Commit 769564c1 authored by Andrey Morozov's avatar Andrey Morozov

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

parent 1ead3a5b
......@@ -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__ */
\ No newline at end of file
#endif /* __OPENCV_GPU_HPP__ */
......@@ -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);
}
}
}
......
This diff is collapsed.
......@@ -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); }
......
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