Class for computing the optical flow vectors between two images using NVIDIA Optical Flow hardware and Optical Flow SDK 1.0. More...

#include <opencv2/cudaoptflow.hpp>

Collaboration diagram for cv::cuda::NvidiaOpticalFlow_1_0:

Public Types
enum	NVIDIA_OF_PERF_LEVEL { NV_OF_PERF_LEVEL_UNDEFINED , NV_OF_PERF_LEVEL_SLOW = 5 , NV_OF_PERF_LEVEL_MEDIUM = 10 , NV_OF_PERF_LEVEL_FAST = 20 , NV_OF_PERF_LEVEL_MAX }

Public Member Functions
virtual void	upSampler (InputArray flow, cv::Size imageSize, int gridSize, InputOutputArray upsampledFlow)=0
	The NVIDIA optical flow hardware generates flow vectors at granularity gridSize, which can be queried via function getGridSize(). Upsampler() helper function converts the hardware-generated flow vectors to dense representation (1 flow vector for each pixel) using nearest neighbour upsampling method.

Public Member Functions inherited from cv::cuda::NvidiaHWOpticalFlow
virtual void	calc (InputArray inputImage, InputArray referenceImage, InputOutputArray flow, Stream &stream=Stream::Null(), InputArray hint=cv::noArray(), OutputArray cost=cv::noArray())=0
	Calculates Optical Flow using NVIDIA Optical Flow SDK.

virtual void	collectGarbage ()=0
	Releases all buffers, contexts and device pointers.

virtual int	getGridSize () const =0
	Returns grid size of output buffer as per the hardware's capability.

Public Member Functions inherited from cv::Algorithm
	Algorithm ()

virtual	~Algorithm ()

virtual void	clear ()
	Clears the algorithm state.

virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.

virtual String	getDefaultName () const

virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage.

virtual void	save (const String &filename) const

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage.

void	write (FileStorage &fs, const String &name) const

Static Public Member Functions
static Ptr< NvidiaOpticalFlow_1_0 >	create (cv::Size imageSize, cv::cuda::NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL perfPreset=cv::cuda::NvidiaOpticalFlow_1_0::NV_OF_PERF_LEVEL_SLOW, bool enableTemporalHints=false, bool enableExternalHints=false, bool enableCostBuffer=false, int gpuId=0, Stream &inputStream=Stream::Null(), Stream &outputStream=Stream::Null())
	Instantiate NVIDIA Optical Flow.

Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file.

template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String.

template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.

Additional Inherited Members
Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Class for computing the optical flow vectors between two images using NVIDIA Optical Flow hardware and Optical Flow SDK 1.0.

Note

A sample application demonstrating the use of NVIDIA Optical Flow can be found at opencv_contrib_source_code/modules/cudaoptflow/samples/nvidia_optical_flow.cpp
An example application comparing accuracy and performance of NVIDIA Optical Flow with other optical flow algorithms in OpenCV can be found at opencv_contrib_source_code/modules/cudaoptflow/samples/optical_flow.cpp

Member Enumeration Documentation

◆ NVIDIA_OF_PERF_LEVEL

enum cv::cuda::NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL

Supported optical flow performance levels.

Enumerator
NV_OF_PERF_LEVEL_UNDEFINED
NV_OF_PERF_LEVEL_SLOW	Slow perf level results in lowest performance and best quality
NV_OF_PERF_LEVEL_MEDIUM	Medium perf level results in low performance and medium quality
NV_OF_PERF_LEVEL_FAST	Fast perf level results in high performance and low quality
NV_OF_PERF_LEVEL_MAX

Member Function Documentation

◆ create()

static Ptr< NvidiaOpticalFlow_1_0 > cv::cuda::NvidiaOpticalFlow_1_0::create	(	cv::Size	imageSize,
		cv::cuda::NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL	perfPreset = cv::cuda::NvidiaOpticalFlow_1_0::NV_OF_PERF_LEVEL_SLOW,
		bool	enableTemporalHints = false,
		bool	enableExternalHints = false,
		bool	enableCostBuffer = false,
		int	gpuId = 0,
		Stream &	inputStream = Stream::Null(),
		Stream &	outputStream = Stream::Null() )

static

Instantiate NVIDIA Optical Flow.

Parameters

imageSize	Size of input image in pixels.
perfPreset	Optional parameter. Refer NV OF SDK documentation for details about presets. Defaults to NV_OF_PERF_LEVEL_SLOW.
enableTemporalHints	Optional parameter. Flag to enable temporal hints. When set to true, the hardware uses the flow vectors generated in previous call to calc() as internal hints for the current call to calc(). Useful when computing flow vectors between successive video frames. Defaults to false.
enableExternalHints	Optional Parameter. Flag to enable passing external hints buffer to calc(). Defaults to false.
enableCostBuffer	Optional Parameter. Flag to enable cost buffer output from calc(). Defaults to false.
gpuId	Optional parameter to select the GPU ID on which the optical flow should be computed. Useful in multi-GPU systems. Defaults to 0.
inputStream	Optical flow algorithm may optionally involve cuda preprocessing on the input buffers. The input cuda stream can be used to pipeline and synchronize the cuda preprocessing tasks with OF HW engine. If input stream is not set, the execute function will use default stream which is NULL stream;
outputStream	Optical flow algorithm may optionally involve cuda post processing on the output flow vectors. The output cuda stream can be used to pipeline and synchronize the cuda post processing tasks with OF HW engine. If output stream is not set, the execute function will use default stream which is NULL stream;

◆ upSampler()

virtual void cv::cuda::NvidiaOpticalFlow_1_0::upSampler	(	InputArray	flow,
		cv::Size	imageSize,
		int	gridSize,
		InputOutputArray	upsampledFlow )

pure virtual

The NVIDIA optical flow hardware generates flow vectors at granularity gridSize, which can be queried via function getGridSize(). Upsampler() helper function converts the hardware-generated flow vectors to dense representation (1 flow vector for each pixel) using nearest neighbour upsampling method.

Parameters

flow	Buffer of type CV_16FC2 containing flow vectors generated by calc().
imageSize	Size of the input image in pixels for which these flow vectors were generated.
gridSize	Granularity of the optical flow vectors returned by calc() function. Can be queried using getGridSize().
upsampledFlow	Buffer of type CV_32FC2, containing upsampled flow vectors, each flow vector for 1 pixel, in the pitch-linear layout.

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

opencv2/cudaoptflow.hpp

Public Types

Public Member Functions