2012-10-17 07:18:30 +08:00
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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 "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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2013-04-03 21:09:31 +08:00
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cv::gpu::Stream::Stream() { throw_no_cuda(); }
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2013-02-13 19:51:27 +08:00
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cv::gpu::Stream::~Stream() {}
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2013-04-03 21:09:31 +08:00
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cv::gpu::Stream::Stream(const Stream&) { throw_no_cuda(); }
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Stream& cv::gpu::Stream::operator=(const Stream&) { throw_no_cuda(); return *this; }
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bool cv::gpu::Stream::queryIfComplete() { throw_no_cuda(); return false; }
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void cv::gpu::Stream::waitForCompletion() { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueDownload(const GpuMat&, Mat&) { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueDownload(const GpuMat&, CudaMem&) { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueUpload(const CudaMem&, GpuMat&) { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueUpload(const Mat&, GpuMat&) { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueCopy(const GpuMat&, GpuMat&) { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueMemSet(GpuMat&, Scalar) { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueMemSet(GpuMat&, Scalar, const GpuMat&) { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueConvert(const GpuMat&, GpuMat&, int, double, double) { throw_no_cuda(); }
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void cv::gpu::Stream::enqueueHostCallback(StreamCallback, void*) { throw_no_cuda(); }
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Stream& cv::gpu::Stream::Null() { throw_no_cuda(); static Stream s; return s; }
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cv::gpu::Stream::operator bool() const { throw_no_cuda(); return false; }
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cv::gpu::Stream::Stream(Impl*) { throw_no_cuda(); }
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void cv::gpu::Stream::create() { throw_no_cuda(); }
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void cv::gpu::Stream::release() { throw_no_cuda(); }
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2012-10-17 07:18:30 +08:00
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#else /* !defined (HAVE_CUDA) */
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namespace cv { namespace gpu
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{
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void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream);
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void convertTo(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream);
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void setTo(GpuMat& src, Scalar s, cudaStream_t stream);
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void setTo(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream);
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}}
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2013-02-13 19:51:27 +08:00
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struct Stream::Impl
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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static cudaStream_t getStream(const Impl* impl)
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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return impl ? impl->stream : 0;
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}
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2012-10-17 07:18:30 +08:00
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cudaStream_t stream;
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2013-02-13 19:51:27 +08:00
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int ref_counter;
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};
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2012-10-17 07:18:30 +08:00
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2013-02-13 19:51:27 +08:00
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cudaStream_t cv::gpu::StreamAccessor::getStream(const Stream& stream)
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{
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return Stream::Impl::getStream(stream.impl);
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2012-10-17 07:18:30 +08:00
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}
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2013-02-13 19:51:27 +08:00
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cv::gpu::Stream::Stream() : impl(0)
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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create();
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2012-10-17 07:18:30 +08:00
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}
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2013-02-13 19:51:27 +08:00
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cv::gpu::Stream::~Stream()
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{
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release();
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}
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2012-10-17 07:18:30 +08:00
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cv::gpu::Stream::Stream(const Stream& stream) : impl(stream.impl)
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{
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2013-02-13 19:51:27 +08:00
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if (impl)
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2012-10-17 07:18:30 +08:00
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CV_XADD(&impl->ref_counter, 1);
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}
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2013-02-13 19:51:27 +08:00
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Stream& cv::gpu::Stream::operator =(const Stream& stream)
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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if (this != &stream)
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2012-10-17 07:18:30 +08:00
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{
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release();
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impl = stream.impl;
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2013-02-13 19:51:27 +08:00
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if (impl)
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CV_XADD(&impl->ref_counter, 1);
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2012-10-17 07:18:30 +08:00
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}
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2013-02-13 19:51:27 +08:00
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2012-10-17 07:18:30 +08:00
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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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2013-02-13 19:51:27 +08:00
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cudaStream_t stream = Impl::getStream(impl);
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cudaError_t err = cudaStreamQuery(stream);
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2012-10-17 07:18:30 +08:00
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if (err == cudaErrorNotReady || err == cudaSuccess)
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return err == cudaSuccess;
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall(err);
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2012-10-17 07:18:30 +08:00
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return false;
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}
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2013-02-13 19:51:27 +08:00
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void cv::gpu::Stream::waitForCompletion()
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{
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cudaStream_t stream = Impl::getStream(impl);
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall( cudaStreamSynchronize(stream) );
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2013-02-13 19:51:27 +08:00
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}
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2012-10-17 07:18:30 +08:00
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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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2013-02-13 19:51:27 +08:00
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CV_Assert( src.size() == dst.size() && src.type() == dst.type() );
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cudaStream_t stream = Impl::getStream(impl);
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size_t bwidth = src.cols * src.elemSize();
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, cudaMemcpyDeviceToHost, stream) );
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2013-02-13 19:51:27 +08:00
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}
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void cv::gpu::Stream::enqueueDownload(const GpuMat& src, CudaMem& dst)
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{
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dst.create(src.size(), src.type(), CudaMem::ALLOC_PAGE_LOCKED);
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cudaStream_t stream = Impl::getStream(impl);
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size_t bwidth = src.cols * src.elemSize();
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, cudaMemcpyDeviceToHost, stream) );
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2013-02-13 19:51:27 +08:00
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}
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void cv::gpu::Stream::enqueueUpload(const CudaMem& src, GpuMat& dst)
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{
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dst.create(src.size(), src.type());
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cudaStream_t stream = Impl::getStream(impl);
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size_t bwidth = src.cols * src.elemSize();
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, cudaMemcpyHostToDevice, stream) );
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2012-10-17 07:18:30 +08:00
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}
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2013-02-13 19:51:27 +08:00
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void cv::gpu::Stream::enqueueUpload(const Mat& src, GpuMat& dst)
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{
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dst.create(src.size(), src.type());
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cudaStream_t stream = Impl::getStream(impl);
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size_t bwidth = src.cols * src.elemSize();
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, cudaMemcpyHostToDevice, stream) );
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2013-02-13 19:51:27 +08:00
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}
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void cv::gpu::Stream::enqueueCopy(const GpuMat& src, GpuMat& dst)
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{
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dst.create(src.size(), src.type());
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cudaStream_t stream = Impl::getStream(impl);
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size_t bwidth = src.cols * src.elemSize();
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, cudaMemcpyDeviceToDevice, stream) );
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2013-02-13 19:51:27 +08:00
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}
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2012-10-17 07:18:30 +08:00
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2013-02-13 19:51:27 +08:00
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void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val)
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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const int sdepth = src.depth();
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2012-10-17 07:18:30 +08:00
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2013-02-13 19:51:27 +08:00
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if (sdepth == CV_64F)
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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if (!deviceSupports(NATIVE_DOUBLE))
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CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
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}
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cudaStream_t stream = Impl::getStream(impl);
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if (val[0] == 0.0 && val[1] == 0.0 && val[2] == 0.0 && val[3] == 0.0)
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{
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall( cudaMemset2DAsync(src.data, src.step, 0, src.cols * src.elemSize(), src.rows, stream) );
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2012-10-17 07:18:30 +08:00
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return;
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}
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2013-02-13 19:51:27 +08:00
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if (sdepth == CV_8U)
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2012-10-17 07:18:30 +08:00
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{
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int cn = src.channels();
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2013-02-13 19:51:27 +08:00
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if (cn == 1 || (cn == 2 && val[0] == val[1]) || (cn == 3 && val[0] == val[1] && val[0] == val[2]) || (cn == 4 && val[0] == val[1] && val[0] == val[2] && val[0] == val[3]))
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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int ival = saturate_cast<uchar>(val[0]);
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2013-04-03 21:09:31 +08:00
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cvCudaSafeCall( cudaMemset2DAsync(src.data, src.step, ival, src.cols * src.elemSize(), src.rows, stream) );
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2012-10-17 07:18:30 +08:00
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return;
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}
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}
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2013-02-13 19:51:27 +08:00
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setTo(src, val, stream);
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2012-10-17 07:18:30 +08:00
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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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2013-02-13 19:51:27 +08:00
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const int sdepth = src.depth();
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if (sdepth == CV_64F)
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{
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if (!deviceSupports(NATIVE_DOUBLE))
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CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
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}
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2012-10-17 07:18:30 +08:00
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CV_Assert(mask.type() == CV_8UC1);
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2013-02-13 19:51:27 +08:00
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cudaStream_t stream = Impl::getStream(impl);
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setTo(src, val, mask, stream);
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2012-10-17 07:18:30 +08:00
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}
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2013-02-13 19:51:27 +08:00
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void cv::gpu::Stream::enqueueConvert(const GpuMat& src, GpuMat& dst, int dtype, double alpha, double beta)
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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if (dtype < 0)
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dtype = src.type();
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else
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dtype = CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels());
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2012-10-17 07:18:30 +08:00
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2013-02-13 19:51:27 +08:00
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const int sdepth = src.depth();
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const int ddepth = CV_MAT_DEPTH(dtype);
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2012-10-17 07:18:30 +08:00
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2013-02-13 19:51:27 +08:00
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if (sdepth == CV_64F || ddepth == CV_64F)
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{
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if (!deviceSupports(NATIVE_DOUBLE))
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CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
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}
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2013-02-25 00:14:01 +08:00
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bool noScale = fabs(alpha - 1) < std::numeric_limits<double>::epsilon()
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&& fabs(beta) < std::numeric_limits<double>::epsilon();
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2012-10-17 07:18:30 +08:00
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2013-02-13 19:51:27 +08:00
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if (sdepth == ddepth && noScale)
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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enqueueCopy(src, dst);
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2012-10-17 07:18:30 +08:00
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return;
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}
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2013-02-13 19:51:27 +08:00
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dst.create(src.size(), dtype);
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2012-10-17 07:18:30 +08:00
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2013-02-13 19:51:27 +08:00
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cudaStream_t stream = Impl::getStream(impl);
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convertTo(src, dst, alpha, beta, stream);
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2012-10-17 07:18:30 +08:00
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}
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2013-03-27 17:07:58 +08:00
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#if CUDART_VERSION >= 5000
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2013-02-13 19:51:27 +08:00
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namespace
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2012-10-17 07:18:30 +08:00
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{
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2013-02-13 19:51:27 +08:00
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struct CallbackData
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{
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cv::gpu::Stream::StreamCallback callback;
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void* userData;
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Stream stream;
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};
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void CUDART_CB cudaStreamCallback(cudaStream_t, cudaError_t status, void* userData)
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{
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CallbackData* data = reinterpret_cast<CallbackData*>(userData);
|
|
|
|
data->callback(data->stream, static_cast<int>(status), data->userData);
|
|
|
|
delete data;
|
|
|
|
}
|
2012-10-17 07:18:30 +08:00
|
|
|
}
|
|
|
|
|
2013-02-13 19:51:27 +08:00
|
|
|
#endif
|
|
|
|
|
|
|
|
void cv::gpu::Stream::enqueueHostCallback(StreamCallback callback, void* userData)
|
|
|
|
{
|
2013-03-27 17:07:58 +08:00
|
|
|
#if CUDART_VERSION >= 5000
|
2013-02-13 19:51:27 +08:00
|
|
|
CallbackData* data = new CallbackData;
|
|
|
|
data->callback = callback;
|
|
|
|
data->userData = userData;
|
|
|
|
data->stream = *this;
|
|
|
|
|
|
|
|
cudaStream_t stream = Impl::getStream(impl);
|
|
|
|
|
2013-04-03 21:09:31 +08:00
|
|
|
cvCudaSafeCall( cudaStreamAddCallback(stream, cudaStreamCallback, data, 0) );
|
2013-02-13 19:51:27 +08:00
|
|
|
#else
|
|
|
|
(void) callback;
|
|
|
|
(void) userData;
|
|
|
|
CV_Error(CV_StsNotImplemented, "This function requires CUDA 5.0");
|
|
|
|
#endif
|
|
|
|
}
|
2012-10-17 07:18:30 +08:00
|
|
|
|
|
|
|
cv::gpu::Stream& cv::gpu::Stream::Null()
|
|
|
|
{
|
2013-02-13 19:51:27 +08:00
|
|
|
static Stream s((Impl*) 0);
|
2012-10-17 07:18:30 +08:00
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
2013-02-13 19:51:27 +08:00
|
|
|
cv::gpu::Stream::operator bool() const
|
|
|
|
{
|
|
|
|
return impl && impl->stream;
|
|
|
|
}
|
|
|
|
|
|
|
|
cv::gpu::Stream::Stream(Impl* impl_) : impl(impl_)
|
|
|
|
{
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::gpu::Stream::create()
|
|
|
|
{
|
|
|
|
if (impl)
|
|
|
|
release();
|
|
|
|
|
|
|
|
cudaStream_t stream;
|
2013-04-03 21:09:31 +08:00
|
|
|
cvCudaSafeCall( cudaStreamCreate( &stream ) );
|
2013-02-13 19:51:27 +08:00
|
|
|
|
|
|
|
impl = (Stream::Impl*) fastMalloc(sizeof(Stream::Impl));
|
|
|
|
|
|
|
|
impl->stream = stream;
|
|
|
|
impl->ref_counter = 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::gpu::Stream::release()
|
|
|
|
{
|
|
|
|
if (impl && CV_XADD(&impl->ref_counter, -1) == 1)
|
|
|
|
{
|
2013-04-03 21:09:31 +08:00
|
|
|
cvCudaSafeCall( cudaStreamDestroy(impl->stream) );
|
2013-02-13 19:51:27 +08:00
|
|
|
cv::fastFree(impl);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2012-10-17 07:18:30 +08:00
|
|
|
#endif /* !defined (HAVE_CUDA) */
|