Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
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// derived from this software without specific prior written permission.
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// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
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//M*/
#include "precomp.hpp"
#if !defined HAVE_CUDA || defined(CUDA_DISABLER)
void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
{
(void)src;
(void)dst;
(void)dsize;
(void)fx;
(void)fy;
(void)interpolation;
(void)s;
throw_nogpu();
}
#else // HAVE_CUDA
namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
template <typename T>
void resize_gpu(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float fx, float fy,
PtrStepSzb dst, int interpolation, cudaStream_t stream);
}
}}}
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);
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)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float fx, float fy, PtrStepSzb 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, PtrStepSzb(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);
}
}
#endif // HAVE_CUDA