Class cv::cuda::GpuMatND#
#include <opencv2/core/cuda.hpp>Collaboration diagram for cv::cuda::GpuMatND:
Member Typedef Documentation#
IndexArray#
typedef std::vector< int > cv::cuda::GpuMatND::IndexArray
SizeArray#
StepArray#
Constructor & Destructor Documentation#
GpuMatND()#
cv::cuda::GpuMatND::GpuMatND()
default constructor
GpuMatND()#
GpuMatND()#
cv::cuda::GpuMatND::GpuMatND(
const MatShape & shape,
int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters
shape— Array of integers specifying an n-dimensional array shape.type— Array type. Use CV_8UC1, …, CV_16FC4 to create 1-4 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
GpuMatND()#
cv::cuda::GpuMatND::GpuMatND(
const MatShape & shape,
int type,
void * data,
StepArray step = StepArray() )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters
shape— Array of integers specifying an n-dimensional array shape.type— Array type. Use CV_8UC1, …, CV_16FC4 to create 1-4 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.data— Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. This operation is very efficient and can be used to process external data using OpenCV functions. The external data is not automatically deallocated, so you should take care of it.step— Array of shape.size() or shape.size()-1 steps in case of a multi-dimensional array (if specified, the last step must be equal to the element size, otherwise it will be added as such). If not specified, the matrix is assumed to be continuous.
GpuMatND()#
~GpuMatND()#
cv::cuda::GpuMatND::~GpuMatND()
destructor
Member Function Documentation#
clone()#
GpuMatND cv::cuda::GpuMatND::clone()
Creates a full copy of the array and the underlying data. The method creates a full copy of the array. It mimics the behavior of Mat::clone(), i.e. the original step is not taken into account. So, the array copy is a continuous array occupying total()*elemSize() bytes.
clone()#
GpuMatND cv::cuda::GpuMatND::clone(Stream & stream)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. This overload is non-blocking, so it may return even if the copy operation is not finished.
create()#
void cv::cuda::GpuMatND::create(
const MatShape & shape,
int type )
Allocates GPU memory. Suppose there is some GPU memory already allocated. In that case, this method may choose to reuse that GPU memory under the specific condition: it must be of the same size and type, not externally allocated, the GPU memory is continuous(i.e., isContinuous() is true), and is not a sub-matrix of another GpuMatND (i.e., isSubmatrix() is false). In other words, this method guarantees that the GPU memory allocated by this method is always continuous and is not a sub-region of another GpuMatND.
createGpuMatHeader()#
GpuMat cv::cuda::GpuMatND::createGpuMatHeader()
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. Creates a GpuMat header if this GpuMatND is effectively 2D.
createGpuMatHeader()#
GpuMat cv::cuda::GpuMatND::createGpuMatHeader(
IndexArray idx,
Range rowRange,
Range colRange )
Creates a GpuMat header for a 2D plane part of an n-dim matrix.
download()#
void cv::cuda::GpuMatND::download(OutputArray dst)
download()#
void cv::cuda::GpuMatND::download(
OutputArray dst,
Stream & stream )
elemSize()#
size_t cv::cuda::GpuMatND::elemSize()
returns element size in bytes
elemSize1()#
size_t cv::cuda::GpuMatND::elemSize1()
returns the size of element channel in bytes
empty()#
bool cv::cuda::GpuMatND::empty()
returns true if data is null
external()#
bool cv::cuda::GpuMatND::external()
returns true if not empty and points to external(user-allocated) gpu memory
fit()#
void cv::cuda::GpuMatND::fit(
const MatShape & shape,
int type )
Allocates or reuses underlying storage to fit the requested n-D size and type.
No-op if already compatible (sufficient capacity, continuous, not a submatrix, not external, no ROI).
Reallocates otherwise. Mirrors 2D GpuMat::fit semantics for multi-dimensional tensors.
getDevicePtr()#
uchar * cv::cuda::GpuMatND::getDevicePtr()
returns pointer to the first byte of the GPU memory
isContinuous()#
bool cv::cuda::GpuMatND::isContinuous()
returns true iff the GpuMatND data is continuous (i.e. when there are no gaps between successive rows)
isSubmatrix()#
bool cv::cuda::GpuMatND::isSubmatrix()
returns true if the matrix is a sub-matrix of another matrix
operator GpuMat()#
cv::cuda::GpuMatND::operator GpuMat()
Extracts a 2D plane part of an n-dim matrix if this GpuMatND is effectively 2D. It differs from createGpuMatHeader() in that it clones a part of this GpuMatND.
Note
This operator does not increment this GpuMatND’s reference counter;
operator()()#
GpuMatND cv::cuda::GpuMatND::operator()(const std::vector< Range > & ranges)
Extracts a sub-matrix. The operator makes a new header for the specified sub-array of *this. The operator is an O(1) operation, that is, no matrix data is copied.
Parameters
ranges— Array of selected ranges along each dimension.
operator()()#
GpuMat cv::cuda::GpuMatND::operator()(
IndexArray idx,
Range rowRange,
Range colRange )
Extracts a 2D plane part of an n-dim matrix. It differs from createGpuMatHeader(IndexArray, Range, Range) in that it clones a part of this GpuMatND to the returned GpuMat.
Note
This operator does not increment this GpuMatND’s reference counter;
operator=()#
operator=()#
release()#
void cv::cuda::GpuMatND::release()
swap()#
total()#
size_t cv::cuda::GpuMatND::total()
returns the total number of array elements
totalMemSize()#
size_t cv::cuda::GpuMatND::totalMemSize()
returns the size of underlying memory in bytes
type()#
int cv::cuda::GpuMatND::type()
returns element type
upload()#
void cv::cuda::GpuMatND::upload(InputArray src)
upload()#
void cv::cuda::GpuMatND::upload(
InputArray src,
Stream & stream )
setFields()#
void cv::cuda::GpuMatND::setFields(
MatShape size,
int type,
StepArray step = StepArray() )
internal use
Member Data Documentation#
dims#
int cv::cuda::GpuMatND::dims
matrix dimensionality
flags#
int cv::cuda::GpuMatND::flags
includes several bit-fields:
the magic signature
continuity flag
depth
number of channels
size#
MatShape cv::cuda::GpuMatND::size
shape of this array
step#
StepArray cv::cuda::GpuMatND::step
step values Their semantics is identical to the semantics of step for Mat.
data#
uchar * cv::cuda::GpuMatND::data
internal use If this GpuMatND manages memory with reference counting, this value is always equal to data_->data. If this GpuMatND holds external memory, data_ is empty and data points to the external memory.
data_#
std::shared_ptr< GpuData > cv::cuda::GpuMatND::data_
internal use If this GpuMatND holds external memory, this is empty.
offset#
size_t cv::cuda::GpuMatND::offset
internal use If this GpuMatND is a sub-matrix of a larger matrix, this value is the difference of the first byte between the sub-matrix and the whole matrix.
Source file#
The documentation for this class was generated from the following file:
opencv2/core/cuda.hpp