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240 lines
9.1 KiB
C++
240 lines
9.1 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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// 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 "precomp.hpp"
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using namespace cv;
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using namespace cv::gpu;
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#if !defined (HAVE_CUDA)
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void cv::gpu::Stream::create() { throw_nogpu(); }
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void cv::gpu::Stream::release() { throw_nogpu(); }
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cv::gpu::Stream::Stream() : impl(0) { throw_nogpu(); }
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cv::gpu::Stream::~Stream() { throw_nogpu(); }
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cv::gpu::Stream::Stream(const Stream& /*stream*/) { throw_nogpu(); }
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Stream& cv::gpu::Stream::operator=(const Stream& /*stream*/) { throw_nogpu(); return *this; }
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bool cv::gpu::Stream::queryIfComplete() { throw_nogpu(); return true; }
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void cv::gpu::Stream::waitForCompletion() { throw_nogpu(); }
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void cv::gpu::Stream::enqueueDownload(const GpuMat& /*src*/, Mat& /*dst*/) { throw_nogpu(); }
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void cv::gpu::Stream::enqueueDownload(const GpuMat& /*src*/, CudaMem& /*dst*/) { throw_nogpu(); }
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void cv::gpu::Stream::enqueueUpload(const CudaMem& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
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void cv::gpu::Stream::enqueueUpload(const Mat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
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void cv::gpu::Stream::enqueueCopy(const GpuMat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
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void cv::gpu::Stream::enqueueMemSet(GpuMat& /*src*/, Scalar /*val*/) { throw_nogpu(); }
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void cv::gpu::Stream::enqueueMemSet(GpuMat& /*src*/, Scalar /*val*/, const GpuMat& /*mask*/) { throw_nogpu(); }
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void cv::gpu::Stream::enqueueConvert(const GpuMat& /*src*/, GpuMat& /*dst*/, int /*type*/, double /*a*/, double /*b*/) { throw_nogpu(); }
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#else /* !defined (HAVE_CUDA) */
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#include "opencv2/gpu/stream_accessor.hpp"
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namespace cv
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{
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namespace gpu
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{
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namespace matrix_operations
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{
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void copy_to_with_mask(const DevMem2D& src, DevMem2D dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
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template <typename T>
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void set_to_gpu(const DevMem2D& mat, const T* scalar, int channels, cudaStream_t stream);
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template <typename T>
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void set_to_gpu(const DevMem2D& mat, const T* scalar, const DevMem2D& mask, int channels, cudaStream_t stream);
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void convert_gpu(const DevMem2D& src, int sdepth, const DevMem2D& dst, int ddepth, double alpha, double beta, cudaStream_t stream = 0);
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}
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}
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}
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struct Stream::Impl
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{
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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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{
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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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};
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template <typename T>
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void kernelSet(GpuMat& src, const Scalar& s, cudaStream_t stream)
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{
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Scalar_<T> sf = s;
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matrix_operations::set_to_gpu(src, sf.val, src.channels(), stream);
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}
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template <typename T>
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void kernelSetMask(GpuMat& src, const Scalar& s, const GpuMat& mask, cudaStream_t stream)
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{
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Scalar_<T> sf = s;
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matrix_operations::set_to_gpu(src, sf.val, mask, src.channels(), stream);
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}
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}
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CV_EXPORTS cudaStream_t cv::gpu::StreamAccessor::getStream(const Stream& stream) { return stream.impl->stream; };
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void cv::gpu::Stream::create()
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{
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if (impl)
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release();
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cudaStream_t stream;
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cudaSafeCall( cudaStreamCreate( &stream ) );
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impl = (Stream::Impl*)fastMalloc(sizeof(Stream::Impl));
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impl->stream = stream;
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impl->ref_counter = 1;
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}
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void cv::gpu::Stream::release()
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{
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if( impl && CV_XADD(&impl->ref_counter, -1) == 1 )
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{
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cudaSafeCall( cudaStreamDestroy( impl->stream ) );
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cv::fastFree( impl );
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}
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}
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cv::gpu::Stream::Stream() : impl(0) { create(); }
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cv::gpu::Stream::~Stream() { release(); }
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cv::gpu::Stream::Stream(const Stream& stream) : impl(stream.impl)
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{
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if( impl )
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CV_XADD(&impl->ref_counter, 1);
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}
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Stream& cv::gpu::Stream::operator=(const Stream& stream)
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{
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if( this != &stream )
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{
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if( stream.impl )
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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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}
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return *this;
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}
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bool cv::gpu::Stream::queryIfComplete()
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{
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cudaError_t err = cudaStreamQuery( impl->stream );
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if (err == cudaErrorNotReady || err == cudaSuccess)
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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::Stream::waitForCompletion() { cudaSafeCall( cudaStreamSynchronize( impl->stream ) ); }
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void cv::gpu::Stream::enqueueDownload(const GpuMat& src, Mat& dst)
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{
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// if not -> allocation will be done, but after that dst will not point to page locked memory
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CV_Assert(src.cols == dst.cols && src.rows == dst.rows && src.type() == dst.type() );
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devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost);
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}
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void cv::gpu::Stream::enqueueDownload(const GpuMat& src, CudaMem& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost); }
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void cv::gpu::Stream::enqueueUpload(const CudaMem& src, GpuMat& dst){ devcopy(src, dst, impl->stream, cudaMemcpyHostToDevice); }
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void cv::gpu::Stream::enqueueUpload(const Mat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyHostToDevice); }
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void cv::gpu::Stream::enqueueCopy(const GpuMat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToDevice); }
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void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val)
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{
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typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, cudaStream_t stream);
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static const set_caller_t set_callers[] =
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{
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kernelSet<uchar>, kernelSet<schar>, kernelSet<ushort>, kernelSet<short>,
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kernelSet<int>, kernelSet<float>, kernelSet<double>
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};
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set_callers[src.depth()](src, val, impl->stream);
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}
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void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val, const GpuMat& mask)
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{
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typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, const GpuMat& mask, cudaStream_t stream);
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static const set_caller_t set_callers[] =
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{
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kernelSetMask<uchar>, kernelSetMask<schar>, kernelSetMask<ushort>, kernelSetMask<short>,
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kernelSetMask<int>, kernelSetMask<float>, kernelSetMask<double>
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};
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set_callers[src.depth()](src, val, mask, impl->stream);
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}
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void cv::gpu::Stream::enqueueConvert(const GpuMat& src, GpuMat& dst, int rtype, double alpha, double beta)
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{
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bool noScale = fabs(alpha-1) < std::numeric_limits<double>::epsilon() && fabs(beta) < std::numeric_limits<double>::epsilon();
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if( rtype < 0 )
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rtype = src.type();
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else
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rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), src.channels());
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int sdepth = src.depth(), ddepth = CV_MAT_DEPTH(rtype);
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if( sdepth == ddepth && noScale )
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{
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src.copyTo(dst);
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return;
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}
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GpuMat temp;
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const GpuMat* psrc = &src;
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if( sdepth != ddepth && psrc == &dst )
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psrc = &(temp = src);
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dst.create( src.size(), rtype );
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matrix_operations::convert_gpu(psrc->reshape(1), sdepth, dst.reshape(1), ddepth, alpha, beta, impl->stream);
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}
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#endif /* !defined (HAVE_CUDA) */
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