Open Source Computer Vision Library
https://opencv.org/
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189 lines
6.4 KiB
189 lines
6.4 KiB
/*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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