namespace
{
#if defined(HAVE_CUDA) && !defined(DYNAMIC_CUDA_SUPPORT)

    #define cudaSafeCall(expr)  ___cudaSafeCall(expr, __FILE__, __LINE__, CV_Func)
    #define nppSafeCall(expr)  ___nppSafeCall(expr, __FILE__, __LINE__, CV_Func)

    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);
        }
    }
#endif
}

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

        // DeviceInfo routines
        virtual int getCudaEnabledDeviceCount() const = 0;

        virtual void setDevice(int) const = 0;
        virtual int getDevice() const = 0;

        virtual void resetDevice() const  = 0;

        virtual bool deviceSupports(FeatureSet) const = 0;

        virtual bool builtWith(FeatureSet) const = 0;
        virtual bool has(int, int) const = 0;
        virtual bool hasPtx(int, int) const = 0;
        virtual bool hasBin(int, int) const = 0;
        virtual bool hasEqualOrLessPtx(int, int) const = 0;
        virtual bool hasEqualOrGreater(int, int) const = 0;
        virtual bool hasEqualOrGreaterPtx(int, int) const = 0;
        virtual bool hasEqualOrGreaterBin(int, int) const = 0;

        virtual size_t sharedMemPerBlock() const = 0;
        virtual void queryMemory(size_t&, size_t&) const = 0;
        virtual size_t freeMemory() const = 0;
        virtual size_t totalMemory() const = 0;
        virtual bool supports(FeatureSet) const = 0;
        virtual bool isCompatible() const = 0;
        virtual void query() const = 0;

        virtual void printCudaDeviceInfo(int) const = 0;
        virtual void printShortCudaDeviceInfo(int) const = 0;
        
        // GpuMat routines
        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;

        // gpu::device::convertTo funcs
        virtual void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream = 0) const = 0;
        virtual void convert(const GpuMat& src, GpuMat& dst) const = 0;

        // for gpu::device::setTo funcs
        virtual void setTo(cv::gpu::GpuMat&, cv::Scalar, CUstream_st*) const = 0;
        virtual void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&, CUstream_st*) 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;
    };
}

#if !defined(HAVE_CUDA) || defined(DYNAMIC_CUDA_SUPPORT)
namespace
{
    class EmptyFuncTable : public GpuFuncTable
    {
    public:
        
        // DeviceInfo routines
        int getCudaEnabledDeviceCount() const { return 0; }
        
        void setDevice(int) const { throw_nogpu; }
        int getDevice() const { throw_nogpu; return 0; }
        
        void resetDevice() const { throw_nogpu; }
        
        bool deviceSupports(FeatureSet) const { throw_nogpu; return false; }

        bool builtWith(FeatureSet) const { throw_nogpu; return false; }
        bool has(int, int) const { throw_nogpu; return false; }
        bool hasPtx(int, int) const { throw_nogpu; return false; }
        bool hasBin(int, int) const { throw_nogpu; return false; }
        bool hasEqualOrLessPtx(int, int) const { throw_nogpu; return false; }
        bool hasEqualOrGreater(int, int) const { throw_nogpu; return false; }
        bool hasEqualOrGreaterPtx(int, int) const { throw_nogpu; return false; }
        bool hasEqualOrGreaterBin(int, int) const { throw_nogpu; return false; }
        
        size_t sharedMemPerBlock() const { throw_nogpu; return 0; }
        void queryMemory(size_t&, size_t&) const { throw_nogpu; }
        size_t freeMemory() const { throw_nogpu; return 0; }
        size_t totalMemory() const { throw_nogpu; return 0; }
        bool supports(FeatureSet) const { throw_nogpu; return false; }
        bool isCompatible() const { throw_nogpu; return false; }
        void query() const { throw_nogpu; }
        
        void printCudaDeviceInfo(int) const { throw_nogpu; }
        void printShortCudaDeviceInfo(int) const { throw_nogpu; }
        
        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, cudaStream_t stream = 0) const { (void)stream; throw_nogpu; }

        virtual void setTo(cv::gpu::GpuMat&, cv::Scalar, CUstream_st*) const { throw_nogpu; }
        virtual void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&, CUstream_st*) const { throw_nogpu; }

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

#else

namespace cv { namespace gpu { namespace device
{
    void copyToWithMask_gpu(PtrStepSzb src, PtrStepSzb dst, size_t elemSize1, int cn, PtrStepSzb mask, bool colorMask, cudaStream_t stream);

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

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

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

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
{
    template<int n> struct NPPTypeTraits;
    template<> struct NPPTypeTraits<CV_8U>  { typedef Npp8u npp_type; };
    template<> struct NPPTypeTraits<CV_8S>  { typedef Npp8s 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<> struct NPPTypeTraits<CV_64F> { typedef Npp64f npp_type; };

    //////////////////////////////////////////////////////////////////////////
    // Convert

    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 call(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 call(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 SCN> struct NppSetFunc<CV_8S, SCN>
    {
        typedef NppStatus (*func_ptr)(Npp8s values[], Npp8s* pSrc, int nSrcStep, NppiSize oSizeROI);
    };
    template<> struct NppSetFunc<CV_8S, 1>
    {
        typedef NppStatus (*func_ptr)(Npp8s val, Npp8s* 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 call(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 call(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 call(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 call(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() );
        }
    };
    
    //////////////////////////////////////////////////////////////////////////
    // CopyMasked
    
    template<int SDEPTH> struct NppCopyMaskedFunc
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
        
        typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, src_t* pDst, int nDstStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
    };
    
    template<int SDEPTH, typename NppCopyMaskedFunc<SDEPTH>::func_ptr func> struct NppCopyMasked
    {
        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
        
        static void call(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t /*stream*/)
        {
            NppiSize sz;
            sz.width = src.cols;
            sz.height = src.rows;
            
            nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<src_t>(), static_cast<int>(dst.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
            
            cudaSafeCall( cudaDeviceSynchronize() );
        }
    };
    
    template <typename T> static inline bool isAligned(const T* ptr, size_t size)
    {
        return reinterpret_cast<size_t>(ptr) % size == 0;
    }
}
     
    namespace cv { namespace gpu { namespace devices
    {
        void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream = 0)
        {
            CV_Assert(src.size() == dst.size() && src.type() == dst.type());
            CV_Assert(src.size() == mask.size() && mask.depth() == CV_8U && (mask.channels() == 1 || mask.channels() == src.channels()));
            
            cv::gpu::device::copyToWithMask_gpu(src.reshape(1), dst.reshape(1), src.elemSize1(), src.channels(), mask.reshape(1), mask.channels() != 1, stream);
        }
        
        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);
        }
        
        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);
        }
        
        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);
        }
        
        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);
        }
        
        void setTo(GpuMat& src, Scalar s)
        {
            setTo(src, s, 0);
        }
        
        void setTo(GpuMat& src, Scalar s, const GpuMat& mask)
        {
            setTo(src, s, mask, 0);
        }
    }}

namespace
{
    class CudaFuncTable : public GpuFuncTable
    {
    protected:
        
        class CudaArch
        {
        public:
            CudaArch();
            
            bool builtWith(FeatureSet feature_set) const;
            bool hasPtx(int major, int minor) const;
            bool hasBin(int major, int minor) const;
            bool hasEqualOrLessPtx(int major, int minor) const;
            bool hasEqualOrGreaterPtx(int major, int minor) const;
            bool hasEqualOrGreaterBin(int major, int minor) const;
            
        private:
            static void fromStr(const string& set_as_str, vector<int>& arr);
            
            vector<int> bin;
            vector<int> ptx;
            vector<int> features;
        };
        
        const CudaArch cudaArch;
        
        CudaArch::CudaArch()
        {
            fromStr(CUDA_ARCH_BIN, bin);
            fromStr(CUDA_ARCH_PTX, ptx);
            fromStr(CUDA_ARCH_FEATURES, features);
        }
        
        bool CudaArch::builtWith(FeatureSet feature_set) const
        {
            return !features.empty() && (features.back() >= feature_set);
        }
        
        bool CudaArch::hasPtx(int major, int minor) const
        {
            return find(ptx.begin(), ptx.end(), major * 10 + minor) != ptx.end();
        }
        
        bool CudaArch::hasBin(int major, int minor) const
        {
            return find(bin.begin(), bin.end(), major * 10 + minor) != bin.end();
        }
        
        bool CudaArch::hasEqualOrLessPtx(int major, int minor) const
        {
            return !ptx.empty() && (ptx.front() <= major * 10 + minor);
        }
        
        bool CudaArch::hasEqualOrGreaterPtx(int major, int minor) const
        {
            return !ptx.empty() && (ptx.back() >= major * 10 + minor);
        }
        
        bool CudaArch::hasEqualOrGreaterBin(int major, int minor) const
        {
            return !bin.empty() && (bin.back() >= major * 10 + minor);
        }
        
        void CudaArch::fromStr(const string& set_as_str, vector<int>& arr)
        {
            if (set_as_str.find_first_not_of(" ") == string::npos)
                return;
            
            istringstream stream(set_as_str);
            int cur_value;
            
            while (!stream.eof())
            {
                stream >> cur_value;
                arr.push_back(cur_value);
            }
            
            sort(arr.begin(), arr.end());
        }

        class DeviceProps
        {
        public:
            DeviceProps();
            ~DeviceProps();
            
            cudaDeviceProp* get(int devID);
            
        private:
            std::vector<cudaDeviceProp*> props_;
        };
        
        DeviceProps::DeviceProps()
        {
            props_.resize(10, 0);
        }
        
        DeviceProps::~DeviceProps()
        {
            for (size_t i = 0; i < props_.size(); ++i)
            {
                if (props_[i])
                    delete props_[i];
            }
            props_.clear();
        }
        
        cudaDeviceProp* DeviceProps::get(int devID)
        {
            if (devID >= (int) props_.size())
                props_.resize(devID + 5, 0);
            
            if (!props_[devID])
            {
                props_[devID] = new cudaDeviceProp;
                cudaSafeCall( cudaGetDeviceProperties(props_[devID], devID) );
            }
            
            return props_[devID];
        }
        
        DeviceProps deviceProps;

        int convertSMVer2Cores(int major, int minor)
        {
            // Defines for GPU Architecture types (using the SM version to determine the # of cores per SM
            typedef struct {
                int SM; // 0xMm (hexidecimal notation), M = SM Major version, and m = SM minor version
                int Cores;
            } SMtoCores;
            
            SMtoCores gpuArchCoresPerSM[] =  { { 0x10,  8 }, { 0x11,  8 }, { 0x12,  8 }, { 0x13,  8 }, { 0x20, 32 }, { 0x21, 48 }, {0x30, 192}, {0x35, 192}, { -1, -1 }  };
            
            int index = 0;
            while (gpuArchCoresPerSM[index].SM != -1)
            {
                if (gpuArchCoresPerSM[index].SM == ((major << 4) + minor) )
                    return gpuArchCoresPerSM[index].Cores;
                index++;
            }
            
            return -1;
        }
        
    public:

        int getCudaEnabledDeviceCount() const
        {
            int count;
            cudaError_t error = cudaGetDeviceCount( &count );
            
            if (error == cudaErrorInsufficientDriver)
                return -1;
            
            if (error == cudaErrorNoDevice)
                return 0;
            
            cudaSafeCall( error );
            return count;
        }
        
        void setDevice(int device) const
        {
            cudaSafeCall( cudaSetDevice( device ) );
        }
        
        int getDevice() const
        {
            int device;
            cudaSafeCall( cudaGetDevice( &device ) );
            return device;
        }
        
        void resetDevice() const
        {
            cudaSafeCall( cudaDeviceReset() );
        }
        
        bool TargetArchs::builtWith(FeatureSet feature_set) const
        {
            return cudaArch.builtWith(feature_set);
        }
        
        bool TargetArchs::has(int major, int minor) const
        {
            return hasPtx(major, minor) || hasBin(major, minor);
        }
        
        bool TargetArchs::hasPtx(int major, int minor) const
        {
            return cudaArch.hasPtx(major, minor);
        }
        
        bool TargetArchs::hasBin(int major, int minor) const
        {
            return cudaArch.hasBin(major, minor);
        }
        
        bool TargetArchs::hasEqualOrLessPtx(int major, int minor) const
        {
            return cudaArch.hasEqualOrLessPtx(major, minor);
        }
        
        bool TargetArchs::hasEqualOrGreater(int major, int minor) const
        {
            return hasEqualOrGreaterPtx(major, minor) || hasEqualOrGreaterBin(major, minor);
        }
        
        bool TargetArchs::hasEqualOrGreaterPtx(int major, int minor) const
        {
            return cudaArch.hasEqualOrGreaterPtx(major, minor);
        }
        
        bool TargetArchs::hasEqualOrGreaterBin(int major, int minor) const
        {
            return cudaArch.hasEqualOrGreaterBin(major, minor);
        }
        
        bool deviceSupports(FeatureSet feature_set) const
        {
            static int versions[] =
            {
                -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1
            };
            static const int cache_size = static_cast<int>(sizeof(versions) / sizeof(versions[0]));
            
            const int devId = getDevice();
            
            int version;
            
            if (devId < cache_size && versions[devId] >= 0)
                version = versions[devId];
            else
            {
                DeviceInfo dev(devId);
                version = dev.majorVersion() * 10 + dev.minorVersion();
                if (devId < cache_size)
                    versions[devId] = version;
            }
            
            return TargetArchs::builtWith(feature_set) && (version >= feature_set);
        }
        
        size_t sharedMemPerBlock() const
        {
            return deviceProps.get(device_id_)->sharedMemPerBlock;
        }
        
        void queryMemory(size_t& _totalMemory, size_t& _freeMemory) const
        {
            int prevDeviceID = getDevice();
            if (prevDeviceID != device_id_)
                setDevice(device_id_);
            
            cudaSafeCall( cudaMemGetInfo(&_freeMemory, &_totalMemory) );
            
            if (prevDeviceID != device_id_)
                setDevice(prevDeviceID);
        }
        
        size_t freeMemory() const
        {
            size_t _totalMemory, _freeMemory;
            queryMemory(_totalMemory, _freeMemory);
            return _freeMemory;
        }
        
        size_t totalMemory() const
        {
            size_t _totalMemory, _freeMemory;
            queryMemory(_totalMemory, _freeMemory);
            return _totalMemory;
        }
        
        bool supports(FeatureSet feature_set) const
        {
            int version = majorVersion() * 10 + minorVersion();
            return version >= feature_set;
        }
        
        bool isCompatible() const
        {
            // Check PTX compatibility
            if (TargetArchs::hasEqualOrLessPtx(majorVersion(), minorVersion()))
                return true;
            
            // Check BIN compatibility
                for (int i = minorVersion(); i >= 0; --i)
                    if (TargetArchs::hasBin(majorVersion(), i))
                        return true;
                    
                    return false;
        }
        
        void query() const
        {
            const cudaDeviceProp* prop = deviceProps.get(device_id_);
            
            name_ = prop->name;
            multi_processor_count_ = prop->multiProcessorCount;
            majorVersion_ = prop->major;
            minorVersion_ = prop->minor;
        }
                
        void printCudaDeviceInfo(int device) const
        {
            int count = getCudaEnabledDeviceCount();
            bool valid = (device >= 0) && (device < count);
            
            int beg = valid ? device   : 0;
            int end = valid ? device+1 : count;
            
            printf("*** CUDA Device Query (Runtime API) version (CUDART static linking) *** \n\n");
            printf("Device count: %d\n", count);
            
            int driverVersion = 0, runtimeVersion = 0;
            cudaSafeCall( cudaDriverGetVersion(&driverVersion) );
            cudaSafeCall( cudaRuntimeGetVersion(&runtimeVersion) );
            
            const char *computeMode[] = {
                "Default (multiple host threads can use ::cudaSetDevice() with device simultaneously)",
                "Exclusive (only one host thread in one process is able to use ::cudaSetDevice() with this device)",
                "Prohibited (no host thread can use ::cudaSetDevice() with this device)",
                "Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device)",
                "Unknown",
                NULL
            };
            
            for(int dev = beg; dev < end; ++dev)
            {
                cudaDeviceProp prop;
                cudaSafeCall( cudaGetDeviceProperties(&prop, dev) );
                
                printf("\nDevice %d: \"%s\"\n", dev, prop.name);
                printf("  CUDA Driver Version / Runtime Version          %d.%d / %d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
                printf("  CUDA Capability Major/Minor version number:    %d.%d\n", prop.major, prop.minor);
                printf("  Total amount of global memory:                 %.0f MBytes (%llu bytes)\n", (float)prop.totalGlobalMem/1048576.0f, (unsigned long long) prop.totalGlobalMem);
                
                int cores = convertSMVer2Cores(prop.major, prop.minor);
                if (cores > 0)
                    printf("  (%2d) Multiprocessors x (%2d) CUDA Cores/MP:     %d CUDA Cores\n", prop.multiProcessorCount, cores, cores * prop.multiProcessorCount);
                
                printf("  GPU Clock Speed:                               %.2f GHz\n", prop.clockRate * 1e-6f);
                
                printf("  Max Texture Dimension Size (x,y,z)             1D=(%d), 2D=(%d,%d), 3D=(%d,%d,%d)\n",
                prop.maxTexture1D, prop.maxTexture2D[0], prop.maxTexture2D[1],
                prop.maxTexture3D[0], prop.maxTexture3D[1], prop.maxTexture3D[2]);
                printf("  Max Layered Texture Size (dim) x layers        1D=(%d) x %d, 2D=(%d,%d) x %d\n",
                prop.maxTexture1DLayered[0], prop.maxTexture1DLayered[1],
                prop.maxTexture2DLayered[0], prop.maxTexture2DLayered[1], prop.maxTexture2DLayered[2]);
                
                printf("  Total amount of constant memory:               %u bytes\n", (int)prop.totalConstMem);
                printf("  Total amount of shared memory per block:       %u bytes\n", (int)prop.sharedMemPerBlock);
                printf("  Total number of registers available per block: %d\n", prop.regsPerBlock);
                printf("  Warp size:                                     %d\n", prop.warpSize);
                printf("  Maximum number of threads per block:           %d\n", prop.maxThreadsPerBlock);
                printf("  Maximum sizes of each dimension of a block:    %d x %d x %d\n", prop.maxThreadsDim[0], prop.maxThreadsDim[1], prop.maxThreadsDim[2]);
                printf("  Maximum sizes of each dimension of a grid:     %d x %d x %d\n", prop.maxGridSize[0], prop.maxGridSize[1],  prop.maxGridSize[2]);
                printf("  Maximum memory pitch:                          %u bytes\n", (int)prop.memPitch);
                printf("  Texture alignment:                             %u bytes\n", (int)prop.textureAlignment);
                
                printf("  Concurrent copy and execution:                 %s with %d copy engine(s)\n", (prop.deviceOverlap ? "Yes" : "No"), prop.asyncEngineCount);
                printf("  Run time limit on kernels:                     %s\n", prop.kernelExecTimeoutEnabled ? "Yes" : "No");
                printf("  Integrated GPU sharing Host Memory:            %s\n", prop.integrated ? "Yes" : "No");
                printf("  Support host page-locked memory mapping:       %s\n", prop.canMapHostMemory ? "Yes" : "No");
                
                printf("  Concurrent kernel execution:                   %s\n", prop.concurrentKernels ? "Yes" : "No");
                printf("  Alignment requirement for Surfaces:            %s\n", prop.surfaceAlignment ? "Yes" : "No");
                printf("  Device has ECC support enabled:                %s\n", prop.ECCEnabled ? "Yes" : "No");
                printf("  Device is using TCC driver mode:               %s\n", prop.tccDriver ? "Yes" : "No");
                printf("  Device supports Unified Addressing (UVA):      %s\n", prop.unifiedAddressing ? "Yes" : "No");
                printf("  Device PCI Bus ID / PCI location ID:           %d / %d\n", prop.pciBusID, prop.pciDeviceID );
                printf("  Compute Mode:\n");
                printf("      %s \n", computeMode[prop.computeMode]);
            }
            
            printf("\n");
            printf("deviceQuery, CUDA Driver = CUDART");
            printf(", CUDA Driver Version  = %d.%d", driverVersion / 1000, driverVersion % 100);
            printf(", CUDA Runtime Version = %d.%d", runtimeVersion/1000, runtimeVersion%100);
            printf(", NumDevs = %d\n\n", count);
            fflush(stdout);
        }
        
        void printShortCudaDeviceInfo(int device) const
        {
            int count = getCudaEnabledDeviceCount();
            bool valid = (device >= 0) && (device < count);
            
            int beg = valid ? device   : 0;
            int end = valid ? device+1 : count;
            
            int driverVersion = 0, runtimeVersion = 0;
            cudaSafeCall( cudaDriverGetVersion(&driverVersion) );
            cudaSafeCall( cudaRuntimeGetVersion(&runtimeVersion) );
            
            for(int dev = beg; dev < end; ++dev)
            {
                cudaDeviceProp prop;
                cudaSafeCall( cudaGetDeviceProperties(&prop, dev) );
                
                const char *arch_str = prop.major < 2 ? " (not Fermi)" : "";
                printf("Device %d:  \"%s\"  %.0fMb", dev, prop.name, (float)prop.totalGlobalMem/1048576.0f);
                printf(", sm_%d%d%s", prop.major, prop.minor, arch_str);
                
                int cores = convertSMVer2Cores(prop.major, prop.minor);
                if (cores > 0)
                    printf(", %d cores", cores * prop.multiProcessorCount);
                
                printf(", Driver/Runtime ver.%d.%d/%d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
            }
            fflush(stdout);
        }
        
        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_Assert(src.depth() <= CV_64F && src.channels() <= 4);
            CV_Assert(src.size() == dst.size() && src.type() == dst.type());
            CV_Assert(src.size() == mask.size() && mask.depth() == CV_8U && (mask.channels() == 1 || mask.channels() == src.channels()));

            if (src.depth() == CV_64F)
            {
                if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
                    CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
            }

            typedef void (*func_t)(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream);
            static const func_t funcs[7][4] =
            {
                /*  8U */ {NppCopyMasked<CV_8U , nppiCopy_8u_C1MR >::call, cv::gpu::details::copyWithMask, NppCopyMasked<CV_8U , nppiCopy_8u_C3MR >::call, NppCopyMasked<CV_8U , nppiCopy_8u_C4MR >::call},
                /*  8S */ {cv::gpu::details::copyWithMask                , cv::gpu::details::copyWithMask, cv::gpu::details::copyWithMask                         , cv::gpu::details::copyWithMask                         },
                /* 16U */ {NppCopyMasked<CV_16U, nppiCopy_16u_C1MR>::call, cv::gpu::details::copyWithMask, NppCopyMasked<CV_16U, nppiCopy_16u_C3MR>::call, NppCopyMasked<CV_16U, nppiCopy_16u_C4MR>::call},
                /* 16S */ {NppCopyMasked<CV_16S, nppiCopy_16s_C1MR>::call, cv::gpu::details::copyWithMask, NppCopyMasked<CV_16S, nppiCopy_16s_C3MR>::call, NppCopyMasked<CV_16S, nppiCopy_16s_C4MR>::call},
                /* 32S */ {NppCopyMasked<CV_32S, nppiCopy_32s_C1MR>::call, cv::gpu::details::copyWithMask, NppCopyMasked<CV_32S, nppiCopy_32s_C3MR>::call, NppCopyMasked<CV_32S, nppiCopy_32s_C4MR>::call},
                /* 32F */ {NppCopyMasked<CV_32F, nppiCopy_32f_C1MR>::call, cv::gpu::details::copyWithMask, NppCopyMasked<CV_32F, nppiCopy_32f_C3MR>::call, NppCopyMasked<CV_32F, nppiCopy_32f_C4MR>::call},
                /* 64F */ {cv::gpu::details::copyWithMask                , cv::gpu::details::copyWithMask, cv::gpu::details::copyWithMask                         , cv::gpu::details::copyWithMask                         }
            };

            const func_t func =  mask.channels() == src.channels() ? funcs[src.depth()][src.channels() - 1] : cv::gpu::details::copyWithMask;

            func(src, dst, mask, 0);
        }

        void convert(const GpuMat& src, GpuMat& dst) const
        {
            typedef void (*func_t)(const GpuMat& src, GpuMat& dst);
            static const func_t funcs[7][7][4] =
            {
                {
                    /*  8U ->  8U */ {0, 0, 0, 0},
                    /*  8U ->  8S */ {cv::gpu::device::convertTo                        , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /*  8U -> 16U */ {NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C4R>::call},
                    /*  8U -> 16S */ {NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C4R>::call},
                    /*  8U -> 32S */ {cv::gpu::device::convertTo                        , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /*  8U -> 32F */ {NppCvt<CV_8U, CV_32F, nppiConvert_8u32f_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /*  8U -> 64F */ {cv::gpu::device::convertTo                        , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                }
                },
                {
                    /*  8S ->  8U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /*  8S ->  8S */ {0,0,0,0},
                    /*  8S -> 16U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /*  8S -> 16S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /*  8S -> 32S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /*  8S -> 32F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /*  8S -> 64F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo}
                },
                {
                    /* 16U ->  8U */ {NppCvt<CV_16U, CV_8U , nppiConvert_16u8u_C1R >::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C4R>::call},
                    /* 16U ->  8S */ {cv::gpu::device::convertTo                                  , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /* 16U -> 16U */ {0,0,0,0},
                    /* 16U -> 16S */ {cv::gpu::device::convertTo                                  , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /* 16U -> 32S */ {NppCvt<CV_16U, CV_32S, nppiConvert_16u32s_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /* 16U -> 32F */ {NppCvt<CV_16U, CV_32F, nppiConvert_16u32f_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /* 16U -> 64F */ {cv::gpu::device::convertTo                                  , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                }
                },
                {
                    /* 16S ->  8U */ {NppCvt<CV_16S, CV_8U , nppiConvert_16s8u_C1R >::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C4R>::call},
                    /* 16S ->  8S */ {cv::gpu::device::convertTo                                  , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /* 16S -> 16U */ {cv::gpu::device::convertTo                                  , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /* 16S -> 16S */ {0,0,0,0},
                    /* 16S -> 32S */ {NppCvt<CV_16S, CV_32S, nppiConvert_16s32s_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /* 16S -> 32F */ {NppCvt<CV_16S, CV_32F, nppiConvert_16s32f_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                },
                    /* 16S -> 64F */ {cv::gpu::device::convertTo                                  , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo                                }
                },
                {
                    /* 32S ->  8U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32S ->  8S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32S -> 16U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32S -> 16S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32S -> 32S */ {0,0,0,0},
                    /* 32S -> 32F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32S -> 64F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo}
                },
                {
                    /* 32F ->  8U */ {NppCvt<CV_32F, CV_8U , nppiConvert_32f8u_C1R >::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32F ->  8S */ {cv::gpu::device::convertTo                          , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32F -> 16U */ {NppCvt<CV_32F, CV_16U, nppiConvert_32f16u_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32F -> 16S */ {NppCvt<CV_32F, CV_16S, nppiConvert_32f16s_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32F -> 32S */ {cv::gpu::device::convertTo                          , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 32F -> 32F */ {0,0,0,0},
                    /* 32F -> 64F */ {cv::gpu::device::convertTo                          , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo}
                },
                {
                    /* 64F ->  8U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 64F ->  8S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 64F -> 16U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 64F -> 16S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 64F -> 32S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 64F -> 32F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
                    /* 64F -> 64F */ {0,0,0,0}
                }
            };

            CV_Assert(src.depth() <= CV_64F && src.channels() <= 4);
            CV_Assert(dst.depth() <= CV_64F);
            CV_Assert(src.size() == dst.size() && src.channels() == dst.channels());

            if (src.depth() == CV_64F || dst.depth() == CV_64F)
            {
                if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
                    CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
            }

            bool aligned = isAligned(src.data, 16) && isAligned(dst.data, 16);
            if (!aligned)
            {
                cv::gpu::device::convertTo(src, dst);
                return;
            }

            const func_t func = funcs[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_Assert(src.depth() <= CV_64F && src.channels() <= 4);
            CV_Assert(dst.depth() <= CV_64F);

            if (src.depth() == CV_64F || dst.depth() == CV_64F)
            {
                if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
                    CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
            }

            cv::gpu::device::convertTo(src, dst, alpha, beta);
        }

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

                CV_Assert(m.depth() <= CV_64F && m.channels() <= 4);

                if (m.depth() == CV_64F)
                {
                    if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
                        CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
                }

                funcs[m.depth()][m.channels() - 1](m, s);
            }
            else
            {
                typedef void (*func_t)(GpuMat& src, Scalar s, const GpuMat& mask);
                static const func_t funcs[7][4] =
                {
                    {NppSetMask<CV_8U , 1, nppiSet_8u_C1MR >::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_8U , 4, nppiSet_8u_C4MR >::call},
                    {cv::gpu::device::setTo                       , cv::gpu::device::setTo, cv::gpu::device::setTo, cv::gpu::device::setTo                               },
                    {NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::call},
                    {NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::call},
                    {NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::call},
                    {NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::call},
                    {cv::gpu::device::setTo                       , cv::gpu::device::setTo, cv::gpu::device::setTo, cv::gpu::device::setTo                               }
                };

                CV_Assert(m.depth() <= CV_64F && m.channels() <= 4);

                if (m.depth() == CV_64F)
                {
                    if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
                        CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
                }

                funcs[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);
        }
    };
}
#endif