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#include "precomp.hpp"

/****************************************************************************************/

/* lightweight convolution with 3x3 kernel */
void icvSepConvSmall3_32f( float* src, int src_step, float* dst, int dst_step,
            CvSize src_size, const float* kx, const float* ky, float* buffer )
{
    int  dst_width, buffer_step = 0;
    int  x, y;

    assert( src && dst && src_size.width > 2 && src_size.height > 2 &&
            (src_step & 3) == 0 && (dst_step & 3) == 0 &&
            (kx || ky) && (buffer || !kx || !ky));

    src_step /= sizeof(src[0]);
    dst_step /= sizeof(dst[0]);

    dst_width = src_size.width - 2;

    if( !kx )
    {
        /* set vars, so that vertical convolution
           will write results into destination ROI and
           horizontal convolution won't run */
        src_size.width = dst_width;
        buffer_step = dst_step;
        buffer = dst;
        dst_width = 0;
    }

    assert( src_step >= src_size.width && dst_step >= dst_width );

    src_size.height -= 3;
    if( !ky )
    {
        /* set vars, so that vertical convolution won't run and
           horizontal convolution will write results into destination ROI */
        src_size.height += 3;
        buffer_step = src_step;
        buffer = src;
        src_size.width = 0;
    }

    for( y = 0; y <= src_size.height; y++, src += src_step,
                                           dst += dst_step,
                                           buffer += buffer_step )
    {
        float* src2 = src + src_step;
        float* src3 = src + src_step*2;
        for( x = 0; x < src_size.width; x++ )
        {
            buffer[x] = (float)(ky[0]*src[x] + ky[1]*src2[x] + ky[2]*src3[x]);
        }

        for( x = 0; x < dst_width; x++ )
        {
            dst[x] = (float)(kx[0]*buffer[x] + kx[1]*buffer[x+1] + kx[2]*buffer[x+2]);
        }
    }
}


/****************************************************************************************\
                             Sobel & Scharr Derivative Filters
\****************************************************************************************/

namespace cv
{

static void getScharrKernels( Mat& kx, Mat& ky, int dx, int dy, bool normalize, int ktype )
{
    const int ksize = 3;

    CV_Assert( ktype == CV_32F || ktype == CV_64F );

    if( kx.cols != ksize || kx.rows != 1 || kx.type() != ktype )
        kx.create( ksize, 1, ktype );
    if( ky.cols != ksize || ky.rows != 1 || ky.type() != ktype )
        ky.create( ksize, 1, ktype );

    CV_Assert( dx >= 0 && dy >= 0 && dx+dy == 1 );

    for( int k = 0; k < 2; k++ )
    {
        Mat* kernel = k == 0 ? &kx : &ky;
        int order = k == 0 ? dx : dy;
        int kerI[3];

        if( order == 0 )
            kerI[0] = 3, kerI[1] = 10, kerI[2] = 3;
        else if( order == 1 )
            kerI[0] = -1, kerI[1] = 0, kerI[2] = 1;

        Mat temp(kernel->rows, kernel->cols, CV_32S, &kerI[0]);
        double scale = !normalize || order == 1 ? 1. : 1./32;
        temp.convertTo(*kernel, ktype, scale);
    }
}


static void getSobelKernels( Mat& kx, Mat& ky, int dx, int dy, int _ksize, bool normalize, int ktype )
{
    int i, j, ksizeX = _ksize, ksizeY = _ksize;
    if( ksizeX == 1 && dx > 0 )
        ksizeX = 3;
    if( ksizeY == 1 && dy > 0 )
        ksizeY = 3;

    CV_Assert( ktype == CV_32F || ktype == CV_64F );

    if( kx.cols != ksizeX || kx.rows != 1 || kx.type() != ktype )
        kx.create( ksizeX, 1, ktype );
    if( ky.cols != ksizeY || ky.rows != 1 || ky.type() != ktype )
        ky.create( ksizeY, 1, ktype );

    if( _ksize % 2 == 0 || _ksize > 31 )
        CV_Error( CV_StsOutOfRange, "The kernel size must be odd and not larger than 31" );
    vector<int> kerI(std::max(ksizeX, ksizeY) + 1);

    CV_Assert( dx >= 0 && dy >= 0 && dx+dy > 0 );

    for( int k = 0; k < 2; k++ )
    {
        Mat* kernel = k == 0 ? &kx : &ky;
        int order = k == 0 ? dx : dy;
        int ksize = k == 0 ? ksizeX : ksizeY;

        CV_Assert( ksize > order );

        if( ksize == 1 )
            kerI[0] = 1;
        else if( ksize == 3 )
        {
            if( order == 0 )
                kerI[0] = 1, kerI[1] = 2, kerI[2] = 1;
            else if( order == 1 )
                kerI[0] = -1, kerI[1] = 0, kerI[2] = 1;
            else
                kerI[0] = 1, kerI[1] = -2, kerI[2] = 1;
        }
        else
        {
            int oldval, newval;
            kerI[0] = 1;
            for( i = 0; i < ksize; i++ )
                kerI[i+1] = 0;

            for( i = 0; i < ksize - order - 1; i++ )
            {
                oldval = kerI[0];
                for( j = 1; j <= ksize; j++ )
                {
                    newval = kerI[j]+kerI[j-1];
                    kerI[j-1] = oldval;
                    oldval = newval;
                }
            }

            for( i = 0; i < order; i++ )
            {
                oldval = -kerI[0];
                for( j = 1; j <= ksize; j++ )
                {
                    newval = kerI[j-1] - kerI[j];
                    kerI[j-1] = oldval;
                    oldval = newval;
                }
            }
        }

        Mat temp(kernel->rows, kernel->cols, CV_32S, &kerI[0]);
        double scale = !normalize ? 1. : 1./(1 << (ksize-order-1));
        temp.convertTo(*kernel, ktype, scale);
    }
}


void getDerivKernels( Mat& kx, Mat& ky, int dx, int dy,
                      int ksize, bool normalize, int ktype )
{
    if( ksize <= 0 )
        getScharrKernels( kx, ky, dx, dy, normalize, ktype );
    else
        getSobelKernels( kx, ky, dx, dy, ksize, normalize, ktype );
}


Ptr<FilterEngine> createDerivFilter(int srcType, int dstType,
                                    int dx, int dy, int ksize, int borderType )
{
    Mat kx, ky;
    getDerivKernels( kx, ky, dx, dy, ksize, false, CV_32F );
    return createSeparableLinearFilter(srcType, dstType,
        kx, ky, Point(-1,-1), 0, borderType );
}


void Sobel( const Mat& src, Mat& dst, int ddepth, int dx, int dy,
            int ksize, double scale, double delta, int borderType )
{
    int ktype = std::max(CV_32F, std::max(ddepth, src.depth()));

    Mat kx, ky;
    getDerivKernels( kx, ky, dx, dy, ksize, false, ktype );
    if( scale != 1 )
    {
        // usually the smoothing part is the slowest to compute,
        // so try to scale it instead of the faster differenciating part
        if( dx == 0 )
            kx *= scale;
        else
            ky *= scale;
    }
    sepFilter2D( src, dst, ddepth, kx, ky, Point(-1,-1), delta, borderType );
}


void Scharr( const Mat& src, Mat& dst, int ddepth, int dx, int dy,
             double scale, double delta, int borderType )
{
    int ktype = std::max(CV_32F, std::max(ddepth, src.depth()));

    Mat kx, ky;
    getScharrKernels( kx, ky, dx, dy, false, ktype );
    if( scale != 1 )
    {
        // usually the smoothing part is the slowest to compute,
        // so try to scale it instead of the faster differenciating part
        if( dx == 0 )
            kx *= scale;
        else
            ky *= scale;
    }
    sepFilter2D( src, dst, ddepth, kx, ky, Point(-1,-1), delta, borderType );
}


void Laplacian( const Mat& src, Mat& dst, int ddepth, int ksize,
                double scale, double delta, int borderType )
{
    if( ksize == 1 || ksize == 3 )
    {
        float K[2][9] =
        {{0, 1, 0, 1, -4, 1, 0, 1, 0},
         {2, 0, 2, 0, -8, 0, 2, 0, 2}};
        Mat kernel(3, 3, CV_32F, K[ksize == 3]);
        if( scale != 1 )
            kernel *= scale;
        filter2D( src, dst, ddepth, kernel, Point(-1,-1), delta, borderType );
    }
    else
    {
        const size_t STRIPE_SIZE = 1 << 14;

        int depth = src.depth();
        int ktype = std::max(CV_32F, std::max(ddepth, depth));
        int wdepth = depth == CV_8U && ksize <= 5 ? CV_16S : depth <= CV_32F ? CV_32F : CV_64F;
        int wtype = CV_MAKETYPE(wdepth, src.channels());
        Mat kd, ks;
        getSobelKernels( kd, ks, 2, 0, ksize, false, ktype );
        if( ddepth < 0 )
            ddepth = src.depth();
        int dtype = CV_MAKETYPE(ddepth, src.channels());
        dst.create( src.size(), dtype );

        int dy0 = std::min(std::max((int)(STRIPE_SIZE/(getElemSize(src.type())*src.cols)), 1), src.rows);
        Ptr<FilterEngine> fx = createSeparableLinearFilter(src.type(),
            wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() ); 
        Ptr<FilterEngine> fy = createSeparableLinearFilter(src.type(),
            wtype, ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() );

        int y = fx->start(src), dsty = 0, dy = 0;
        fy->start(src);
        const uchar* sptr = src.data + y*src.step;

        Mat d2x( dy0 + kd.rows - 1, src.cols, wtype );
        Mat d2y( dy0 + kd.rows - 1, src.cols, wtype );

        for( ; dsty < src.rows; sptr += dy0*src.step, dsty += dy )
        {
            fx->proceed( sptr, (int)src.step, dy0, d2x.data, (int)d2x.step );
            dy = fy->proceed( sptr, (int)src.step, dy0, d2y.data, (int)d2y.step );
            if( dy > 0 )
            {
                Mat dstripe = dst.rowRange(dsty, dsty + dy);
                d2x.rows = d2y.rows = dy; // modify the headers, which should work
                d2x += d2y;
                d2x.convertTo( dstripe, dtype, scale, delta );
            }
        }
    }
}

}

/////////////////////////////////////////////////////////////////////////////////////////

CV_IMPL void
cvSobel( const void* srcarr, void* dstarr, int dx, int dy, int aperture_size )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);

    CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() &&
        ((src.depth() == CV_8U && (dst.depth() == CV_16S || dst.depth() == CV_32F)) ||
        (src.depth() == CV_32F && dst.depth() == CV_32F)));

    cv::Sobel( src, dst, dst.depth(), dx, dy, aperture_size, 1, 0, cv::BORDER_REPLICATE );
    if( CV_IS_IMAGE(srcarr) && ((IplImage*)srcarr)->origin && dy % 2 != 0 )
        dst *= -1;
}


CV_IMPL void
cvLaplace( const void* srcarr, void* dstarr, int aperture_size )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);

    CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() &&
        ((src.depth() == CV_8U && (dst.depth() == CV_16S || dst.depth() == CV_32F)) ||
        (src.depth() == CV_32F && dst.depth() == CV_32F)));

    cv::Laplacian( src, dst, dst.depth(), aperture_size, 1, 0, cv::BORDER_REPLICATE );
}

/* End of file. */
