Class cv::cuda::NvidiaHWOpticalFlow#

Base Interface for optical flow algorithms using NVIDIA Optical Flow SDK.

#include <opencv2/cudaoptflow.hpp>

Collaboration diagram for cv::cuda::NvidiaHWOpticalFlow:

Public Member Functions#

Public Member Functions inherited from cv::Algorithm

Return	Name	Description
	`Algorithm()`
	`~Algorithm()`
`void`	`clear()`	Clears the algorithm state.
`bool`	`empty()`	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
`String`	`getDefaultName()`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`save(const String & filename)`
`void`	`write(` `const Ptr< FileStorage > & fs,` `const String & name = String() )`
`void`	`write(FileStorage & fs)`	Stores algorithm parameters in a file storage.
`void`	`write(` `FileStorage & fs,` `const String & name )`

Static Public Member Functions#

Static Public Member Functions inherited from cv::Algorithm

Return	Name	Description
`static Ptr< _Tp >`	`load(` `const String & filename,` `const String & objname = String() )`	Loads algorithm from the file.
`static Ptr< _Tp >`	`loadFromString(` `const String & strModel,` `const String & objname = String() )`	Loads algorithm from a String.
`static Ptr< _Tp >`	`read(const FileNode & fn)`	Reads algorithm from the file node.

Additional Inherited Members#

Detailed Description#

Base Interface for optical flow algorithms using NVIDIA Optical Flow SDK.

Member Function Documentation#

calc()#

void cv::cuda::NvidiaHWOpticalFlow::calc(
InputArray inputImage,
InputArray referenceImage,
InputOutputArray flow,
Stream & stream = Stream::Null(),
InputArray hint = cv::noArray(),
OutputArray cost = cv::noArray() )

Calculates Optical Flow using NVIDIA Optical Flow SDK.

NVIDIA GPUs starting with Turing contain a dedicated hardware accelerator for computing optical flow vectors between pairs of images. The optical flow hardware accelerator generates block-based optical flow vectors. The size of the block depends on hardware in use, and can be queried using the function getGridSize(). The block-based flow vectors generated by the hardware can be converted to dense representation (i.e. per-pixel flow vectors) using upSampler() helper function, if needed. The flow vectors are stored in CV_16SC2 format with x and y components of each flow vector in 16-bit signed fixed point representation S10.5.

Note

Client must use critical sections around each calc() function if calling it from multiple threads.

Parameters

inputImage — Input image.
referenceImage — Reference image of the same size and the same type as input image.
flow — A buffer consisting of inputImage.Size() / getGridSize() flow vectors in CV_16SC2 format.
stream — It is highly recommended that CUDA streams for pre and post processing of optical flow vectors should be set once per session in create() function as a part of optical flow session creation. This parameter is left here for backward compatibility and may be removed in the future. Default value is NULL stream;
hint — Hint buffer if client provides external hints. Must have same size as flow buffer. Caller can provide flow vectors as hints for optical flow calculation.
cost — Cost buffer contains numbers indicating the confidence associated with each of the generated flow vectors. Higher the cost, lower the confidence. Cost buffer is of type CV_32SC1.

collectGarbage()#

void cv::cuda::NvidiaHWOpticalFlow::collectGarbage()

Releases all buffers, contexts and device pointers.

getGridSize()#

int cv::cuda::NvidiaHWOpticalFlow::getGridSize()

Returns grid size of output buffer as per the hardware’s capability.

Source file#

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

opencv2/cudaoptflow.hpp