Open Source Computer Vision Library
https://opencv.org/
253 lines
9.4 KiB
253 lines
9.4 KiB
/*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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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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#include "opencv2/gpu/stream_accessor.hpp" |
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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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#endif /* !defined (HAVE_CUDA) */ |
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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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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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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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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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