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724 lines
15 KiB
C++
724 lines
15 KiB
C++
/*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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// Copyright (C) 2013, OpenCV Foundation, 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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#ifndef OPENCV_CORE_CUDAINL_HPP
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#define OPENCV_CORE_CUDAINL_HPP
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#include "opencv2/core/cuda.hpp"
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//! @cond IGNORED
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namespace cv { namespace cuda {
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//===================================================================================
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// GpuMat
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//===================================================================================
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inline
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GpuMat::GpuMat(Allocator* allocator_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
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{}
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inline
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GpuMat::GpuMat(int rows_, int cols_, int type_, Allocator* allocator_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
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{
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if (rows_ > 0 && cols_ > 0)
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create(rows_, cols_, type_);
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}
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inline
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GpuMat::GpuMat(Size size_, int type_, Allocator* allocator_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
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{
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if (size_.height > 0 && size_.width > 0)
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create(size_.height, size_.width, type_);
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}
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inline
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GpuMat::GpuMat(int rows_, int cols_, int type_, Scalar s_, Allocator* allocator_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
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{
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if (rows_ > 0 && cols_ > 0)
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{
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create(rows_, cols_, type_);
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setTo(s_);
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}
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}
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inline
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GpuMat::GpuMat(Size size_, int type_, Scalar s_, Allocator* allocator_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
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{
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if (size_.height > 0 && size_.width > 0)
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{
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create(size_.height, size_.width, type_);
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setTo(s_);
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}
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}
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inline
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GpuMat::GpuMat(const GpuMat& m)
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: flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), allocator(m.allocator)
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{
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if (refcount)
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CV_XADD(refcount, 1);
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}
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inline
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GpuMat::GpuMat(InputArray arr, Allocator* allocator_) :
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flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
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{
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upload(arr);
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}
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inline
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GpuMat::~GpuMat()
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{
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release();
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}
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inline
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GpuMat& GpuMat::operator =(const GpuMat& m)
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{
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if (this != &m)
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{
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GpuMat temp(m);
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swap(temp);
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}
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return *this;
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}
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inline
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void GpuMat::create(Size size_, int type_)
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{
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create(size_.height, size_.width, type_);
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}
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inline
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void GpuMat::swap(GpuMat& b)
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{
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std::swap(flags, b.flags);
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std::swap(rows, b.rows);
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std::swap(cols, b.cols);
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std::swap(step, b.step);
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std::swap(data, b.data);
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std::swap(datastart, b.datastart);
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std::swap(dataend, b.dataend);
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std::swap(refcount, b.refcount);
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std::swap(allocator, b.allocator);
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}
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inline
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GpuMat GpuMat::clone() const
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{
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GpuMat m;
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copyTo(m);
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return m;
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}
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inline
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void GpuMat::copyTo(OutputArray dst, InputArray mask) const
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{
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copyTo(dst, mask, Stream::Null());
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}
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inline
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GpuMat& GpuMat::setTo(Scalar s)
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{
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return setTo(s, Stream::Null());
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}
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inline
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GpuMat& GpuMat::setTo(Scalar s, InputArray mask)
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{
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return setTo(s, mask, Stream::Null());
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}
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inline
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void GpuMat::convertTo(OutputArray dst, int rtype) const
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{
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convertTo(dst, rtype, Stream::Null());
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}
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inline
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void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, double beta) const
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{
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convertTo(dst, rtype, alpha, beta, Stream::Null());
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}
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inline
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void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const
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{
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convertTo(dst, rtype, alpha, 0.0, stream);
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}
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inline
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void GpuMat::assignTo(GpuMat& m, int _type) const
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{
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if (_type < 0)
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m = *this;
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else
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convertTo(m, _type);
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}
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inline
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uchar* GpuMat::ptr(int y)
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{
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CV_DbgAssert( (unsigned)y < (unsigned)rows );
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return data + step * y;
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}
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inline
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const uchar* GpuMat::ptr(int y) const
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{
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CV_DbgAssert( (unsigned)y < (unsigned)rows );
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return data + step * y;
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}
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template<typename _Tp> inline
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_Tp* GpuMat::ptr(int y)
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{
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return (_Tp*)ptr(y);
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}
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template<typename _Tp> inline
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const _Tp* GpuMat::ptr(int y) const
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{
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return (const _Tp*)ptr(y);
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}
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template <class T> inline
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GpuMat::operator PtrStepSz<T>() const
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{
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return PtrStepSz<T>(rows, cols, (T*)data, step);
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}
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template <class T> inline
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GpuMat::operator PtrStep<T>() const
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{
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return PtrStep<T>((T*)data, step);
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}
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inline
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GpuMat GpuMat::row(int y) const
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{
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return GpuMat(*this, Range(y, y+1), Range::all());
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}
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inline
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GpuMat GpuMat::col(int x) const
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{
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return GpuMat(*this, Range::all(), Range(x, x+1));
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}
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inline
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GpuMat GpuMat::rowRange(int startrow, int endrow) const
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{
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return GpuMat(*this, Range(startrow, endrow), Range::all());
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}
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inline
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GpuMat GpuMat::rowRange(Range r) const
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{
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return GpuMat(*this, r, Range::all());
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}
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inline
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GpuMat GpuMat::colRange(int startcol, int endcol) const
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{
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return GpuMat(*this, Range::all(), Range(startcol, endcol));
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}
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inline
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GpuMat GpuMat::colRange(Range r) const
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{
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return GpuMat(*this, Range::all(), r);
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}
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inline
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GpuMat GpuMat::operator ()(Range rowRange_, Range colRange_) const
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{
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return GpuMat(*this, rowRange_, colRange_);
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}
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inline
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GpuMat GpuMat::operator ()(Rect roi) const
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{
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return GpuMat(*this, roi);
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}
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inline
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bool GpuMat::isContinuous() const
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{
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return (flags & Mat::CONTINUOUS_FLAG) != 0;
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}
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inline
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size_t GpuMat::elemSize() const
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{
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return CV_ELEM_SIZE(flags);
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}
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inline
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size_t GpuMat::elemSize1() const
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{
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return CV_ELEM_SIZE1(flags);
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}
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inline
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int GpuMat::type() const
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{
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return CV_MAT_TYPE(flags);
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}
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inline
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int GpuMat::depth() const
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{
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return CV_MAT_DEPTH(flags);
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}
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inline
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int GpuMat::channels() const
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{
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return CV_MAT_CN(flags);
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}
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inline
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size_t GpuMat::step1() const
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{
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return step / elemSize1();
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}
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inline
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Size GpuMat::size() const
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{
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return Size(cols, rows);
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}
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inline
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bool GpuMat::empty() const
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{
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return data == 0;
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}
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inline
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void* GpuMat::cudaPtr() const
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{
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return data;
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}
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static inline
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GpuMat createContinuous(int rows, int cols, int type)
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{
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GpuMat m;
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createContinuous(rows, cols, type, m);
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return m;
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}
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static inline
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void createContinuous(Size size, int type, OutputArray arr)
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{
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createContinuous(size.height, size.width, type, arr);
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}
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static inline
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GpuMat createContinuous(Size size, int type)
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{
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GpuMat m;
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createContinuous(size, type, m);
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return m;
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}
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static inline
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void ensureSizeIsEnough(Size size, int type, OutputArray arr)
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{
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ensureSizeIsEnough(size.height, size.width, type, arr);
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}
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static inline
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void swap(GpuMat& a, GpuMat& b)
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{
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a.swap(b);
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}
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//===================================================================================
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// GpuMatND
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//===================================================================================
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inline
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GpuMatND::GpuMatND() :
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flags(0), dims(0), data(nullptr), offset(0)
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{
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}
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inline
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GpuMatND::GpuMatND(SizeArray _size, int _type) :
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flags(0), dims(0), data(nullptr), offset(0)
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{
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create(std::move(_size), _type);
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}
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inline
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void GpuMatND::swap(GpuMatND& m) noexcept
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{
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std::swap(*this, m);
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}
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inline
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bool GpuMatND::isContinuous() const
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{
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return (flags & Mat::CONTINUOUS_FLAG) != 0;
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}
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inline
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bool GpuMatND::isSubmatrix() const
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{
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return (flags & Mat::SUBMATRIX_FLAG) != 0;
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}
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inline
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size_t GpuMatND::elemSize() const
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{
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return CV_ELEM_SIZE(flags);
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}
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inline
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size_t GpuMatND::elemSize1() const
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{
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return CV_ELEM_SIZE1(flags);
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}
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inline
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bool GpuMatND::empty() const
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{
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return data == nullptr;
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}
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inline
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bool GpuMatND::external() const
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{
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return !empty() && data_.use_count() == 0;
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}
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inline
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uchar* GpuMatND::getDevicePtr() const
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{
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return data + offset;
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}
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inline
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size_t GpuMatND::total() const
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{
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size_t p = 1;
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for(auto s : size)
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p *= s;
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return p;
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}
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inline
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size_t GpuMatND::totalMemSize() const
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{
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return size[0] * step[0];
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}
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inline
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int GpuMatND::type() const
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{
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return CV_MAT_TYPE(flags);
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}
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//===================================================================================
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// HostMem
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//===================================================================================
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inline
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HostMem::HostMem(AllocType alloc_type_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
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{
|
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}
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inline
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HostMem::HostMem(const HostMem& m)
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: flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), alloc_type(m.alloc_type)
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{
|
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if( refcount )
|
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CV_XADD(refcount, 1);
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}
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|
|
inline
|
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HostMem::HostMem(int rows_, int cols_, int type_, AllocType alloc_type_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
|
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{
|
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if (rows_ > 0 && cols_ > 0)
|
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create(rows_, cols_, type_);
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}
|
|
|
|
inline
|
|
HostMem::HostMem(Size size_, int type_, AllocType alloc_type_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
|
|
{
|
|
if (size_.height > 0 && size_.width > 0)
|
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create(size_.height, size_.width, type_);
|
|
}
|
|
|
|
inline
|
|
HostMem::HostMem(InputArray arr, AllocType alloc_type_)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
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|
{
|
|
arr.getMat().copyTo(*this);
|
|
}
|
|
|
|
inline
|
|
HostMem::~HostMem()
|
|
{
|
|
release();
|
|
}
|
|
|
|
inline
|
|
HostMem& HostMem::operator =(const HostMem& m)
|
|
{
|
|
if (this != &m)
|
|
{
|
|
HostMem temp(m);
|
|
swap(temp);
|
|
}
|
|
|
|
return *this;
|
|
}
|
|
|
|
inline
|
|
void HostMem::swap(HostMem& b)
|
|
{
|
|
std::swap(flags, b.flags);
|
|
std::swap(rows, b.rows);
|
|
std::swap(cols, b.cols);
|
|
std::swap(step, b.step);
|
|
std::swap(data, b.data);
|
|
std::swap(datastart, b.datastart);
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|
std::swap(dataend, b.dataend);
|
|
std::swap(refcount, b.refcount);
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std::swap(alloc_type, b.alloc_type);
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}
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|
|
inline
|
|
HostMem HostMem::clone() const
|
|
{
|
|
HostMem m(size(), type(), alloc_type);
|
|
createMatHeader().copyTo(m);
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|
return m;
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|
}
|
|
|
|
inline
|
|
void HostMem::create(Size size_, int type_)
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|
{
|
|
create(size_.height, size_.width, type_);
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|
}
|
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|
|
inline
|
|
Mat HostMem::createMatHeader() const
|
|
{
|
|
return Mat(size(), type(), data, step);
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|
}
|
|
|
|
inline
|
|
bool HostMem::isContinuous() const
|
|
{
|
|
return (flags & Mat::CONTINUOUS_FLAG) != 0;
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|
}
|
|
|
|
inline
|
|
size_t HostMem::elemSize() const
|
|
{
|
|
return CV_ELEM_SIZE(flags);
|
|
}
|
|
|
|
inline
|
|
size_t HostMem::elemSize1() const
|
|
{
|
|
return CV_ELEM_SIZE1(flags);
|
|
}
|
|
|
|
inline
|
|
int HostMem::type() const
|
|
{
|
|
return CV_MAT_TYPE(flags);
|
|
}
|
|
|
|
inline
|
|
int HostMem::depth() const
|
|
{
|
|
return CV_MAT_DEPTH(flags);
|
|
}
|
|
|
|
inline
|
|
int HostMem::channels() const
|
|
{
|
|
return CV_MAT_CN(flags);
|
|
}
|
|
|
|
inline
|
|
size_t HostMem::step1() const
|
|
{
|
|
return step / elemSize1();
|
|
}
|
|
|
|
inline
|
|
Size HostMem::size() const
|
|
{
|
|
return Size(cols, rows);
|
|
}
|
|
|
|
inline
|
|
bool HostMem::empty() const
|
|
{
|
|
return data == 0;
|
|
}
|
|
|
|
static inline
|
|
void swap(HostMem& a, HostMem& b)
|
|
{
|
|
a.swap(b);
|
|
}
|
|
|
|
//===================================================================================
|
|
// Stream
|
|
//===================================================================================
|
|
|
|
inline
|
|
Stream::Stream(const Ptr<Impl>& impl)
|
|
: impl_(impl)
|
|
{
|
|
}
|
|
|
|
//===================================================================================
|
|
// Event
|
|
//===================================================================================
|
|
|
|
inline
|
|
Event::Event(const Ptr<Impl>& impl)
|
|
: impl_(impl)
|
|
{
|
|
}
|
|
|
|
//===================================================================================
|
|
// Initialization & Info
|
|
//===================================================================================
|
|
|
|
inline
|
|
bool TargetArchs::has(int major, int minor)
|
|
{
|
|
return hasPtx(major, minor) || hasBin(major, minor);
|
|
}
|
|
|
|
inline
|
|
bool TargetArchs::hasEqualOrGreater(int major, int minor)
|
|
{
|
|
return hasEqualOrGreaterPtx(major, minor) || hasEqualOrGreaterBin(major, minor);
|
|
}
|
|
|
|
inline
|
|
DeviceInfo::DeviceInfo()
|
|
{
|
|
device_id_ = getDevice();
|
|
}
|
|
|
|
inline
|
|
DeviceInfo::DeviceInfo(int device_id)
|
|
{
|
|
CV_Assert( device_id >= 0 && device_id < getCudaEnabledDeviceCount() );
|
|
device_id_ = device_id;
|
|
}
|
|
|
|
inline
|
|
int DeviceInfo::deviceID() const
|
|
{
|
|
return device_id_;
|
|
}
|
|
|
|
inline
|
|
size_t DeviceInfo::freeMemory() const
|
|
{
|
|
size_t _totalMemory = 0, _freeMemory = 0;
|
|
queryMemory(_totalMemory, _freeMemory);
|
|
return _freeMemory;
|
|
}
|
|
|
|
inline
|
|
size_t DeviceInfo::totalMemory() const
|
|
{
|
|
size_t _totalMemory = 0, _freeMemory = 0;
|
|
queryMemory(_totalMemory, _freeMemory);
|
|
return _totalMemory;
|
|
}
|
|
|
|
inline
|
|
bool DeviceInfo::supports(FeatureSet feature_set) const
|
|
{
|
|
int version = majorVersion() * 10 + minorVersion();
|
|
return version >= feature_set;
|
|
}
|
|
|
|
|
|
}} // namespace cv { namespace cuda {
|
|
|
|
//===================================================================================
|
|
// Mat
|
|
//===================================================================================
|
|
|
|
namespace cv {
|
|
|
|
inline
|
|
Mat::Mat(const cuda::GpuMat& m)
|
|
: flags(0), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows)
|
|
{
|
|
m.download(*this);
|
|
}
|
|
|
|
}
|
|
|
|
//! @endcond
|
|
|
|
#endif // OPENCV_CORE_CUDAINL_HPP
|