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cv::cuda::NvidiaOpticalFlow_2_0 Class Referenceabstract
Class for computing the optical flow vectors between two images using NVIDIA Optical Flow hardware and Optical Flow SDK 2.0. More...
#include <opencv2/cudaoptflow.hpp>
Inheritance diagram for cv::cuda::NvidiaOpticalFlow_2_0:

Public Member Functions | |
virtual void | convertToFloat (InputArray flow, InputOutputArray floatFlow)=0 |
convertToFloat() helper function converts the hardware-generated flow vectors to floating point representation (1 flow vector for gridSize). gridSize can be queried via function getGridSize(). | |
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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. | |
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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 |
void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
virtual void | write (FileStorage &fs) const |
Stores algorithm parameters in a file storage. | |
void | write (FileStorage &fs, const String &name) const |
Additional Inherited Members | |
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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 2.0.
- 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_HINT_VECTOR_GRID_SIZE
Supported grid size for hint buffer.
◆ NVIDIA_OF_OUTPUT_VECTOR_GRID_SIZE
Supported grid size for output buffer.
◆ NVIDIA_OF_PERF_LEVEL
Supported optical flow performance levels.
Member Function Documentation
◆ convertToFloat()
|
pure virtual |
convertToFloat() helper function converts the hardware-generated flow vectors to floating point representation (1 flow vector for gridSize). gridSize can be queried via function getGridSize().
- Parameters
-
flow Buffer of type CV_16FC2 containing flow vectors generated by calc(). floatFlow Buffer of type CV_32FC2, containing flow vectors in floating point representation, each flow vector for 1 pixel per gridSize, in the pitch-linear layout.
◆ create() [1/2]
|
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. outputGridSize Optional parameter. Refer NV OF SDK documentation for details about output grid sizes. Defaults to NV_OF_OUTPUT_VECTOR_GRID_SIZE_1. hintGridSize Optional parameter. Refer NV OF SDK documentation for details about hint grid sizes. Defaults to NV_OF_HINT_VECTOR_GRID_SIZE_1. 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;
◆ create() [2/2]
|
static |
Instantiate NVIDIA Optical Flow with ROI Feature.
- Parameters
-
imageSize Size of input image in pixels. roiData Pointer to ROI data. perfPreset Optional parameter. Refer NV OF SDK documentation for details about presets. Defaults to NV_OF_PERF_LEVEL_SLOW. outputGridSize Optional parameter. Refer NV OF SDK documentation for details about output grid sizes. Defaults to NV_OF_OUTPUT_VECTOR_GRID_SIZE_1. hintGridSize Optional parameter. Refer NV OF SDK documentation for details about hint grid sizes. Defaults to NV_OF_HINT_VECTOR_GRID_SIZE_1. 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;
The documentation for this class was generated from the following file:
- opencv2/cudaoptflow.hpp