opencv warpAffine仿射变换C++源码分析

Kelvin_Ngan2025-01-11 12:43

基于opencv 3.1.0源代码
sources\modules\imgproc\src\imgwarp.cpp

cpp 复制代码 
void cv::warpAffine( InputArray _src, OutputArray _dst,
                     InputArray _M0, Size dsize,
                     int flags, int borderType, const Scalar& borderValue )
{
    ...
    if( !(flags & WARP_INVERSE_MAP) )
    {
    //变换矩阵求逆
        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;
    }
    ...
//优先采用IPP加速
//省略
//...
//没有IPP库或处理失败时，才会继续运行下面的
    for( x = 0; x < dst.cols; x++ )
    {
        adelta[x] = saturate_cast<int>(M[0]*x*AB_SCALE);
        bdelta[x] = saturate_cast<int>(M[3]*x*AB_SCALE);
    }

    Range range(0, dst.rows);
    //仿射变换类WarpAffineInvoker
    WarpAffineInvoker invoker(src, dst, interpolation, borderType,
                              borderValue, adelta, bdelta, M);
    parallel_for_(range, invoker, dst.total()/(double)(1<<16));
}

//类WarpAffineInvoker实现
class WarpAffineInvoker :
    public ParallelLoopBody
{
public:
    WarpAffineInvoker(const Mat &_src, Mat &_dst, int _interpolation, int _borderType,
                      const Scalar &_borderValue, int *_adelta, int *_bdelta, double *_M) :
        ParallelLoopBody(), src(_src), dst(_dst), interpolation(_interpolation),
        borderType(_borderType), borderValue(_borderValue), adelta(_adelta), bdelta(_bdelta),
        M(_M)
    {
    }
	//核心代码就在这里，直接上CPU指令集来加速的，经过优化的代码会比较难读
    virtual void operator() (const Range& range) const
    {
    ...
        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);            
			    //根据目标坐标（变换后）和逆矩阵求出源坐标
			   ...
                   Mat _XY(bh, bw, CV_16SC2, XY), matA;  //源坐标矩阵
                   Mat dpart(dst, Rect(x, y, bw, bh));  //目标矩阵
			    ...
			    //调用remap函数
                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 );
                }    
            }
       }    		
	}
...
}

...

//remap函数实现
void cv::remap( InputArray _src, OutputArray _dst,
                InputArray _map1, InputArray _map2,
                int interpolation, int borderType, const Scalar& borderValue )
{
//不同的插值算子
    static RemapNNFunc nn_tab[] =
    {
        remapNearest<uchar>, remapNearest<schar>, remapNearest<ushort>, remapNearest<short>,
        remapNearest<int>, remapNearest<float>, remapNearest<double>, 0
    };

    static RemapFunc linear_tab[] =
    {
        remapBilinear<FixedPtCast<int, uchar, INTER_REMAP_COEF_BITS>, RemapVec_8u, short>, 0,
        remapBilinear<Cast<float, ushort>, RemapNoVec, float>,
        remapBilinear<Cast<float, short>, RemapNoVec, float>, 0,
        remapBilinear<Cast<float, float>, RemapNoVec, float>,
        remapBilinear<Cast<double, double>, RemapNoVec, float>, 0
    };

    static RemapFunc cubic_tab[] =
    {
        remapBicubic<FixedPtCast<int, uchar, INTER_REMAP_COEF_BITS>, short, INTER_REMAP_COEF_SCALE>, 0,
        remapBicubic<Cast<float, ushort>, float, 1>,
        remapBicubic<Cast<float, short>, float, 1>, 0,
        remapBicubic<Cast<float, float>, float, 1>,
        remapBicubic<Cast<double, double>, float, 1>, 0
    };

    static RemapFunc lanczos4_tab[] =
    {
        remapLanczos4<FixedPtCast<int, uchar, INTER_REMAP_COEF_BITS>, short, INTER_REMAP_COEF_SCALE>, 0,
        remapLanczos4<Cast<float, ushort>, float, 1>,
        remapLanczos4<Cast<float, short>, float, 1>, 0,
        remapLanczos4<Cast<float, float>, float, 1>,
        remapLanczos4<Cast<double, double>, float, 1>, 0
    };

 ...

    if( interpolation == INTER_AREA )
        interpolation = INTER_LINEAR;

//优先采用IPP加速
//省略
//...
//没有IPP库或处理失败时，才会继续运行下面的
    RemapNNFunc nnfunc = 0;
    RemapFunc ifunc = 0;
    const void* ctab = 0;
    bool fixpt = depth == CV_8U;
    bool planar_input = false;

    if( interpolation == INTER_NEAREST )
    {    
        nnfunc = nn_tab[depth];
        CV_Assert( nnfunc != 0 );
    }
    else
    {
        if( interpolation == INTER_LINEAR )
            ifunc = linear_tab[depth];
        else if( interpolation == INTER_CUBIC )
            ifunc = cubic_tab[depth];
        else if( interpolation == INTER_LANCZOS4 )
            ifunc = lanczos4_tab[depth];
        else
            CV_Error( CV_StsBadArg, "Unknown interpolation method" );
        CV_Assert( ifunc != 0 );
        ctab = initInterTab2D( interpolation, fixpt );
    }

    const Mat *m1 = &map1, *m2 = &map2;

    if( (map1.type() == CV_16SC2 && (map2.type() == CV_16UC1 || map2.type() == CV_16SC1 || map2.empty())) ||
        (map2.type() == CV_16SC2 && (map1.type() == CV_16UC1 || map1.type() == CV_16SC1 || map1.empty())) )
    {
        if( map1.type() != CV_16SC2 )
            std::swap(m1, m2);
    }
    else
    {
        CV_Assert( ((map1.type() == CV_32FC2 || map1.type() == CV_16SC2) && map2.empty()) ||
            (map1.type() == CV_32FC1 && map2.type() == CV_32FC1) );
        planar_input = map1.channels() == 1;
    }

//插值处理在RemapInvoker类实现
    RemapInvoker invoker(src, dst, m1, m2,
                         borderType, borderValue, planar_input, nnfunc, ifunc,
                         ctab);
    parallel_for_(Range(0, dst.rows), invoker, dst.total()/(double)(1<<16));
}

//类RemapInvoker实现
class RemapInvoker :
    public ParallelLoopBody
{
public:
    RemapInvoker(const Mat& _src, Mat& _dst, const Mat *_m1,
                 const Mat *_m2, int _borderType, const Scalar &_borderValue,
                 int _planar_input, RemapNNFunc _nnfunc, RemapFunc _ifunc, const void *_ctab) :
        ParallelLoopBody(), src(&_src), dst(&_dst), m1(_m1), m2(_m2),
        borderType(_borderType), borderValue(_borderValue),
        planar_input(_planar_input), nnfunc(_nnfunc), ifunc(_ifunc), ctab(_ctab)
    {
    }
	//直接上CPU指令集来加速的，经过优化的代码会比较难读
    virtual void operator() (const Range& range) const
    {
        int x, y, x1, y1;
        const int buf_size = 1 << 14;
        int brows0 = std::min(128, dst->rows), map_depth = m1->depth();
        int bcols0 = std::min(buf_size/brows0, dst->cols);
        brows0 = std::min(buf_size/bcols0, dst->rows);
    #if CV_SSE2
        bool useSIMD = checkHardwareSupport(CV_CPU_SSE2);
    #endif

        Mat _bufxy(brows0, bcols0, CV_16SC2), _bufa;
        if( !nnfunc )
            _bufa.create(brows0, bcols0, CV_16UC1);

        for( y = range.start; y < range.end; y += brows0 )
        {
            for( x = 0; x < dst->cols; x += bcols0 )
            {
                int brows = std::min(brows0, range.end - y);
                int bcols = std::min(bcols0, dst->cols - x);
                Mat dpart(*dst, Rect(x, y, bcols, brows));
                Mat bufxy(_bufxy, Rect(0, 0, bcols, brows));

				//最近邻插值
                if( nnfunc )
                {
                    if( m1->type() == CV_16SC2 && m2->empty() ) // the data is already in the right format
                        bufxy = (*m1)(Rect(x, y, bcols, brows));
                    else if( map_depth != CV_32F )
                    {
                        for( y1 = 0; y1 < brows; y1++ )
                        {
                            short* XY = bufxy.ptr<short>(y1);
                            const short* sXY = m1->ptr<short>(y+y1) + x*2;
                            const ushort* sA = m2->ptr<ushort>(y+y1) + x;

                            for( x1 = 0; x1 < bcols; x1++ )
                            {
                                int a = sA[x1] & (INTER_TAB_SIZE2-1);
                                XY[x1*2] = sXY[x1*2] + NNDeltaTab_i[a][0];
                                XY[x1*2+1] = sXY[x1*2+1] + NNDeltaTab_i[a][1];
                            }
                        }
                    }
                    else if( !planar_input )
                        (*m1)(Rect(x, y, bcols, brows)).convertTo(bufxy, bufxy.depth());
                    else
                    {
                        for( y1 = 0; y1 < brows; y1++ )
                        {
                            short* XY = bufxy.ptr<short>(y1);
                            const float* sX = m1->ptr<float>(y+y1) + x;
                            const float* sY = m2->ptr<float>(y+y1) + x;
                            x1 = 0;

                        #if CV_SSE2
                            if( useSIMD )
                            {
                                for( ; x1 <= bcols - 8; x1 += 8 )
                                {
                                    __m128 fx0 = _mm_loadu_ps(sX + x1);
                                    __m128 fx1 = _mm_loadu_ps(sX + x1 + 4);
                                    __m128 fy0 = _mm_loadu_ps(sY + x1);
                                    __m128 fy1 = _mm_loadu_ps(sY + x1 + 4);
                                    __m128i ix0 = _mm_cvtps_epi32(fx0);
                                    __m128i ix1 = _mm_cvtps_epi32(fx1);
                                    __m128i iy0 = _mm_cvtps_epi32(fy0);
                                    __m128i iy1 = _mm_cvtps_epi32(fy1);
                                    ix0 = _mm_packs_epi32(ix0, ix1);
                                    iy0 = _mm_packs_epi32(iy0, iy1);
                                    ix1 = _mm_unpacklo_epi16(ix0, iy0);
                                    iy1 = _mm_unpackhi_epi16(ix0, iy0);
                                    _mm_storeu_si128((__m128i*)(XY + x1*2), ix1);
                                    _mm_storeu_si128((__m128i*)(XY + x1*2 + 8), iy1);
                                }
                            }
                        #endif

                            for( ; x1 < bcols; x1++ )
                            {
                                XY[x1*2] = saturate_cast<short>(sX[x1]);
                                XY[x1*2+1] = saturate_cast<short>(sY[x1]);
                            }
                        }
                    }
                    nnfunc( *src, dpart, bufxy, borderType, borderValue );
                    continue;
                }

				//其它插值算法
                Mat bufa(_bufa, Rect(0, 0, bcols, brows));
                for( y1 = 0; y1 < brows; y1++ )
                {
                    short* XY = bufxy.ptr<short>(y1);
                    ushort* A = bufa.ptr<ushort>(y1);

                    if( m1->type() == CV_16SC2 && (m2->type() == CV_16UC1 || m2->type() == CV_16SC1) )
                    {
                        bufxy = (*m1)(Rect(x, y, bcols, brows));

                        const ushort* sA = m2->ptr<ushort>(y+y1) + x;
                        x1 = 0;

                    #if CV_NEON
...
                    #elif CV_SSE2
                        __m128i v_scale = _mm_set1_epi16(INTER_TAB_SIZE2-1);
                        for ( ; x1 <= bcols - 8; x1 += 8)
                            _mm_storeu_si128((__m128i *)(A + x1), _mm_and_si128(_mm_loadu_si128((const __m128i *)(sA + x1)), v_scale));
                    #endif

                        for( ; x1 < bcols; x1++ )
                            A[x1] = (ushort)(sA[x1] & (INTER_TAB_SIZE2-1));
                    }
                    else if( planar_input )
                    {
                        const float* sX = m1->ptr<float>(y+y1) + x;
                        const float* sY = m2->ptr<float>(y+y1) + x;

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

                        for( ; x1 < bcols; x1++ )
                        {
                            int sx = cvRound(sX[x1]*INTER_TAB_SIZE);
                            int sy = cvRound(sY[x1]*INTER_TAB_SIZE);
                            int v = (sy & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (sx & (INTER_TAB_SIZE-1));
                            XY[x1*2] = saturate_cast<short>(sx >> INTER_BITS);
                            XY[x1*2+1] = saturate_cast<short>(sy >> INTER_BITS);
                            A[x1] = (ushort)v;
                        }
                    }
                    else
                    {
                        const float* sXY = m1->ptr<float>(y+y1) + x*2;
                        x1 = 0;

                    #if CV_NEON
	...
                    #endif

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

//以下只截取最近邻插值算子的代码
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 = _src.ptr<T>();
    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 = _dst.ptr<T>(dy);
        const short* XY = _xy.ptr<short>(dy);
		
        if( cn == 1 )  //单通道
        {
            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  //越界
                {
                    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 )
                    {
                    	//边界处理
                        sx = borderInterpolate(sx, ssize.width, borderType);
                        sy = borderInterpolate(sy, ssize.height, borderType);
                        D[dx] = S0[sy*sstep + sx];
                    }
                }
            }
        }
        else  //多通道
        {
            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];
                }
            }
        }
    }
}

边界处理的代码在sources\modules\core\src\copy.cpp

cpp 复制代码 
/*
 Various border types, image boundaries are denoted with '|'

 * BORDER_REPLICATE:     aaaaaa|abcdefgh|hhhhhhh
 * BORDER_REFLECT:       fedcba|abcdefgh|hgfedcb
 * BORDER_REFLECT_101:   gfedcb|abcdefgh|gfedcba
 * BORDER_WRAP:          cdefgh|abcdefgh|abcdefg
 * BORDER_CONSTANT:      iiiiii|abcdefgh|iiiiiii  with some specified 'i'
 */
int cv::borderInterpolate( int p, int len, int borderType )
{
    if( (unsigned)p < (unsigned)len )
        ;
    else if( borderType == BORDER_REPLICATE )
        p = p < 0 ? 0 : len - 1;
    else if( borderType == BORDER_REFLECT || borderType == BORDER_REFLECT_101 )
    {
        int delta = borderType == BORDER_REFLECT_101;
        if( len == 1 )
            return 0;
        do
        {
            if( p < 0 )
                p = -p - 1 + delta;
            else
                p = len - 1 - (p - len) - delta;
        }
        while( (unsigned)p >= (unsigned)len );
    }
    else if( borderType == BORDER_WRAP )
    {
        CV_Assert(len > 0);
        if( p < 0 )
            p -= ((p-len+1)/len)*len;
        if( p >= len )
            p %= len;
    }
    else if( borderType == BORDER_CONSTANT )
        p = -1;
    else
        CV_Error( CV_StsBadArg, "Unknown/unsupported border type" );
    return p;
}
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