Package org.opencv.video

Class TrackerVit

java.lang.Object

org.opencv.video.Tracker

org.opencv.video.TrackerVit

public class TrackerVit
extends Tracker

the VIT tracker is a super lightweight dnn-based general object tracking. VIT tracker is much faster and extremely lightweight due to special model structure, the model file is about 767KB. Model download link: https://github.com/opencv/opencv_zoo/tree/main/models/object_tracking_vittrack Author: PengyuLiu, 1872918507@qq.com

Method Summary

Modifier and Type	Method	Description
static TrackerVit	__fromPtr__(long addr)
static TrackerVit	create()	Constructor
static TrackerVit	create(Net model)	Constructor
static TrackerVit	create(Net model, Scalar meanvalue)	Constructor
static TrackerVit	create(Net model, Scalar meanvalue, Scalar stdvalue)	Constructor
static TrackerVit	create(Net model, Scalar meanvalue, Scalar stdvalue, float tracking_score_threshold)	Constructor
static TrackerVit	create(TrackerVit_Params parameters)	Constructor
float	getTrackingScore()	Return tracking score

Methods inherited from class org.opencv.video.Tracker

getNativeObjAddr, init, update

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

__fromPtr__

public static TrackerVit __fromPtr__(long addr)

create

public static TrackerVit create(TrackerVit_Params parameters)

Constructor

Parameters:

parameters - vit tracker parameters TrackerVit::Params

Returns:

automatically generated

create

public static TrackerVit create()

Constructor

Returns:

automatically generated

create

public static TrackerVit create(Net model,
 Scalar meanvalue,
 Scalar stdvalue,
 float tracking_score_threshold)

Constructor

Parameters:

model - pre-loaded DNN model

meanvalue - mean value for image preprocessing

stdvalue - std value for image preprocessing

tracking_score_threshold - threshold for tracking score

Returns:

automatically generated

create

public static TrackerVit create(Net model,
 Scalar meanvalue,
 Scalar stdvalue)

Constructor

Parameters:

model - pre-loaded DNN model

meanvalue - mean value for image preprocessing

stdvalue - std value for image preprocessing

Returns:

automatically generated

create

public static TrackerVit create(Net model,
 Scalar meanvalue)

Constructor

Parameters:

model - pre-loaded DNN model

meanvalue - mean value for image preprocessing

Returns:

automatically generated

create

public static TrackerVit create(Net model)

Constructor

Parameters:

model - pre-loaded DNN model

Returns:

automatically generated

getTrackingScore

public float getTrackingScore()

Return tracking score

Returns:

automatically generated