OpenCV  4.0.0-pre
Open Source Computer Vision
Classes | Public Member Functions | Static Public Member Functions | Public Attributes | List of all members
cv::cuda::GpuMat Class Reference

Base storage class for GPU memory with reference counting. More...

#include "cuda.hpp"

Inheritance diagram for cv::cuda::GpuMat:
cv::cudev::GpuMat_< T >

Classes

class  Allocator
 

Public Member Functions

 GpuMat (GpuMat::Allocator *allocator=GpuMat::defaultAllocator())
 default constructor More...
 
 GpuMat (int rows, int cols, int type, GpuMat::Allocator *allocator=GpuMat::defaultAllocator())
 constructs GpuMat of the specified size and type More...
 
 GpuMat (Size size, int type, GpuMat::Allocator *allocator=GpuMat::defaultAllocator())
 
 GpuMat (int rows, int cols, int type, Scalar s, GpuMat::Allocator *allocator=GpuMat::defaultAllocator())
 constucts GpuMat and fills it with the specified value _s More...
 
 GpuMat (Size size, int type, Scalar s, GpuMat::Allocator *allocator=GpuMat::defaultAllocator())
 
 GpuMat (const GpuMat &m)
 copy constructor More...
 
 GpuMat (int rows, int cols, int type, void *data, size_t step=Mat::AUTO_STEP)
 constructor for GpuMat headers pointing to user-allocated data More...
 
 GpuMat (Size size, int type, void *data, size_t step=Mat::AUTO_STEP)
 
 GpuMat (const GpuMat &m, Range rowRange, Range colRange)
 creates a GpuMat header for a part of the bigger matrix More...
 
 GpuMat (const GpuMat &m, Rect roi)
 
 GpuMat (InputArray arr, GpuMat::Allocator *allocator=GpuMat::defaultAllocator())
 builds GpuMat from host memory (Blocking call) More...
 
 ~GpuMat ()
 destructor - calls release() More...
 
GpuMatadjustROI (int dtop, int dbottom, int dleft, int dright)
 moves/resizes the current GpuMat ROI inside the parent GpuMat More...
 
void assignTo (GpuMat &m, int type=-1) const
 
int channels () const
 returns number of channels More...
 
GpuMat clone () const
 returns deep copy of the GpuMat, i.e. the data is copied More...
 
GpuMat col (int x) const
 returns a new GpuMat header for the specified column More...
 
GpuMat colRange (int startcol, int endcol) const
 ... for the specified column span More...
 
GpuMat colRange (Range r) const
 
void convertTo (OutputArray dst, int rtype) const
 converts GpuMat to another datatype (Blocking call) More...
 
void convertTo (OutputArray dst, int rtype, Stream &stream) const
 converts GpuMat to another datatype (Non-Blocking call) More...
 
void convertTo (OutputArray dst, int rtype, double alpha, double beta=0.0) const
 converts GpuMat to another datatype with scaling (Blocking call) More...
 
void convertTo (OutputArray dst, int rtype, double alpha, Stream &stream) const
 converts GpuMat to another datatype with scaling (Non-Blocking call) More...
 
void convertTo (OutputArray dst, int rtype, double alpha, double beta, Stream &stream) const
 converts GpuMat to another datatype with scaling (Non-Blocking call) More...
 
void copyTo (OutputArray dst) const
 copies the GpuMat content to device memory (Blocking call) More...
 
void copyTo (OutputArray dst, Stream &stream) const
 copies the GpuMat content to device memory (Non-Blocking call) More...
 
void copyTo (OutputArray dst, InputArray mask) const
 copies those GpuMat elements to "m" that are marked with non-zero mask elements (Blocking call) More...
 
void copyTo (OutputArray dst, InputArray mask, Stream &stream) const
 copies those GpuMat elements to "m" that are marked with non-zero mask elements (Non-Blocking call) More...
 
void create (int rows, int cols, int type)
 allocates new GpuMat data unless the GpuMat already has specified size and type More...
 
void create (Size size, int type)
 
int depth () const
 returns element type More...
 
void download (OutputArray dst) const
 Performs data download from GpuMat (Blocking call) More...
 
void download (OutputArray dst, Stream &stream) const
 Performs data download from GpuMat (Non-Blocking call) More...
 
size_t elemSize () const
 returns element size in bytes More...
 
size_t elemSize1 () const
 returns the size of element channel in bytes More...
 
bool empty () const
 returns true if GpuMat data is NULL More...
 
bool isContinuous () const
 
void locateROI (Size &wholeSize, Point &ofs) const
 locates GpuMat header within a parent GpuMat More...
 
template<typename _Tp >
 operator PtrStep< _Tp > () const
 
template<typename _Tp >
 operator PtrStepSz< _Tp > () const
 
GpuMat operator() (Range rowRange, Range colRange) const
 extracts a rectangular sub-GpuMat (this is a generalized form of row, rowRange etc.) More...
 
GpuMat operator() (Rect roi) const
 
GpuMatoperator= (const GpuMat &m)
 assignment operators More...
 
ucharptr (int y=0)
 returns pointer to y-th row More...
 
const ucharptr (int y=0) const
 
template<typename _Tp >
_Tp * ptr (int y=0)
 template version of the above method More...
 
template<typename _Tp >
const _Tp * ptr (int y=0) const
 
void release ()
 decreases reference counter, deallocate the data when reference counter reaches 0 More...
 
GpuMat reshape (int cn, int rows=0) const
 
GpuMat row (int y) const
 returns a new GpuMat header for the specified row More...
 
GpuMat rowRange (int startrow, int endrow) const
 ... for the specified row span More...
 
GpuMat rowRange (Range r) const
 
GpuMatsetTo (Scalar s)
 sets some of the GpuMat elements to s (Blocking call) More...
 
GpuMatsetTo (Scalar s, Stream &stream)
 sets some of the GpuMat elements to s (Non-Blocking call) More...
 
GpuMatsetTo (Scalar s, InputArray mask)
 sets some of the GpuMat elements to s, according to the mask (Blocking call) More...
 
GpuMatsetTo (Scalar s, InputArray mask, Stream &stream)
 sets some of the GpuMat elements to s, according to the mask (Non-Blocking call) More...
 
Size size () const
 returns GpuMat size : width == number of columns, height == number of rows More...
 
size_t step1 () const
 returns step/elemSize1() More...
 
void swap (GpuMat &mat)
 swaps with other smart pointer More...
 
int type () const
 returns element type More...
 
void updateContinuityFlag ()
 internal use method: updates the continuity flag More...
 
void upload (InputArray arr)
 Performs data upload to GpuMat (Blocking call) More...
 
void upload (InputArray arr, Stream &stream)
 Performs data upload to GpuMat (Non-Blocking call) More...
 

Static Public Member Functions

static GpuMat::AllocatordefaultAllocator ()
 default allocator More...
 
static void setDefaultAllocator (GpuMat::Allocator *allocator)
 

Public Attributes

Allocatorallocator
 allocator More...
 
int cols
 
uchardata
 pointer to the data More...
 
const uchardataend
 
uchardatastart
 helper fields used in locateROI and adjustROI More...
 
int flags
 
int * refcount
 
int rows
 the number of rows and columns More...
 
size_t step
 a distance between successive rows in bytes; includes the gap if any More...
 

Detailed Description

Base storage class for GPU memory with reference counting.

Its interface matches the Mat interface with the following limitations:

Beware that the latter limitation may lead to overloaded matrix operators that cause memory allocations. The GpuMat class is convertible to cuda::PtrStepSz and cuda::PtrStep so it can be passed directly to the kernel.

Note
In contrast with Mat, in most cases GpuMat::isContinuous() == false . This means that rows are aligned to a size depending on the hardware. Single-row GpuMat is always a continuous matrix.
You are not recommended to leave static or global GpuMat variables allocated, that is, to rely on its destructor. The destruction order of such variables and CUDA context is undefined. GPU memory release function returns error if the CUDA context has been destroyed before.

Some member functions are described as a "Blocking Call" while some are described as a "Non-Blocking Call". Blocking functions are synchronous to host. It is guaranteed that the GPU operation is finished when the function returns. However, non-blocking functions are asynchronous to host. Those functions may return even if the GPU operation is not finished.

Compared to their blocking counterpart, non-blocking functions accept Stream as an additional argument. If a non-default stream is passed, the GPU operation may overlap with operations in other streams.

See also
Mat

Constructor & Destructor Documentation

§ GpuMat() [1/11]

cv::cuda::GpuMat::GpuMat ( GpuMat::Allocator allocator = GpuMat::defaultAllocator())
explicit
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

default constructor

§ GpuMat() [2/11]

cv::cuda::GpuMat::GpuMat ( int  rows,
int  cols,
int  type,
GpuMat::Allocator allocator = GpuMat::defaultAllocator() 
)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

constructs GpuMat of the specified size and type

§ GpuMat() [3/11]

cv::cuda::GpuMat::GpuMat ( Size  size,
int  type,
GpuMat::Allocator allocator = GpuMat::defaultAllocator() 
)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

§ GpuMat() [4/11]

cv::cuda::GpuMat::GpuMat ( int  rows,
int  cols,
int  type,
Scalar  s,
GpuMat::Allocator allocator = GpuMat::defaultAllocator() 
)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

constucts GpuMat and fills it with the specified value _s

§ GpuMat() [5/11]

cv::cuda::GpuMat::GpuMat ( Size  size,
int  type,
Scalar  s,
GpuMat::Allocator allocator = GpuMat::defaultAllocator() 
)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

§ GpuMat() [6/11]

cv::cuda::GpuMat::GpuMat ( const GpuMat m)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

copy constructor

§ GpuMat() [7/11]

cv::cuda::GpuMat::GpuMat ( int  rows,
int  cols,
int  type,
void *  data,
size_t  step = Mat::AUTO_STEP 
)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

constructor for GpuMat headers pointing to user-allocated data

§ GpuMat() [8/11]

cv::cuda::GpuMat::GpuMat ( Size  size,
int  type,
void *  data,
size_t  step = Mat::AUTO_STEP 
)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

§ GpuMat() [9/11]

cv::cuda::GpuMat::GpuMat ( const GpuMat m,
Range  rowRange,
Range  colRange 
)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

creates a GpuMat header for a part of the bigger matrix

§ GpuMat() [10/11]

cv::cuda::GpuMat::GpuMat ( const GpuMat m,
Rect  roi 
)
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

§ GpuMat() [11/11]

cv::cuda::GpuMat::GpuMat ( InputArray  arr,
GpuMat::Allocator allocator = GpuMat::defaultAllocator() 
)
explicit
Python:
<cuda_GpuMat object>=cv.cuda_GpuMat([, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(rows, cols, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(size, type, s[, allocator])
<cuda_GpuMat object>=cv.cuda_GpuMat(m)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, rowRange, colRange)
<cuda_GpuMat object>=cv.cuda_GpuMat(m, roi)
<cuda_GpuMat object>=cv.cuda_GpuMat(arr[, allocator])

builds GpuMat from host memory (Blocking call)

§ ~GpuMat()

cv::cuda::GpuMat::~GpuMat ( )

destructor - calls release()

Member Function Documentation

§ adjustROI()

GpuMat& cv::cuda::GpuMat::adjustROI ( int  dtop,
int  dbottom,
int  dleft,
int  dright 
)
Python:
retval=cv.cuda_GpuMat.adjustROI(dtop, dbottom, dleft, dright)

moves/resizes the current GpuMat ROI inside the parent GpuMat

§ assignTo()

void cv::cuda::GpuMat::assignTo ( GpuMat m,
int  type = -1 
) const
Python:
None=cv.cuda_GpuMat.assignTo(m[, type])

§ channels()

int cv::cuda::GpuMat::channels ( ) const
Python:
retval=cv.cuda_GpuMat.channels()

returns number of channels

§ clone()

GpuMat cv::cuda::GpuMat::clone ( ) const
Python:
retval=cv.cuda_GpuMat.clone()

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

§ col()

GpuMat cv::cuda::GpuMat::col ( int  x) const
Python:
retval=cv.cuda_GpuMat.col(x)

returns a new GpuMat header for the specified column

§ colRange() [1/2]

GpuMat cv::cuda::GpuMat::colRange ( int  startcol,
int  endcol 
) const
Python:
retval=cv.cuda_GpuMat.colRange(startcol, endcol)
retval=cv.cuda_GpuMat.colRange(r)

... for the specified column span

§ colRange() [2/2]

GpuMat cv::cuda::GpuMat::colRange ( Range  r) const
Python:
retval=cv.cuda_GpuMat.colRange(startcol, endcol)
retval=cv.cuda_GpuMat.colRange(r)

§ convertTo() [1/5]

void cv::cuda::GpuMat::convertTo ( OutputArray  dst,
int  rtype 
) const
Python:
dst=cv.cuda_GpuMat.convertTo(rtype[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha[, dst[, beta]])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, beta, stream[, dst])

converts GpuMat to another datatype (Blocking call)

§ convertTo() [2/5]

void cv::cuda::GpuMat::convertTo ( OutputArray  dst,
int  rtype,
Stream stream 
) const
Python:
dst=cv.cuda_GpuMat.convertTo(rtype[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha[, dst[, beta]])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, beta, stream[, dst])

converts GpuMat to another datatype (Non-Blocking call)

§ convertTo() [3/5]

void cv::cuda::GpuMat::convertTo ( OutputArray  dst,
int  rtype,
double  alpha,
double  beta = 0.0 
) const
Python:
dst=cv.cuda_GpuMat.convertTo(rtype[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha[, dst[, beta]])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, beta, stream[, dst])

converts GpuMat to another datatype with scaling (Blocking call)

§ convertTo() [4/5]

void cv::cuda::GpuMat::convertTo ( OutputArray  dst,
int  rtype,
double  alpha,
Stream stream 
) const
Python:
dst=cv.cuda_GpuMat.convertTo(rtype[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha[, dst[, beta]])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, beta, stream[, dst])

converts GpuMat to another datatype with scaling (Non-Blocking call)

§ convertTo() [5/5]

void cv::cuda::GpuMat::convertTo ( OutputArray  dst,
int  rtype,
double  alpha,
double  beta,
Stream stream 
) const
Python:
dst=cv.cuda_GpuMat.convertTo(rtype[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha[, dst[, beta]])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, stream[, dst])
dst=cv.cuda_GpuMat.convertTo(rtype, alpha, beta, stream[, dst])

converts GpuMat to another datatype with scaling (Non-Blocking call)

§ copyTo() [1/4]

void cv::cuda::GpuMat::copyTo ( OutputArray  dst) const
Python:
dst=cv.cuda_GpuMat.copyTo([, dst])
dst=cv.cuda_GpuMat.copyTo(stream[, dst])
dst=cv.cuda_GpuMat.copyTo(mask[, dst])
dst=cv.cuda_GpuMat.copyTo(mask, stream[, dst])

copies the GpuMat content to device memory (Blocking call)

§ copyTo() [2/4]

void cv::cuda::GpuMat::copyTo ( OutputArray  dst,
Stream stream 
) const
Python:
dst=cv.cuda_GpuMat.copyTo([, dst])
dst=cv.cuda_GpuMat.copyTo(stream[, dst])
dst=cv.cuda_GpuMat.copyTo(mask[, dst])
dst=cv.cuda_GpuMat.copyTo(mask, stream[, dst])

copies the GpuMat content to device memory (Non-Blocking call)

§ copyTo() [3/4]

void cv::cuda::GpuMat::copyTo ( OutputArray  dst,
InputArray  mask 
) const
Python:
dst=cv.cuda_GpuMat.copyTo([, dst])
dst=cv.cuda_GpuMat.copyTo(stream[, dst])
dst=cv.cuda_GpuMat.copyTo(mask[, dst])
dst=cv.cuda_GpuMat.copyTo(mask, stream[, dst])

copies those GpuMat elements to "m" that are marked with non-zero mask elements (Blocking call)

§ copyTo() [4/4]

void cv::cuda::GpuMat::copyTo ( OutputArray  dst,
InputArray  mask,
Stream stream 
) const
Python:
dst=cv.cuda_GpuMat.copyTo([, dst])
dst=cv.cuda_GpuMat.copyTo(stream[, dst])
dst=cv.cuda_GpuMat.copyTo(mask[, dst])
dst=cv.cuda_GpuMat.copyTo(mask, stream[, dst])

copies those GpuMat elements to "m" that are marked with non-zero mask elements (Non-Blocking call)

§ create() [1/2]

void cv::cuda::GpuMat::create ( int  rows,
int  cols,
int  type 
)
Python:
None=cv.cuda_GpuMat.create(rows, cols, type)
None=cv.cuda_GpuMat.create(size, type)

allocates new GpuMat data unless the GpuMat already has specified size and type

§ create() [2/2]

void cv::cuda::GpuMat::create ( Size  size,
int  type 
)
Python:
None=cv.cuda_GpuMat.create(rows, cols, type)
None=cv.cuda_GpuMat.create(size, type)

§ defaultAllocator()

static GpuMat::Allocator* cv::cuda::GpuMat::defaultAllocator ( )
static
Python:
retval=cv.cuda.GpuMat_defaultAllocator()

default allocator

§ depth()

int cv::cuda::GpuMat::depth ( ) const
Python:
retval=cv.cuda_GpuMat.depth()

returns element type

§ download() [1/2]

void cv::cuda::GpuMat::download ( OutputArray  dst) const
Python:
dst=cv.cuda_GpuMat.download([, dst])
dst=cv.cuda_GpuMat.download(stream[, dst])

Performs data download from GpuMat (Blocking call)

This function copies data from device memory to host memory. As being a blocking call, it is guaranteed that the copy operation is finished when this function returns.

§ download() [2/2]

void cv::cuda::GpuMat::download ( OutputArray  dst,
Stream stream 
) const
Python:
dst=cv.cuda_GpuMat.download([, dst])
dst=cv.cuda_GpuMat.download(stream[, dst])

Performs data download from GpuMat (Non-Blocking call)

This function copies data from device memory to host memory. As being a non-blocking call, this function may return even if the copy operation is not finished.

The copy operation may be overlapped with operations in other non-default streams if stream is not the default stream and dst is HostMem allocated with HostMem::PAGE_LOCKED option.

§ elemSize()

size_t cv::cuda::GpuMat::elemSize ( ) const
Python:
retval=cv.cuda_GpuMat.elemSize()

returns element size in bytes

§ elemSize1()

size_t cv::cuda::GpuMat::elemSize1 ( ) const
Python:
retval=cv.cuda_GpuMat.elemSize1()

returns the size of element channel in bytes

§ empty()

bool cv::cuda::GpuMat::empty ( ) const
Python:
retval=cv.cuda_GpuMat.empty()

returns true if GpuMat data is NULL

§ isContinuous()

bool cv::cuda::GpuMat::isContinuous ( ) const
Python:
retval=cv.cuda_GpuMat.isContinuous()

returns true iff the GpuMat data is continuous (i.e. when there are no gaps between successive rows)

§ locateROI()

void cv::cuda::GpuMat::locateROI ( Size wholeSize,
Point ofs 
) const
Python:
None=cv.cuda_GpuMat.locateROI(wholeSize, ofs)

locates GpuMat header within a parent GpuMat

§ operator PtrStep< _Tp >()

template<typename _Tp >
cv::cuda::GpuMat::operator PtrStep< _Tp > ( ) const

§ operator PtrStepSz< _Tp >()

template<typename _Tp >
cv::cuda::GpuMat::operator PtrStepSz< _Tp > ( ) const

§ operator()() [1/2]

GpuMat cv::cuda::GpuMat::operator() ( Range  rowRange,
Range  colRange 
) const

extracts a rectangular sub-GpuMat (this is a generalized form of row, rowRange etc.)

§ operator()() [2/2]

GpuMat cv::cuda::GpuMat::operator() ( Rect  roi) const

§ operator=()

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

assignment operators

§ ptr() [1/4]

uchar* cv::cuda::GpuMat::ptr ( int  y = 0)

returns pointer to y-th row

§ ptr() [2/4]

const uchar* cv::cuda::GpuMat::ptr ( int  y = 0) const

§ ptr() [3/4]

template<typename _Tp >
_Tp* cv::cuda::GpuMat::ptr ( int  y = 0)

template version of the above method

§ ptr() [4/4]

template<typename _Tp >
const _Tp* cv::cuda::GpuMat::ptr ( int  y = 0) const

§ release()

void cv::cuda::GpuMat::release ( )

decreases reference counter, deallocate the data when reference counter reaches 0

§ reshape()

GpuMat cv::cuda::GpuMat::reshape ( int  cn,
int  rows = 0 
) const
Python:
retval=cv.cuda_GpuMat.reshape(cn[, rows])

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

§ row()

GpuMat cv::cuda::GpuMat::row ( int  y) const
Python:
retval=cv.cuda_GpuMat.row(y)

returns a new GpuMat header for the specified row

§ rowRange() [1/2]

GpuMat cv::cuda::GpuMat::rowRange ( int  startrow,
int  endrow 
) const
Python:
retval=cv.cuda_GpuMat.rowRange(startrow, endrow)
retval=cv.cuda_GpuMat.rowRange(r)

... for the specified row span

§ rowRange() [2/2]

GpuMat cv::cuda::GpuMat::rowRange ( Range  r) const
Python:
retval=cv.cuda_GpuMat.rowRange(startrow, endrow)
retval=cv.cuda_GpuMat.rowRange(r)

§ setDefaultAllocator()

static void cv::cuda::GpuMat::setDefaultAllocator ( GpuMat::Allocator allocator)
static
Python:
None=cv.cuda.GpuMat_setDefaultAllocator(allocator)

§ setTo() [1/4]

GpuMat& cv::cuda::GpuMat::setTo ( Scalar  s)
Python:
retval=cv.cuda_GpuMat.setTo(s)
retval=cv.cuda_GpuMat.setTo(s, stream)
retval=cv.cuda_GpuMat.setTo(s, mask)
retval=cv.cuda_GpuMat.setTo(s, mask, stream)

sets some of the GpuMat elements to s (Blocking call)

§ setTo() [2/4]

GpuMat& cv::cuda::GpuMat::setTo ( Scalar  s,
Stream stream 
)
Python:
retval=cv.cuda_GpuMat.setTo(s)
retval=cv.cuda_GpuMat.setTo(s, stream)
retval=cv.cuda_GpuMat.setTo(s, mask)
retval=cv.cuda_GpuMat.setTo(s, mask, stream)

sets some of the GpuMat elements to s (Non-Blocking call)

§ setTo() [3/4]

GpuMat& cv::cuda::GpuMat::setTo ( Scalar  s,
InputArray  mask 
)
Python:
retval=cv.cuda_GpuMat.setTo(s)
retval=cv.cuda_GpuMat.setTo(s, stream)
retval=cv.cuda_GpuMat.setTo(s, mask)
retval=cv.cuda_GpuMat.setTo(s, mask, stream)

sets some of the GpuMat elements to s, according to the mask (Blocking call)

§ setTo() [4/4]

GpuMat& cv::cuda::GpuMat::setTo ( Scalar  s,
InputArray  mask,
Stream stream 
)
Python:
retval=cv.cuda_GpuMat.setTo(s)
retval=cv.cuda_GpuMat.setTo(s, stream)
retval=cv.cuda_GpuMat.setTo(s, mask)
retval=cv.cuda_GpuMat.setTo(s, mask, stream)

sets some of the GpuMat elements to s, according to the mask (Non-Blocking call)

§ size()

Size cv::cuda::GpuMat::size ( ) const
Python:
retval=cv.cuda_GpuMat.size()

returns GpuMat size : width == number of columns, height == number of rows

§ step1()

size_t cv::cuda::GpuMat::step1 ( ) const
Python:
retval=cv.cuda_GpuMat.step1()

returns step/elemSize1()

§ swap()

void cv::cuda::GpuMat::swap ( GpuMat mat)
Python:
None=cv.cuda_GpuMat.swap(mat)

swaps with other smart pointer

§ type()

int cv::cuda::GpuMat::type ( ) const
Python:
retval=cv.cuda_GpuMat.type()

returns element type

§ updateContinuityFlag()

void cv::cuda::GpuMat::updateContinuityFlag ( )
Python:
None=cv.cuda_GpuMat.updateContinuityFlag()

internal use method: updates the continuity flag

§ upload() [1/2]

void cv::cuda::GpuMat::upload ( InputArray  arr)
Python:
None=cv.cuda_GpuMat.upload(arr)
None=cv.cuda_GpuMat.upload(arr, stream)

Performs data upload to GpuMat (Blocking call)

This function copies data from host memory to device memory. As being a blocking call, it is guaranteed that the copy operation is finished when this function returns.

§ upload() [2/2]

void cv::cuda::GpuMat::upload ( InputArray  arr,
Stream stream 
)
Python:
None=cv.cuda_GpuMat.upload(arr)
None=cv.cuda_GpuMat.upload(arr, stream)

Performs data upload to GpuMat (Non-Blocking call)

This function copies data from host memory to device memory. As being a non-blocking call, this function may return even if the copy operation is not finished.

The copy operation may be overlapped with operations in other non-default streams if stream is not the default stream and dst is HostMem allocated with HostMem::PAGE_LOCKED option.

Member Data Documentation

§ allocator

Allocator* cv::cuda::GpuMat::allocator

allocator

§ cols

int cv::cuda::GpuMat::cols

§ data

uchar* cv::cuda::GpuMat::data

pointer to the data

§ dataend

const uchar* cv::cuda::GpuMat::dataend

§ datastart

uchar* cv::cuda::GpuMat::datastart

helper fields used in locateROI and adjustROI

§ flags

int cv::cuda::GpuMat::flags

includes several bit-fields:

  • the magic signature
  • continuity flag
  • depth
  • number of channels

§ refcount

int* cv::cuda::GpuMat::refcount

pointer to the reference counter; when GpuMat points to user-allocated data, the pointer is NULL

§ rows

int cv::cuda::GpuMat::rows

the number of rows and columns

§ step

size_t cv::cuda::GpuMat::step

a distance between successive rows in bytes; includes the gap if any


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