Chiebot-Mirror
/
opencv
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

implemented asynchronous call for gpumat::setTo(), gpumat::copyTo(), gpumat::converTo()

Browse Source
pull/13383/head
Andrey Morozov 15 years ago
parent 1ead3a5b02
commit 769564c130
4 changed files with 114 additions and 86 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 102
      modules/gpu/include/opencv2/gpu/gpu.hpp
  2. 8
      modules/gpu/src/cuda/cuda_shared.hpp
  3. 87
      modules/gpu/src/cuda/matrix_operations.cu
  4. 3
      modules/gpu/src/cudastream.cpp

102
modules/gpu/include/opencv2/gpu/gpu.hpp
Unescape View File

@ -49,24 +49,24 @@
namespace cv
{
namespace gpu
{
{
//////////////////////////////// Initialization ////////////////////////
//! This is the only function that do not throw exceptions if the library is compiled without Cuda.
CV_EXPORTS int getCudaEnabledDeviceCount();
//! Functions below throw cv::Expception if the library is compiled without Cuda.
CV_EXPORTS string getDeviceName(int device);
CV_EXPORTS void setDevice(int device);
CV_EXPORTS int getDevice();
CV_EXPORTS void setDevice(int device);
CV_EXPORTS int getDevice();
CV_EXPORTS void getComputeCapability(int device, int* major, int* minor);
CV_EXPORTS int getNumberOfSMs(int device);
//////////////////////////////// GpuMat ////////////////////////////////
class CudaStrem;
class CudaStream;
//! Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat.
//! Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat.
class CV_EXPORTS GpuMat
{
public:
@ -81,7 +81,7 @@ namespace cv
GpuMat(Size _size, int _type, const Scalar& _s);
//! copy constructor
GpuMat(const GpuMat& m);
//! constructor for GpuMatrix headers pointing to user-allocated data
GpuMat(int _rows, int _cols, int _type, void* _data, size_t _step = Mat::AUTO_STEP);
GpuMat(Size _size, int _type, void* _data, size_t _step = Mat::AUTO_STEP);
@ -89,7 +89,7 @@ namespace cv
//! creates a matrix header for a part of the bigger matrix
GpuMat(const GpuMat& m, const Range& rowRange, const Range& colRange);
GpuMat(const GpuMat& m, const Rect& roi);
//! builds GpuMat from Mat. Perfom blocking upload to device.
explicit GpuMat (const Mat& m);
@ -99,7 +99,7 @@ namespace cv
//! assignment operators
GpuMat& operator = (const GpuMat& m);
//! assignment operator. Perfom blocking upload to device.
GpuMat& operator = (const Mat& m);
GpuMat& operator = (const Mat& m);
//! returns lightweight DevMem2D_ structure for passing to nvcc-compiled code.
// Contains just image size, data ptr and step.
@ -110,7 +110,7 @@ namespace cv
//! Downloads data from device to host memory. Blocking calls.
operator Mat() const;
void download(cv::Mat& m) const;
void download(cv::Mat& m) const;
//! returns a new GpuMatrix header for the specified row
GpuMat row(int y) const;
@ -161,7 +161,7 @@ namespace cv
//! extracts a rectangular sub-GpuMatrix
// (this is a generalized form of row, rowRange etc.)
GpuMat operator()( Range rowRange, Range colRange ) const;
GpuMat operator()( const Rect& roi ) const;
GpuMat operator()( const Rect& roi ) const;
//! returns true iff the GpuMatrix data is continuous
// (i.e. when there are no gaps between successive rows).
@ -222,33 +222,33 @@ namespace cv
// Page locked memory is only needed for async and faster coping to GPU.
// It is convertable to cv::Mat header without reference counting
// so you can use it with other opencv functions.
class CV_EXPORTS MatPL
{
public:
public:
//Not supported. Now behaviour is like ALLOC_DEFAULT.
//enum { ALLOC_DEFAULT = 0, ALLOC_PORTABLE = 1, ALLOC_WRITE_COMBINED = 4 }
MatPL();
MatPL(const MatPL& m);
MatPL();
MatPL(const MatPL& m);
MatPL(int _rows, int _cols, int _type);
MatPL(Size _size, int _type);
MatPL(Size _size, int _type);
//! creates from cv::Mat with coping data
explicit MatPL(const Mat& m);
~MatPL();
~MatPL();
MatPL& operator = (const MatPL& m);
//! returns deep copy of the matrix, i.e. the data is copied
MatPL clone() const;
//! allocates new matrix data unless the matrix already has specified size and type.
//! allocates new matrix data unless the matrix already has specified size and type.
void create(int _rows, int _cols, int _type);
void create(Size _size, int _type);
void create(Size _size, int _type);
//! decrements reference counter and released memory if needed.
void release();
@ -256,25 +256,25 @@ namespace cv
//! returns matrix header with disabled reference counting for MatPL data.
Mat createMatHeader() const;
operator Mat() const;
// Please see cv::Mat for descriptions
bool isContinuous() const;
size_t elemSize() const;
size_t elemSize1() const;
int type() const;
int depth() const;
int channels() const;
size_t step1() const;
Size size() const;
bool isContinuous() const;
size_t elemSize() const;
size_t elemSize1() const;
int type() const;
int depth() const;
int channels() const;
size_t step1() const;
Size size() const;
bool empty() const;
// Please see cv::Mat for descriptions
int flags;
int rows, cols;
int flags;
int rows, cols;
size_t step;
uchar* data;
int* refcount;
uchar* data;
int* refcount;
uchar* datastart;
uchar* dataend;
@ -288,37 +288,37 @@ namespace cv
class CV_EXPORTS CudaStream
{
public:
CudaStream();
CudaStream();
~CudaStream();
CudaStream(const CudaStream&);
CudaStream(const CudaStream&);
CudaStream& operator=(const CudaStream&);
bool queryIfComplete();
void waitForCompletion();
void waitForCompletion();
//! downloads asynchronously.
//! downloads asynchronously.
// Warning! cv::Mat must point to page locked memory (i.e. to MatPL data or to its subMat)
void enqueueDownload(const GpuMat& src, MatPL& dst);
void enqueueDownload(const GpuMat& src, Mat& dst);
//! uploads asynchronously.
//! uploads asynchronously.
// Warning! cv::Mat must point to page locked memory (i.e. to MatPL data or to its ROI)
void enqueueUpload(const MatPL& src, GpuMat& dst);
void enqueueUpload(const MatPL& src, GpuMat& dst);
void enqueueUpload(const Mat& src, GpuMat& dst);
void enqueueCopy(const GpuMat& src, GpuMat& dst);
void enqueueMemSet(const GpuMat& src, Scalar val);
void enqueueMemSet(const GpuMat& src, Scalar val);
void enqueueMemSet(const GpuMat& src, Scalar val, const GpuMat& mask);
// converts matrix type, ex from float to uchar depending on type
void enqueueConvert(const GpuMat& src, GpuMat& dst, int type, double a = 1, double b = 0);
void enqueueConvert(const GpuMat& src, GpuMat& dst, int type, double a = 1, double b = 0);
private:
void create();
void release();
struct Impl;
Impl *impl;
Impl *impl;
friend struct StreamAccessor;
};
@ -348,7 +348,7 @@ namespace cv
//! Acync version
void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const CudaStream& stream);
//! Some heuristics that tries to estmate
//! Some heuristics that tries to estmate
// if current GPU will be faster then CPU in this algorithm.
// It queries current active device.
static bool checkIfGpuCallReasonable();
@ -356,11 +356,11 @@ namespace cv
int ndisp;
int winSize;
int preset;
// If avergeTexThreshold == 0 => post procesing is disabled
// If avergeTexThreshold != 0 then disparity is set 0 in each point (x,y) where for left image
// SumOfHorizontalGradiensInWindow(x, y, winSize) < (winSize * winSize) * avergeTexThreshold
// i.e. input left image is low textured.
// i.e. input left image is low textured.
float avergeTexThreshold;
private:
GpuMat minSSD, leBuf, riBuf;
@ -369,4 +369,4 @@ namespace cv
}
#include "opencv2/gpu/matrix_operations.hpp"
#endif /* __OPENCV_GPU_HPP__ */
#endif /* __OPENCV_GPU_HPP__ */

8
modules/gpu/src/cuda/cuda_shared.hpp
Unescape View File

@ -61,12 +61,12 @@ namespace cv
{
static inline int divUp(int a, int b) { return (a % b == 0) ? a/b : a/b + 1; }
extern "C" void copy_to_with_mask(const DevMem2D& mat_src, const DevMem2D& mat_dst, int depth, const DevMem2D& mask, int channels);
extern "C" void copy_to_with_mask(const DevMem2D& mat_src, const DevMem2D& mat_dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
extern "C" void set_to_without_mask (const DevMem2D& mat, int depth, const double * scalar, int channels);
extern "C" void set_to_with_mask (const DevMem2D& mat, int depth, const double * scalar, const DevMem2D& mask, int channels);
extern "C" void set_to_without_mask (const DevMem2D& mat, int depth, const double * scalar, int channels, const cudaStream_t & stream = 0);
extern "C" void set_to_with_mask (const DevMem2D& mat, int depth, const double * scalar, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
extern "C" void convert_to(const DevMem2D& src, int sdepth, DevMem2D dst, int ddepth, size_t width, size_t height, double alpha, double beta);
extern "C" void convert_to(const DevMem2D& src, int sdepth, DevMem2D dst, int ddepth, size_t width, size_t height, double alpha, double beta, const cudaStream_t & stream = 0);
}
}
}

87
modules/gpu/src/cuda/matrix_operations.cu
Unescape View File

@ -42,7 +42,6 @@
#include <stddef.h>
#include <stdio.h>
//#include <iostream>
#include "cuda_shared.hpp"
#include "cuda_runtime.h"
@ -239,19 +238,27 @@ namespace cv
////////////////////////////////// CopyTo /////////////////////////////////
///////////////////////////////////////////////////////////////////////////
typedef void (*CopyToFunc)(const DevMem2D& mat_src, const DevMem2D& mat_dst, const DevMem2D& mask, int channels);
typedef void (*CopyToFunc)(const DevMem2D& mat_src, const DevMem2D& mat_dst, const DevMem2D& mask, int channels, const cudaStream_t & stream);
template<typename T>
void copy_to_with_mask_run(const DevMem2D& mat_src, const DevMem2D& mat_dst, const DevMem2D& mask, int channels)
void copy_to_with_mask_run(const DevMem2D& mat_src, const DevMem2D& mat_dst, const DevMem2D& mask, int channels, const cudaStream_t & stream)
{
dim3 threadsPerBlock(16,16, 1);
dim3 numBlocks ( divUp(mat_src.cols * channels , threadsPerBlock.x) , divUp(mat_src.rows , threadsPerBlock.y), 1);
::mat_operators::kernel_copy_to_with_mask<T><<<numBlocks,threadsPerBlock>>>
((T*)mat_src.ptr, (T*)mat_dst.ptr, (unsigned char*)mask.ptr, mat_src.cols, mat_src.rows, mat_src.step, mask.step, channels);
cudaSafeCall ( cudaThreadSynchronize() );
if (stream == 0)
{
::mat_operators::kernel_copy_to_with_mask<T><<<numBlocks,threadsPerBlock>>>
((T*)mat_src.ptr, (T*)mat_dst.ptr, (unsigned char*)mask.ptr, mat_src.cols, mat_src.rows, mat_src.step, mask.step, channels);
cudaSafeCall ( cudaThreadSynchronize() );
}
else
{
::mat_operators::kernel_copy_to_with_mask<T><<<numBlocks,threadsPerBlock, 0, stream>>>
((T*)mat_src.ptr, (T*)mat_dst.ptr, (unsigned char*)mask.ptr, mat_src.cols, mat_src.rows, mat_src.step, mask.step, channels);
}
}
extern "C" void copy_to_with_mask(const DevMem2D& mat_src, const DevMem2D& mat_dst, int depth, const DevMem2D& mask, int channels)
extern "C" void copy_to_with_mask(const DevMem2D& mat_src, const DevMem2D& mat_dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream)
{
static CopyToFunc tab[8] =
{
@ -269,7 +276,7 @@ namespace cv
if (func == 0) cv::gpu::error("Unsupported convert operation", __FILE__, __LINE__);
func(mat_src, mat_dst, mask, channels);
func(mat_src, mat_dst, mask, channels, stream);
}
@ -277,28 +284,43 @@ namespace cv
////////////////////////////////// SetTo //////////////////////////////////
///////////////////////////////////////////////////////////////////////////
typedef void (*SetToFunc_with_mask)(const DevMem2D& mat, const DevMem2D& mask, int channels);
typedef void (*SetToFunc_without_mask)(const DevMem2D& mat, int channels);
typedef void (*SetToFunc_with_mask)(const DevMem2D& mat, const DevMem2D& mask, int channels, const cudaStream_t & stream);
typedef void (*SetToFunc_without_mask)(const DevMem2D& mat, int channels, const cudaStream_t & stream);
template <typename T>
void set_to_with_mask_run(const DevMem2D& mat, const DevMem2D& mask, int channels)
void set_to_with_mask_run(const DevMem2D& mat, const DevMem2D& mask, int channels, const cudaStream_t & stream)
{
dim3 threadsPerBlock(32, 8, 1);
dim3 numBlocks (mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
::mat_operators::kernel_set_to_with_mask<T><<<numBlocks,threadsPerBlock>>>((T*)mat.ptr, (unsigned char *)mask.ptr, mat.cols, mat.rows, mat.step, channels, mask.step);
cudaSafeCall ( cudaThreadSynchronize() );
if (stream == 0)
{
::mat_operators::kernel_set_to_with_mask<T><<<numBlocks,threadsPerBlock>>>((T*)mat.ptr, (unsigned char *)mask.ptr, mat.cols, mat.rows, mat.step, channels, mask.step);
cudaSafeCall ( cudaThreadSynchronize() );
}
else
{
::mat_operators::kernel_set_to_with_mask<T><<<numBlocks,threadsPerBlock, 0, stream>>>((T*)mat.ptr, (unsigned char *)mask.ptr, mat.cols, mat.rows, mat.step, channels, mask.step);
}
}
template <typename T>
void set_to_without_mask_run(const DevMem2D& mat, int channels)
void set_to_without_mask_run(const DevMem2D& mat, int channels, const cudaStream_t & stream)
{
dim3 threadsPerBlock(32, 8, 1);
dim3 numBlocks (mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
::mat_operators::kernel_set_to_without_mask<T><<<numBlocks,threadsPerBlock>>>((T*)mat.ptr, mat.cols, mat.rows, mat.step, channels);
cudaSafeCall ( cudaThreadSynchronize() );
if (stream == 0)
{
::mat_operators::kernel_set_to_without_mask<T><<<numBlocks,threadsPerBlock>>>((T*)mat.ptr, mat.cols, mat.rows, mat.step, channels);
cudaSafeCall ( cudaThreadSynchronize() );
}
else
{
::mat_operators::kernel_set_to_without_mask<T><<<numBlocks,threadsPerBlock, 0, stream>>>((T*)mat.ptr, mat.cols, mat.rows, mat.step, channels);
}
}
extern "C" void set_to_without_mask(const DevMem2D& mat, int depth, const double * scalar, int channels)
extern "C" void set_to_without_mask(const DevMem2D& mat, int depth, const double * scalar, int channels, const cudaStream_t & stream)
{
double data[4];
data[0] = scalar[0];
@ -323,11 +345,11 @@ namespace cv
if (func == 0) cv::gpu::error("Unsupported convert operation", __FILE__, __LINE__);
func(mat, channels);
func(mat, channels, stream);
}
extern "C" void set_to_with_mask(const DevMem2D& mat, int depth, const double * scalar, const DevMem2D& mask, int channels)
extern "C" void set_to_with_mask(const DevMem2D& mat, int depth, const double * scalar, const DevMem2D& mask, int channels, const cudaStream_t & stream)
{
double data[4];
data[0] = scalar[0];
@ -352,7 +374,7 @@ namespace cv
if (func == 0) cv::gpu::error("Unsupported convert operation", __FILE__, __LINE__);
func(mat, mask, channels);
func(mat, mask, channels, stream);
}
@ -360,22 +382,27 @@ namespace cv
//////////////////////////////// ConvertTo ////////////////////////////////
///////////////////////////////////////////////////////////////////////////
typedef void (*CvtFunc)(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta);
typedef void (*CvtFunc)(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta, const cudaStream_t & stream);
template<typename T, typename DT>
void cvt_(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta)
void cvt_(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta, const cudaStream_t & stream)
{
const int shift = ::mat_operators::ReadWriteTraits<T, DT, sizeof(T), sizeof(DT)>::shift;
dim3 block(32, 8);
dim3 grid(divUp(width, block.x * shift), divUp(height, block.y));
::mat_operators::kernel_convert_to<T, DT><<<grid, block>>>(src.ptr, src.step, dst.ptr, dst.step, width, height, alpha, beta);
cudaSafeCall( cudaThreadSynchronize() );
}
extern "C" void convert_to(const DevMem2D& src, int sdepth, DevMem2D dst, int ddepth, size_t width, size_t height, double alpha, double beta)
if (stream == 0)
{
::mat_operators::kernel_convert_to<T, DT><<<grid, block>>>(src.ptr, src.step, dst.ptr, dst.step, width, height, alpha, beta);
cudaSafeCall( cudaThreadSynchronize() );
}
else
{
::mat_operators::kernel_convert_to<T, DT><<<grid, block, 0, stream>>>(src.ptr, src.step, dst.ptr, dst.step, width, height, alpha, beta);
}
}
extern "C" void convert_to(const DevMem2D& src, int sdepth, DevMem2D dst, int ddepth, size_t width, size_t height, double alpha, double beta, const cudaStream_t & stream)
{
static CvtFunc tab[8][8] =
{
@ -406,7 +433,7 @@ namespace cv
CvtFunc func = tab[sdepth][ddepth];
if (func == 0)
cv::gpu::error("Unsupported convert operation", __FILE__, __LINE__);
func(src, dst, width, height, alpha, beta);
func(src, dst, width, height, alpha, beta, stream);
}
} // namespace impl
} // namespace gpu

3
modules/gpu/src/cudastream.cpp
Unescape View File

@ -74,6 +74,7 @@ struct CudaStream::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)
@ -147,7 +148,7 @@ void cv::gpu::CudaStream::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);
devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost);
}
void cv::gpu::CudaStream::enqueueDownload(const GpuMat& src, MatPL& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost); }

Write Preview
Loading…
Cancel
Save