opencv/modules/cudawarping/src/warp.cpp

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#include "precomp.hpp"

using namespace cv;
using namespace cv::cuda;

#if !defined HAVE_CUDA || defined(CUDA_DISABLER)

void cv::cuda::warpAffine(InputArray, OutputArray, InputArray, Size, int, int, Scalar, Stream&) { throw_no_cuda(); }
void cv::cuda::buildWarpAffineMaps(InputArray, bool, Size, OutputArray, OutputArray, Stream&) { throw_no_cuda(); }

void cv::cuda::warpPerspective(InputArray, OutputArray, InputArray, Size, int, int, Scalar, Stream&) { throw_no_cuda(); }
void cv::cuda::buildWarpPerspectiveMaps(InputArray, bool, Size, OutputArray, OutputArray, Stream&) { throw_no_cuda(); }

void cv::cuda::buildWarpPlaneMaps(Size, Rect, InputArray, InputArray, InputArray, float, OutputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::cuda::buildWarpCylindricalMaps(Size, Rect, InputArray, InputArray, float, OutputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::cuda::buildWarpSphericalMaps(Size, Rect, InputArray, InputArray, float, OutputArray, OutputArray, Stream&) { throw_no_cuda(); }

void cv::cuda::rotate(InputArray, OutputArray, Size, double, double, double, int, Stream&) { throw_no_cuda(); }

#else // HAVE_CUDA

namespace cv { namespace cuda { namespace device
{
    namespace imgproc
    {
        void buildWarpAffineMaps_gpu(float coeffs[2 * 3], PtrStepSzf xmap, PtrStepSzf ymap, cudaStream_t stream);

        template <typename T>
        void warpAffine_gpu(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float coeffs[2 * 3], PtrStepSzb dst, int interpolation,
                            int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);

        void buildWarpPerspectiveMaps_gpu(float coeffs[3 * 3], PtrStepSzf xmap, PtrStepSzf ymap, cudaStream_t stream);

        template <typename T>
        void warpPerspective_gpu(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float coeffs[3 * 3], PtrStepSzb dst, int interpolation,
                            int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);
    }
}}}

void cv::cuda::buildWarpAffineMaps(InputArray _M, bool inverse, Size dsize, OutputArray _xmap, OutputArray _ymap, Stream& stream)
{
    using namespace cv::cuda::device::imgproc;

    Mat M = _M.getMat();

    CV_Assert( M.rows == 2 && M.cols == 3 );

    _xmap.create(dsize, CV_32FC1);
    _ymap.create(dsize, CV_32FC1);

    GpuMat xmap = _xmap.getGpuMat();
    GpuMat ymap = _ymap.getGpuMat();

    float coeffs[2 * 3];
    Mat coeffsMat(2, 3, CV_32F, (void*)coeffs);

    if (inverse)
        M.convertTo(coeffsMat, coeffsMat.type());
    else
    {
        cv::Mat iM;
        invertAffineTransform(M, iM);
        iM.convertTo(coeffsMat, coeffsMat.type());
    }

    buildWarpAffineMaps_gpu(coeffs, xmap, ymap, StreamAccessor::getStream(stream));
}

void cv::cuda::buildWarpPerspectiveMaps(InputArray _M, bool inverse, Size dsize, OutputArray _xmap, OutputArray _ymap, Stream& stream)
{
    using namespace cv::cuda::device::imgproc;

    Mat M = _M.getMat();

    CV_Assert( M.rows == 3 && M.cols == 3 );

    _xmap.create(dsize, CV_32FC1);
    _ymap.create(dsize, CV_32FC1);

    GpuMat xmap = _xmap.getGpuMat();
    GpuMat ymap = _ymap.getGpuMat();

    float coeffs[3 * 3];
    Mat coeffsMat(3, 3, CV_32F, (void*)coeffs);

    if (inverse)
        M.convertTo(coeffsMat, coeffsMat.type());
    else
    {
        cv::Mat iM;
        invert(M, iM);
        iM.convertTo(coeffsMat, coeffsMat.type());
    }

    buildWarpPerspectiveMaps_gpu(coeffs, xmap, ymap, StreamAccessor::getStream(stream));
}

namespace
{
    template <int DEPTH> struct NppWarpFunc
    {
        typedef typename NPPTypeTraits<DEPTH>::npp_type npp_type;

        typedef NppStatus (*func_t)(const npp_type* pSrc, NppiSize srcSize, int srcStep, NppiRect srcRoi, npp_type* pDst,
                                    int dstStep, NppiRect dstRoi, const double coeffs[][3],
                                    int interpolation);
    };

    template <int DEPTH, typename NppWarpFunc<DEPTH>::func_t func> struct NppWarp
    {
        typedef typename NppWarpFunc<DEPTH>::npp_type npp_type;

        static void call(const cv::cuda::GpuMat& src, cv::cuda::GpuMat& dst, double coeffs[][3], int interpolation, cudaStream_t stream)
        {
            static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC};

            NppiSize srcsz;
            srcsz.height = src.rows;
            srcsz.width = src.cols;

            NppiRect srcroi;
            srcroi.x = 0;
            srcroi.y = 0;
            srcroi.height = src.rows;
            srcroi.width = src.cols;

            NppiRect dstroi;
            dstroi.x = 0;
            dstroi.y = 0;
            dstroi.height = dst.rows;
            dstroi.width = dst.cols;

            cv::cuda::NppStreamHandler h(stream);

            nppSafeCall( func(src.ptr<npp_type>(), srcsz, static_cast<int>(src.step), srcroi,
                              dst.ptr<npp_type>(), static_cast<int>(dst.step), dstroi,
                              coeffs, npp_inter[interpolation]) );

            if (stream == 0)
                cudaSafeCall( cudaDeviceSynchronize() );
        }
    };
}

void cv::cuda::warpAffine(InputArray _src, OutputArray _dst, InputArray _M, Size dsize, int flags, int borderMode, Scalar borderValue, Stream& stream)
{
    GpuMat src = _src.getGpuMat();
    Mat M = _M.getMat();

    CV_Assert( M.rows == 2 && M.cols == 3 );

    const int interpolation = flags & INTER_MAX;

    CV_Assert( src.depth() <= CV_32F && src.channels() <= 4 );
    CV_Assert( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC );
    CV_Assert( borderMode == BORDER_REFLECT101 || borderMode == BORDER_REPLICATE || borderMode == BORDER_CONSTANT || borderMode == BORDER_REFLECT || borderMode == BORDER_WRAP );

    _dst.create(dsize, src.type());
    GpuMat dst = _dst.getGpuMat();

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

    static const bool useNppTab[6][4][3] =
    {
        {
            {false, false, true},
            {false, false, false},
            {false, true, true},
            {false, false, false}
        },
        {
            {false, false, false},
            {false, false, false},
            {false, false, false},
            {false, false, false}
        },
        {
            {false, true, true},
            {false, false, false},
            {false, true, true},
            {false, false, false}
        },
        {
            {false, false, false},
            {false, false, false},
            {false, false, false},
            {false, false, false}
        },
        {
            {false, true, true},
            {false, false, false},
            {false, true, true},
            {false, false, true}
        },
        {
            {false, true, true},
            {false, false, false},
            {false, true, true},
            {false, false, true}
        }
    };

    bool useNpp = borderMode == BORDER_CONSTANT && ofs.x == 0 && ofs.y == 0 && useNppTab[src.depth()][src.channels() - 1][interpolation];
    // NPP bug on float data
    useNpp = useNpp && src.depth() != CV_32F;

    if (useNpp)
    {
        typedef void (*func_t)(const cv::cuda::GpuMat& src, cv::cuda::GpuMat& dst, double coeffs[][3], int flags, cudaStream_t stream);

        static const func_t funcs[2][6][4] =
        {
            {
                {NppWarp<CV_8U, nppiWarpAffine_8u_C1R>::call, 0, NppWarp<CV_8U, nppiWarpAffine_8u_C3R>::call, NppWarp<CV_8U, nppiWarpAffine_8u_C4R>::call},
                {0, 0, 0, 0},
                {NppWarp<CV_16U, nppiWarpAffine_16u_C1R>::call, 0, NppWarp<CV_16U, nppiWarpAffine_16u_C3R>::call, NppWarp<CV_16U, nppiWarpAffine_16u_C4R>::call},
                {0, 0, 0, 0},
                {NppWarp<CV_32S, nppiWarpAffine_32s_C1R>::call, 0, NppWarp<CV_32S, nppiWarpAffine_32s_C3R>::call, NppWarp<CV_32S, nppiWarpAffine_32s_C4R>::call},
                {NppWarp<CV_32F, nppiWarpAffine_32f_C1R>::call, 0, NppWarp<CV_32F, nppiWarpAffine_32f_C3R>::call, NppWarp<CV_32F, nppiWarpAffine_32f_C4R>::call}
            },
            {
                {NppWarp<CV_8U, nppiWarpAffineBack_8u_C1R>::call, 0, NppWarp<CV_8U, nppiWarpAffineBack_8u_C3R>::call, NppWarp<CV_8U, nppiWarpAffineBack_8u_C4R>::call},
                {0, 0, 0, 0},
                {NppWarp<CV_16U, nppiWarpAffineBack_16u_C1R>::call, 0, NppWarp<CV_16U, nppiWarpAffineBack_16u_C3R>::call, NppWarp<CV_16U, nppiWarpAffineBack_16u_C4R>::call},
                {0, 0, 0, 0},
                {NppWarp<CV_32S, nppiWarpAffineBack_32s_C1R>::call, 0, NppWarp<CV_32S, nppiWarpAffineBack_32s_C3R>::call, NppWarp<CV_32S, nppiWarpAffineBack_32s_C4R>::call},
                {NppWarp<CV_32F, nppiWarpAffineBack_32f_C1R>::call, 0, NppWarp<CV_32F, nppiWarpAffineBack_32f_C3R>::call, NppWarp<CV_32F, nppiWarpAffineBack_32f_C4R>::call}
            }
        };

        dst.setTo(borderValue, stream);

        double coeffs[2][3];
        Mat coeffsMat(2, 3, CV_64F, (void*)coeffs);
        M.convertTo(coeffsMat, coeffsMat.type());

        const func_t func = funcs[(flags & WARP_INVERSE_MAP) != 0][src.depth()][src.channels() - 1];
        CV_Assert(func != 0);

        func(src, dst, coeffs, interpolation, StreamAccessor::getStream(stream));
    }
    else
    {
        using namespace cv::cuda::device::imgproc;

        typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float coeffs[2 * 3], PtrStepSzb dst, int interpolation,
            int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);

        static const func_t funcs[6][4] =
        {
            {warpAffine_gpu<uchar>      , 0 /*warpAffine_gpu<uchar2>*/ , warpAffine_gpu<uchar3>     , warpAffine_gpu<uchar4>     },
            {0 /*warpAffine_gpu<schar>*/, 0 /*warpAffine_gpu<char2>*/  , 0 /*warpAffine_gpu<char3>*/, 0 /*warpAffine_gpu<char4>*/},
            {warpAffine_gpu<ushort>     , 0 /*warpAffine_gpu<ushort2>*/, warpAffine_gpu<ushort3>    , warpAffine_gpu<ushort4>    },
            {warpAffine_gpu<short>      , 0 /*warpAffine_gpu<short2>*/ , warpAffine_gpu<short3>     , warpAffine_gpu<short4>     },
            {0 /*warpAffine_gpu<int>*/  , 0 /*warpAffine_gpu<int2>*/   , 0 /*warpAffine_gpu<int3>*/ , 0 /*warpAffine_gpu<int4>*/ },
            {warpAffine_gpu<float>      , 0 /*warpAffine_gpu<float2>*/ , warpAffine_gpu<float3>     , warpAffine_gpu<float4>     }
        };

        const func_t func = funcs[src.depth()][src.channels() - 1];
        CV_Assert(func != 0);

        float coeffs[2 * 3];
        Mat coeffsMat(2, 3, CV_32F, (void*)coeffs);

        if (flags & WARP_INVERSE_MAP)
            M.convertTo(coeffsMat, coeffsMat.type());
        else
        {
            cv::Mat iM;
            invertAffineTransform(M, iM);
            iM.convertTo(coeffsMat, coeffsMat.type());
        }

        Scalar_<float> borderValueFloat;
        borderValueFloat = borderValue;

        func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, coeffs,
            dst, interpolation, borderMode, borderValueFloat.val, StreamAccessor::getStream(stream), deviceSupports(FEATURE_SET_COMPUTE_20));
    }
}

void cv::cuda::warpPerspective(InputArray _src, OutputArray _dst, InputArray _M, Size dsize, int flags, int borderMode, Scalar borderValue, Stream& stream)
{
    GpuMat src = _src.getGpuMat();
    Mat M = _M.getMat();

    CV_Assert( M.rows == 3 && M.cols == 3 );

    const int interpolation = flags & INTER_MAX;

    CV_Assert( src.depth() <= CV_32F && src.channels() <= 4 );
    CV_Assert( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC );
    CV_Assert( borderMode == BORDER_REFLECT101 || borderMode == BORDER_REPLICATE || borderMode == BORDER_CONSTANT || borderMode == BORDER_REFLECT || borderMode == BORDER_WRAP) ;

    _dst.create(dsize, src.type());
    GpuMat dst = _dst.getGpuMat();

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

    static const bool useNppTab[6][4][3] =
    {
        {
            {false, false, true},
            {false, false, false},
            {false, true, true},
            {false, false, false}
        },
        {
            {false, false, false},
            {false, false, false},
            {false, false, false},
            {false, false, false}
        },
        {
            {false, true, true},
            {false, false, false},
            {false, true, true},
            {false, false, false}
        },
        {
            {false, false, false},
            {false, false, false},
            {false, false, false},
            {false, false, false}
        },
        {
            {false, true, true},
            {false, false, false},
            {false, true, true},
            {false, false, true}
        },
        {
            {false, true, true},
            {false, false, false},
            {false, true, true},
            {false, false, true}
        }
    };

    bool useNpp = borderMode == BORDER_CONSTANT && ofs.x == 0 && ofs.y == 0 && useNppTab[src.depth()][src.channels() - 1][interpolation];
    // NPP bug on float data
    useNpp = useNpp && src.depth() != CV_32F;

    if (useNpp)
    {
        typedef void (*func_t)(const cv::cuda::GpuMat& src, cv::cuda::GpuMat& dst, double coeffs[][3], int flags, cudaStream_t stream);

        static const func_t funcs[2][6][4] =
        {
            {
                {NppWarp<CV_8U, nppiWarpPerspective_8u_C1R>::call, 0, NppWarp<CV_8U, nppiWarpPerspective_8u_C3R>::call, NppWarp<CV_8U, nppiWarpPerspective_8u_C4R>::call},
                {0, 0, 0, 0},
                {NppWarp<CV_16U, nppiWarpPerspective_16u_C1R>::call, 0, NppWarp<CV_16U, nppiWarpPerspective_16u_C3R>::call, NppWarp<CV_16U, nppiWarpPerspective_16u_C4R>::call},
                {0, 0, 0, 0},
                {NppWarp<CV_32S, nppiWarpPerspective_32s_C1R>::call, 0, NppWarp<CV_32S, nppiWarpPerspective_32s_C3R>::call, NppWarp<CV_32S, nppiWarpPerspective_32s_C4R>::call},
                {NppWarp<CV_32F, nppiWarpPerspective_32f_C1R>::call, 0, NppWarp<CV_32F, nppiWarpPerspective_32f_C3R>::call, NppWarp<CV_32F, nppiWarpPerspective_32f_C4R>::call}
            },
            {
                {NppWarp<CV_8U, nppiWarpPerspectiveBack_8u_C1R>::call, 0, NppWarp<CV_8U, nppiWarpPerspectiveBack_8u_C3R>::call, NppWarp<CV_8U, nppiWarpPerspectiveBack_8u_C4R>::call},
                {0, 0, 0, 0},
                {NppWarp<CV_16U, nppiWarpPerspectiveBack_16u_C1R>::call, 0, NppWarp<CV_16U, nppiWarpPerspectiveBack_16u_C3R>::call, NppWarp<CV_16U, nppiWarpPerspectiveBack_16u_C4R>::call},
                {0, 0, 0, 0},
                {NppWarp<CV_32S, nppiWarpPerspectiveBack_32s_C1R>::call, 0, NppWarp<CV_32S, nppiWarpPerspectiveBack_32s_C3R>::call, NppWarp<CV_32S, nppiWarpPerspectiveBack_32s_C4R>::call},
                {NppWarp<CV_32F, nppiWarpPerspectiveBack_32f_C1R>::call, 0, NppWarp<CV_32F, nppiWarpPerspectiveBack_32f_C3R>::call, NppWarp<CV_32F, nppiWarpPerspectiveBack_32f_C4R>::call}
            }
        };

        dst.setTo(borderValue, stream);

        double coeffs[3][3];
        Mat coeffsMat(3, 3, CV_64F, (void*)coeffs);
        M.convertTo(coeffsMat, coeffsMat.type());

        const func_t func = funcs[(flags & WARP_INVERSE_MAP) != 0][src.depth()][src.channels() - 1];
        CV_Assert(func != 0);

        func(src, dst, coeffs, interpolation, StreamAccessor::getStream(stream));
    }
    else
    {
        using namespace cv::cuda::device::imgproc;

        typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float coeffs[2 * 3], PtrStepSzb dst, int interpolation,
            int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);

        static const func_t funcs[6][4] =
        {
            {warpPerspective_gpu<uchar>      , 0 /*warpPerspective_gpu<uchar2>*/ , warpPerspective_gpu<uchar3>     , warpPerspective_gpu<uchar4>     },
            {0 /*warpPerspective_gpu<schar>*/, 0 /*warpPerspective_gpu<char2>*/  , 0 /*warpPerspective_gpu<char3>*/, 0 /*warpPerspective_gpu<char4>*/},
            {warpPerspective_gpu<ushort>     , 0 /*warpPerspective_gpu<ushort2>*/, warpPerspective_gpu<ushort3>    , warpPerspective_gpu<ushort4>    },
            {warpPerspective_gpu<short>      , 0 /*warpPerspective_gpu<short2>*/ , warpPerspective_gpu<short3>     , warpPerspective_gpu<short4>     },
            {0 /*warpPerspective_gpu<int>*/  , 0 /*warpPerspective_gpu<int2>*/   , 0 /*warpPerspective_gpu<int3>*/ , 0 /*warpPerspective_gpu<int4>*/ },
            {warpPerspective_gpu<float>      , 0 /*warpPerspective_gpu<float2>*/ , warpPerspective_gpu<float3>     , warpPerspective_gpu<float4>     }
        };

        const func_t func = funcs[src.depth()][src.channels() - 1];
        CV_Assert(func != 0);

        float coeffs[3 * 3];
        Mat coeffsMat(3, 3, CV_32F, (void*)coeffs);

        if (flags & WARP_INVERSE_MAP)
            M.convertTo(coeffsMat, coeffsMat.type());
        else
        {
            cv::Mat iM;
            invert(M, iM);
            iM.convertTo(coeffsMat, coeffsMat.type());
        }

        Scalar_<float> borderValueFloat;
        borderValueFloat = borderValue;

        func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, coeffs,
            dst, interpolation, borderMode, borderValueFloat.val, StreamAccessor::getStream(stream), deviceSupports(FEATURE_SET_COMPUTE_20));
    }
}

//////////////////////////////////////////////////////////////////////////////
// buildWarpPlaneMaps

namespace cv { namespace cuda { namespace device
{
    namespace imgproc
    {
        void buildWarpPlaneMaps(int tl_u, int tl_v, PtrStepSzf map_x, PtrStepSzf map_y,
                                const float k_rinv[9], const float r_kinv[9], const float t[3], float scale,
                                cudaStream_t stream);
    }
}}}

void cv::cuda::buildWarpPlaneMaps(Size src_size, Rect dst_roi, InputArray _K, InputArray _R, InputArray _T,
                                 float scale, OutputArray _map_x, OutputArray _map_y, Stream& stream)
{
    (void) src_size;

    Mat K = _K.getMat();
    Mat R = _R.getMat();
    Mat T = _T.getMat();

    CV_Assert( K.size() == Size(3,3) && K.type() == CV_32FC1 );
    CV_Assert( R.size() == Size(3,3) && R.type() == CV_32FC1 );
    CV_Assert( (T.size() == Size(3,1) || T.size() == Size(1,3)) && T.type() == CV_32FC1 && T.isContinuous() );

    Mat K_Rinv = K * R.t();
    Mat R_Kinv = R * K.inv();
    CV_Assert( K_Rinv.isContinuous() );
    CV_Assert( R_Kinv.isContinuous() );

    _map_x.create(dst_roi.size(), CV_32FC1);
    _map_y.create(dst_roi.size(), CV_32FC1);

    GpuMat map_x = _map_x.getGpuMat();
    GpuMat map_y = _map_y.getGpuMat();

    device::imgproc::buildWarpPlaneMaps(dst_roi.tl().x, dst_roi.tl().y, map_x, map_y, K_Rinv.ptr<float>(), R_Kinv.ptr<float>(),
                       T.ptr<float>(), scale, StreamAccessor::getStream(stream));
}

//////////////////////////////////////////////////////////////////////////////
// buildWarpCylyndricalMaps

namespace cv { namespace cuda { namespace device
{
    namespace imgproc
    {
        void buildWarpCylindricalMaps(int tl_u, int tl_v, PtrStepSzf map_x, PtrStepSzf map_y,
                                      const float k_rinv[9], const float r_kinv[9], float scale,
                                      cudaStream_t stream);
    }
}}}

void cv::cuda::buildWarpCylindricalMaps(Size src_size, Rect dst_roi, InputArray _K, InputArray _R, float scale,
                                       OutputArray _map_x, OutputArray _map_y, Stream& stream)
{
    (void) src_size;

    Mat K = _K.getMat();
    Mat R = _R.getMat();

    CV_Assert( K.size() == Size(3,3) && K.type() == CV_32FC1 );
    CV_Assert( R.size() == Size(3,3) && R.type() == CV_32FC1 );

    Mat K_Rinv = K * R.t();
    Mat R_Kinv = R * K.inv();
    CV_Assert( K_Rinv.isContinuous() );
    CV_Assert( R_Kinv.isContinuous() );

    _map_x.create(dst_roi.size(), CV_32FC1);
    _map_y.create(dst_roi.size(), CV_32FC1);

    GpuMat map_x = _map_x.getGpuMat();
    GpuMat map_y = _map_y.getGpuMat();

    device::imgproc::buildWarpCylindricalMaps(dst_roi.tl().x, dst_roi.tl().y, map_x, map_y, K_Rinv.ptr<float>(), R_Kinv.ptr<float>(), scale, StreamAccessor::getStream(stream));
}


//////////////////////////////////////////////////////////////////////////////
// buildWarpSphericalMaps

namespace cv { namespace cuda { namespace device
{
    namespace imgproc
    {
        void buildWarpSphericalMaps(int tl_u, int tl_v, PtrStepSzf map_x, PtrStepSzf map_y,
                                    const float k_rinv[9], const float r_kinv[9], float scale,
                                    cudaStream_t stream);
    }
}}}

void cv::cuda::buildWarpSphericalMaps(Size src_size, Rect dst_roi, InputArray _K, InputArray _R, float scale,
                                     OutputArray _map_x, OutputArray _map_y, Stream& stream)
{
    (void) src_size;

    Mat K = _K.getMat();
    Mat R = _R.getMat();

    CV_Assert( K.size() == Size(3,3) && K.type() == CV_32FC1 );
    CV_Assert( R.size() == Size(3,3) && R.type() == CV_32FC1 );

    Mat K_Rinv = K * R.t();
    Mat R_Kinv = R * K.inv();
    CV_Assert( K_Rinv.isContinuous() );
    CV_Assert( R_Kinv.isContinuous() );

    _map_x.create(dst_roi.size(), CV_32FC1);
    _map_y.create(dst_roi.size(), CV_32FC1);

    GpuMat map_x = _map_x.getGpuMat();
    GpuMat map_y = _map_y.getGpuMat();

    device::imgproc::buildWarpSphericalMaps(dst_roi.tl().x, dst_roi.tl().y, map_x, map_y, K_Rinv.ptr<float>(), R_Kinv.ptr<float>(), scale, StreamAccessor::getStream(stream));
}

////////////////////////////////////////////////////////////////////////
// rotate

namespace
{
    template <int DEPTH> struct NppRotateFunc
    {
        typedef typename NPPTypeTraits<DEPTH>::npp_type npp_type;

        typedef NppStatus (*func_t)(const npp_type* pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI,
                                    npp_type* pDst, int nDstStep, NppiRect oDstROI,
                                    double nAngle, double nShiftX, double nShiftY, int eInterpolation);
    };

    template <int DEPTH, typename NppRotateFunc<DEPTH>::func_t func> struct NppRotate
    {
        typedef typename NppRotateFunc<DEPTH>::npp_type npp_type;

        static void call(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift, double yShift, int interpolation, cudaStream_t stream)
        {
            (void)dsize;
            static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC};

            NppStreamHandler h(stream);

            NppiSize srcsz;
            srcsz.height = src.rows;
            srcsz.width = src.cols;
            NppiRect srcroi;
            srcroi.x = srcroi.y = 0;
            srcroi.height = src.rows;
            srcroi.width = src.cols;
            NppiRect dstroi;
            dstroi.x = dstroi.y = 0;
            dstroi.height = dst.rows;
            dstroi.width = dst.cols;

            nppSafeCall( func(src.ptr<npp_type>(), srcsz, static_cast<int>(src.step), srcroi,
                dst.ptr<npp_type>(), static_cast<int>(dst.step), dstroi, angle, xShift, yShift, npp_inter[interpolation]) );

            if (stream == 0)
                cudaSafeCall( cudaDeviceSynchronize() );
        }
    };
}

void cv::cuda::rotate(InputArray _src, OutputArray _dst, Size dsize, double angle, double xShift, double yShift, int interpolation, Stream& stream)
{
    typedef void (*func_t)(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift, double yShift, int interpolation, cudaStream_t stream);
    static const func_t funcs[6][4] =
    {
        {NppRotate<CV_8U, nppiRotate_8u_C1R>::call, 0, NppRotate<CV_8U, nppiRotate_8u_C3R>::call, NppRotate<CV_8U, nppiRotate_8u_C4R>::call},
        {0,0,0,0},
        {NppRotate<CV_16U, nppiRotate_16u_C1R>::call, 0, NppRotate<CV_16U, nppiRotate_16u_C3R>::call, NppRotate<CV_16U, nppiRotate_16u_C4R>::call},
        {0,0,0,0},
        {0,0,0,0},
        {NppRotate<CV_32F, nppiRotate_32f_C1R>::call, 0, NppRotate<CV_32F, nppiRotate_32f_C3R>::call, NppRotate<CV_32F, nppiRotate_32f_C4R>::call}
    };

    GpuMat src = _src.getGpuMat();

    CV_Assert( src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_32F );
    CV_Assert( src.channels() == 1 || src.channels() == 3 || src.channels() == 4 );
    CV_Assert( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC );

    _dst.create(dsize, src.type());
    GpuMat dst = _dst.getGpuMat();

    dst.setTo(Scalar::all(0), stream);

    funcs[src.depth()][src.channels() - 1](src, dst, dsize, angle, xShift, yShift, interpolation, StreamAccessor::getStream(stream));
}

#endif // HAVE_CUDA