mirror of
https://github.com/opencv/opencv.git
synced 2024-12-02 16:00:17 +08:00
251 lines
9.6 KiB
C++
251 lines
9.6 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
|
|
//
|
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
|
//
|
|
// By downloading, copying, installing or using the software you agree to this license.
|
|
// If you do not agree to this license, do not download, install,
|
|
// copy or use the software.
|
|
//
|
|
//
|
|
// License Agreement
|
|
// For Open Source Computer Vision Library
|
|
//
|
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
|
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
|
|
// Third party copyrights are property of their respective owners.
|
|
//
|
|
// Redistribution and use in source and binary forms, with or without modification,
|
|
// are permitted provided that the following conditions are met:
|
|
//
|
|
// * Redistribution's of source code must retain the above copyright notice,
|
|
// this list of conditions and the following disclaimer.
|
|
//
|
|
// * Redistribution's in binary form must reproduce the above copyright notice,
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
// and/or other materials provided with the distribution.
|
|
//
|
|
// * The name of the copyright holders may not be used to endorse or promote products
|
|
// derived from this software without specific prior written permission.
|
|
//
|
|
// This software is provided by the copyright holders and contributors "as is" and
|
|
// any express or implied warranties, including, but not limited to, the implied
|
|
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
|
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
|
// indirect, incidental, special, exemplary, or consequential damages
|
|
// (including, but not limited to, procurement of substitute goods or services;
|
|
// loss of use, data, or profits; or business interruption) however caused
|
|
// and on any theory of liability, whether in contract, strict liability,
|
|
// or tort (including negligence or otherwise) arising in any way out of
|
|
// the use of this software, even if advised of the possibility of such damage.
|
|
//
|
|
//M*/
|
|
|
|
#include "precomp.hpp"
|
|
|
|
using namespace cv;
|
|
using namespace cv::gpu;
|
|
|
|
|
|
#if !defined (HAVE_CUDA)
|
|
|
|
void cv::gpu::Stream::create() { throw_nogpu(); }
|
|
void cv::gpu::Stream::release() { throw_nogpu(); }
|
|
cv::gpu::Stream::Stream() : impl(0) { throw_nogpu(); }
|
|
cv::gpu::Stream::~Stream() { throw_nogpu(); }
|
|
cv::gpu::Stream::Stream(const Stream& /*stream*/) { throw_nogpu(); }
|
|
Stream& cv::gpu::Stream::operator=(const Stream& /*stream*/) { throw_nogpu(); return *this; }
|
|
bool cv::gpu::Stream::queryIfComplete() { throw_nogpu(); return true; }
|
|
void cv::gpu::Stream::waitForCompletion() { throw_nogpu(); }
|
|
void cv::gpu::Stream::enqueueDownload(const GpuMat& /*src*/, Mat& /*dst*/) { throw_nogpu(); }
|
|
void cv::gpu::Stream::enqueueDownload(const GpuMat& /*src*/, CudaMem& /*dst*/) { throw_nogpu(); }
|
|
void cv::gpu::Stream::enqueueUpload(const CudaMem& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
|
|
void cv::gpu::Stream::enqueueUpload(const Mat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
|
|
void cv::gpu::Stream::enqueueCopy(const GpuMat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
|
|
void cv::gpu::Stream::enqueueMemSet(GpuMat& /*src*/, Scalar /*val*/) { throw_nogpu(); }
|
|
void cv::gpu::Stream::enqueueMemSet(GpuMat& /*src*/, Scalar /*val*/, const GpuMat& /*mask*/) { throw_nogpu(); }
|
|
void cv::gpu::Stream::enqueueConvert(const GpuMat& /*src*/, GpuMat& /*dst*/, int /*type*/, double /*a*/, double /*b*/) { throw_nogpu(); }
|
|
|
|
#else /* !defined (HAVE_CUDA) */
|
|
|
|
#include "opencv2/gpu/stream_accessor.hpp"
|
|
|
|
namespace cv
|
|
{
|
|
namespace gpu
|
|
{
|
|
namespace matrix_operations
|
|
{
|
|
void copy_to_with_mask(const DevMem2D& src, DevMem2D dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
|
|
|
|
template <typename T>
|
|
void set_to_gpu(const DevMem2D& mat, const T* scalar, int channels, cudaStream_t stream);
|
|
template <typename T>
|
|
void set_to_gpu(const DevMem2D& mat, const T* scalar, const DevMem2D& mask, int channels, cudaStream_t stream);
|
|
|
|
void convert_gpu(const DevMem2D& src, int sdepth, const DevMem2D& dst, int ddepth, double alpha, double beta, cudaStream_t stream = 0);
|
|
}
|
|
}
|
|
}
|
|
|
|
struct Stream::Impl
|
|
{
|
|
cudaStream_t stream;
|
|
int ref_counter;
|
|
};
|
|
|
|
namespace
|
|
{
|
|
template<class S, class D> void devcopy(const S& src, D& dst, cudaStream_t s, cudaMemcpyKind k)
|
|
{
|
|
dst.create(src.size(), src.type());
|
|
size_t bwidth = src.cols * src.elemSize();
|
|
cudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, k, s) );
|
|
};
|
|
|
|
template <typename T>
|
|
void kernelSet(GpuMat& src, const Scalar& s, cudaStream_t stream)
|
|
{
|
|
Scalar_<T> sf = s;
|
|
matrix_operations::set_to_gpu(src, sf.val, src.channels(), stream);
|
|
}
|
|
|
|
template <typename T>
|
|
void kernelSetMask(GpuMat& src, const Scalar& s, const GpuMat& mask, cudaStream_t stream)
|
|
{
|
|
Scalar_<T> sf = s;
|
|
matrix_operations::set_to_gpu(src, sf.val, mask, src.channels(), stream);
|
|
}
|
|
}
|
|
|
|
CV_EXPORTS cudaStream_t cv::gpu::StreamAccessor::getStream(const Stream& stream) { return stream.impl->stream; };
|
|
|
|
void cv::gpu::Stream::create()
|
|
{
|
|
if (impl)
|
|
release();
|
|
|
|
cudaStream_t stream;
|
|
cudaSafeCall( cudaStreamCreate( &stream ) );
|
|
|
|
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 )
|
|
{
|
|
cudaSafeCall( cudaStreamDestroy( impl->stream ) );
|
|
cv::fastFree( impl );
|
|
}
|
|
}
|
|
|
|
cv::gpu::Stream::Stream() : impl(0) { create(); }
|
|
cv::gpu::Stream::~Stream() { release(); }
|
|
|
|
cv::gpu::Stream::Stream(const Stream& stream) : impl(stream.impl)
|
|
{
|
|
if( impl )
|
|
CV_XADD(&impl->ref_counter, 1);
|
|
}
|
|
Stream& cv::gpu::Stream::operator=(const Stream& stream)
|
|
{
|
|
if( this != &stream )
|
|
{
|
|
if( stream.impl )
|
|
CV_XADD(&stream.impl->ref_counter, 1);
|
|
|
|
release();
|
|
impl = stream.impl;
|
|
}
|
|
return *this;
|
|
}
|
|
|
|
bool cv::gpu::Stream::queryIfComplete()
|
|
{
|
|
cudaError_t err = cudaStreamQuery( impl->stream );
|
|
|
|
if (err == cudaErrorNotReady || err == cudaSuccess)
|
|
return err == cudaSuccess;
|
|
|
|
cudaSafeCall(err);
|
|
return false;
|
|
}
|
|
|
|
void cv::gpu::Stream::waitForCompletion() { cudaSafeCall( cudaStreamSynchronize( impl->stream ) ); }
|
|
|
|
void cv::gpu::Stream::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);
|
|
}
|
|
void cv::gpu::Stream::enqueueDownload(const GpuMat& src, CudaMem& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost); }
|
|
|
|
void cv::gpu::Stream::enqueueUpload(const CudaMem& src, GpuMat& dst){ devcopy(src, dst, impl->stream, cudaMemcpyHostToDevice); }
|
|
void cv::gpu::Stream::enqueueUpload(const Mat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyHostToDevice); }
|
|
void cv::gpu::Stream::enqueueCopy(const GpuMat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToDevice); }
|
|
|
|
void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val)
|
|
{
|
|
CV_Assert((src.depth() != CV_64F) ||
|
|
(TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
|
|
|
|
typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, cudaStream_t stream);
|
|
static const set_caller_t set_callers[] =
|
|
{
|
|
kernelSet<uchar>, kernelSet<schar>, kernelSet<ushort>, kernelSet<short>,
|
|
kernelSet<int>, kernelSet<float>, kernelSet<double>
|
|
};
|
|
set_callers[src.depth()](src, val, impl->stream);
|
|
}
|
|
|
|
void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val, const GpuMat& mask)
|
|
{
|
|
CV_Assert((src.depth() != CV_64F) ||
|
|
(TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
|
|
|
|
CV_Assert(mask.type() == CV_8UC1);
|
|
|
|
typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, const GpuMat& mask, cudaStream_t stream);
|
|
static const set_caller_t set_callers[] =
|
|
{
|
|
kernelSetMask<uchar>, kernelSetMask<schar>, kernelSetMask<ushort>, kernelSetMask<short>,
|
|
kernelSetMask<int>, kernelSetMask<float>, kernelSetMask<double>
|
|
};
|
|
set_callers[src.depth()](src, val, mask, impl->stream);
|
|
}
|
|
|
|
void cv::gpu::Stream::enqueueConvert(const GpuMat& src, GpuMat& dst, int rtype, double alpha, double beta)
|
|
{
|
|
CV_Assert((src.depth() != CV_64F && CV_MAT_DEPTH(rtype) != CV_64F) ||
|
|
(TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
|
|
|
|
bool noScale = fabs(alpha-1) < std::numeric_limits<double>::epsilon() && fabs(beta) < std::numeric_limits<double>::epsilon();
|
|
|
|
if( rtype < 0 )
|
|
rtype = src.type();
|
|
else
|
|
rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), src.channels());
|
|
|
|
int sdepth = src.depth(), ddepth = CV_MAT_DEPTH(rtype);
|
|
if( sdepth == ddepth && noScale )
|
|
{
|
|
src.copyTo(dst);
|
|
return;
|
|
}
|
|
|
|
GpuMat temp;
|
|
const GpuMat* psrc = &src;
|
|
if( sdepth != ddepth && psrc == &dst )
|
|
psrc = &(temp = src);
|
|
|
|
dst.create( src.size(), rtype );
|
|
matrix_operations::convert_gpu(psrc->reshape(1), sdepth, dst.reshape(1), ddepth, alpha, beta, impl->stream);
|
|
}
|
|
|
|
|
|
#endif /* !defined (HAVE_CUDA) */
|