Class with reference counting wrapping special memory type allocation functions from CUDA. More...

#include <opencv2/core/cuda.hpp>

Public Types
enum	AllocType { PAGE_LOCKED = 1, SHARED = 2, WRITE_COMBINED = 4 }

Public Member Functions
	HostMem (HostMem::AllocType alloc_type=HostMem::AllocType::PAGE_LOCKED)

	HostMem (const HostMem &m)

	HostMem (int rows, int cols, int type, HostMem::AllocType alloc_type=HostMem::AllocType::PAGE_LOCKED)

	HostMem (Size size, int type, HostMem::AllocType alloc_type=HostMem::AllocType::PAGE_LOCKED)

	HostMem (InputArray arr, HostMem::AllocType alloc_type=HostMem::AllocType::PAGE_LOCKED)
	creates from host memory with coping data More...

	~HostMem ()

int	channels () const

HostMem	clone () const
	returns deep copy of the matrix, i.e. the data is copied More...

void	create (int rows, int cols, int type)
	allocates new matrix data unless the matrix already has specified size and type. More...

void	create (Size size, int type)

GpuMat	createGpuMatHeader () const
	Maps CPU memory to GPU address space and creates the cuda::GpuMat header without reference counting for it. More...

Mat	createMatHeader () const
	returns matrix header with disabled reference counting for HostMem data. More...

int	depth () const

size_t	elemSize () const

size_t	elemSize1 () const

bool	empty () const

bool	isContinuous () const

HostMem &	operator= (const HostMem &m)

void	release ()
	decrements reference counter and released memory if needed. More...

HostMem	reshape (int cn, int rows=0) const

Size	size () const

size_t	step1 () const

void	swap (HostMem &b)
	swaps with other smart pointer More...

int	type () const

Static Public Member Functions
static MatAllocator *	getAllocator (HostMem::AllocType alloc_type=HostMem::AllocType::PAGE_LOCKED)

Public Attributes
AllocType	alloc_type

int	cols

uchar *	data

const uchar *	dataend

uchar *	datastart

int	flags

int *	refcount

int	rows

size_t	step

Detailed Description

Class with reference counting wrapping special memory type allocation functions from CUDA.

Its interface is also Mat-like but with additional memory type parameters.

PAGE_LOCKED sets a page locked memory type used commonly for fast and asynchronous uploading/downloading data from/to GPU.
SHARED specifies a zero copy memory allocation that enables mapping the host memory to GPU address space, if supported.
WRITE_COMBINED sets the write combined buffer that is not cached by CPU. Such buffers are used to supply GPU with data when GPU only reads it. The advantage is a better CPU cache utilization.

Note: Allocation size of such memory types is usually limited. For more details, see CUDA 2.2 Pinned Memory APIs document or CUDA C Programming Guide.

Member Enumeration Documentation

◆ AllocType

enum cv::cuda::HostMem::AllocType

Enumerator
PAGE_LOCKED
SHARED
WRITE_COMBINED

Constructor & Destructor Documentation

◆ HostMem() [1/5]

cv::cuda::HostMem::HostMem ( HostMem::AllocType alloc_type = HostMem::AllocType::PAGE_LOCKED )

explicit


cv.cuda_HostMem(	[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	rows, cols, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	size, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	arr[, alloc_type]	) ->	<cuda_HostMem object>

◆ HostMem() [2/5]

cv::cuda::HostMem::HostMem ( const HostMem & m )


cv.cuda_HostMem(	[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	rows, cols, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	size, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	arr[, alloc_type]	) ->	<cuda_HostMem object>

◆ HostMem() [3/5]

cv::cuda::HostMem::HostMem	(	int	rows,
		int	cols,
		int	type,
		HostMem::AllocType	alloc_type = `HostMem::AllocType::PAGE_LOCKED`
	)


cv.cuda_HostMem(	[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	rows, cols, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	size, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	arr[, alloc_type]	) ->	<cuda_HostMem object>

◆ HostMem() [4/5]

cv::cuda::HostMem::HostMem	(	Size	size,
		int	type,
		HostMem::AllocType	alloc_type = `HostMem::AllocType::PAGE_LOCKED`
	)


cv.cuda_HostMem(	[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	rows, cols, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	size, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	arr[, alloc_type]	) ->	<cuda_HostMem object>

◆ HostMem() [5/5]

cv::cuda::HostMem::HostMem	(	InputArray	arr,
		HostMem::AllocType	alloc_type = `HostMem::AllocType::PAGE_LOCKED`
	)

explicit


cv.cuda_HostMem(	[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	rows, cols, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	size, type[, alloc_type]	) ->	<cuda_HostMem object>
cv.cuda_HostMem(	arr[, alloc_type]	) ->	<cuda_HostMem object>

creates from host memory with coping data

◆ ~HostMem()

cv::cuda::HostMem::~HostMem ( )

Member Function Documentation

◆ channels()

int cv::cuda::HostMem::channels ( ) const

Python:
	cv.cuda_HostMem.channels(		) ->	retval

◆ clone()

HostMem cv::cuda::HostMem::clone ( ) const

Python:
	cv.cuda_HostMem.clone(		) ->	retval

returns deep copy of the matrix, i.e. the data is copied

◆ create() [1/2]

void cv::cuda::HostMem::create	(	int	rows,
		int	cols,
		int	type
	)

Python:
	cv.cuda_HostMem.create(	rows, cols, type	) ->	None

allocates new matrix data unless the matrix already has specified size and type.

◆ create() [2/2]

void cv::cuda::HostMem::create	(	Size	size,
		int	type
	)

Python:
	cv.cuda_HostMem.create(	rows, cols, type	) ->	None

◆ createGpuMatHeader()

GpuMat cv::cuda::HostMem::createGpuMatHeader ( ) const

Maps CPU memory to GPU address space and creates the cuda::GpuMat header without reference counting for it.

This can be done only if memory was allocated with the SHARED flag and if it is supported by the hardware. Laptops often share video and CPU memory, so address spaces can be mapped, which eliminates an extra copy.

◆ createMatHeader()

Mat cv::cuda::HostMem::createMatHeader ( ) const

Python:
	cv.cuda_HostMem.createMatHeader(		) ->	retval

returns matrix header with disabled reference counting for HostMem data.

◆ depth()

int cv::cuda::HostMem::depth ( ) const

Python:
	cv.cuda_HostMem.depth(		) ->	retval

◆ elemSize()

size_t cv::cuda::HostMem::elemSize ( ) const

Python:
	cv.cuda_HostMem.elemSize(		) ->	retval

◆ elemSize1()

size_t cv::cuda::HostMem::elemSize1 ( ) const

Python:
	cv.cuda_HostMem.elemSize1(		) ->	retval

◆ empty()

bool cv::cuda::HostMem::empty ( ) const

Python:
	cv.cuda_HostMem.empty(		) ->	retval

◆ getAllocator()

static MatAllocator* cv::cuda::HostMem::getAllocator ( HostMem::AllocType alloc_type = HostMem::AllocType::PAGE_LOCKED )

static

◆ isContinuous()

bool cv::cuda::HostMem::isContinuous ( ) const

Python:
	cv.cuda_HostMem.isContinuous(		) ->	retval

◆ operator=()

HostMem& cv::cuda::HostMem::operator= ( const HostMem & m )

◆ release()

void cv::cuda::HostMem::release ( )

decrements reference counter and released memory if needed.

◆ reshape()

HostMem cv::cuda::HostMem::reshape	(	int	cn,
		int	rows = `0`
	)		const

Python:
	cv.cuda_HostMem.reshape(	cn[, rows]	) ->	retval

creates alternative HostMem header for the same data, with different number of channels and/or different number of rows

◆ size()

Size cv::cuda::HostMem::size ( ) const

Python:
	cv.cuda_HostMem.size(		) ->	retval

◆ step1()

size_t cv::cuda::HostMem::step1 ( ) const

Python:
	cv.cuda_HostMem.step1(		) ->	retval

◆ swap()

void cv::cuda::HostMem::swap ( HostMem & b )

Python:
	cv.cuda_HostMem.swap(	b	) ->	None

swaps with other smart pointer

◆ type()

int cv::cuda::HostMem::type ( ) const

Python:
	cv.cuda_HostMem.type(		) ->	retval

Member Data Documentation

◆ alloc_type

AllocType cv::cuda::HostMem::alloc_type

◆ cols

int cv::cuda::HostMem::cols

◆ data

uchar* cv::cuda::HostMem::data

◆ dataend

const uchar* cv::cuda::HostMem::dataend

◆ datastart

uchar* cv::cuda::HostMem::datastart

◆ flags

int cv::cuda::HostMem::flags

◆ refcount

int* cv::cuda::HostMem::refcount

◆ rows

int cv::cuda::HostMem::rows

◆ step

size_t cv::cuda::HostMem::step

The documentation for this class was generated from the following file:

opencv2/core/cuda.hpp

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes