OpenCV  4.1.2-dev
Open Source Computer Vision
Classes | Functions

Classes

class  cv::cuda::BufferPool
 BufferPool for use with CUDA streams. More...
 
class  cv::cuda::Event
 
struct  cv::cuda::EventAccessor
 Class that enables getting cudaEvent_t from cuda::Event. More...
 
class  cv::cuda::GpuMat
 Base storage class for GPU memory with reference counting. More...
 
class  cv::cuda::HostMem
 Class with reference counting wrapping special memory type allocation functions from CUDA. More...
 
class  cv::cuda::Stream
 This class encapsulates a queue of asynchronous calls. More...
 
struct  cv::cuda::StreamAccessor
 Class that enables getting cudaStream_t from cuda::Stream. More...
 

Functions

void cv::cuda::createContinuous (int rows, int cols, int type, OutputArray arr)
 Creates a continuous matrix. More...
 
void cv::cuda::ensureSizeIsEnough (int rows, int cols, int type, OutputArray arr)
 Ensures that the size of a matrix is big enough and the matrix has a proper type. More...
 
void cv::cuda::registerPageLocked (Mat &m)
 Page-locks the memory of matrix and maps it for the device(s). More...
 
void cv::cuda::setBufferPoolConfig (int deviceId, size_t stackSize, int stackCount)
 
void cv::cuda::setBufferPoolUsage (bool on)
 BufferPool management (must be called before Stream creation) More...
 
void cv::cuda::unregisterPageLocked (Mat &m)
 Unmaps the memory of matrix and makes it pageable again. More...
 

Detailed Description

Function Documentation

◆ createContinuous()

void cv::cuda::createContinuous ( int  rows,
int  cols,
int  type,
OutputArray  arr 
)
Python:
arr=cv.cuda.createContinuous(rows, cols, type[, arr])

#include <opencv2/core/cuda.hpp>

Creates a continuous matrix.

Parameters
rowsRow count.
colsColumn count.
typeType of the matrix.
arrDestination matrix. This parameter changes only if it has a proper type and area ( \(\texttt{rows} \times \texttt{cols}\) ).

Matrix is called continuous if its elements are stored continuously, that is, without gaps at the end of each row.

◆ ensureSizeIsEnough()

void cv::cuda::ensureSizeIsEnough ( int  rows,
int  cols,
int  type,
OutputArray  arr 
)
Python:
arr=cv.cuda.ensureSizeIsEnough(rows, cols, type[, arr])

#include <opencv2/core/cuda.hpp>

Ensures that the size of a matrix is big enough and the matrix has a proper type.

Parameters
rowsMinimum desired number of rows.
colsMinimum desired number of columns.
typeDesired matrix type.
arrDestination matrix.

The function does not reallocate memory if the matrix has proper attributes already.

◆ registerPageLocked()

void cv::cuda::registerPageLocked ( Mat m)
Python:
None=cv.cuda.registerPageLocked(m)

#include <opencv2/core/cuda.hpp>

Page-locks the memory of matrix and maps it for the device(s).

Parameters
mInput matrix.

◆ setBufferPoolConfig()

void cv::cuda::setBufferPoolConfig ( int  deviceId,
size_t  stackSize,
int  stackCount 
)
Python:
None=cv.cuda.setBufferPoolConfig(deviceId, stackSize, stackCount)

◆ setBufferPoolUsage()

void cv::cuda::setBufferPoolUsage ( bool  on)
Python:
None=cv.cuda.setBufferPoolUsage(on)

#include <opencv2/core/cuda.hpp>

BufferPool management (must be called before Stream creation)

◆ unregisterPageLocked()

void cv::cuda::unregisterPageLocked ( Mat m)
Python:
None=cv.cuda.unregisterPageLocked(m)

#include <opencv2/core/cuda.hpp>

Unmaps the memory of matrix and makes it pageable again.

Parameters
mInput matrix.