the Nano tracker is a super lightweight dnn-based general object tracking. More...

#include <opencv2/video/tracking.hpp>

Collaboration diagram for cv::TrackerNano:

Public Member Functions
virtual	~TrackerNano () CV_OVERRIDE

virtual float	getTrackingScore ()=0
	Return tracking score.

Public Member Functions inherited from cv::Tracker
virtual	~Tracker ()

virtual void	init (InputArray image, const Rect &boundingBox)=0
	Initialize the tracker with a known bounding box that surrounded the target.

virtual bool	update (InputArray image, Rect &boundingBox)=0
	Update the tracker, find the new most likely bounding box for the target.

Static Public Member Functions
static Ptr< TrackerNano >	create (const TrackerNano::Params &parameters=TrackerNano::Params())
	Constructor.

Protected Member Functions
	TrackerNano ()

Protected Member Functions inherited from cv::Tracker
	Tracker ()

Detailed Description

the Nano tracker is a super lightweight dnn-based general object tracking.

Nano tracker is much faster and extremely lightweight due to special model structure, the whole model size is about 1.9 MB. Nano tracker needs two models: one for feature extraction (backbone) and the another for localization (neckhead). Model download link: https://github.com/HonglinChu/SiamTrackers/tree/master/NanoTrack/models/nanotrackv2 Original repo is here: https://github.com/HonglinChu/NanoTrack Author: HongLinChu, 16284.nosp@m.6434.nosp@m.5@qq..nosp@m.com

Constructor & Destructor Documentation

cv::TrackerNano::TrackerNano ( )

protected

virtual cv::TrackerNano::~TrackerNano ( )

virtual

static Ptr< TrackerNano > cv::TrackerNano::create ( const TrackerNano::Params & parameters = TrackerNano::Params() )

static

Python:
	cv.TrackerNano.create(	[, parameters]	) ->	retval
	cv.TrackerNano_create(	[, parameters]	) ->	retval

Constructor.

Parameters

parameters NanoTrack parameters TrackerNano::Params

virtual float cv::TrackerNano::getTrackingScore ( )

pure virtual

Python:
	cv.TrackerNano.getTrackingScore(		) ->	retval

Return tracking score.

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