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rename cv::cuda::internal namespace to cv::cuda::device to prevent conflicts with cv::internal
190 lines
6.4 KiB
Plaintext
190 lines
6.4 KiB
Plaintext
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "opencv2/opencv_modules.hpp"
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#ifndef HAVE_OPENCV_CUDEV
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#error "opencv_cudev is required"
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#else
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#include "opencv2/cudaarithm.hpp"
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#include "opencv2/cudev.hpp"
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#include "opencv2/core/private.cuda.hpp"
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using namespace cv;
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using namespace cv::cuda;
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using namespace cv::cudev;
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namespace
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{
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void normDiffInf(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _dst, Stream& stream)
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{
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const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1;
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const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2;
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GpuMat_<int>& dst = (GpuMat_<int>&) _dst;
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gridFindMaxVal(abs_(cvt_<int>(src1) - cvt_<int>(src2)), dst, stream);
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}
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void normDiffL1(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _dst, Stream& stream)
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{
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const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1;
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const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2;
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GpuMat_<int>& dst = (GpuMat_<int>&) _dst;
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gridCalcSum(abs_(cvt_<int>(src1) - cvt_<int>(src2)), dst, stream);
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}
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void normDiffL2(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _dst, Stream& stream)
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{
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const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1;
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const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2;
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GpuMat_<double>& dst = (GpuMat_<double>&) _dst;
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BufferPool pool(stream);
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GpuMat_<double> buf(1, 1, pool.getAllocator());
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gridCalcSum(sqr_(cvt_<double>(src1) - cvt_<double>(src2)), buf, stream);
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gridTransformUnary(buf, dst, sqrt_func<double>(), stream);
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}
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}
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void cv::cuda::calcNormDiff(InputArray _src1, InputArray _src2, OutputArray _dst, int normType, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _dst, Stream& stream);
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static const func_t funcs[] =
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{
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0, normDiffInf, normDiffL1, 0, normDiffL2
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};
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GpuMat src1 = getInputMat(_src1, stream);
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GpuMat src2 = getInputMat(_src2, stream);
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CV_Assert( src1.type() == CV_8UC1 );
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CV_Assert( src1.size() == src2.size() && src1.type() == src2.type() );
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CV_Assert( normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2 );
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GpuMat dst = getOutputMat(_dst, 1, 1, normType == NORM_L2 ? CV_64FC1 : CV_32SC1, stream);
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const func_t func = funcs[normType];
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func(src1, src2, dst, stream);
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syncOutput(dst, _dst, stream);
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}
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double cv::cuda::norm(InputArray _src1, InputArray _src2, int normType)
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{
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Stream& stream = Stream::Null();
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HostMem dst;
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calcNormDiff(_src1, _src2, dst, normType, stream);
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stream.waitForCompletion();
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double val;
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dst.createMatHeader().convertTo(Mat(1, 1, CV_64FC1, &val), CV_64F);
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return val;
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}
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namespace cv { namespace cuda { namespace device {
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void normL2(cv::InputArray _src, cv::OutputArray _dst, cv::InputArray _mask, Stream& stream);
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}}}
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namespace
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{
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template <typename T, typename R>
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void normL2Impl(const GpuMat& _src, const GpuMat& mask, GpuMat& _dst, Stream& stream)
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{
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const GpuMat_<T>& src = (const GpuMat_<T>&) _src;
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GpuMat_<R>& dst = (GpuMat_<R>&) _dst;
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BufferPool pool(stream);
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GpuMat_<double> buf(1, 1, pool.getAllocator());
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if (mask.empty())
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{
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gridCalcSum(sqr_(cvt_<double>(src)), buf, stream);
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}
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else
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{
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gridCalcSum(sqr_(cvt_<double>(src)), buf, globPtr<uchar>(mask), stream);
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}
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gridTransformUnary(buf, dst, sqrt_func<double>(), stream);
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}
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}
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void cv::cuda::device::normL2(InputArray _src, OutputArray _dst, InputArray _mask, Stream& stream)
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{
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typedef void (*func_t)(const GpuMat& _src, const GpuMat& mask, GpuMat& _dst, Stream& stream);
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static const func_t funcs[] =
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{
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normL2Impl<uchar, double>,
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normL2Impl<schar, double>,
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normL2Impl<ushort, double>,
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normL2Impl<short, double>,
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normL2Impl<int, double>,
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normL2Impl<float, double>,
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normL2Impl<double, double>
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};
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const GpuMat src = getInputMat(_src, stream);
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const GpuMat mask = getInputMat(_mask, stream);
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CV_Assert( src.channels() == 1 );
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CV_Assert( mask.empty() || (mask.size() == src.size() && mask.type() == CV_8U) );
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GpuMat dst = getOutputMat(_dst, 1, 1, CV_64FC1, stream);
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const func_t func = funcs[src.depth()];
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func(src, mask, dst, stream);
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syncOutput(dst, _dst, stream);
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}
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#endif
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