloor(fsx2);

1768 1769 1770 1771
        sx2 = std::min(sx2, ssize - 1);
        sx1 = std::min(sx1, sx2);

        if( sx1 - fsx1 > 1e-3 )
V
Vadim Pisarevsky 已提交
1772 1773
        {
            assert( k < ssize*2 );
1774 1775 1776
            tab[k].di = dx * cn;
            tab[k].si = (sx1 - 1) * cn;
            tab[k++].alpha = (float)((sx1 - fsx1) / cellWidth);
V
Vadim Pisarevsky 已提交
1777 1778
        }

1779
        for(int sx = sx1; sx < sx2; sx++ )
V
Vadim Pisarevsky 已提交
1780 1781
        {
            assert( k < ssize*2 );
1782 1783 1784
            tab[k].di = dx * cn;
            tab[k].si = sx * cn;
            tab[k++].alpha = float(1.0 / cellWidth);
V
Vadim Pisarevsky 已提交
1785 1786 1787 1788 1789
        }

        if( fsx2 - sx2 > 1e-3 )
        {
            assert( k < ssize*2 );
1790 1791 1792
            tab[k].di = dx * cn;
            tab[k].si = sx2 * cn;
            tab[k++].alpha = (float)(min(min(fsx2 - sx2, 1.), cellWidth) / cellWidth);
V
Vadim Pisarevsky 已提交
1793 1794 1795 1796 1797
        }
    }
    return k;
}

1798

1799
}
M
Marina Kolpakova 已提交
1800

1801

1802 1803
//////////////////////////////////////////////////////////////////////////////////////////

1804
void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
1805
                 double inv_scale_x, double inv_scale_y, int interpolation )
1806 1807 1808 1809 1810 1811
{
    static ResizeFunc linear_tab[] =
    {
        resizeGeneric_<
            HResizeLinear<uchar, int, short,
                INTER_RESIZE_COEF_SCALE,
M
Marina Kolpakova 已提交
1812
                HResizeLinearVec_8u32s>,
1813 1814
            VResizeLinear<uchar, int, short,
                FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
M
Marina Kolpakova 已提交
1815 1816
                VResizeLinearVec_32s8u> >,
        0,
1817 1818 1819 1820 1821 1822 1823 1824 1825 1826
        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> >,
M
Marina Kolpakova 已提交
1827
        0,
1828 1829 1830 1831 1832
        resizeGeneric_<
            HResizeLinear<float, float, float, 1,
                HResizeLinearVec_32f>,
            VResizeLinear<float, float, float, Cast<float, float>,
                VResizeLinearVec_32f> >,
V
Vadim Pisarevsky 已提交
1833 1834 1835 1836 1837 1838
        resizeGeneric_<
            HResizeLinear<double, double, float, 1,
                HResizeNoVec>,
            VResizeLinear<double, double, float, Cast<double, double>,
                VResizeNoVec> >,
        0
1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856
    };

    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> >,
M
Marina Kolpakova 已提交
1857
        0,
1858 1859 1860 1861
        resizeGeneric_<
            HResizeCubic<float, float, float>,
            VResizeCubic<float, float, float, Cast<float, float>,
            VResizeCubicVec_32f> >,
V
Vadim Pisarevsky 已提交
1862 1863 1864 1865 1866
        resizeGeneric_<
            HResizeCubic<double, double, float>,
            VResizeCubic<double, double, float, Cast<double, double>,
            VResizeNoVec> >,
        0
1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878
    };

    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> >,
M
Marina Kolpakova 已提交
1879
        resizeGeneric_<HResizeLanczos4<short, float, float>,
1880 1881
            VResizeLanczos4<short, float, float, Cast<float, short>,
            VResizeNoVec> >,
M
Marina Kolpakova 已提交
1882
        0,
1883 1884 1885
        resizeGeneric_<HResizeLanczos4<float, float, float>,
            VResizeLanczos4<float, float, float, Cast<float, float>,
            VResizeNoVec> >,
V
Vadim Pisarevsky 已提交
1886 1887 1888 1889
        resizeGeneric_<HResizeLanczos4<double, double, float>,
            VResizeLanczos4<double, double, float, Cast<double, double>,
            VResizeNoVec> >,
        0
1890 1891 1892 1893
    };

    static ResizeAreaFastFunc areafast_tab[] =
    {
1894
        resizeAreaFast_<uchar, int, ResizeAreaFastVec<uchar, ResizeAreaFastVec_SIMD_8u> >,
1895
        0,
1896 1897
        resizeAreaFast_<ushort, float, ResizeAreaFastVec<ushort, ResizeAreaFastVec_SIMD_16u> >,
        resizeAreaFast_<short, float, ResizeAreaFastVec<short, ResizeAreaFastNoVec<short, float> > >,
V
Vadim Pisarevsky 已提交
1898
        0,
1899 1900
        resizeAreaFast_<float, float, ResizeAreaFastNoVec<float, float> >,
        resizeAreaFast_<double, double, ResizeAreaFastNoVec<double, double> >,
V
Vadim Pisarevsky 已提交
1901
        0
1902 1903 1904 1905
    };

    static ResizeAreaFunc area_tab[] =
    {
1906
        resizeArea_<uchar, float>, 0, resizeArea_<ushort, float>,
1907 1908
        resizeArea_<short, float>, 0, resizeArea_<float, float>,
        resizeArea_<double, double>, 0
1909 1910
    };

1911
    Mat src = _src.getMat();
1912
    Size ssize = src.size();
M
Marina Kolpakova 已提交
1913

1914
    CV_Assert( ssize.area() > 0 );
1915 1916
    CV_Assert( dsize.area() || (inv_scale_x > 0 && inv_scale_y > 0) );
    if( !dsize.area() )
1917 1918 1919
    {
        dsize = Size(saturate_cast<int>(src.cols*inv_scale_x),
            saturate_cast<int>(src.rows*inv_scale_y));
1920
        CV_Assert( dsize.area() );
1921 1922 1923 1924 1925 1926
    }
    else
    {
        inv_scale_x = (double)dsize.width/src.cols;
        inv_scale_y = (double)dsize.height/src.rows;
    }
1927 1928
    _dst.create(dsize, src.type());
    Mat dst = _dst.getMat();
1929

A
Andrey Kamaev 已提交
1930 1931 1932 1933 1934 1935

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

1936 1937 1938 1939 1940 1941 1942 1943 1944
    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;

    if( interpolation == INTER_NEAREST )
    {
        resizeNN( src, dst, inv_scale_x, inv_scale_y );
        return;
    }
1945

1946 1947 1948
    {
        int iscale_x = saturate_cast<int>(scale_x);
        int iscale_y = saturate_cast<int>(scale_y);
1949

1950 1951
        bool is_area_fast = std::abs(scale_x - iscale_x) < DBL_EPSILON &&
                std::abs(scale_y - iscale_y) < DBL_EPSILON;
1952 1953

        // in case of scale_x && scale_y is equal to 2
1954
        // INTER_AREA (fast) also is equal to INTER_LINEAR
1955
        if( interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 )
1956 1957 1958 1959 1960
            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 )
1961
        {
1962
            if( is_area_fast )
1963
            {
1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
                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);
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                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;
                }
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                func( src, dst, ofs, xofs, iscale_x, iscale_y );
                return;
            }
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            ResizeAreaFunc func = area_tab[depth];
            CV_Assert( func != 0 && cn <= 4 );
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            AutoBuffer<DecimateAlpha> _xytab((ssize.width + ssize.height)*2);
            DecimateAlpha* xtab = _xytab, *ytab = xtab + ssize.width*2;
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            int xtab_size = computeResizeAreaTab(ssize.width, dsize.width, cn, scale_x, xtab);
            int ytab_size = computeResizeAreaTab(ssize.height, dsize.height, 1, scale_y, ytab);
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            AutoBuffer<int> _tabofs(dsize.height + 1);
            int* tabofs = _tabofs;
            for( k = 0, dy = 0; k < ytab_size; k++ )
            {
                if( k == 0 || ytab[k].di != ytab[k-1].di )
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                {
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                    assert( ytab[k].di == dy );
                    tabofs[dy++] = k;
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                }
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            }
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            tabofs[dy] = ytab_size;
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            func( src, dst, xtab, xtab_size, ytab, ytab_size, tabofs );
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            return;
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        }
    }

    int xmin = 0, xmax = dsize.width, width = dsize.width*cn;
    bool area_mode = interpolation == INTER_AREA;
    bool fixpt = depth == CV_8U;
    float fx, fy;
    ResizeFunc func=0;
    int ksize=0, ksize2;
    if( interpolation == INTER_CUBIC )
        ksize = 4, func = cubic_tab[depth];
    else if( interpolation == INTER_LANCZOS4 )
        ksize = 8, func = lanczos4_tab[depth];
    else if( interpolation == INTER_LINEAR || interpolation == INTER_AREA )
        ksize = 2, func = linear_tab[depth];
    else
        CV_Error( CV_StsBadArg, "Unknown interpolation method" );
    ksize2 = ksize/2;

    CV_Assert( func != 0 );

    AutoBuffer<uchar> _buffer((width + dsize.height)*(sizeof(int) + sizeof(float)*ksize));
    int* xofs = (int*)(uchar*)_buffer;
    int* yofs = xofs + width;
    float* alpha = (float*)(yofs + dsize.height);
    short* ialpha = (short*)alpha;
    float* beta = alpha + width*ksize;
    short* ibeta = ialpha + width*ksize;
    float cbuf[MAX_ESIZE];

    for( dx = 0; dx < dsize.width; dx++ )
    {
        if( !area_mode )
        {
            fx = (float)((dx+0.5)*scale_x - 0.5);
            sx = cvFloor(fx);
            fx -= sx;
        }
        else
        {
            sx = cvFloor(dx*scale_x);
            fx = (float)((dx+1) - (sx+1)*inv_scale_x);
            fx = fx <= 0 ? 0.f : fx - cvFloor(fx);
        }

        if( sx < ksize2-1 )
        {
            xmin = dx+1;
            if( sx < 0 )
                fx = 0, sx = 0;
        }

        if( sx + ksize2 >= ssize.width )
        {
            xmax = std::min( xmax, dx );
            if( sx >= ssize.width-1 )
                fx = 0, sx = ssize.width-1;
        }

        for( k = 0, sx *= cn; k < cn; k++ )
            xofs[dx*cn + k] = sx + k;

        if( interpolation == INTER_CUBIC )
            interpolateCubic( fx, cbuf );
        else if( interpolation == INTER_LANCZOS4 )
            interpolateLanczos4( fx, cbuf );
        else
        {
            cbuf[0] = 1.f - fx;
            cbuf[1] = fx;
        }
        if( fixpt )
        {
            for( k = 0; k < ksize; k++ )
                ialpha[dx*cn*ksize + k] = saturate_cast<short>(cbuf[k]*INTER_RESIZE_COEF_SCALE);
            for( ; k < cn*ksize; k++ )
                ialpha[dx*cn*ksize + k] = ialpha[dx*cn*ksize + k - ksize];
        }
        else
        {
            for( k = 0; k < ksize; k++ )
                alpha[dx*cn*ksize + k] = cbuf[k];
            for( ; k < cn*ksize; k++ )
                alpha[dx*cn*ksize + k] = alpha[dx*cn*ksize + k - ksize];
        }
    }

    for( dy = 0; dy < dsize.height; dy++ )
    {
        if( !area_mode )
        {
            fy = (float)((dy+0.5)*scale_y - 0.5);
            sy = cvFloor(fy);
            fy -= sy;
        }
        else
        {
            sy = cvFloor(dy*scale_y);
            fy = (float)((dy+1) - (sy+1)*inv_scale_y);
            fy = fy <= 0 ? 0.f : fy - cvFloor(fy);
        }

        yofs[dy] = sy;
        if( interpolation == INTER_CUBIC )
            interpolateCubic( fy, cbuf );
        else if( interpolation == INTER_LANCZOS4 )
            interpolateLanczos4( fy, cbuf );
        else
        {
            cbuf[0] = 1.f - fy;
            cbuf[1] = fy;
        }

        if( fixpt )
        {
            for( k = 0; k < ksize; k++ )
                ibeta[dy*ksize + k] = saturate_cast<short>(cbuf[k]*INTER_RESIZE_COEF_SCALE);
        }
        else
        {
            for( k = 0; k < ksize; k++ )
                beta[dy*ksize + k] = cbuf[k];
        }
    }

    func( src, dst, xofs, fixpt ? (void*)ialpha : (void*)alpha, yofs,
          fixpt ? (void*)ibeta : (void*)beta, xmin, xmax, ksize );
}


/****************************************************************************************\
*                       General warping (affine, perspective, remap)                     *
\****************************************************************************************/

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namespace cv
{

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template<typename T>
static void remapNearest( const Mat& _src, Mat& _dst, const Mat& _xy,
                          int borderType, const Scalar& _borderValue )
{
    Size ssize = _src.size(), dsize = _dst.size();
    int cn = _src.channels();
    const T* S0 = (const T*)_src.data;
    size_t sstep = _src.step/sizeof(S0[0]);
    Scalar_<T> cval(saturate_cast<T>(_borderValue[0]),
        saturate_cast<T>(_borderValue[1]),
        saturate_cast<T>(_borderValue[2]),
        saturate_cast<T>(_borderValue[3]));
    int dx, dy;

    unsigned width1 = ssize.width, height1 = ssize.height;

    if( _dst.isContinuous() && _xy.isContinuous() )
    {
        dsize.width *= dsize.height;
        dsize.height = 1;
    }

    for( dy = 0; dy < dsize.height; dy++ )
    {
        T* D = (T*)(_dst.data + _dst.step*dy);
        const short* XY = (const short*)(_xy.data + _xy.step*dy);

        if( cn == 1 )
        {
            for( dx = 0; dx < dsize.width; dx++ )
            {
                int sx = XY[dx*2], sy = XY[dx*2+1];
                if( (unsigned)sx < width1 && (unsigned)sy < height1 )
                    D[dx] = S0[sy*sstep + sx];
                else
                {
                    if( borderType == BORDER_REPLICATE )
                    {
                        sx = clip(sx, 0, ssize.width);
                        sy = clip(sy, 0, ssize.height);
                        D[dx] = S0[sy*sstep + sx];
                    }
                    else if( borderType == BORDER_CONSTANT )
                        D[dx] = cval[0];
                    else if( borderType != BORDER_TRANSPARENT )
                    {
                        sx = borderInterpolate(sx, ssize.width, borderType);
                        sy = borderInterpolate(sy, ssize.height, borderType);
                        D[dx] = S0[sy*sstep + sx];
                    }
                }
            }
        }
        else
        {
            for( dx = 0; dx < dsize.width; dx++, D += cn )
            {
                int sx = XY[dx*2], sy = XY[dx*2+1], k;
                const T *S;
                if( (unsigned)sx < width1 && (unsigned)sy < height1 )
                {
                    if( cn == 3 )
                    {
                        S = S0 + sy*sstep + sx*3;
                        D[0] = S[0], D[1] = S[1], D[2] = S[2];
                    }
                    else if( cn == 4 )
                    {
                        S = S0 + sy*sstep + sx*4;
                        D[0] = S[0], D[1] = S[1], D[2] = S[2], D[3] = S[3];
                    }
                    else
                    {
                        S = S0 + sy*sstep + sx*cn;
                        for( k = 0; k < cn; k++ )
                            D[k] = S[k];
                    }
                }
                else if( borderType != BORDER_TRANSPARENT )
                {
                    if( borderType == BORDER_REPLICATE )
                    {
                        sx = clip(sx, 0, ssize.width);
                        sy = clip(sy, 0, ssize.height);
                        S = S0 + sy*sstep + sx*cn;
                    }
                    else if( borderType == BORDER_CONSTANT )
                        S = &cval[0];
                    else
                    {
                        sx = borderInterpolate(sx, ssize.width, borderType);
                        sy = borderInterpolate(sy, ssize.height, borderType);
                        S = S0 + sy*sstep + sx*cn;
                    }
                    for( k = 0; k < cn; k++ )
                        D[k] = S[k];
                }
            }
        }
    }
}


struct RemapNoVec
{
    int operator()( const Mat&, void*, const short*, const ushort*,
                    const void*, int ) const { return 0; }
};

#if CV_SSE2

struct RemapVec_8u
{
    int operator()( const Mat& _src, void* _dst, const short* XY,
                    const ushort* FXY, const void* _wtab, int width ) const
    {
        int cn = _src.channels();

        if( (cn != 1 && cn != 3 && cn != 4) || !checkHardwareSupport(CV_CPU_SSE2) )
            return 0;

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        return x;
    }
};

#else

typedef RemapNoVec RemapVec_8u;

#endif


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

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

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

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

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

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

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

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


template<class CastOp, typename AT, int ONE>
static void remapBicubic( const Mat& _src, Mat& _dst, const Mat& _xy,
                          const Mat& _fxy, const void* _wtab,
                          int borderType, const Scalar& _borderValue )
{
    typedef typename CastOp::rtype T;
    typedef typename CastOp::type1 WT;
    Size ssize = _src.size(), dsize = _dst.size();
    int cn = _src.channels();
    const AT* wtab = (const AT*)_wtab;
    const T* S0 = (const T*)_src.data;
    size_t sstep = _src.step/sizeof(S0[0]);
    Scalar_<T> cval(saturate_cast<T>(_borderValue[0]),
        saturate_cast<T>(_borderValue[1]),
        saturate_cast<T>(_borderValue[2]),
        saturate_cast<T>(_borderValue[3]));
    int dx, dy;
    CastOp castOp;
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    int borderType1 = borderType != BORDER_TRANSPARENT ? borderType : BORDER_REFLECT_101;
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    unsigned width1 = std::max(ssize.width-3, 0), height1 = std::max(ssize.height-3, 0);

    if( _dst.isContinuous() && _xy.isContinuous() && _fxy.isContinuous() )
    {
        dsize.width *= dsize.height;
        dsize.height = 1;
    }

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

        for( dx = 0; dx < dsize.width; dx++, D += cn )
        {
            int sx = XY[dx*2]-1, sy = XY[dx*2+1]-1;
            const AT* w = wtab + FXY[dx]*16;
            int i, k;
            if( (unsigned)sx < width1 && (unsigned)sy < height1 )
            {
                const T* S = S0 + sy*sstep + sx*cn;
                for( k = 0; k < cn; k++ )
                {
                    WT sum = S[0]*w[0] + S[cn]*w[1] + S[cn*2]*w[2] + S[cn*3]*w[3];
                    S += sstep;
                    sum += S[0]*w[4] + S[cn]*w[5] + S[cn*2]*w[6] + S[cn*3]*w[7];
                    S += sstep;
                    sum += S[0]*w[8] + S[cn]*w[9] + S[cn*2]*w[10] + S[cn*3]*w[11];
                    S += sstep;
                    sum += S[0]*w[12] + S[cn]*w[13] + S[cn*2]*w[14] + S[cn*3]*w[15];
                    S += 1 - sstep*3;
                    D[k] = castOp(sum);
                }
            }
            else
            {
                int x[4], y[4];
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                if( borderType == BORDER_TRANSPARENT &&
                    ((unsigned)(sx+1) >= (unsigned)ssize.width ||
                    (unsigned)(sy+1) >= (unsigned)ssize.height) )
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                    continue;

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                if( borderType1 == BORDER_CONSTANT &&
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                    (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++ )
                {
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                    x[i] = borderInterpolate(sx + i, ssize.width, borderType1)*cn;
                    y[i] = borderInterpolate(sy + i, ssize.height, borderType1);
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                }

                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;
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    int borderType1 = borderType != BORDER_TRANSPARENT ? borderType : BORDER_REFLECT_101;
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    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];
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                if( borderType == BORDER_TRANSPARENT &&
                    ((unsigned)(sx+3) >= (unsigned)ssize.width ||
                    (unsigned)(sy+3) >= (unsigned)ssize.height) )
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                    continue;

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                if( borderType1 == BORDER_CONSTANT &&
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                    (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++ )
                {
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                    x[i] = borderInterpolate(sx + i, ssize.width, borderType1)*cn;
                    y[i] = borderInterpolate(sy + i, ssize.height, borderType1);
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                }

                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;
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                        if( yi < 0 )
                            continue;
                        if( x[0] >= 0 )
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                            sum += (S1[x[0]] - cv)*w[0];
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                        if( x[1] >= 0 )
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                            sum += (S1[x[1]] - cv)*w[1];
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                        if( x[2] >= 0 )
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                            sum += (S1[x[2]] - cv)*w[2];
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                        if( x[3] >= 0 )
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                            sum += (S1[x[3]] - cv)*w[3];
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                        if( x[4] >= 0 )
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                            sum += (S1[x[4]] - cv)*w[4];
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                        if( x[5] >= 0 )
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                            sum += (S1[x[5]] - cv)*w[5];
2866
                        if( x[6] >= 0 )
A
Andrey Kamaev 已提交
2867
                            sum += (S1[x[6]] - cv)*w[6];
2868
                        if( x[7] >= 0 )
A
Andrey Kamaev 已提交
2869
                            sum += (S1[x[7]] - cv)*w[7];
2870 2871 2872 2873 2874 2875 2876 2877 2878 2879 2880 2881 2882 2883 2884 2885 2886
                    }
                    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);

2887
class RemapInvoker :
2888 2889 2890
    public ParallelLoopBody
{
public:
2891
    RemapInvoker(const Mat& _src, Mat& _dst, const Mat *_m1,
2892 2893
                 const Mat *_m2, int _interpolation, int _borderType, const Scalar &_borderValue,
                 int _planar_input, RemapNNFunc _nnfunc, RemapFunc _ifunc, const void *_ctab) :
2894
        ParallelLoopBody(), src(&_src), dst(&_dst), m1(_m1), m2(_m2),
2895
        interpolation(_interpolation), borderType(_borderType), borderValue(_borderValue),
2896
        planar_input(_planar_input), nnfunc(_nnfunc), ifunc(_ifunc), ctab(_ctab)
2897 2898 2899
    {
    }

2900 2901 2902 2903
    virtual void operator() (const Range& range) const
    {
        int x, y, x1, y1;
        const int buf_size = 1 << 14;
2904 2905 2906
        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);
2907 2908 2909 2910 2911 2912 2913 2914 2915 2916
    #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 )
        {
2917
            for( x = 0; x < dst->cols; x += bcols0 )
2918 2919
            {
                int brows = std::min(brows0, range.end - y);
2920 2921
                int bcols = std::min(bcols0, dst->cols - x);
                Mat dpart(*dst, Rect(x, y, bcols, brows));
2922 2923 2924 2925
                Mat bufxy(_bufxy, Rect(0, 0, bcols, brows));

                if( nnfunc )
                {
2926 2927
                    if( m1->type() == CV_16SC2 && !m2->data ) // the data is already in the right format
                        bufxy = (*m1)(Rect(x, y, bcols, brows));
2928 2929 2930 2931 2932 2933 2934 2935 2936 2937 2938 2939 2940 2941 2942 2943 2944
                    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 )
2945
                        (*m1)(Rect(x, y, bcols, brows)).convertTo(bufxy, bufxy.depth());
2946 2947 2948 2949 2950
                    else
                    {
                        for( y1 = 0; y1 < brows; y1++ )
                        {
                            short* XY = (short*)(bufxy.data + bufxy.step*y1);
2951 2952
                            const float* sX = (const float*)(m1->data + m1->step*(y+y1)) + x;
                            const float* sY = (const float*)(m2->data + m2->step*(y+y1)) + x;
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
                            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]);
                            }
                        }
                    }
2985
                    nnfunc( *src, dpart, bufxy, borderType, borderValue );
2986 2987 2988 2989 2990 2991 2992 2993 2994
                    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);

2995
                    if( m1->type() == CV_16SC2 && (m2->type() == CV_16UC1 || m2->type() == CV_16SC1) )
2996
                    {
2997 2998
                        bufxy = (*m1)(Rect(x, y, bcols, brows));
                        bufa = (*m2)(Rect(x, y, bcols, brows));
2999 3000 3001
                    }
                    else if( planar_input )
                    {
3002 3003
                        const float* sX = (const float*)(m1->data + m1->step*(y+y1)) + x;
                        const float* sY = (const float*)(m2->data + m2->step*(y+y1)) + x;
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

                        x1 = 0;
                    #if CV_SSE2
                        if( useSIMD )
                        {
                            __m128 scale = _mm_set1_ps((float)INTER_TAB_SIZE);
                            __m128i mask = _mm_set1_epi32(INTER_TAB_SIZE-1);
                            for( ; x1 <= bcols - 8; x1 += 8 )
                            {
                                __m128 fx0 = _mm_loadu_ps(sX + x1);
                                __m128 fx1 = _mm_loadu_ps(sX + x1 + 4);
                                __m128 fy0 = _mm_loadu_ps(sY + x1);
                                __m128 fy1 = _mm_loadu_ps(sY + x1 + 4);
                                __m128i ix0 = _mm_cvtps_epi32(_mm_mul_ps(fx0, scale));
                                __m128i ix1 = _mm_cvtps_epi32(_mm_mul_ps(fx1, scale));
                                __m128i iy0 = _mm_cvtps_epi32(_mm_mul_ps(fy0, scale));
                                __m128i iy1 = _mm_cvtps_epi32(_mm_mul_ps(fy1, scale));
                                __m128i mx0 = _mm_and_si128(ix0, mask);
                                __m128i mx1 = _mm_and_si128(ix1, mask);
                                __m128i my0 = _mm_and_si128(iy0, mask);
                                __m128i my1 = _mm_and_si128(iy1, mask);
                                mx0 = _mm_packs_epi32(mx0, mx1);
                                my0 = _mm_packs_epi32(my0, my1);
                                my0 = _mm_slli_epi16(my0, INTER_BITS);
                                mx0 = _mm_or_si128(mx0, my0);
                                _mm_storeu_si128((__m128i*)(A + x1), mx0);
                                ix0 = _mm_srai_epi32(ix0, INTER_BITS);
                                ix1 = _mm_srai_epi32(ix1, INTER_BITS);
                                iy0 = _mm_srai_epi32(iy0, INTER_BITS);
                                iy1 = _mm_srai_epi32(iy1, INTER_BITS);
                                ix0 = _mm_packs_epi32(ix0, ix1);
                                iy0 = _mm_packs_epi32(iy0, iy1);
                                ix1 = _mm_unpacklo_epi16(ix0, iy0);
                                iy1 = _mm_unpackhi_epi16(ix0, iy0);
                                _mm_storeu_si128((__m128i*)(XY + x1*2), ix1);
                                _mm_storeu_si128((__m128i*)(XY + x1*2 + 8), iy1);
                            }
                        }
                    #endif

                        for( ; x1 < bcols; x1++ )
                        {
                            int sx = cvRound(sX[x1]*INTER_TAB_SIZE);
                            int sy = cvRound(sY[x1]*INTER_TAB_SIZE);
                            int v = (sy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (sx & (INTER_TAB_SIZE-1));
                            XY[x1*2] = (short)(sx >> INTER_BITS);
                            XY[x1*2+1] = (short)(sy >> INTER_BITS);
                            A[x1] = (ushort)v;
                        }
                    }
                    else
                    {
3056
                        const float* sXY = (const float*)(m1->data + m1->step*(y+y1)) + x*2;
3057 3058 3059 3060 3061 3062 3063 3064 3065 3066 3067 3068

                        for( x1 = 0; x1 < bcols; x1++ )
                        {
                            int sx = cvRound(sXY[x1*2]*INTER_TAB_SIZE);
                            int sy = cvRound(sXY[x1*2+1]*INTER_TAB_SIZE);
                            int v = (sy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (sx & (INTER_TAB_SIZE-1));
                            XY[x1*2] = (short)(sx >> INTER_BITS);
                            XY[x1*2+1] = (short)(sy >> INTER_BITS);
                            A[x1] = (ushort)v;
                        }
                    }
                }
3069
                ifunc(*src, dpart, bufxy, bufa, ctab, borderType, borderValue);
3070 3071 3072
            }
        }
    }
3073

3074
private:
3075 3076
    const Mat* src;
    Mat* dst;
3077
    const Mat *m1, *m2;
3078
    int interpolation, borderType;
3079
    Scalar borderValue;
3080 3081 3082 3083 3084 3085
    int planar_input;
    RemapNNFunc nnfunc;
    RemapFunc ifunc;
    const void *ctab;
};

3086
}
M
Marina Kolpakova 已提交
3087

3088 3089
void cv::remap( InputArray _src, OutputArray _dst,
                InputArray _map1, InputArray _map2,
3090
                int interpolation, int borderType, const Scalar& borderValue )
3091 3092 3093
{
    static RemapNNFunc nn_tab[] =
    {
3094 3095
        remapNearest<uchar>, remapNearest<schar>, remapNearest<ushort>, remapNearest<short>,
        remapNearest<int>, remapNearest<float>, remapNearest<double>, 0
3096 3097 3098 3099 3100 3101 3102
    };

    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,
3103 3104
        remapBilinear<Cast<float, float>, RemapNoVec, float>,
        remapBilinear<Cast<double, double>, RemapNoVec, float>, 0
3105 3106 3107 3108 3109 3110 3111
    };

    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,
3112 3113
        remapBicubic<Cast<float, float>, float, 1>,
        remapBicubic<Cast<double, double>, float, 1>, 0
3114 3115 3116 3117 3118 3119 3120
    };

    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,
3121 3122
        remapLanczos4<Cast<float, float>, float, 1>,
        remapLanczos4<Cast<double, double>, float, 1>, 0
3123 3124
    };

3125
    Mat src = _src.getMat(), map1 = _map1.getMat(), map2 = _map2.getMat();
M
Marina Kolpakova 已提交
3126

3127 3128
    CV_Assert( map1.size().area() > 0 );
    CV_Assert( !map2.data || (map2.size() == map1.size()));
M
Marina Kolpakova 已提交
3129

3130 3131
    _dst.create( map1.size(), src.type() );
    Mat dst = _dst.getMat();
3132 3133
    if( dst.data == src.data )
        src = src.clone();
3134

3135
    int depth = src.depth();
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
    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;

3166 3167
    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)) )
3168 3169 3170 3171 3172 3173
    {
        if( map1.type() != CV_16SC2 )
            std::swap(m1, m2);
    }
    else
    {
3174
        CV_Assert( ((map1.type() == CV_32FC2 || map1.type() == CV_16SC2) && !map2.data) ||
3175 3176 3177 3178
            (map1.type() == CV_32FC1 && map2.type() == CV_32FC1) );
        planar_input = map1.channels() == 1;
    }

3179
    RemapInvoker invoker(src, dst, m1, m2, interpolation,
3180 3181
                         borderType, borderValue, planar_input, nnfunc, ifunc,
                         ctab);
3182
    parallel_for_(Range(0, dst.rows), invoker, dst.total()/(double)(1<<16));
3183 3184 3185
}


3186
void cv::convertMaps( InputArray _map1, InputArray _map2,
3187 3188
                      OutputArray _dstmap1, OutputArray _dstmap2,
                      int dstm1type, bool nninterpolate )
3189
{
3190
    Mat map1 = _map1.getMat(), map2 = _map2.getMat(), dstmap1, dstmap2;
3191 3192 3193 3194 3195 3196 3197 3198 3199 3200 3201 3202 3203 3204 3205 3206 3207 3208
    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 );
3209 3210
    _dstmap1.create( size, dstm1type );
    dstmap1 = _dstmap1.getMat();
M
Marina Kolpakova 已提交
3211

3212
    if( !nninterpolate && dstm1type != CV_32FC2 )
3213 3214 3215 3216
    {
        _dstmap2.create( size, dstm1type == CV_16SC2 ? CV_16UC1 : CV_32FC1 );
        dstmap2 = _dstmap2.getMat();
    }
3217
    else
3218
        _dstmap2.release();
3219 3220 3221 3222 3223 3224 3225 3226 3227 3228 3229 3230 3231 3232 3233 3234 3235 3236 3237 3238 3239 3240 3241 3242 3243 3244 3245 3246 3247 3248 3249 3250 3251 3252 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 3300 3301 3302 3303 3304 3305 3306 3307 3308 3309 3310 3311 3312 3313 3314 3315 3316 3317 3318 3319 3320 3321 3322 3323

    if( m1type == dstm1type || (nninterpolate &&
        ((m1type == CV_16SC2 && dstm1type == CV_32FC2) ||
        (m1type == CV_32FC2 && dstm1type == CV_16SC2))) )
    {
        m1->convertTo( dstmap1, dstmap1.type() );
        if( dstmap2.data && dstmap2.type() == m2->type() )
            m2->copyTo( dstmap2 );
        return;
    }

    if( m1type == CV_32FC1 && dstm1type == CV_32FC2 )
    {
        Mat vdata[] = { *m1, *m2 };
        merge( vdata, 2, dstmap1 );
        return;
    }

    if( m1type == CV_32FC2 && dstm1type == CV_32FC1 )
    {
        Mat mv[] = { dstmap1, dstmap2 };
        split( *m1, mv );
        return;
    }

    if( m1->isContinuous() && (!m2->data || m2->isContinuous()) &&
        dstmap1.isContinuous() && (!dstmap2.data || dstmap2.isContinuous()) )
    {
        size.width *= size.height;
        size.height = 1;
    }

    const float scale = 1.f/INTER_TAB_SIZE;
    int x, y;
    for( y = 0; y < size.height; y++ )
    {
        const float* src1f = (const float*)(m1->data + m1->step*y);
        const float* src2f = (const float*)(m2->data + m2->step*y);
        const short* src1 = (const short*)src1f;
        const ushort* src2 = (const ushort*)src2f;

        float* dst1f = (float*)(dstmap1.data + dstmap1.step*y);
        float* dst2f = (float*)(dstmap2.data + dstmap2.step*y);
        short* dst1 = (short*)dst1f;
        ushort* dst2 = (ushort*)dst2f;

        if( m1type == CV_32FC1 && dstm1type == CV_16SC2 )
        {
            if( nninterpolate )
                for( x = 0; x < size.width; x++ )
                {
                    dst1[x*2] = saturate_cast<short>(src1f[x]);
                    dst1[x*2+1] = saturate_cast<short>(src2f[x]);
                }
            else
                for( x = 0; x < size.width; x++ )
                {
                    int ix = saturate_cast<int>(src1f[x]*INTER_TAB_SIZE);
                    int iy = saturate_cast<int>(src2f[x]*INTER_TAB_SIZE);
                    dst1[x*2] = (short)(ix >> INTER_BITS);
                    dst1[x*2+1] = (short)(iy >> INTER_BITS);
                    dst2[x] = (ushort)((iy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (ix & (INTER_TAB_SIZE-1)));
                }
        }
        else if( m1type == CV_32FC2 && dstm1type == CV_16SC2 )
        {
            if( nninterpolate )
                for( x = 0; x < size.width; x++ )
                {
                    dst1[x*2] = saturate_cast<short>(src1f[x*2]);
                    dst1[x*2+1] = saturate_cast<short>(src1f[x*2+1]);
                }
            else
                for( x = 0; x < size.width; x++ )
                {
                    int ix = saturate_cast<int>(src1f[x*2]*INTER_TAB_SIZE);
                    int iy = saturate_cast<int>(src1f[x*2+1]*INTER_TAB_SIZE);
                    dst1[x*2] = (short)(ix >> INTER_BITS);
                    dst1[x*2+1] = (short)(iy >> INTER_BITS);
                    dst2[x] = (ushort)((iy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (ix & (INTER_TAB_SIZE-1)));
                }
        }
        else if( m1type == CV_16SC2 && dstm1type == CV_32FC1 )
        {
            for( x = 0; x < size.width; x++ )
            {
                int fxy = src2 ? src2[x] : 0;
                dst1f[x] = src1[x*2] + (fxy & (INTER_TAB_SIZE-1))*scale;
                dst2f[x] = src1[x*2+1] + (fxy >> INTER_BITS)*scale;
            }
        }
        else if( m1type == CV_16SC2 && dstm1type == CV_32FC2 )
        {
            for( x = 0; x < size.width; x++ )
            {
                int fxy = src2 ? src2[x] : 0;
                dst1f[x*2] = src1[x*2] + (fxy & (INTER_TAB_SIZE-1))*scale;
                dst1f[x*2+1] = src1[x*2+1] + (fxy >> INTER_BITS)*scale;
            }
        }
        else
            CV_Error( CV_StsNotImplemented, "Unsupported combination of input/output matrices" );
    }
}

3324

3325 3326 3327
namespace cv
{

3328
class warpAffineInvoker :
3329 3330 3331
    public ParallelLoopBody
{
public:
3332
    warpAffineInvoker(const Mat &_src, Mat &_dst, int _interpolation, int _borderType,
3333 3334 3335 3336 3337 3338
                      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)
    {
    }
3339

3340 3341 3342 3343 3344
    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);
3345
        const int AB_SCALE = 1 << AB_BITS;
3346 3347 3348 3349
        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
3350

3351 3352 3353 3354 3355 3356 3357 3358 3359 3360 3361 3362 3363 3364 3365 3366 3367 3368 3369 3370 3371 3372 3373 3374 3375 3376 3377 3378 3379 3380 3381 3382 3383 3384 3385 3386 3387 3388 3389 3390 3391 3392 3393 3394 3395 3396 3397 3398 3399 3400 3401 3402 3403 3404 3405 3406 3407 3408 3409 3410 3411 3412 3413 3414 3415 3416 3417 3418 3419 3420 3421 3422 3423 3424 3425 3426 3427
        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)));
                        }
                    }
                }
3428

3429 3430 3431 3432 3433 3434 3435 3436 3437 3438
                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 );
                }
            }
        }
    }
3439

3440
private:
3441
    Mat src;
3442 3443
    Mat dst;
    int interpolation, borderType;
3444
    Scalar borderValue;
3445 3446 3447
    int *adelta, *bdelta;
    double *M;
};
3448

3449
}
3450 3451


3452 3453
void cv::warpAffine( InputArray _src, OutputArray _dst,
                     InputArray _M0, Size dsize,
3454
                     int flags, int borderType, const Scalar& borderValue )
3455
{
3456
    Mat src = _src.getMat(), M0 = _M0.getMat();
3457
    _dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
3458
    Mat dst = _dst.getMat();
3459 3460 3461
    CV_Assert( src.cols > 0 && src.rows > 0 );
    if( dst.data == src.data )
        src = src.clone();
3462 3463 3464 3465 3466 3467 3468 3469 3470 3471

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

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

A
Andrey Kamaev 已提交
3472 3473 3474 3475 3476
#ifdef HAVE_TEGRA_OPTIMIZATION
    if( tegra::warpAffine(src, dst, M, flags, borderType, borderValue) )
        return;
#endif

3477 3478 3479 3480 3481 3482 3483 3484 3485 3486 3487 3488
    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;
    }

3489 3490 3491
    int x;
    AutoBuffer<int> _abdelta(dst.cols*2);
    int* adelta = &_abdelta[0], *bdelta = adelta + dst.cols;
3492 3493 3494
    const int AB_BITS = MAX(10, (int)INTER_BITS);
    const int AB_SCALE = 1 << AB_BITS;

3495
    for( x = 0; x < dst.cols; x++ )
3496 3497 3498 3499 3500
    {
        adelta[x] = saturate_cast<int>(M[0]*x*AB_SCALE);
        bdelta[x] = saturate_cast<int>(M[3]*x*AB_SCALE);
    }

3501 3502 3503
    Range range(0, dst.rows);
    warpAffineInvoker invoker(src, dst, interpolation, borderType,
                              borderValue, adelta, bdelta, M);
3504
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
3505
}
3506 3507


3508 3509
namespace cv
{
3510

3511 3512 3513 3514
class warpPerspectiveInvoker :
    public ParallelLoopBody
{
public:
3515

3516 3517 3518 3519 3520 3521
    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)
    {
    }
3522

3523 3524 3525 3526 3527
    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;
3528

3529 3530 3531
        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);
3532

3533 3534 3535
        for( y = range.start; y < range.end; y += bh0 )
        {
            for( x = 0; x < width; x += bw0 )
3536
            {
3537 3538
                int bw = std::min( bw0, width - x);
                int bh = std::min( bh0, range.end - y); // height
3539

3540 3541
                Mat _XY(bh, bw, CV_16SC2, XY), matA;
                Mat dpart(dst, Rect(x, y, bw, bh));
3542

3543
                for( y1 = 0; y1 < bh; y1++ )
3544
                {
3545 3546 3547 3548
                    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];
3549

3550 3551
                    if( interpolation == INTER_NEAREST )
                        for( x1 = 0; x1 < bw; x1++ )
3552
                        {
3553 3554 3555 3556 3557 3558
                            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);
3559

3560 3561
                            xy[x1*2] = saturate_cast<short>(X);
                            xy[x1*2+1] = saturate_cast<short>(Y);
3562
                        }
3563
                    else
3564
                    {
3565 3566 3567 3568 3569 3570 3571 3572 3573
                        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);
3574

3575 3576 3577 3578 3579
                            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)));
                        }
3580 3581
                    }
                }
3582

3583 3584 3585 3586 3587 3588 3589
                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 );
                }
3590 3591 3592
            }
        }
    }
3593

3594
private:
3595
    Mat src;
3596 3597 3598
    Mat dst;
    double* M;
    int interpolation, borderType;
3599
    Scalar borderValue;
3600
};
3601

3602 3603
}

3604
void cv::warpPerspective( InputArray _src, OutputArray _dst, InputArray _M0,
3605
                          Size dsize, int flags, int borderType, const Scalar& borderValue )
3606
{
3607
    Mat src = _src.getMat(), M0 = _M0.getMat();
3608
    _dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
3609
    Mat dst = _dst.getMat();
M
Marina Kolpakova 已提交
3610

3611 3612 3613
    CV_Assert( src.cols > 0 && src.rows > 0 );
    if( dst.data == src.data )
        src = src.clone();
3614 3615 3616 3617 3618 3619 3620 3621 3622 3623

    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());

3624
#ifdef HAVE_TEGRA_OPTIMIZATION
A
Andrey Kamaev 已提交
3625
    if( tegra::warpPerspective(src, dst, M, flags, borderType, borderValue) )
3626 3627 3628
        return;
#endif

A
Andrey Kamaev 已提交
3629 3630 3631
    if( !(flags & WARP_INVERSE_MAP) )
         invert(matM, matM);

3632 3633
    Range range(0, dst.rows);
    warpPerspectiveInvoker invoker(src, dst, M, interpolation, borderType, borderValue);
3634
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
3635 3636 3637
}


3638
cv::Mat cv::getRotationMatrix2D( Point2f center, double angle, double scale )
3639 3640 3641 3642 3643 3644 3645 3646 3647 3648 3649 3650 3651 3652 3653 3654 3655 3656 3657 3658 3659 3660 3661 3662 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 3673 3674 3675 3676 3677 3678 3679 3680
{
    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
 */
3681
cv::Mat cv::getPerspectiveTransform( const Point2f src[], const Point2f dst[] )
3682 3683 3684 3685 3686 3687 3688 3689 3690 3691 3692 3693 3694 3695 3696 3697 3698 3699 3700 3701 3702 3703 3704 3705 3706 3707 3708 3709 3710 3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725
{
    Mat M(3, 3, CV_64F), X(8, 1, CV_64F, M.data);
    double a[8][8], b[8];
    Mat A(8, 8, CV_64F, a), B(8, 1, CV_64F, b);

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

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

    return M;
}

/* Calculates coefficients of affine transformation
 * which maps (xi,yi) to (ui,vi), (i=1,2,3):
 *
 * ui = c00*xi + c01*yi + c02
 *
 * vi = c10*xi + c11*yi + c12
 *
 * Coefficients are calculated by solving linear system:
 * / x0 y0  1  0  0  0 \ /c00\ /u0\
 * | x1 y1  1  0  0  0 | |c01| |u1|
 * | x2 y2  1  0  0  0 | |c02| |u2|
 * |  0  0  0 x0 y0  1 | |c10| |v0|
 * |  0  0  0 x1 y1  1 | |c11| |v1|
 * \  0  0  0 x2 y2  1 / |c12| |v2|
 *
 * where:
 *   cij - matrix coefficients
 */
K
Kirill Kornyakov 已提交
3726

3727
cv::Mat cv::getAffineTransform( const Point2f src[], const Point2f dst[] )
3728 3729 3730 3731 3732 3733 3734 3735 3736 3737 3738 3739 3740 3741 3742 3743 3744 3745 3746 3747 3748
{
    Mat M(2, 3, CV_64F), X(6, 1, CV_64F, M.data);
    double a[6*6], b[6];
    Mat A(6, 6, CV_64F, a), B(6, 1, CV_64F, b);

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

    solve( A, B, X );
    return M;
}
M
Marina Kolpakova 已提交
3749

3750
void cv::invertAffineTransform(InputArray _matM, OutputArray __iM)
3751
{
3752
    Mat matM = _matM.getMat();
3753
    CV_Assert(matM.rows == 2 && matM.cols == 3);
3754 3755
    __iM.create(2, 3, matM.type());
    Mat _iM = __iM.getMat();
M
Marina Kolpakova 已提交
3756

3757 3758 3759 3760
    if( matM.type() == CV_32F )
    {
        const float* M = (const float*)matM.data;
        float* iM = (float*)_iM.data;
3761
        int step = (int)(matM.step/sizeof(M[0])), istep = (int)(_iM.step/sizeof(iM[0]));
M
Marina Kolpakova 已提交
3762

3763 3764 3765 3766 3767
        double D = M[0]*M[step+1] - M[1]*M[step];
        D = D != 0 ? 1./D : 0;
        double A11 = M[step+1]*D, A22 = M[0]*D, A12 = -M[1]*D, A21 = -M[step]*D;
        double b1 = -A11*M[2] - A12*M[step+2];
        double b2 = -A21*M[2] - A22*M[step+2];
M
Marina Kolpakova 已提交
3768

3769 3770 3771 3772 3773 3774 3775
        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;
3776
        int step = (int)(matM.step/sizeof(M[0])), istep = (int)(_iM.step/sizeof(iM[0]));
M
Marina Kolpakova 已提交
3777

3778 3779 3780 3781 3782
        double D = M[0]*M[step+1] - M[1]*M[step];
        D = D != 0 ? 1./D : 0;
        double A11 = M[step+1]*D, A22 = M[0]*D, A12 = -M[1]*D, A21 = -M[step]*D;
        double b1 = -A11*M[2] - A12*M[step+2];
        double b2 = -A21*M[2] - A22*M[step+2];
M
Marina Kolpakova 已提交
3783

3784 3785 3786 3787 3788
        iM[0] = A11; iM[1] = A12; iM[2] = b1;
        iM[istep] = A21; iM[istep+1] = A22; iM[istep+2] = b2;
    }
    else
        CV_Error( CV_StsUnsupportedFormat, "" );
M
Marina Kolpakova 已提交
3789
}
3790

3791 3792 3793 3794 3795 3796 3797 3798 3799 3800 3801 3802 3803 3804
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);
    CV_Assert( M.size() == M.size() );
    M.convertTo(M0, M0.type());
    return matrix;
}


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


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


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

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

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

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

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

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

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

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

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

    mapx = cvCreateMat( dsize.height, dsize.width, CV_32F );
    mapy = cvCreateMat( dsize.height, dsize.width, CV_32F );

    if( !(flags & CV_WARP_INVERSE_MAP) )
    {
        int phi, rho;
        cv::AutoBuffer<double> _exp_tab(dsize.width);
        double* exp_tab = _exp_tab;

        for( rho = 0; rho < dst->width; rho++ )
            exp_tab[rho] = std::exp(rho/M);

        for( phi = 0; phi < dsize.height; phi++ )
        {
            double cp = cos(phi*2*CV_PI/dsize.height);
            double sp = sin(phi*2*CV_PI/dsize.height);
            float* mx = (float*)(mapx->data.ptr + phi*mapx->step);
            float* my = (float*)(mapy->data.ptr + phi*mapy->step);

            for( rho = 0; rho < dsize.width; rho++ )
            {
                double r = exp_tab[rho];
                double x = r*cp + center.x;
                double y = r*sp + center.y;

                mx[rho] = (float)x;
                my[rho] = (float)y;
            }
        }
    }
    else
    {
        int x, y;
        CvMat bufx, bufy, bufp, bufa;
        double ascale = ssize.height/(2*CV_PI);
        cv::AutoBuffer<float> _buf(4*dsize.width);
        float* buf = _buf;

        bufx = cvMat( 1, dsize.width, CV_32F, buf );
        bufy = cvMat( 1, dsize.width, CV_32F, buf + dsize.width );
        bufp = cvMat( 1, dsize.width, CV_32F, buf + dsize.width*2 );
        bufa = cvMat( 1, dsize.width, CV_32F, buf + dsize.width*3 );

        for( x = 0; x < dsize.width; x++ )
            bufx.data.fl[x] = (float)x - center.x;

        for( y = 0; y < dsize.height; y++ )
        {
            float* mx = (float*)(mapx->data.ptr + y*mapx->step);
            float* my = (float*)(mapy->data.ptr + y*mapy->step);

            for( x = 0; x < dsize.width; x++ )
                bufy.data.fl[x] = (float)y - center.y;

#if 1
            cvCartToPolar( &bufx, &bufy, &bufp, &bufa );

            for( x = 0; x < dsize.width; x++ )
                bufp.data.fl[x] += 1.f;

            cvLog( &bufp, &bufp );

            for( x = 0; x < dsize.width; x++ )
            {
                double rho = bufp.data.fl[x]*M;
                double phi = bufa.data.fl[x]*ascale;

                mx[x] = (float)rho;
                my[x] = (float)phi;
            }
#else
            for( x = 0; x < dsize.width; x++ )
            {
                double xx = bufx.data.fl[x];
                double yy = bufy.data.fl[x];

                double p = log(sqrt(xx*xx + yy*yy) + 1.)*M;
                double a = atan2(yy,xx);
                if( a < 0 )
                    a = 2*CV_PI + a;
                a *= ascale;

                mx[x] = (float)p;
                my[x] = (float)a;
            }
#endif
        }
    }

    cvRemap( src, dst, mapx, mapy, flags, cvScalarAll(0) );
}


/****************************************************************************************
                                   Linear-Polar Transform
  J.L. Blanco, Apr 2009
 ****************************************************************************************/
CV_IMPL
void cvLinearPolar( const CvArr* srcarr, CvArr* dstarr,
            CvPoint2D32f center, double maxRadius, int flags )
{
    cv::Ptr<CvMat> mapx, mapy;

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

    src = cvGetMat( srcarr, &srcstub,0,0 );
    dst = cvGetMat( dstarr, &dststub,0,0 );

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

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    ssize.width = src->cols;
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    ssize.height = src->rows;
    dsize.width = dst->cols;
    dsize.height = dst->rows;

    mapx = cvCreateMat( dsize.height, dsize.width, CV_32F );
    mapy = cvCreateMat( dsize.height, dsize.width, CV_32F );

    if( !(flags & CV_WARP_INVERSE_MAP) )
    {
        int phi, rho;

        for( phi = 0; phi < dsize.height; phi++ )
        {
            double cp = cos(phi*2*CV_PI/dsize.height);
            double sp = sin(phi*2*CV_PI/dsize.height);
            float* mx = (float*)(mapx->data.ptr + phi*mapx->step);
            float* my = (float*)(mapy->data.ptr + phi*mapy->step);

            for( rho = 0; rho < dsize.width; rho++ )
            {
                double r = maxRadius*(rho+1)/dsize.width;
                double x = r*cp + center.x;
                double y = r*sp + center.y;

                mx[rho] = (float)x;
                my[rho] = (float)y;
            }
        }
    }
    else
    {
        int x, y;
        CvMat bufx, bufy, bufp, bufa;
        const double ascale = ssize.height/(2*CV_PI);
        const double pscale = ssize.width/maxRadius;

        cv::AutoBuffer<float> _buf(4*dsize.width);
        float* buf = _buf;

        bufx = cvMat( 1, dsize.width, CV_32F, buf );
        bufy = cvMat( 1, dsize.width, CV_32F, buf + dsize.width );
        bufp = cvMat( 1, dsize.width, CV_32F, buf + dsize.width*2 );
        bufa = cvMat( 1, dsize.width, CV_32F, buf + dsize.width*3 );

        for( x = 0; x < dsize.width; x++ )
            bufx.data.fl[x] = (float)x - center.x;

        for( y = 0; y < dsize.height; y++ )
        {
            float* mx = (float*)(mapx->data.ptr + y*mapx->step);
            float* my = (float*)(mapy->data.ptr + y*mapy->step);

            for( x = 0; x < dsize.width; x++ )
                bufy.data.fl[x] = (float)y - center.y;

            cvCartToPolar( &bufx, &bufy, &bufp, &bufa, 0 );

            for( x = 0; x < dsize.width; x++ )
                bufp.data.fl[x] += 1.f;

            for( x = 0; x < dsize.width; x++ )
            {
                double rho = bufp.data.fl[x]*pscale;
                double phi = bufa.data.fl[x]*ascale;
                mx[x] = (float)rho;
                my[x] = (float)phi;
            }
        }
    }

    cvRemap( src, dst, mapx, mapy, flags, cvScalarAll(0) );
}


/* End of file. */