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250 lines
9.4 KiB
C++
250 lines
9.4 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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Stream& cv::gpu::Stream::Null() { throw_nogpu(); static Stream s; return s; }
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cv::gpu::Stream::operator bool() const { throw_nogpu(); return false; }
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#else /* !defined (HAVE_CUDA) */
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#include "opencv2/gpu/stream_accessor.hpp"
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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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struct Stream::Impl
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{
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static cudaStream_t getStream(const Impl* impl) { return impl ? impl->stream : 0; }
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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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}
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CV_EXPORTS 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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};
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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::getStream(impl) );
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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::getStream(impl) ) ); }
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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::getStream(impl), cudaMemcpyDeviceToHost);
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}
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void cv::gpu::Stream::enqueueDownload(const GpuMat& src, CudaMem& dst) { devcopy(src, dst, Impl::getStream(impl), cudaMemcpyDeviceToHost); }
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void cv::gpu::Stream::enqueueUpload(const CudaMem& src, GpuMat& dst){ devcopy(src, dst, Impl::getStream(impl), cudaMemcpyHostToDevice); }
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void cv::gpu::Stream::enqueueUpload(const Mat& src, GpuMat& dst) { devcopy(src, dst, Impl::getStream(impl), cudaMemcpyHostToDevice); }
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void cv::gpu::Stream::enqueueCopy(const GpuMat& src, GpuMat& dst) { devcopy(src, dst, Impl::getStream(impl), cudaMemcpyDeviceToDevice); }
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void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar s)
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{
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CV_Assert((src.depth() != CV_64F) ||
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(TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
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if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0)
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{
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cudaSafeCall( cudaMemset2DAsync(src.data, src.step, 0, src.cols * src.elemSize(), src.rows, Impl::getStream(impl)) );
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return;
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}
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if (src.depth() == CV_8U)
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{
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int cn = src.channels();
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if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3]))
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{
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int val = saturate_cast<uchar>(s[0]);
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cudaSafeCall( cudaMemset2DAsync(src.data, src.step, val, src.cols * src.elemSize(), src.rows, Impl::getStream(impl)) );
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return;
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}
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}
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setTo(src, s, Impl::getStream(impl));
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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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CV_Assert((src.depth() != CV_64F) ||
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(TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
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CV_Assert(mask.type() == CV_8UC1);
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setTo(src, val, mask, Impl::getStream(impl));
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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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CV_Assert((src.depth() != CV_64F && CV_MAT_DEPTH(rtype) != CV_64F) ||
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(TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
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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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convertTo(src, dst, alpha, beta, Impl::getStream(impl));
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}
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cv::gpu::Stream::operator bool() const
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{
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return impl && impl->stream;
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}
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cv::gpu::Stream::Stream(Impl* impl_) : impl(impl_) {}
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cv::gpu::Stream& cv::gpu::Stream::Null()
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{
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static Stream s((Impl*)0);
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return s;
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}
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#endif /* !defined (HAVE_CUDA) */
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