removed NPP implementation
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@ -44,18 +44,7 @@
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#if !defined HAVE_CUDA || defined(CUDA_DISABLER)
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void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
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{
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(void)src;
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(void)dst;
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(void)dsize;
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(void)fx;
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(void)fy;
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(void)interpolation;
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(void)s;
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throw_nogpu();
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}
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void cv::gpu::resize(const GpuMat&, GpuMat&, Size, double, double, int, Stream&) { throw_nogpu(); }
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#else // HAVE_CUDA
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@ -69,94 +58,57 @@ namespace cv { namespace gpu { namespace device
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}
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}}}
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void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
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void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& stream)
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{
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CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
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CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR
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|| interpolation == INTER_CUBIC || interpolation == INTER_AREA);
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CV_Assert(!(dsize == Size()) || (fx > 0 && fy > 0));
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using namespace ::cv::gpu::device::imgproc;
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typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float fx, float fy, PtrStepSzb dst, int interpolation, cudaStream_t stream);
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static const func_t funcs[6][4] =
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{
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{resize_gpu<uchar> , 0 /*resize_gpu<uchar2>*/ , resize_gpu<uchar3> , resize_gpu<uchar4> },
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{0 /*resize_gpu<schar>*/, 0 /*resize_gpu<char2>*/ , 0 /*resize_gpu<char3>*/, 0 /*resize_gpu<char4>*/},
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{resize_gpu<ushort> , 0 /*resize_gpu<ushort2>*/, resize_gpu<ushort3> , resize_gpu<ushort4> },
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{resize_gpu<short> , 0 /*resize_gpu<short2>*/ , resize_gpu<short3> , resize_gpu<short4> },
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{0 /*resize_gpu<int>*/ , 0 /*resize_gpu<int2>*/ , 0 /*resize_gpu<int3>*/ , 0 /*resize_gpu<int4>*/ },
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{resize_gpu<float> , 0 /*resize_gpu<float2>*/ , resize_gpu<float3> , resize_gpu<float4> }
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};
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CV_Assert( src.depth() <= CV_32F && src.channels() <= 4 );
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CV_Assert( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC || interpolation == INTER_AREA );
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CV_Assert( !(dsize == Size()) || (fx > 0 && fy > 0) );
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if (dsize == Size())
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{
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dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
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}
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else
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{
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fx = static_cast<double>(dsize.width) / src.cols;
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fy = static_cast<double>(dsize.height) / src.rows;
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}
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if (dsize != dst.size())
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dst.create(dsize, src.type());
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dst.create(dsize, src.type());
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if (dsize == src.size())
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{
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if (s)
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s.enqueueCopy(src, dst);
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if (stream)
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stream.enqueueCopy(src, dst);
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else
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src.copyTo(dst);
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return;
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}
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cudaStream_t stream = StreamAccessor::getStream(s);
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const func_t func = funcs[src.depth()][src.channels() - 1];
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if (!func)
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CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
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Size wholeSize;
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Point ofs;
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src.locateROI(wholeSize, ofs);
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PtrStepSzb wholeSrc(wholeSize.height, wholeSize.width, src.datastart, src.step);
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bool useNpp = (src.type() == CV_8UC1 || src.type() == CV_8UC4);
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useNpp = useNpp && (interpolation == INTER_NEAREST || interpolation == INTER_LINEAR);
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if (useNpp)
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{
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typedef NppStatus (*func_t)(const Npp8u * pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, Npp8u * pDst, int nDstStep, NppiSize dstROISize,
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double xFactor, double yFactor, int eInterpolation);
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const func_t funcs[4] = { nppiResize_8u_C1R, 0, 0, nppiResize_8u_C4R };
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static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC, 0, NPPI_INTER_LANCZOS};
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NppiSize srcsz;
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srcsz.width = wholeSize.width;
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srcsz.height = wholeSize.height;
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NppiRect srcrect;
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srcrect.x = ofs.x;
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srcrect.y = ofs.y;
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srcrect.width = src.cols;
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srcrect.height = src.rows;
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NppiSize dstsz;
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dstsz.width = dst.cols;
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dstsz.height = dst.rows;
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NppStreamHandler h(stream);
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nppSafeCall( funcs[src.channels() - 1](src.datastart, srcsz, static_cast<int>(src.step), srcrect,
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dst.ptr<Npp8u>(), static_cast<int>(dst.step), dstsz, fx, fy, npp_inter[interpolation]) );
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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else
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{
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using namespace ::cv::gpu::device::imgproc;
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typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float fx, float fy, PtrStepSzb dst, int interpolation, cudaStream_t stream);
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static const func_t funcs[6][4] =
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{
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{resize_gpu<uchar> , 0 /*resize_gpu<uchar2>*/ , resize_gpu<uchar3> , resize_gpu<uchar4> },
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{0 /*resize_gpu<schar>*/, 0 /*resize_gpu<char2>*/ , 0 /*resize_gpu<char3>*/, 0 /*resize_gpu<char4>*/},
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{resize_gpu<ushort> , 0 /*resize_gpu<ushort2>*/, resize_gpu<ushort3> , resize_gpu<ushort4> },
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{resize_gpu<short> , 0 /*resize_gpu<short2>*/ , resize_gpu<short3> , resize_gpu<short4> },
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{0 /*resize_gpu<int>*/ , 0 /*resize_gpu<int2>*/ , 0 /*resize_gpu<int3>*/ , 0 /*resize_gpu<int4>*/ },
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{resize_gpu<float> , 0 /*resize_gpu<float2>*/ , resize_gpu<float3> , resize_gpu<float4> }
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};
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const func_t func = funcs[src.depth()][src.channels() - 1];
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CV_Assert(func != 0);
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func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y,
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static_cast<float>(1.0 / fx), static_cast<float>(1.0 / fy), dst, interpolation, stream);
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}
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func(src, wholeSrc, ofs.x, ofs.y, static_cast<float>(1.0 / fx), static_cast<float>(1.0 / fy), dst, interpolation, StreamAccessor::getStream(stream));
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}
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#endif // HAVE_CUDA
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@ -155,7 +155,7 @@ GPU_TEST_P(Resize, Accuracy)
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Resize, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(MatType(CV_8UC3), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
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testing::Values(0.3, 0.5, 1.5, 2.0),
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testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
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WHOLE_SUBMAT));
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@ -201,50 +201,9 @@ GPU_TEST_P(ResizeSameAsHost, Accuracy)
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeSameAsHost, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(MatType(CV_8UC3), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
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testing::Values(0.3, 0.5),
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testing::Values(Interpolation(cv::INTER_AREA), Interpolation(cv::INTER_NEAREST)), //, Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)
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testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_AREA)),
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WHOLE_SUBMAT));
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///////////////////////////////////////////////////////////////////
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// Test NPP
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PARAM_TEST_CASE(ResizeNPP, cv::gpu::DeviceInfo, MatType, double, Interpolation)
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{
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cv::gpu::DeviceInfo devInfo;
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double coeff;
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int interpolation;
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int type;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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type = GET_PARAM(1);
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coeff = GET_PARAM(2);
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interpolation = GET_PARAM(3);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(ResizeNPP, Accuracy)
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{
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cv::Mat src = readImageType("stereobp/aloe-L.png", type);
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ASSERT_FALSE(src.empty());
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cv::gpu::GpuMat dst;
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cv::gpu::resize(loadMat(src), dst, cv::Size(), coeff, coeff, interpolation);
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cv::Mat dst_gold;
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resizeGold(src, dst_gold, coeff, coeff, interpolation);
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EXPECT_MAT_SIMILAR(dst_gold, dst, 1e-1);
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}
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeNPP, testing::Combine(
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ALL_DEVICES,
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC4)),
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testing::Values(0.3, 0.5, 1.5, 2.0),
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testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR))));
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#endif // HAVE_CUDA
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