Пример #1
0
void cv::cuda::resize(InputArray _src, OutputArray _dst, Size dsize, double fx, double fy, int interpolation, Stream& stream)
{
    GpuMat src = _src.getGpuMat();

    typedef void (*func_t)(const PtrStepSzb& src, const PtrStepSzb& srcWhole, int yoff, int xoff, const PtrStepSzb& dst, float fy, float fx, int interpolation, cudaStream_t stream);
    static const func_t funcs[6][4] =
    {
        {device::resize<uchar>      , 0 /*device::resize<uchar2>*/ , device::resize<uchar3>     , device::resize<uchar4>     },
        {0 /*device::resize<schar>*/, 0 /*device::resize<char2>*/  , 0 /*device::resize<char3>*/, 0 /*device::resize<char4>*/},
        {device::resize<ushort>     , 0 /*device::resize<ushort2>*/, device::resize<ushort3>    , device::resize<ushort4>    },
        {device::resize<short>      , 0 /*device::resize<short2>*/ , device::resize<short3>     , device::resize<short4>     },
        {0 /*device::resize<int>*/  , 0 /*device::resize<int2>*/   , 0 /*device::resize<int3>*/ , 0 /*device::resize<int4>*/ },
        {device::resize<float>      , 0 /*device::resize<float2>*/ , device::resize<float3>     , device::resize<float4>     }
    };

    CV_Assert( src.depth() <= CV_32F && src.channels() <= 4 );
    CV_Assert( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC || interpolation == INTER_AREA );
    CV_Assert( !(dsize == Size()) || (fx > 0 && fy > 0) );

    if (dsize == Size())
    {
        dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
    }
    else
    {
        fx = static_cast<double>(dsize.width) / src.cols;
        fy = static_cast<double>(dsize.height) / src.rows;
    }

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

    if (dsize == src.size())
    {
        src.copyTo(dst, stream);
        return;
    }

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

    if (!func)
        CV_Error(Error::StsUnsupportedFormat, "Unsupported combination of source and destination types");

    Size wholeSize;
    Point ofs;
    src.locateROI(wholeSize, ofs);
    PtrStepSzb wholeSrc(wholeSize.height, wholeSize.width, src.datastart, src.step);

    func(src, wholeSrc, ofs.y, ofs.x, dst, static_cast<float>(1.0 / fy), static_cast<float>(1.0 / fx), interpolation, StreamAccessor::getStream(stream));
}
Пример #2
0
void cv::gpu::remap(const GpuMat& src, GpuMat& dst, const GpuMat& xmap, const GpuMat& ymap, int interpolation, int borderMode, Scalar borderValue, Stream& stream)
{
    using namespace cv::gpu::device::imgproc;

    typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, PtrStepSzf xmap, PtrStepSzf ymap, PtrStepSzb dst, int interpolation,
                           int borderMode, const float* borderValue, cudaStream_t stream, int cc);

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

    CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
    CV_Assert(xmap.type() == CV_32F && ymap.type() == CV_32F && xmap.size() == ymap.size());
    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);

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

    int gpuBorderType;
    CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType));

    dst.create(xmap.size(), src.type());

    Scalar_<float> borderValueFloat;
    borderValueFloat = borderValue;

    DeviceInfo info;
    int cc = info.majorVersion() * 10 + info.minorVersion();

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

    func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, xmap, ymap,
         dst, interpolation, gpuBorderType, borderValueFloat.val, StreamAccessor::getStream(stream), cc);
}
Пример #3
0
void cv::cuda::remap(InputArray _src, OutputArray _dst, InputArray _xmap, InputArray _ymap, int interpolation, int borderMode, Scalar borderValue, Stream& stream)
{
    using namespace cv::cuda::device::imgproc;

    typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, PtrStepSzf xmap, PtrStepSzf ymap, PtrStepSzb dst, int interpolation,
        int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);
    static const func_t funcs[6][4] =
    {
        {remap_gpu<uchar>      , 0 /*remap_gpu<uchar2>*/ , remap_gpu<uchar3>     , remap_gpu<uchar4>     },
        {0 /*remap_gpu<schar>*/, 0 /*remap_gpu<char2>*/  , 0 /*remap_gpu<char3>*/, 0 /*remap_gpu<char4>*/},
        {remap_gpu<ushort>     , 0 /*remap_gpu<ushort2>*/, remap_gpu<ushort3>    , remap_gpu<ushort4>    },
        {remap_gpu<short>      , 0 /*remap_gpu<short2>*/ , remap_gpu<short3>     , remap_gpu<short4>     },
        {0 /*remap_gpu<int>*/  , 0 /*remap_gpu<int2>*/   , 0 /*remap_gpu<int3>*/ , 0 /*remap_gpu<int4>*/ },
        {remap_gpu<float>      , 0 /*remap_gpu<float2>*/ , remap_gpu<float3>     , remap_gpu<float4>     }
    };

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

    CV_Assert( src.depth() <= CV_32F && src.channels() <= 4 );
    CV_Assert( xmap.type() == CV_32F && ymap.type() == CV_32F && xmap.size() == ymap.size() );
    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 );

    const func_t func = funcs[src.depth()][src.channels() - 1];
    if (!func)
        CV_Error(Error::StsUnsupportedFormat, "Unsupported input type");

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

    Scalar_<float> borderValueFloat;
    borderValueFloat = borderValue;

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

    func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, xmap, ymap,
        dst, interpolation, borderMode, borderValueFloat.val, StreamAccessor::getStream(stream), deviceSupports(FEATURE_SET_COMPUTE_20));
}
Пример #4
0
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));
    }
}
Пример #5
0
void cv::gpu::warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags, int borderMode, Scalar borderValue, Stream& s)
{
    CV_Assert(M.rows == 3 && M.cols == 3);

    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);

    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;
    useNpp = useNpp && useNppTab[src.depth()][src.channels() - 1][interpolation];
    #ifdef linux
        // NPP bug on float data
        useNpp = useNpp && src.depth() != CV_32F;
    #endif

    if (useNpp)
    {
        typedef void (*func_t)(const cv::gpu::GpuMat& src, cv::Size wholeSize, cv::Point ofs, cv::gpu::GpuMat& dst, double coeffs[][3], cv::Size dsize, 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}
            }
        };

        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, wholeSize, ofs, dst, coeffs, dsize, interpolation, StreamAccessor::getStream(s));
    }
    else
    {
        using namespace cv::gpu::device::imgproc;

        typedef void (*func_t)(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation,
            int borderMode, const float* borderValue, cudaStream_t stream, int cc);

        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);

        int gpuBorderType;
        CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType));

        dst.create(dsize, src.type());

        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;

        DeviceInfo info;
        int cc = info.majorVersion() * 10 + info.minorVersion();

        func(src, DevMem2Db(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, coeffs,
            dst, interpolation, gpuBorderType, borderValueFloat.val, StreamAccessor::getStream(s), cc);
    }
}
Пример #6
0
void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
{
    CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
    CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR
            || interpolation == INTER_CUBIC || interpolation == INTER_AREA);
    CV_Assert(!(dsize == Size()) || (fx > 0 && fy > 0));

    if (dsize == Size())
        dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
    else
    {
        fx = static_cast<double>(dsize.width) / src.cols;
        fy = static_cast<double>(dsize.height) / src.rows;
    }
    if (dsize != dst.size())
        dst.create(dsize, src.type());

    if (dsize == src.size())
    {
        if (s)
            s.enqueueCopy(src, dst);
        else
            src.copyTo(dst);
        return;
    }

    cudaStream_t stream = StreamAccessor::getStream(s);

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

    bool useNpp = (src.type() == CV_8UC1 || src.type() == CV_8UC4);
    useNpp = useNpp && (interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || (src.type() == CV_8UC4 && interpolation != INTER_AREA));

    if (useNpp)
    {
        typedef NppStatus (*func_t)(const Npp8u * pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, Npp8u * pDst, int nDstStep, NppiSize dstROISize,
                                    double xFactor, double yFactor, int eInterpolation);

        const func_t funcs[4] = { nppiResize_8u_C1R, 0, 0, nppiResize_8u_C4R };

        static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC, 0, NPPI_INTER_LANCZOS};

        NppiSize srcsz;
        srcsz.width  = wholeSize.width;
        srcsz.height = wholeSize.height;

        NppiRect srcrect;
        srcrect.x = ofs.x;
        srcrect.y = ofs.y;
        srcrect.width  = src.cols;
        srcrect.height = src.rows;

        NppiSize dstsz;
        dstsz.width  = dst.cols;
        dstsz.height = dst.rows;

        NppStreamHandler h(stream);

        nppSafeCall( funcs[src.channels() - 1](src.datastart, srcsz, static_cast<int>(src.step), srcrect,
                dst.ptr<Npp8u>(), static_cast<int>(dst.step), dstsz, fx, fy, npp_inter[interpolation]) );

        if (stream == 0)
            cudaSafeCall( cudaDeviceSynchronize() );
    }
    else
    {
        using namespace ::cv::gpu::device::imgproc;

        typedef void (*func_t)(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float fx, float fy, DevMem2Db dst, int interpolation, cudaStream_t stream);

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

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

        func(src, DevMem2Db(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y,
            static_cast<float>(1.0 / fx), static_cast<float>(1.0 / fy), dst, interpolation, stream);
    }
}