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linux compiletion error
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07825bad1e
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@ -76,7 +76,7 @@ inline GpuMat::GpuMat(int _rows, int _cols, int _type, const Scalar& _s)
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*this = _s;
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}
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}
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inline GpuMat::GpuMat(Size _size, int _type, const Scalar& _s)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
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{
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@ -85,7 +85,7 @@ inline GpuMat::GpuMat(Size _size, int _type, const Scalar& _s)
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create( _size.height, _size.width, _type );
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*this = _s;
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}
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}
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}
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inline 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)
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@ -182,8 +182,8 @@ inline GpuMat::GpuMat(const GpuMat& m, const Rect& roi)
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if( rows <= 0 || cols <= 0 )
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rows = cols = 0;
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}
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inline GpuMat::GpuMat(const Mat& m)
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inline GpuMat::GpuMat(const Mat& m)
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: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) { upload(m); }
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inline GpuMat::~GpuMat() { release(); }
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@ -217,7 +217,7 @@ template <class T> inline GpuMat::operator DevMem2D_<T>() const { return DevMem2
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return m;
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}
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//CPP void GpuMat::download(cv::Mat& m) const;
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//CPP void GpuMat::download(cv::Mat& m) const;
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inline GpuMat GpuMat::row(int y) const { return GpuMat(*this, Range(y, y+1), Range::all()); }
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inline GpuMat GpuMat::col(int x) const { return GpuMat(*this, Range::all(), Range(x, x+1)); }
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@ -252,7 +252,7 @@ inline void GpuMat::create(Size _size, int _type) { create(_size.height, _size.w
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//CPP void GpuMat::create(int _rows, int _cols, int _type);
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//CPP void GpuMat::release();
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inline void GpuMat::swap(GpuMat& b)
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inline 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 ); std::swap( cols, b.cols );
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@ -342,27 +342,27 @@ static inline void swap( GpuMat& a, GpuMat& b ) { a.swap(b); }
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//////////////////////////////// MatPL ////////////////////////////////
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///////////////////////////////////////////////////////////////////////
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MatPL::MatPL() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) {}
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MatPL::MatPL(int _rows, int _cols, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
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inline MatPL::MatPL() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) {}
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inline MatPL::MatPL(int _rows, int _cols, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
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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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MatPL::MatPL(Size _size, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
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inline MatPL::MatPL(Size _size, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
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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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MatPL::MatPL(const MatPL& m) : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(0), dataend(0)
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inline MatPL::MatPL(const MatPL& m) : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(0), dataend(0)
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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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MatPL::MatPL(const Mat& m) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
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inline MatPL::MatPL(const Mat& m) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
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{
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if( m.rows > 0 && m.cols > 0 )
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create( m.size(), m.type() );
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@ -371,11 +371,11 @@ MatPL::MatPL(const Mat& m) : flags(0), rows(0), cols(0), step(0), data(0), refco
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m.copyTo(tmp);
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}
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MatPL::~MatPL()
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inline MatPL::~MatPL()
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{
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release();
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}
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MatPL& MatPL::operator = (const MatPL& m)
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inline MatPL& MatPL::operator = (const MatPL& m)
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{
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if( this != &m )
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{
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@ -384,7 +384,7 @@ MatPL& MatPL::operator = (const MatPL& m)
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release();
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flags = m.flags;
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rows = m.rows; cols = m.cols;
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step = m.step; data = m.data;
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step = m.step; data = m.data;
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datastart = m.datastart;
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dataend = m.dataend;
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refcount = m.refcount;
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@ -392,17 +392,17 @@ MatPL& MatPL::operator = (const MatPL& m)
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return *this;
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}
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MatPL MatPL::clone() const
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inline MatPL MatPL::clone() const
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{
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MatPL m(size(), type());
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MatPL m(size(), type());
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Mat to = m;
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Mat from = *this;
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from.copyTo(to);
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return m;
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}
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inline void MatPL::create(Size _size, int _type) { create(_size.height, _size.width, _type); }
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//CCP void MatPL::create(int _rows, int _cols, int _type);
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inline void MatPL::create(Size _size, int _type) { create(_size.height, _size.width, _type); }
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//CCP void MatPL::create(int _rows, int _cols, int _type);
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//CPP void MatPL::release();
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inline Mat MatPL::createMatHeader() const { return Mat(size(), type(), data); }
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@ -416,11 +416,11 @@ inline int MatPL::depth() const { return CV_MAT_DEPTH(flags); }
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inline int MatPL::channels() const { return CV_MAT_CN(flags); }
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inline size_t MatPL::step1() const { return step/elemSize1(); }
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inline Size MatPL::size() const { return Size(cols, rows); }
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inline bool MatPL::empty() const { return data == 0; }
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inline bool MatPL::empty() const { return data == 0; }
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} /* end of namespace gpu */
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} /* end of namespace cv */
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#endif /* __OPENCV_GPU_MATRIX_OPERATIONS_HPP__ */
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#endif /* __OPENCV_GPU_MATRIX_OPERATIONS_HPP__ */
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@ -44,23 +44,26 @@
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#define __OPENCV_CUDA_SHARED_HPP__
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#include "opencv2/gpu/devmem2d.hpp"
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#include "cuda_runtime_api.h"
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#include "cuda_runtime_api.h"
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namespace cv
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{
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namespace gpu
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{
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{
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typedef unsigned char uchar;
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typedef unsigned short ushort;
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typedef unsigned int uint;
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typedef unsigned int uint;
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extern "C" void error( const char *error_string, const char *file, const int line, const char *func = "");
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namespace impl
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{
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{
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static inline int divUp(int a, int b) { return (a % b == 0) ? a/b : a/b + 1; }
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extern "C" void stereoBM_GPU(const DevMem2D& left, const DevMem2D& right, DevMem2D& disp, int maxdisp, DevMem2D_<uint>& minSSD_buf);
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extern "C" void set_to_without_mask (const DevMem2D& mat, const double * scalar, int depth, int channels);
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extern "C" void set_to_with_mask (const DevMem2D& mat, const double * scalar, const DevMem2D& mask, int depth, int channels);
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}
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}
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}
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@ -68,12 +71,12 @@ namespace cv
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#if defined(__GNUC__)
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#define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__, __func__);
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#else /* defined(__CUDACC__) || defined(__MSVC__) */
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#define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__)
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#define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__)
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#endif
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static inline void ___cudaSafeCall(cudaError_t err, const char *file, const int line, const char *func = "")
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{
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if( cudaSuccess != err)
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if( cudaSuccess != err)
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cv::gpu::error(cudaGetErrorString(err), __FILE__, __LINE__, func);
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}
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150
modules/gpu/src/cuda/matrix_operations.cu
Normal file
150
modules/gpu/src/cuda/matrix_operations.cu
Normal file
@ -0,0 +1,150 @@
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/*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 <stddef.h>
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#include "cuda_shared.hpp"
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#include "cuda_runtime.h"
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__constant__ float scalar_d[4];
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namespace mat_operators
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{
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template <typename T, int channels, int count = channels>
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struct unroll
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{
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__device__ static void unroll_set(T * mat, size_t i)
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{
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mat[i] = static_cast<T>(scalar_d[i % channels]);
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unroll<T, channels, count - 1>::unroll_set(mat, i+1);
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}
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__device__ static void unroll_set_with_mask(T * mat, float mask, size_t i)
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{
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mat[i] = mask * static_cast<T>(scalar_d[i % channels]);
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unroll<T, channels, count - 1>::unroll_set_with_mask(mat, mask, i+1);
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}
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};
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template <typename T, int channels>
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struct unroll<T,channels,0>
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{
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__device__ static void unroll_set(T * , size_t){}
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__device__ static void unroll_set_with_mask(T * , float, size_t){}
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};
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template <typename T, int channels>
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__global__ void kernel_set_to_without_mask(T * mat)
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{
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size_t i = (blockIdx.x * blockDim.x + threadIdx.x) * sizeof(T);
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unroll<T, channels>::unroll_set(mat, i);
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}
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template <typename T, int channels>
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__global__ void kernel_set_to_with_mask(T * mat, const float * mask)
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{
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size_t i = (blockIdx.x * blockDim.x + threadIdx.x) * sizeof(T);
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unroll<T, channels>::unroll_set_with_mask(mat, i, mask[i]);
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}
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}
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extern "C" void cv::gpu::impl::set_to_with_mask(const DevMem2D& mat, const double * scalar, const DevMem2D& mask, int depth, int channels)
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{
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scalar_d[0] = scalar[0];
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scalar_d[1] = scalar[1];
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scalar_d[2] = scalar[2];
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scalar_d[3] = scalar[3];
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dim3 numBlocks(mat.rows * mat.step / 256, 1, 1);
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dim3 threadsPerBlock(256);
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if (channels == 1)
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{
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if (depth == 1) ::mat_operators::kernel_set_to_with_mask<unsigned char, 1><<<numBlocks,threadsPerBlock>>>(mat.ptr, (float *)mask.ptr);
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if (depth == 2) ::mat_operators::kernel_set_to_with_mask<unsigned short, 1><<<numBlocks,threadsPerBlock>>>((unsigned short *)mat.ptr, (float *)mask.ptr);
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if (depth == 4) ::mat_operators::kernel_set_to_with_mask<unsigned int, 1><<<numBlocks,threadsPerBlock>>>((unsigned int *)mat.ptr, (float *)mask.ptr);
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}
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if (channels == 2)
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{
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if (depth == 1) ::mat_operators::kernel_set_to_with_mask<unsigned char, 2><<<numBlocks,threadsPerBlock>>>(mat.ptr, (float *)mask.ptr);
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if (depth == 2) ::mat_operators::kernel_set_to_with_mask<unsigned short, 2><<<numBlocks,threadsPerBlock>>>((unsigned short *)mat.ptr, (float *)mask.ptr);
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if (depth == 4) ::mat_operators::kernel_set_to_with_mask<unsigned int, 2><<<numBlocks,threadsPerBlock>>>((unsigned int *)mat.ptr, (float *)mask.ptr);
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}
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if (channels == 3)
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{
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if (depth == 1) ::mat_operators::kernel_set_to_with_mask<unsigned char, 3><<<numBlocks,threadsPerBlock>>>(mat.ptr, (float *)mask.ptr);
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if (depth == 2) ::mat_operators::kernel_set_to_with_mask<unsigned short, 3><<<numBlocks,threadsPerBlock>>>((unsigned short *)mat.ptr, (float *)mask.ptr);
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if (depth == 4) ::mat_operators::kernel_set_to_with_mask<unsigned int, 3><<<numBlocks,threadsPerBlock>>>((unsigned int *)mat.ptr, (float *)mask.ptr);
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}
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}
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extern "C" void cv::gpu::impl::set_to_without_mask(const DevMem2D& mat, const double * scalar, int depth, int channels)
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{
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scalar_d[0] = scalar[0];
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scalar_d[1] = scalar[1];
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scalar_d[2] = scalar[2];
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scalar_d[3] = scalar[3];
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int numBlocks = mat.rows * mat.step / 256;
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dim3 threadsPerBlock(256);
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if (channels == 1)
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{
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if (depth == 1) ::mat_operators::kernel_set_to_without_mask<unsigned char, 1><<<numBlocks,threadsPerBlock>>>(mat.ptr);
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if (depth == 2) ::mat_operators::kernel_set_to_without_mask<unsigned short, 1><<<numBlocks,threadsPerBlock>>>((unsigned short *)mat.ptr);
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if (depth == 4) ::mat_operators::kernel_set_to_without_mask<unsigned int, 1><<<numBlocks,threadsPerBlock>>>((unsigned int *)mat.ptr);
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}
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if (channels == 2)
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{
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if (depth == 1) ::mat_operators::kernel_set_to_without_mask<unsigned char, 2><<<numBlocks,threadsPerBlock>>>(mat.ptr);
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if (depth == 2) ::mat_operators::kernel_set_to_without_mask<unsigned short, 2><<<numBlocks,threadsPerBlock>>>((unsigned short *)mat.ptr);
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if (depth == 4) ::mat_operators::kernel_set_to_without_mask<unsigned int, 2><<<numBlocks,threadsPerBlock>>>((unsigned int *)mat.ptr);
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}
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if (channels == 3)
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{
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if (depth == 1) ::mat_operators::kernel_set_to_without_mask<unsigned char, 3><<<numBlocks,threadsPerBlock>>>(mat.ptr);
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if (depth == 2) ::mat_operators::kernel_set_to_without_mask<unsigned short, 3><<<numBlocks,threadsPerBlock>>>((unsigned short *)mat.ptr);
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if (depth == 4) ::mat_operators::kernel_set_to_without_mask<unsigned int, 3><<<numBlocks,threadsPerBlock>>>((unsigned int *)mat.ptr);
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}
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}
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@ -74,13 +74,13 @@ struct CudaStream::Impl
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cudaStream_t stream;
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int ref_counter;
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};
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namespace
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namespace
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{
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template<class S, class D> void devcopy(const S& src, D& dst, cudaStream_t s, cudaMemcpyKind k)
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{
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dst.create(src.size(), src.type());
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size_t bwidth = src.cols * src.elemSize();
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cudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, k, s) );
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cudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, k, s) );
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};
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}
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@ -97,7 +97,7 @@ void cv::gpu::CudaStream::create()
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impl = (CudaStream::Impl*)fastMalloc(sizeof(CudaStream::Impl));
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impl->stream = stream;
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impl->ref_counter = 1;
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impl->ref_counter = 1;
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}
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void cv::gpu::CudaStream::release()
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@ -125,7 +125,7 @@ CudaStream& cv::gpu::CudaStream::operator=(const CudaStream& stream)
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CV_XADD(&stream.impl->ref_counter, 1);
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release();
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impl = stream.impl;
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impl = stream.impl;
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}
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return *this;
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}
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@ -138,20 +138,21 @@ bool cv::gpu::CudaStream::queryIfComplete()
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return err == cudaSuccess;
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cudaSafeCall(err);
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return false;
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}
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void cv::gpu::CudaStream::waitForCompletion() { cudaSafeCall( cudaStreamSynchronize( impl->stream ) ); }
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void cv::gpu::CudaStream::enqueueDownload(const GpuMat& src, Mat& dst)
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{
|
||||
void cv::gpu::CudaStream::enqueueDownload(const GpuMat& src, Mat& dst)
|
||||
{
|
||||
// if not -> allocation will be done, but after that dst will not point to page locked memory
|
||||
CV_Assert(src.cols == dst.cols && src.rows == dst.rows && src.type() == dst.type() )
|
||||
devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost);
|
||||
devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost);
|
||||
}
|
||||
void cv::gpu::CudaStream::enqueueDownload(const GpuMat& src, MatPL& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost); }
|
||||
|
||||
void cv::gpu::CudaStream::enqueueUpload(const MatPL& src, GpuMat& dst){ devcopy(src, dst, impl->stream, cudaMemcpyHostToDevice); }
|
||||
void cv::gpu::CudaStream::enqueueUpload(const Mat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyHostToDevice); }
|
||||
void cv::gpu::CudaStream::enqueueUpload(const Mat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyHostToDevice); }
|
||||
void cv::gpu::CudaStream::enqueueCopy(const GpuMat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToDevice); }
|
||||
|
||||
void cv::gpu::CudaStream::enqueueMemSet(const GpuMat& src, Scalar val)
|
||||
@ -170,4 +171,4 @@ void cv::gpu::CudaStream::enqueueConvert(const GpuMat& src, GpuMat& dst, int typ
|
||||
}
|
||||
|
||||
|
||||
#endif /* !defined (HAVE_CUDA) */
|
||||
#endif /* !defined (HAVE_CUDA) */
|
||||
|
@ -100,7 +100,7 @@ void cv::gpu::GpuMat::copyTo( GpuMat& m ) const
|
||||
}
|
||||
|
||||
void cv::gpu::GpuMat::copyTo( GpuMat& /*m*/, const GpuMat&/* mask */) const
|
||||
{
|
||||
{
|
||||
CV_Assert(!"Not implemented");
|
||||
}
|
||||
|
||||
@ -109,15 +109,27 @@ void cv::gpu::GpuMat::convertTo( GpuMat& /*m*/, int /*rtype*/, double /*alpha*/,
|
||||
CV_Assert(!"Not implemented");
|
||||
}
|
||||
|
||||
GpuMat& cv::gpu::GpuMat::operator = (const Scalar& /*s*/)
|
||||
GpuMat& GpuMat::operator = (const Scalar& s)
|
||||
{
|
||||
CV_Assert(!"Not implemented");
|
||||
cv::gpu::impl::set_to_without_mask(*this, s.val, this->depth(), this->channels());
|
||||
return *this;
|
||||
}
|
||||
|
||||
GpuMat& cv::gpu::GpuMat::setTo(const Scalar& /*s*/, const GpuMat& /*mask*/)
|
||||
GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask)
|
||||
{
|
||||
CV_Assert(!"Not implemented");
|
||||
CV_Assert(mask.type() == CV_8U);
|
||||
|
||||
CV_DbgAssert(!this->empty());
|
||||
|
||||
if (mask.empty())
|
||||
{
|
||||
cv::gpu::impl::set_to_without_mask(*this, s.val, this->depth(), this->channels());
|
||||
}
|
||||
else
|
||||
{
|
||||
cv::gpu::impl::set_to_with_mask(*this, s.val, mask, this->depth(), this->channels());
|
||||
}
|
||||
|
||||
return *this;
|
||||
}
|
||||
|
||||
@ -177,7 +189,7 @@ void cv::gpu::GpuMat::create(int _rows, int _cols, int _type)
|
||||
rows = _rows;
|
||||
cols = _cols;
|
||||
|
||||
size_t esz = elemSize();
|
||||
size_t esz = elemSize();
|
||||
|
||||
void *dev_ptr;
|
||||
cudaSafeCall( cudaMallocPitch(&dev_ptr, &step, esz * cols, rows) );
|
||||
@ -189,7 +201,7 @@ void cv::gpu::GpuMat::create(int _rows, int _cols, int _type)
|
||||
size_t nettosize = (size_t)_nettosize;
|
||||
|
||||
datastart = data = (uchar*)dev_ptr;
|
||||
dataend = data + nettosize;
|
||||
dataend = data + nettosize;
|
||||
|
||||
refcount = (int*)fastMalloc(sizeof(*refcount));
|
||||
*refcount = 1;
|
||||
@ -201,7 +213,7 @@ void cv::gpu::GpuMat::release()
|
||||
if( refcount && CV_XADD(refcount, -1) == 1 )
|
||||
{
|
||||
fastFree(refcount);
|
||||
cudaSafeCall( cudaFree(datastart) );
|
||||
cudaSafeCall( cudaFree(datastart) );
|
||||
}
|
||||
data = datastart = dataend = 0;
|
||||
step = rows = cols = 0;
|
||||
@ -233,12 +245,12 @@ void cv::gpu::MatPL::create(int _rows, int _cols, int _type)
|
||||
CV_Error(CV_StsNoMem, "Too big buffer is allocated");
|
||||
size_t datasize = alignSize(nettosize, (int)sizeof(*refcount));
|
||||
|
||||
//datastart = data = (uchar*)fastMalloc(datasize + sizeof(*refcount));
|
||||
//datastart = data = (uchar*)fastMalloc(datasize + sizeof(*refcount));
|
||||
void *ptr;
|
||||
cudaSafeCall( cudaHostAlloc( &ptr, datasize, cudaHostAllocDefault) );
|
||||
|
||||
datastart = data = (uchar*)ptr;
|
||||
dataend = data + nettosize;
|
||||
datastart = data = (uchar*)ptr;
|
||||
dataend = data + nettosize;
|
||||
|
||||
refcount = (int*)cv::fastMalloc(sizeof(*refcount));
|
||||
*refcount = 1;
|
||||
@ -257,4 +269,4 @@ void cv::gpu::MatPL::release()
|
||||
refcount = 0;
|
||||
}
|
||||
|
||||
#endif /* !defined (HAVE_CUDA) */
|
||||
#endif /* !defined (HAVE_CUDA) */
|
||||
|
Loading…
Reference in New Issue
Block a user