OpenCV  4.10.0-dev
Open Source Computer Vision
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Classes | Namespaces | Typedefs | Enumerations | Functions
video.hpp File Reference
#include <utility>
#include <opencv2/gapi/gkernel.hpp>
Include dependency graph for video.hpp:

Classes

struct  cv::gapi::video::BackgroundSubtractorParams
 Structure for the Background Subtractor operation's initialization parameters. More...
 
struct  cv::detail::CompileArgTag< cv::gapi::video::BackgroundSubtractorParams >
 
struct  cv::gapi::KalmanParams
 Structure for the Kalman filter's initialization parameters. More...
 

Namespaces

namespace  cv
 
namespace  cv::detail
 
namespace  cv::gapi
 
namespace  cv::gapi::video
 This namespace contains G-API Operations and functions for video-oriented algorithms, like optical flow and background subtraction.
 

Typedefs

using cv::gapi::video::GBuildPyrOutput = std::tuple< GArray< GMat >, GScalar >
 
using cv::gapi::video::GOptFlowLKOutput = std::tuple< cv::GArray< cv::Point2f >, cv::GArray< uchar >, cv::GArray< float > >
 

Enumerations

enum  cv::gapi::video::BackgroundSubtractorType {
  cv::gapi::video::TYPE_BS_MOG2 ,
  cv::gapi::video::TYPE_BS_KNN
}
 

Functions

GMat cv::gapi::BackgroundSubtractor (const GMat &src, const cv::gapi::video::BackgroundSubtractorParams &bsParams)
 Gaussian Mixture-based or K-nearest neighbours-based Background/Foreground Segmentation Algorithm. The operation generates a foreground mask.
 
std::tuple< GArray< GMat >, GScalarcv::gapi::buildOpticalFlowPyramid (const GMat &img, const Size &winSize, const GScalar &maxLevel, bool withDerivatives=true, int pyrBorder=BORDER_REFLECT_101, int derivBorder=BORDER_CONSTANT, bool tryReuseInputImage=true)
 Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
 
std::tuple< GArray< Point2f >, GArray< uchar >, GArray< float > > cv::gapi::calcOpticalFlowPyrLK (const GArray< GMat > &prevPyr, const GArray< GMat > &nextPyr, const GArray< Point2f > &prevPts, const GArray< Point2f > &predPts, const Size &winSize=Size(21, 21), const GScalar &maxLevel=3, const TermCriteria &criteria=TermCriteria(TermCriteria::COUNT|TermCriteria::EPS, 30, 0.01), int flags=0, double minEigThresh=1e-4)
 
std::tuple< GArray< Point2f >, GArray< uchar >, GArray< float > > cv::gapi::calcOpticalFlowPyrLK (const GMat &prevImg, const GMat &nextImg, const GArray< Point2f > &prevPts, const GArray< Point2f > &predPts, const Size &winSize=Size(21, 21), const GScalar &maxLevel=3, const TermCriteria &criteria=TermCriteria(TermCriteria::COUNT|TermCriteria::EPS, 30, 0.01), int flags=0, double minEigThresh=1e-4)
 Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.
 
void cv::gapi::video::checkParams (const cv::gapi::KalmanParams &kfParams, const cv::GMatDesc &measurement, const cv::GMatDesc &control={})
 
 cv::gapi::video::G_TYPED_KERNEL (GBackgroundSubtractor,< GMat(GMat, BackgroundSubtractorParams)>, "org.opencv.video.BackgroundSubtractor")
 
 cv::gapi::video::G_TYPED_KERNEL (GBuildOptFlowPyramid,< GBuildPyrOutput(GMat, Size, GScalar, bool, int, int, bool)>, "org.opencv.video.buildOpticalFlowPyramid")
 
 cv::gapi::video::G_TYPED_KERNEL (GCalcOptFlowLK,< GOptFlowLKOutput(GMat, GMat, cv::GArray< cv::Point2f >, cv::GArray< cv::Point2f >, Size, GScalar, TermCriteria, int, double)>, "org.opencv.video.calcOpticalFlowPyrLK")
 
 cv::gapi::video::G_TYPED_KERNEL (GCalcOptFlowLKForPyr,< GOptFlowLKOutput(cv::GArray< cv::GMat >, cv::GArray< cv::GMat >, cv::GArray< cv::Point2f >, cv::GArray< cv::Point2f >, Size, GScalar, TermCriteria, int, double)>, "org.opencv.video.calcOpticalFlowPyrLKForPyr")
 
 cv::gapi::video::G_TYPED_KERNEL (GKalmanFilter,< GMat(GMat, GOpaque< bool >, GMat, KalmanParams)>, "org.opencv.video.KalmanFilter")
 
GMat cv::gapi::KalmanFilter (const GMat &measurement, const GOpaque< bool > &haveMeasurement, const cv::gapi::KalmanParams &kfParams)
 
GMat cv::gapi::KalmanFilter (const GMat &measurement, const GOpaque< bool > &haveMeasurement, const GMat &control, const cv::gapi::KalmanParams &kfParams)
 Standard Kalman filter algorithm http://en.wikipedia.org/wiki/Kalman_filter.