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#include "precomp.hpp"
#include "opencv2/core/gpumat.hpp"

#include <iostream>
#include <sstream>

#ifdef HAVE_CUDA
    #include <cuda_runtime.h>
    #include <npp.h>
#endif

using namespace std;
using namespace cv;
using namespace cv::gpu;

cv::gpu::GpuMat::GpuMat(const GpuMat& m) 
    : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend)
{
    if (refcount)
        CV_XADD(refcount, 1);
}

cv::gpu::GpuMat::GpuMat(int rows_, int cols_, int type_, void* data_, size_t step_) : 
    flags(Mat::MAGIC_VAL + (type_ & TYPE_MASK)), rows(rows_), cols(cols_), 
    step(step_), data((uchar*)data_), refcount(0),
    datastart((uchar*)data_), dataend((uchar*)data_)
{
    size_t minstep = cols * elemSize();

    if (step == Mat::AUTO_STEP)
    {
        step = minstep;
        flags |= Mat::CONTINUOUS_FLAG;
    }
    else
    {
        if (rows == 1) 
            step = minstep;

        CV_DbgAssert(step >= minstep);

        flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0;
    }
    dataend += step * (rows - 1) + minstep;
}

cv::gpu::GpuMat::GpuMat(Size size_, int type_, void* data_, size_t step_) : 
    flags(Mat::MAGIC_VAL + (type_ & TYPE_MASK)), rows(size_.height), cols(size_.width),
    step(step_), data((uchar*)data_), refcount(0),
    datastart((uchar*)data_), dataend((uchar*)data_)
{
    size_t minstep = cols * elemSize();

    if (step == Mat::AUTO_STEP)
    {
        step = minstep;
        flags |= Mat::CONTINUOUS_FLAG;
    }
    else
    {
        if (rows == 1) 
            step = minstep;

        CV_DbgAssert(step >= minstep);

        flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0;
    }
    dataend += step * (rows - 1) + minstep;
}

cv::gpu::GpuMat::GpuMat(const GpuMat& m, Range rowRange, Range colRange)
{
    flags = m.flags;
    step = m.step; refcount = m.refcount;
    data = m.data; datastart = m.datastart; dataend = m.dataend;

    if (rowRange == Range::all())
        rows = m.rows;
    else
    {
        CV_Assert(0 <= rowRange.start && rowRange.start <= rowRange.end && rowRange.end <= m.rows);

        rows = rowRange.size();
        data += step*rowRange.start;
    }

    if (colRange == Range::all())
        cols = m.cols;
    else
    {
        CV_Assert(0 <= colRange.start && colRange.start <= colRange.end && colRange.end <= m.cols);

        cols = colRange.size();
        data += colRange.start*elemSize();
        flags &= cols < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
    }

    if (rows == 1)
        flags |= Mat::CONTINUOUS_FLAG;

    if (refcount)
        CV_XADD(refcount, 1);

    if (rows <= 0 || cols <= 0)
        rows = cols = 0;
}

cv::gpu::GpuMat::GpuMat(const GpuMat& m, Rect roi) : 
    flags(m.flags), rows(roi.height), cols(roi.width),
    step(m.step), data(m.data + roi.y*step), refcount(m.refcount),
    datastart(m.datastart), dataend(m.dataend)
{
    flags &= roi.width < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
    data += roi.x * elemSize();

    CV_Assert(0 <= roi.x && 0 <= roi.width && roi.x + roi.width <= m.cols && 0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows);

    if (refcount)
        CV_XADD(refcount, 1);

    if (rows <= 0 || cols <= 0)
        rows = cols = 0;
}

cv::gpu::GpuMat::GpuMat(const Mat& m) : 
    flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) 
{ 
    upload(m); 
}

GpuMat& cv::gpu::GpuMat::operator = (const GpuMat& m)
{
    if (this != &m)
    {
        GpuMat temp(m);
        swap(temp);
    }

    return *this;
}

void cv::gpu::GpuMat::swap(GpuMat& b)
{
    std::swap(flags, b.flags);
    std::swap(rows, b.rows); 
    std::swap(cols, b.cols);
    std::swap(step, b.step); 
    std::swap(data, b.data);
    std::swap(datastart, b.datastart);
    std::swap(dataend, b.dataend);
    std::swap(refcount, b.refcount);
}

void cv::gpu::GpuMat::locateROI(Size& wholeSize, Point& ofs) const
{
    size_t esz = elemSize();
    ptrdiff_t delta1 = data - datastart;
    ptrdiff_t delta2 = dataend - datastart;

    CV_DbgAssert(step > 0);

    if (delta1 == 0)
        ofs.x = ofs.y = 0;
    else
    {
        ofs.y = static_cast<int>(delta1 / step);
        ofs.x = static_cast<int>((delta1 - step * ofs.y) / esz);

        CV_DbgAssert(data == datastart + ofs.y * step + ofs.x * esz);
    }

    size_t minstep = (ofs.x + cols) * esz;

    wholeSize.height = std::max(static_cast<int>((delta2 - minstep) / step + 1), ofs.y + rows);
    wholeSize.width = std::max(static_cast<int>((delta2 - step * (wholeSize.height - 1)) / esz), ofs.x + cols);
}

GpuMat& cv::gpu::GpuMat::adjustROI(int dtop, int dbottom, int dleft, int dright)
{
    Size wholeSize; 
    Point ofs;
    locateROI(wholeSize, ofs);

    size_t esz = elemSize();

    int row1 = std::max(ofs.y - dtop, 0); 
    int row2 = std::min(ofs.y + rows + dbottom, wholeSize.height);

    int col1 = std::max(ofs.x - dleft, 0);
    int col2 = std::min(ofs.x + cols + dright, wholeSize.width);

    data += (row1 - ofs.y) * step + (col1 - ofs.x) * esz;
    rows = row2 - row1; 
    cols = col2 - col1;

    if (esz * cols == step || rows == 1)
        flags |= Mat::CONTINUOUS_FLAG;
    else
        flags &= ~Mat::CONTINUOUS_FLAG;

    return *this;
}

GpuMat cv::gpu::GpuMat::reshape(int new_cn, int new_rows) const
{
    GpuMat hdr = *this;

    int cn = channels();
    if (new_cn == 0)
        new_cn = cn;

    int total_width = cols * cn;

    if ((new_cn > total_width || total_width % new_cn != 0) && new_rows == 0)
        new_rows = rows * total_width / new_cn;

    if (new_rows != 0 && new_rows != rows)
    {
        int total_size = total_width * rows;

        if (!isContinuous())
            CV_Error(CV_BadStep, "The matrix is not continuous, thus its number of rows can not be changed");

        if ((unsigned)new_rows > (unsigned)total_size)
            CV_Error(CV_StsOutOfRange, "Bad new number of rows");

        total_width = total_size / new_rows;

        if (total_width * new_rows != total_size)
            CV_Error(CV_StsBadArg, "The total number of matrix elements is not divisible by the new number of rows");

        hdr.rows = new_rows;
        hdr.step = total_width * elemSize1();
    }

    int new_width = total_width / new_cn;

    if (new_width * new_cn != total_width)
        CV_Error(CV_BadNumChannels, "The total width is not divisible by the new number of channels");

    hdr.cols = new_width;
    hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn - 1) << CV_CN_SHIFT);

    return hdr;
}

cv::Mat::Mat(const GpuMat& m) : flags(0), dims(0), rows(0), cols(0), data(0), refcount(0), datastart(0), dataend(0), datalimit(0), allocator(0), size(&rows)
{
    m.download(*this);
}

namespace
{
    class CV_EXPORTS GpuFuncTable
    {
    public:
        virtual ~GpuFuncTable() {}

        virtual void copy(const Mat& src, GpuMat& dst) const = 0;
        virtual void copy(const GpuMat& src, Mat& dst) const = 0;
        virtual void copy(const GpuMat& src, GpuMat& dst) const = 0;

        virtual void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const = 0;

        virtual void convert(const GpuMat& src, GpuMat& dst) const = 0;
        virtual void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta) const = 0;

        virtual void setTo(GpuMat& m, Scalar s, const GpuMat& mask) const = 0;

        virtual void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const = 0;
        virtual void free(void* devPtr) const = 0;
    };
}

#ifndef HAVE_CUDA

namespace
{
    void throw_nogpu() 
    { 
        CV_Error(CV_GpuNotSupported, "The library is compiled without GPU support"); 
    }

    class EmptyFuncTable : public GpuFuncTable
    {
    public:
        void copy(const Mat&, GpuMat&) const { throw_nogpu(); }
        void copy(const GpuMat&, Mat&) const { throw_nogpu(); }
        void copy(const GpuMat&, GpuMat&) const { throw_nogpu(); }

        void copyWithMask(const GpuMat&, GpuMat&, const GpuMat&) const { throw_nogpu(); }

        void convert(const GpuMat&, GpuMat&) const { throw_nogpu(); }
        void convert(const GpuMat&, GpuMat&, double, double) const { throw_nogpu(); }

        void setTo(GpuMat&, Scalar, const GpuMat&) const { throw_nogpu(); }

        void mallocPitch(void**, size_t*, size_t, size_t) const { throw_nogpu(); }
        void free(void*) const {}
    };

    const GpuFuncTable* gpuFuncTable()
    {
        static EmptyFuncTable empty;
        return &empty;
    }
}

#else // HAVE_CUDA

namespace cv { namespace gpu { namespace device 
{
    void copy_to_with_mask(DevMem2Db src, DevMem2Db dst, int depth, DevMem2Db mask, int channels, cudaStream_t stream);

    template <typename T>
    void set_to_gpu(DevMem2Db mat, const T* scalar, int channels, cudaStream_t stream);

    template <typename T>
    void set_to_gpu(DevMem2Db mat, const T* scalar, DevMem2Db mask, int channels, cudaStream_t stream);

    void convert_gpu(DevMem2Db src, int sdepth, DevMem2Db dst, int ddepth, double alpha, double beta, cudaStream_t stream);
}}}

namespace
{
#if defined(__GNUC__)
    #define cudaSafeCall(expr)  ___cudaSafeCall(expr, __FILE__, __LINE__, __func__)
    #define nppSafeCall(expr)  ___nppSafeCall(expr, __FILE__, __LINE__, __func__)
#else /* defined(__CUDACC__) || defined(__MSVC__) */
    #define cudaSafeCall(expr)  ___cudaSafeCall(expr, __FILE__, __LINE__)
    #define nppSafeCall(expr)  ___nppSafeCall(expr, __FILE__, __LINE__)
#endif

    inline void ___cudaSafeCall(cudaError_t err, const char *file, const int line, const char *func = "")
    {
        if (cudaSuccess != err)
            cv::gpu::error(cudaGetErrorString(err), file, line, func);
    }

    inline void ___nppSafeCall(int err, const char *file, const int line, const char *func = "")
    {
        if (err < 0)
        {
            std::ostringstream msg;
            msg << "NPP API Call Error: " << err;
            cv::gpu::error(msg.str().c_str(), file, line, func);
        }
    }
}

namespace
{
    template <typename T> void kernelSetCaller(GpuMat& src, Scalar s, cudaStream_t stream)
    {
        Scalar_<T> sf = s;
        ::cv::gpu::device::set_to_gpu(src, sf.val, src.channels(), stream);
    }

    template <typename T> void kernelSetCaller(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
    {
        Scalar_<T> sf = s;
        ::cv::gpu::device::set_to_gpu(src, sf.val, mask, src.channels(), stream);
    }
}

namespace cv { namespace gpu
{
    CV_EXPORTS void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream = 0) 
    { 
        ::cv::gpu::device::copy_to_with_mask(src, dst, src.depth(), mask, src.channels(), stream);
    }

    CV_EXPORTS void convertTo(const GpuMat& src, GpuMat& dst)
    {
        ::cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), 1.0, 0.0, 0);
    }  

    CV_EXPORTS void convertTo(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream = 0)
    {
        ::cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), alpha, beta, stream);
    }

    CV_EXPORTS void setTo(GpuMat& src, Scalar s, cudaStream_t stream)
    {
        typedef void (*caller_t)(GpuMat& src, Scalar s, cudaStream_t stream);

        static const caller_t callers[] = 
        {
            kernelSetCaller<uchar>, kernelSetCaller<schar>, kernelSetCaller<ushort>, kernelSetCaller<short>, kernelSetCaller<int>,
            kernelSetCaller<float>, kernelSetCaller<double>
        };

        callers[src.depth()](src, s, stream);
    }

    CV_EXPORTS void setTo(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
    {
        typedef void (*caller_t)(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream);

        static const caller_t callers[] = 
        {
            kernelSetCaller<uchar>, kernelSetCaller<schar>, kernelSetCaller<ushort>, kernelSetCaller<short>, kernelSetCaller<int>,
            kernelSetCaller<float>, kernelSetCaller<double>
        };

        callers[src.depth()](src, s, mask, stream);
    }

    CV_EXPORTS void setTo(GpuMat& src, Scalar s)
    {
        setTo(src, s, 0);
    }

    CV_EXPORTS void setTo(GpuMat& src, Scalar s, const GpuMat& mask)
    {
        setTo(src, s, mask, 0);
    }
}}

namespace
{
    //////////////////////////////////////////////////////////////////////////
    // Convert

    template<int n> struct NPPTypeTraits;
    template<> struct NPPTypeTraits<CV_8U>  { typedef Npp8u npp_type; };
    template<> struct NPPTypeTraits<CV_16U> { typedef Npp16u npp_type; };
    template<> struct NPPTypeTraits<CV_16S> { typedef Npp16s npp_type; };
    template<> struct NPPTypeTraits<CV_32S> { typedef Npp32s npp_type; };
    template<> struct NPPTypeTraits<CV_32F> { typedef Npp32f npp_type; };

    template<int SDEPTH, int DDEPTH> struct NppConvertFunc
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;

        typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI);
    };
    template<int DDEPTH> struct NppConvertFunc<CV_32F, DDEPTH>
    {
        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;

        typedef NppStatus (*func_ptr)(const Npp32f* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI, NppRoundMode eRoundMode);
    };

    template<int SDEPTH, int DDEPTH, typename NppConvertFunc<SDEPTH, DDEPTH>::func_ptr func> struct NppCvt
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;

        static void cvt(const GpuMat& src, GpuMat& dst)
        {
            NppiSize sz;
            sz.width = src.cols;
            sz.height = src.rows;
            nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz) );

            cudaSafeCall( cudaDeviceSynchronize() );
        }
    };
    template<int DDEPTH, typename NppConvertFunc<CV_32F, DDEPTH>::func_ptr func> struct NppCvt<CV_32F, DDEPTH, func>
    {
        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;

        static void cvt(const GpuMat& src, GpuMat& dst)
        {
            NppiSize sz;
            sz.width = src.cols;
            sz.height = src.rows;
            nppSafeCall( func(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz, NPP_RND_NEAR) );

            cudaSafeCall( cudaDeviceSynchronize() );
        }
    };    

    //////////////////////////////////////////////////////////////////////////
    // Set
    
    template<int SDEPTH, int SCN> struct NppSetFunc
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;

        typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
    };
    template<int SDEPTH> struct NppSetFunc<SDEPTH, 1>
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;

        typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
    };

    template<int SDEPTH, int SCN, typename NppSetFunc<SDEPTH, SCN>::func_ptr func> struct NppSet
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;

        static void set(GpuMat& src, Scalar s)
        {
            NppiSize sz;
            sz.width = src.cols;
            sz.height = src.rows;

            Scalar_<src_t> nppS = s;

            nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz) );

            cudaSafeCall( cudaDeviceSynchronize() );
        }
    };
    template<int SDEPTH, typename NppSetFunc<SDEPTH, 1>::func_ptr func> struct NppSet<SDEPTH, 1, func>
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;

        static void set(GpuMat& src, Scalar s)
        {
            NppiSize sz;
            sz.width = src.cols;
            sz.height = src.rows;

            Scalar_<src_t> nppS = s;

            nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz) );

            cudaSafeCall( cudaDeviceSynchronize() );
        }
    };    

    template<int SDEPTH, int SCN> struct NppSetMaskFunc
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;

        typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
    };
    template<int SDEPTH> struct NppSetMaskFunc<SDEPTH, 1>
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;

        typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
    };

    template<int SDEPTH, int SCN, typename NppSetMaskFunc<SDEPTH, SCN>::func_ptr func> struct NppSetMask
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;

        static void set(GpuMat& src, Scalar s, const GpuMat& mask)
        {
            NppiSize sz;
            sz.width = src.cols;
            sz.height = src.rows;

            Scalar_<src_t> nppS = s;

            nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );

            cudaSafeCall( cudaDeviceSynchronize() );
        }
    };
    template<int SDEPTH, typename NppSetMaskFunc<SDEPTH, 1>::func_ptr func> struct NppSetMask<SDEPTH, 1, func>
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;

        static void set(GpuMat& src, Scalar s, const GpuMat& mask)
        {
            NppiSize sz;
            sz.width = src.cols;
            sz.height = src.rows;

            Scalar_<src_t> nppS = s;

            nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );

            cudaSafeCall( cudaDeviceSynchronize() );
        }
    };    

    class CudaFuncTable : public GpuFuncTable
    {
    public:
        void copy(const Mat& src, GpuMat& dst) const 
        { 
            cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyHostToDevice) );
        }
        void copy(const GpuMat& src, Mat& dst) const
        { 
            cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToHost) );
        }
        void copy(const GpuMat& src, GpuMat& dst) const
        { 
            cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToDevice) );
        }

        void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const 
        { 
            ::cv::gpu::copyWithMask(src, dst, mask);
        }

        void convert(const GpuMat& src, GpuMat& dst) const 
        { 
            typedef void (*caller_t)(const GpuMat& src, GpuMat& dst);
            static const caller_t callers[7][7][7] =
            {
                {                
                    /*  8U ->  8U */ {0, 0, 0, 0},
                    /*  8U ->  8S */ {::cv::gpu::convertTo, ::cv::gpu::convertTo, ::cv::gpu::convertTo, ::cv::gpu::convertTo},
                    /*  8U -> 16U */ {NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C4R>::cvt},
                    /*  8U -> 16S */ {NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C4R>::cvt},
                    /*  8U -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /*  8U -> 32F */ {NppCvt<CV_8U, CV_32F, nppiConvert_8u32f_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /*  8U -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
                },
                {
                    /*  8S ->  8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /*  8S ->  8S */ {0,0,0,0},
                    /*  8S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /*  8S -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /*  8S -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /*  8S -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /*  8S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
                },
                {
                    /* 16U ->  8U */ {NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C4R>::cvt},
                    /* 16U ->  8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 16U -> 16U */ {0,0,0,0},
                    /* 16U -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 16U -> 32S */ {NppCvt<CV_16U, CV_32S, nppiConvert_16u32s_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 16U -> 32F */ {NppCvt<CV_16U, CV_32F, nppiConvert_16u32f_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 16U -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
                },
                {
                    /* 16S ->  8U */ {NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C4R>::cvt},
                    /* 16S ->  8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 16S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 16S -> 16S */ {0,0,0,0},
                    /* 16S -> 32S */ {NppCvt<CV_16S, CV_32S, nppiConvert_16s32s_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 16S -> 32F */ {NppCvt<CV_16S, CV_32F, nppiConvert_16s32f_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 16S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
                },
                {
                    /* 32S ->  8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32S ->  8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32S -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32S -> 32S */ {0,0,0,0},
                    /* 32S -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
                },
                {
                    /* 32F ->  8U */ {NppCvt<CV_32F, CV_8U, nppiConvert_32f8u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32F ->  8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32F -> 16U */ {NppCvt<CV_32F, CV_16U, nppiConvert_32f16u_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32F -> 16S */ {NppCvt<CV_32F, CV_16S, nppiConvert_32f16s_C1R>::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32F -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 32F -> 32F */ {0,0,0,0},
                    /* 32F -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}
                },
                {
                    /* 64F ->  8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 64F ->  8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 64F -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 64F -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 64F -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 64F -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo},
                    /* 64F -> 64F */ {0,0,0,0}
                }
            };

            caller_t func = callers[src.depth()][dst.depth()][src.channels() - 1];
            CV_DbgAssert(func != 0);

            func(src, dst);
        }

        void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta) const 
        { 
            ::cv::gpu::convertTo(src, dst, alpha, beta);
        }

        void setTo(GpuMat& m, Scalar s, const GpuMat& mask) const
        {
            NppiSize sz;
            sz.width  = m.cols;
            sz.height = m.rows;

            if (mask.empty())
            {
                if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0)
                {
                    cudaSafeCall( cudaMemset2D(m.data, m.step, 0, m.cols * m.elemSize(), m.rows) );
                    return;
                }

                if (m.depth() == CV_8U)
                {
                    int cn = m.channels();

                    if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3]))
                    {
                        int val = saturate_cast<uchar>(s[0]);
                        cudaSafeCall( cudaMemset2D(m.data, m.step, val, m.cols * m.elemSize(), m.rows) );
                        return;
                    }
                }

                typedef void (*caller_t)(GpuMat& src, Scalar s);
                static const caller_t callers[7][4] =
                {
                    {NppSet<CV_8U, 1, nppiSet_8u_C1R>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet<CV_8U, 4, nppiSet_8u_C4R>::set},
                    {::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo},
                    {NppSet<CV_16U, 1, nppiSet_16u_C1R>::set, NppSet<CV_16U, 2, nppiSet_16u_C2R>::set, ::cv::gpu::setTo, NppSet<CV_16U, 4, nppiSet_16u_C4R>::set},
                    {NppSet<CV_16S, 1, nppiSet_16s_C1R>::set, NppSet<CV_16S, 2, nppiSet_16s_C2R>::set, ::cv::gpu::setTo, NppSet<CV_16S, 4, nppiSet_16s_C4R>::set},
                    {NppSet<CV_32S, 1, nppiSet_32s_C1R>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet<CV_32S, 4, nppiSet_32s_C4R>::set},
                    {NppSet<CV_32F, 1, nppiSet_32f_C1R>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet<CV_32F, 4, nppiSet_32f_C4R>::set},
                    {::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo}
                };

                callers[m.depth()][m.channels() - 1](m, s);
            }
            else
            {
                typedef void (*caller_t)(GpuMat& src, Scalar s, const GpuMat& mask);

                static const caller_t callers[7][4] =
                {
                    {NppSetMask<CV_8U, 1, nppiSet_8u_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_8U, 4, nppiSet_8u_C4MR>::set},
                    {::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo},
                    {NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::set},
                    {NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::set},
                    {NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::set},
                    {NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::set},
                    {::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo}
                };

                callers[m.depth()][m.channels() - 1](m, s, mask);
            }
        }

        void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const
        {
            cudaSafeCall( cudaMallocPitch(devPtr, step, width, height) );
        }

        void free(void* devPtr) const
        {
            cudaFree(devPtr);
        }
    };
    
    const GpuFuncTable* gpuFuncTable()
    {
        static CudaFuncTable funcTable;
        return &funcTable;
    }
}

#endif // HAVE_CUDA

void cv::gpu::GpuMat::upload(const Mat& m)
{
    CV_DbgAssert(!m.empty());

    create(m.size(), m.type());

    gpuFuncTable()->copy(m, *this);
}

void cv::gpu::GpuMat::download(Mat& m) const
{
    CV_DbgAssert(!empty());

    m.create(size(), type());

    gpuFuncTable()->copy(*this, m);
}

void cv::gpu::GpuMat::copyTo(GpuMat& m) const
{
    CV_DbgAssert(!empty());

    m.create(size(), type());

    gpuFuncTable()->copy(*this, m);
}

void cv::gpu::GpuMat::copyTo(GpuMat& mat, const GpuMat& mask) const
{
    if (mask.empty())
        copyTo(mat);
    else
    {
        mat.create(size(), type());

        gpuFuncTable()->copyWithMask(*this, mat, mask);
    }
}

void cv::gpu::GpuMat::convertTo(GpuMat& dst, int rtype, double alpha, double beta) const
{
    bool noScale = fabs(alpha - 1) < numeric_limits<double>::epsilon() && fabs(beta) < numeric_limits<double>::epsilon();

    if (rtype < 0)
        rtype = type();
    else
        rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), channels());

    int sdepth = depth();
    int ddepth = CV_MAT_DEPTH(rtype);
    if (sdepth == ddepth && noScale)
    {
        copyTo(dst);
        return;
    }

    GpuMat temp;
    const GpuMat* psrc = this;
    if (sdepth != ddepth && psrc == &dst)
    {
        temp = *this;
        psrc = &temp;
    }

    dst.create(size(), rtype);

    if (noScale)
        gpuFuncTable()->convert(*psrc, dst);
    else
        gpuFuncTable()->convert(*psrc, dst, alpha, beta);
}

GpuMat& cv::gpu::GpuMat::setTo(Scalar s, const GpuMat& mask)
{
    CV_Assert(mask.empty() || mask.type() == CV_8UC1);
    CV_DbgAssert(!empty());

    gpuFuncTable()->setTo(*this, s, mask);    

    return *this;
}

void cv::gpu::GpuMat::create(int _rows, int _cols, int _type)
{
    _type &= TYPE_MASK;

    if (rows == _rows && cols == _cols && type() == _type && data)
        return;

    if (data)
        release();

    CV_DbgAssert(_rows >= 0 && _cols >= 0);

    if (_rows > 0 && _cols > 0)
    {
        flags = Mat::MAGIC_VAL + _type;
        rows = _rows;
        cols = _cols;

        size_t esz = elemSize();

        void* devPtr;
        gpuFuncTable()->mallocPitch(&devPtr, &step, esz * cols, rows);

        // Single row must be continuous
        if (rows == 1)
            step = esz * cols;

        if (esz * cols == step)
            flags |= Mat::CONTINUOUS_FLAG;

        int64 _nettosize = static_cast<int64>(step) * rows;
        size_t nettosize = static_cast<size_t>(_nettosize);

        datastart = data = static_cast<uchar*>(devPtr);
        dataend = data + nettosize;

        refcount = static_cast<int*>(fastMalloc(sizeof(*refcount)));
        *refcount = 1;
    }
}

void cv::gpu::GpuMat::release()
{
    if (refcount && CV_XADD(refcount, -1) == 1)
    {
        fastFree(refcount);

        gpuFuncTable()->free(datastart);
    }

    data = datastart = dataend = 0;
    step = rows = cols = 0;
    refcount = 0;
}

void cv::gpu::error(const char *error_string, const char *file, const int line, const char *func)
{
    int code = CV_GpuApiCallError;

    if (uncaught_exception())
    {
        const char* errorStr = cvErrorStr(code);            
        const char* function = func ? func : "unknown function";    

        cerr << "OpenCV Error: " << errorStr << "(" << error_string << ") in " << function << ", file " << file << ", line " << line;
        cerr.flush();            
    }
    else    
        cv::error( cv::Exception(code, error_string, func, file, line) );
}