Open Source Computer Vision Library
https://opencv.org/
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189 lines
6.1 KiB
189 lines
6.1 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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template <typename T, typename R> |
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void minMaxImpl(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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if (mask.empty()) |
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gridFindMinMaxVal(src, dst, stream); |
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else |
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gridFindMinMaxVal(src, dst, globPtr<uchar>(mask), stream); |
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} |
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template <typename T, typename R> |
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void minMaxImpl(const GpuMat& src, const GpuMat& mask, double* minVal, double* maxVal) |
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{ |
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BufferPool pool(Stream::Null()); |
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GpuMat buf(pool.getBuffer(1, 2, DataType<R>::type)); |
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minMaxImpl<T, R>(src, mask, buf, Stream::Null()); |
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R data[2]; |
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buf.download(Mat(1, 2, buf.type(), data)); |
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} |
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} |
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void cv::cuda::findMinMax(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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minMaxImpl<uchar, int>, |
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minMaxImpl<schar, int>, |
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minMaxImpl<ushort, int>, |
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minMaxImpl<short, int>, |
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minMaxImpl<int, int>, |
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minMaxImpl<float, float>, |
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minMaxImpl<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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const int src_depth = src.depth(); |
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const int dst_depth = src_depth < CV_32F ? CV_32S : src_depth; |
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GpuMat dst = getOutputMat(_dst, 1, 2, dst_depth, 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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void cv::cuda::minMax(InputArray _src, double* minVal, double* maxVal, InputArray _mask) |
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{ |
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Stream& stream = Stream::Null(); |
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HostMem dst; |
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findMinMax(_src, dst, _mask, stream); |
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stream.waitForCompletion(); |
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double vals[2]; |
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dst.createMatHeader().convertTo(Mat(1, 2, CV_64FC1, &vals[0]), CV_64F); |
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if (minVal) |
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*minVal = vals[0]; |
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if (maxVal) |
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*maxVal = vals[1]; |
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} |
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namespace cv { namespace cuda { namespace device { |
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void findMaxAbs(InputArray _src, OutputArray _dst, 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 findMaxAbsImpl(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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if (mask.empty()) |
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gridFindMaxVal(abs_(src), dst, stream); |
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else |
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gridFindMaxVal(abs_(src), dst, globPtr<uchar>(mask), stream); |
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} |
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} |
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void cv::cuda::device::findMaxAbs(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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findMaxAbsImpl<uchar, int>, |
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findMaxAbsImpl<schar, int>, |
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findMaxAbsImpl<ushort, int>, |
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findMaxAbsImpl<short, int>, |
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findMaxAbsImpl<int, int>, |
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findMaxAbsImpl<float, float>, |
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findMaxAbsImpl<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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const int src_depth = src.depth(); |
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const int dst_depth = src_depth < CV_32F ? CV_32S : src_depth; |
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GpuMat dst = getOutputMat(_dst, 1, 1, dst_depth, 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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