opencv/modules/imgproc/src/corner.cpp

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#include "precomp.hpp"
#include "opencl_kernels.hpp"

namespace cv
{

static void calcMinEigenVal( const Mat& _cov, Mat& _dst )
{
    int i, j;
    Size size = _cov.size();
#if CV_SSE
    volatile bool simd = checkHardwareSupport(CV_CPU_SSE);
#endif

    if( _cov.isContinuous() && _dst.isContinuous() )
    {
        size.width *= size.height;
        size.height = 1;
    }

    for( i = 0; i < size.height; i++ )
    {
        const float* cov = (const float*)(_cov.data + _cov.step*i);
        float* dst = (float*)(_dst.data + _dst.step*i);
        j = 0;
    #if CV_SSE
        if( simd )
        {
            __m128 half = _mm_set1_ps(0.5f);
            for( ; j <= size.width - 5; j += 4 )
            {
                __m128 t0 = _mm_loadu_ps(cov + j*3); // a0 b0 c0 x
                __m128 t1 = _mm_loadu_ps(cov + j*3 + 3); // a1 b1 c1 x
                __m128 t2 = _mm_loadu_ps(cov + j*3 + 6); // a2 b2 c2 x
                __m128 t3 = _mm_loadu_ps(cov + j*3 + 9); // a3 b3 c3 x
                __m128 a, b, c, t;
                t = _mm_unpacklo_ps(t0, t1); // a0 a1 b0 b1
                c = _mm_unpackhi_ps(t0, t1); // c0 c1 x x
                b = _mm_unpacklo_ps(t2, t3); // a2 a3 b2 b3
                c = _mm_movelh_ps(c, _mm_unpackhi_ps(t2, t3)); // c0 c1 c2 c3
                a = _mm_movelh_ps(t, b);
                b = _mm_movehl_ps(b, t);
                a = _mm_mul_ps(a, half);
                c = _mm_mul_ps(c, half);
                t = _mm_sub_ps(a, c);
                t = _mm_add_ps(_mm_mul_ps(t, t), _mm_mul_ps(b,b));
                a = _mm_sub_ps(_mm_add_ps(a, c), _mm_sqrt_ps(t));
                _mm_storeu_ps(dst + j, a);
            }
        }
    #endif
        for( ; j < size.width; j++ )
        {
            float a = cov[j*3]*0.5f;
            float b = cov[j*3+1];
            float c = cov[j*3+2]*0.5f;
            dst[j] = (float)((a + c) - std::sqrt((a - c)*(a - c) + b*b));
        }
    }
}


static void calcHarris( const Mat& _cov, Mat& _dst, double k )
{
    int i, j;
    Size size = _cov.size();
#if CV_SSE
    volatile bool simd = checkHardwareSupport(CV_CPU_SSE);
#endif

    if( _cov.isContinuous() && _dst.isContinuous() )
    {
        size.width *= size.height;
        size.height = 1;
    }

    for( i = 0; i < size.height; i++ )
    {
        const float* cov = (const float*)(_cov.data + _cov.step*i);
        float* dst = (float*)(_dst.data + _dst.step*i);
        j = 0;

    #if CV_SSE
        if( simd )
        {
            __m128 k4 = _mm_set1_ps((float)k);
            for( ; j <= size.width - 5; j += 4 )
            {
                __m128 t0 = _mm_loadu_ps(cov + j*3); // a0 b0 c0 x
                __m128 t1 = _mm_loadu_ps(cov + j*3 + 3); // a1 b1 c1 x
                __m128 t2 = _mm_loadu_ps(cov + j*3 + 6); // a2 b2 c2 x
                __m128 t3 = _mm_loadu_ps(cov + j*3 + 9); // a3 b3 c3 x
                __m128 a, b, c, t;
                t = _mm_unpacklo_ps(t0, t1); // a0 a1 b0 b1
                c = _mm_unpackhi_ps(t0, t1); // c0 c1 x x
                b = _mm_unpacklo_ps(t2, t3); // a2 a3 b2 b3
                c = _mm_movelh_ps(c, _mm_unpackhi_ps(t2, t3)); // c0 c1 c2 c3
                a = _mm_movelh_ps(t, b);
                b = _mm_movehl_ps(b, t);
                t = _mm_add_ps(a, c);
                a = _mm_sub_ps(_mm_mul_ps(a, c), _mm_mul_ps(b, b));
                t = _mm_mul_ps(_mm_mul_ps(k4, t), t);
                a = _mm_sub_ps(a, t);
                _mm_storeu_ps(dst + j, a);
            }
        }
    #endif

        for( ; j < size.width; j++ )
        {
            float a = cov[j*3];
            float b = cov[j*3+1];
            float c = cov[j*3+2];
            dst[j] = (float)(a*c - b*b - k*(a + c)*(a + c));
        }
    }
}


static void eigen2x2( const float* cov, float* dst, int n )
{
    for( int j = 0; j < n; j++ )
    {
        double a = cov[j*3];
        double b = cov[j*3+1];
        double c = cov[j*3+2];

        double u = (a + c)*0.5;
        double v = std::sqrt((a - c)*(a - c)*0.25 + b*b);
        double l1 = u + v;
        double l2 = u - v;

        double x = b;
        double y = l1 - a;
        double e = fabs(x);

        if( e + fabs(y) < 1e-4 )
        {
            y = b;
            x = l1 - c;
            e = fabs(x);
            if( e + fabs(y) < 1e-4 )
            {
                e = 1./(e + fabs(y) + FLT_EPSILON);
                x *= e, y *= e;
            }
        }

        double d = 1./std::sqrt(x*x + y*y + DBL_EPSILON);
        dst[6*j] = (float)l1;
        dst[6*j + 2] = (float)(x*d);
        dst[6*j + 3] = (float)(y*d);

        x = b;
        y = l2 - a;
        e = fabs(x);

        if( e + fabs(y) < 1e-4 )
        {
            y = b;
            x = l2 - c;
            e = fabs(x);
            if( e + fabs(y) < 1e-4 )
            {
                e = 1./(e + fabs(y) + FLT_EPSILON);
                x *= e, y *= e;
            }
        }

        d = 1./std::sqrt(x*x + y*y + DBL_EPSILON);
        dst[6*j + 1] = (float)l2;
        dst[6*j + 4] = (float)(x*d);
        dst[6*j + 5] = (float)(y*d);
    }
}

static void calcEigenValsVecs( const Mat& _cov, Mat& _dst )
{
    Size size = _cov.size();
    if( _cov.isContinuous() && _dst.isContinuous() )
    {
        size.width *= size.height;
        size.height = 1;
    }

    for( int i = 0; i < size.height; i++ )
    {
        const float* cov = (const float*)(_cov.data + _cov.step*i);
        float* dst = (float*)(_dst.data + _dst.step*i);

        eigen2x2(cov, dst, size.width);
    }
}


enum { MINEIGENVAL=0, HARRIS=1, EIGENVALSVECS=2 };


static void
cornerEigenValsVecs( const Mat& src, Mat& eigenv, int block_size,
                     int aperture_size, int op_type, double k=0.,
                     int borderType=BORDER_DEFAULT )
{
#ifdef HAVE_TEGRA_OPTIMIZATION
    if (tegra::cornerEigenValsVecs(src, eigenv, block_size, aperture_size, op_type, k, borderType))
        return;
#endif

    int depth = src.depth();
    double scale = (double)(1 << ((aperture_size > 0 ? aperture_size : 3) - 1)) * block_size;
    if( aperture_size < 0 )
        scale *= 2.0;
    if( depth == CV_8U )
        scale *= 255.0;
    scale = 1.0/scale;

    CV_Assert( src.type() == CV_8UC1 || src.type() == CV_32FC1 );

    Mat Dx, Dy;
    if( aperture_size > 0 )
    {
        Sobel( src, Dx, CV_32F, 1, 0, aperture_size, scale, 0, borderType );
        Sobel( src, Dy, CV_32F, 0, 1, aperture_size, scale, 0, borderType );
    }
    else
    {
        Scharr( src, Dx, CV_32F, 1, 0, scale, 0, borderType );
        Scharr( src, Dy, CV_32F, 0, 1, scale, 0, borderType );
    }

    Size size = src.size();
    Mat cov( size, CV_32FC3 );
    int i, j;

    for( i = 0; i < size.height; i++ )
    {
        float* cov_data = (float*)(cov.data + i*cov.step);
        const float* dxdata = (const float*)(Dx.data + i*Dx.step);
        const float* dydata = (const float*)(Dy.data + i*Dy.step);

        for( j = 0; j < size.width; j++ )
        {
            float dx = dxdata[j];
            float dy = dydata[j];

            cov_data[j*3] = dx*dx;
            cov_data[j*3+1] = dx*dy;
            cov_data[j*3+2] = dy*dy;
        }
    }

    boxFilter(cov, cov, cov.depth(), Size(block_size, block_size),
        Point(-1,-1), false, borderType );

    if( op_type == MINEIGENVAL )
        calcMinEigenVal( cov, eigenv );
    else if( op_type == HARRIS )
        calcHarris( cov, eigenv, k );
    else if( op_type == EIGENVALSVECS )
        calcEigenValsVecs( cov, eigenv );
}

#ifdef HAVE_OPENCL

static bool extractCovData(InputArray _src, UMat & Dx, UMat & Dy, int depth,
                           float scale, int aperture_size, int borderType)
{
    UMat src = _src.getUMat();

    Size wholeSize;
    Point ofs;
    src.locateROI(wholeSize, ofs);

    const int sobel_lsz = 16;
    if ((aperture_size == 3 || aperture_size == 5 || aperture_size == 7 || aperture_size == -1) &&
        wholeSize.height > sobel_lsz + (aperture_size >> 1) &&
        wholeSize.width > sobel_lsz + (aperture_size >> 1))
    {
        CV_Assert(depth == CV_8U || depth == CV_32F);

        Dx.create(src.size(), CV_32FC1);
        Dy.create(src.size(), CV_32FC1);

        size_t localsize[2] = { sobel_lsz, sobel_lsz };
        size_t globalsize[2] = { localsize[0] * (1 + (src.cols - 1) / localsize[0]),
                                 localsize[1] * (1 + (src.rows - 1) / localsize[1]) };

        int src_offset_x = (int)((src.offset % src.step) / src.elemSize());
        int src_offset_y = (int)(src.offset / src.step);

        const char * const borderTypes[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT",
                                             "BORDER_WRAP", "BORDER_REFLECT101" };

        ocl::Kernel k(format("sobel%d", aperture_size).c_str(), ocl::imgproc::covardata_oclsrc,
                      cv::format("-D BLK_X=%d -D BLK_Y=%d -D %s -D SRCTYPE=%s%s",
                                 (int)localsize[0], (int)localsize[1], borderTypes[borderType], ocl::typeToStr(depth),
                                 aperture_size < 0 ? " -D SCHARR" : ""));
        if (k.empty())
            return false;

        k.args(ocl::KernelArg::PtrReadOnly(src), (int)src.step, src_offset_x, src_offset_y,
               ocl::KernelArg::WriteOnlyNoSize(Dx), ocl::KernelArg::WriteOnly(Dy),
               wholeSize.height, wholeSize.width, scale);

        return k.run(2, globalsize, localsize, false);
    }
    else
    {
        if (aperture_size > 0)
        {
            Sobel(_src, Dx, CV_32F, 1, 0, aperture_size, scale, 0, borderType);
            Sobel(_src, Dy, CV_32F, 0, 1, aperture_size, scale, 0, borderType);
        }
        else
        {
            Scharr(_src, Dx, CV_32F, 1, 0, scale, 0, borderType);
            Scharr(_src, Dy, CV_32F, 0, 1, scale, 0, borderType);
        }
    }

    return true;
}

static bool ocl_cornerMinEigenValVecs(InputArray _src, OutputArray _dst, int block_size,
                                      int aperture_size, double k, int borderType, int op_type)
{
    CV_Assert(op_type == HARRIS || op_type == MINEIGENVAL);

    if ( !(borderType == BORDER_CONSTANT || borderType == BORDER_REPLICATE ||
           borderType == BORDER_REFLECT || borderType == BORDER_REFLECT_101) )
        return false;

    int type = _src.type(), depth = CV_MAT_DEPTH(type);
    if ( !(type == CV_8UC1 || type == CV_32FC1) )
        return false;

    const char * const borderTypes[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT",
                                         "BORDER_WRAP", "BORDER_REFLECT101" };
    const char * const cornerType[] = { "CORNER_MINEIGENVAL", "CORNER_HARRIS", 0 };


    double scale = (double)(1 << ((aperture_size > 0 ? aperture_size : 3) - 1)) * block_size;
    if (aperture_size < 0)
        scale *= 2.0;
    if (depth == CV_8U)
        scale *= 255.0;
    scale = 1.0 / scale;

    UMat Dx, Dy;
    if (!extractCovData(_src, Dx, Dy, depth, (float)scale, aperture_size, borderType))
        return false;

    ocl::Kernel cornelKernel("corner", ocl::imgproc::corner_oclsrc,
                             format("-D anX=%d -D anY=%d -D ksX=%d -D ksY=%d -D %s -D %s",
                                    block_size / 2, block_size / 2, block_size, block_size,
                                    borderTypes[borderType], cornerType[op_type]));
    if (cornelKernel.empty())
        return false;

    _dst.createSameSize(_src, CV_32FC1);
    UMat dst = _dst.getUMat();

    cornelKernel.args(ocl::KernelArg::ReadOnly(Dx), ocl::KernelArg::ReadOnly(Dy),
                      ocl::KernelArg::WriteOnly(dst), (float)k);

    size_t blockSizeX = 256, blockSizeY = 1;
    size_t gSize = blockSizeX - block_size / 2 * 2;
    size_t globalSizeX = (Dx.cols) % gSize == 0 ? Dx.cols / gSize * blockSizeX : (Dx.cols / gSize + 1) * blockSizeX;
    size_t rows_per_thread = 2;
    size_t globalSizeY = ((Dx.rows + rows_per_thread - 1) / rows_per_thread) % blockSizeY == 0 ?
                         ((Dx.rows + rows_per_thread - 1) / rows_per_thread) :
                         (((Dx.rows + rows_per_thread - 1) / rows_per_thread) / blockSizeY + 1) * blockSizeY;

    size_t globalsize[2] = { globalSizeX, globalSizeY }, localsize[2] = { blockSizeX, blockSizeY };
    return cornelKernel.run(2, globalsize, localsize, false);
}

static bool ocl_preCornerDetect( InputArray _src, OutputArray _dst, int ksize, int borderType, int depth )
{
    UMat Dx, Dy, D2x, D2y, Dxy;

    if (!extractCovData(_src, Dx, Dy, depth, 1, ksize, borderType))
        return false;

    Sobel( _src, D2x, CV_32F, 2, 0, ksize, 1, 0, borderType );
    Sobel( _src, D2y, CV_32F, 0, 2, ksize, 1, 0, borderType );
    Sobel( _src, Dxy, CV_32F, 1, 1, ksize, 1, 0, borderType );

    _dst.create( _src.size(), CV_32FC1 );
    UMat dst = _dst.getUMat();

    double factor = 1 << (ksize - 1);
    if( depth == CV_8U )
        factor *= 255;
    factor = 1./(factor * factor * factor);

    ocl::Kernel k("preCornerDetect", ocl::imgproc::precornerdetect_oclsrc);
    if (k.empty())
        return false;

    k.args(ocl::KernelArg::ReadOnlyNoSize(Dx), ocl::KernelArg::ReadOnlyNoSize(Dy),
           ocl::KernelArg::ReadOnlyNoSize(D2x), ocl::KernelArg::ReadOnlyNoSize(D2y),
           ocl::KernelArg::ReadOnlyNoSize(Dxy), ocl::KernelArg::WriteOnly(dst), (float)factor);

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

#endif

}

void cv::cornerMinEigenVal( InputArray _src, OutputArray _dst, int blockSize, int ksize, int borderType )
{
    CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
               ocl_cornerMinEigenValVecs(_src, _dst, blockSize, ksize, 0.0, borderType, MINEIGENVAL))

    Mat src = _src.getMat();
    _dst.create( src.size(), CV_32FC1 );
    Mat dst = _dst.getMat();
    cornerEigenValsVecs( src, dst, blockSize, ksize, MINEIGENVAL, 0, borderType );
}


void cv::cornerHarris( InputArray _src, OutputArray _dst, int blockSize, int ksize, double k, int borderType )
{
    CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
               ocl_cornerMinEigenValVecs(_src, _dst, blockSize, ksize, k, borderType, HARRIS))

    Mat src = _src.getMat();
    _dst.create( src.size(), CV_32FC1 );
    Mat dst = _dst.getMat();

#if IPP_VERSION_X100 >= 801 && !defined HAVE_IPP_ICV_ONLY
    int type = src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
    int borderTypeNI = borderType & ~BORDER_ISOLATED;
    bool isolated = (borderType & BORDER_ISOLATED) != 0;

    if ( (ksize == 3 || ksize == 5) && (type == CV_8UC1 || type == CV_32FC1) &&
        (borderTypeNI == BORDER_CONSTANT || borderTypeNI == BORDER_REPLICATE) && cn == 1 && (!src.isSubmatrix() || isolated) )
    {
        IppiSize roisize = { src.cols, src.rows };
        IppiMaskSize masksize = ksize == 5 ? ippMskSize5x5 : ippMskSize3x3;
        IppDataType datatype = type == CV_8UC1 ? ipp8u : ipp32f;
        Ipp32s bufsize = 0;

        double scale = (double)(1 << ((ksize > 0 ? ksize : 3) - 1)) * blockSize;
        if (ksize < 0)
            scale *= 2.0;
        if (depth == CV_8U)
            scale *= 255.0;
        scale = std::pow(scale, -4.0f);

        if (ippiHarrisCornerGetBufferSize(roisize, masksize, blockSize, datatype, cn, &bufsize) >= 0)
        {
            Ipp8u * buffer = ippsMalloc_8u(bufsize);
            IppiDifferentialKernel filterType = ksize > 0 ? ippFilterSobel : ippFilterScharr;
            IppiBorderType borderTypeIpp = borderTypeNI == BORDER_CONSTANT ? ippBorderConst : ippBorderRepl;
            IppStatus status = (IppStatus)-1;

            if (depth == CV_8U)
                status = ippiHarrisCorner_8u32f_C1R((const Ipp8u *)src.data, (int)src.step, (Ipp32f *)dst.data, (int)dst.step, roisize,
                                                    filterType, masksize, blockSize, (Ipp32f)k, (Ipp32f)scale, borderTypeIpp, 0, buffer);
            else if (depth == CV_32F)
                status = ippiHarrisCorner_32f_C1R((const Ipp32f *)src.data, (int)src.step, (Ipp32f *)dst.data, (int)dst.step, roisize,
                                                  filterType, masksize, blockSize, (Ipp32f)k, (Ipp32f)scale, borderTypeIpp, 0, buffer);
            ippsFree(buffer);

            if (status >= 0)
                return;
        }
    }
#endif

    cornerEigenValsVecs( src, dst, blockSize, ksize, HARRIS, k, borderType );
}


void cv::cornerEigenValsAndVecs( InputArray _src, OutputArray _dst, int blockSize, int ksize, int borderType )
{
    Mat src = _src.getMat();
    Size dsz = _dst.size();
    int dtype = _dst.type();

    if( dsz.height != src.rows || dsz.width*CV_MAT_CN(dtype) != src.cols*6 || CV_MAT_DEPTH(dtype) != CV_32F )
        _dst.create( src.size(), CV_32FC(6) );
    Mat dst = _dst.getMat();
    cornerEigenValsVecs( src, dst, blockSize, ksize, EIGENVALSVECS, 0, borderType );
}


void cv::preCornerDetect( InputArray _src, OutputArray _dst, int ksize, int borderType )
{
    int type = _src.type();
    CV_Assert( type == CV_8UC1 || type == CV_32FC1 );

    CV_OCL_RUN( _src.dims() <= 2 && _dst.isUMat(),
                ocl_preCornerDetect(_src, _dst, ksize, borderType, CV_MAT_DEPTH(type)))

    Mat Dx, Dy, D2x, D2y, Dxy, src = _src.getMat();
    _dst.create( src.size(), CV_32FC1 );
    Mat dst = _dst.getMat();

    Sobel( src, Dx, CV_32F, 1, 0, ksize, 1, 0, borderType );
    Sobel( src, Dy, CV_32F, 0, 1, ksize, 1, 0, borderType );
    Sobel( src, D2x, CV_32F, 2, 0, ksize, 1, 0, borderType );
    Sobel( src, D2y, CV_32F, 0, 2, ksize, 1, 0, borderType );
    Sobel( src, Dxy, CV_32F, 1, 1, ksize, 1, 0, borderType );

    double factor = 1 << (ksize - 1);
    if( src.depth() == CV_8U )
        factor *= 255;
    factor = 1./(factor * factor * factor);

    Size size = src.size();
    int i, j;
    for( i = 0; i < size.height; i++ )
    {
        float* dstdata = (float*)(dst.data + i*dst.step);
        const float* dxdata = (const float*)(Dx.data + i*Dx.step);
        const float* dydata = (const float*)(Dy.data + i*Dy.step);
        const float* d2xdata = (const float*)(D2x.data + i*D2x.step);
        const float* d2ydata = (const float*)(D2y.data + i*D2y.step);
        const float* dxydata = (const float*)(Dxy.data + i*Dxy.step);

        for( j = 0; j < size.width; j++ )
        {
            float dx = dxdata[j];
            float dy = dydata[j];
            dstdata[j] = (float)(factor*(dx*dx*d2ydata[j] + dy*dy*d2xdata[j] - 2*dx*dy*dxydata[j]));
        }
    }
}

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

    CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
    cv::cornerMinEigenVal( src, dst, block_size, aperture_size, cv::BORDER_REPLICATE );
}

CV_IMPL void
cvCornerHarris( const CvArr* srcarr, CvArr* dstarr,
                int block_size, int aperture_size, double k )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);

    CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
    cv::cornerHarris( src, dst, block_size, aperture_size, k, cv::BORDER_REPLICATE );
}


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

    CV_Assert( src.rows == dst.rows && src.cols*6 == dst.cols*dst.channels() && dst.depth() == CV_32F );
    cv::cornerEigenValsAndVecs( src, dst, block_size, aperture_size, cv::BORDER_REPLICATE );
}


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

    CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
    cv::preCornerDetect( src, dst, aperture_size, cv::BORDER_REPLICATE );
}

/* End of file */