Class cv::TrackerVit#

the VIT tracker is a super lightweight dnn-based general object tracking. View details

Collaboration diagram for cv::TrackerVit:

Public Member Functions#

Public Member Functions inherited from cv::Tracker

Return

Name

Description

~Tracker()

float

getTrackingScore()

Return tracking score.

void

init(
    InputArray image,
    const Rect & boundingBox )

Initialize the tracker with a known bounding box that surrounded the target.

bool

update(
    InputArray image,
    Rect & boundingBox )

Update the tracker, find the new most likely bounding box for the target.

Additional Inherited Members#

Protected Member Functions inherited from cv::Tracker

Return

Name

Description

Tracker()

Detailed Description#

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: opencv/opencv_zoo Author: PengyuLiu, 1872918507@qq.com

Constructor & Destructor Documentation#

TrackerVit()#

cv::TrackerVit::TrackerVit()

~TrackerVit()#

cv::TrackerVit::~TrackerVit()

Member Function Documentation#

create()#

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

Python:

cv.TrackerVit.create([, parameters]) -> retval
cv.TrackerVit.create(model[, meanvalue[, stdvalue[, tracking_score_threshold]]]) -> retval
cv.TrackerVit_create([, parameters]) -> retval
cv.TrackerVit_create(model[, meanvalue[, stdvalue[, tracking_score_threshold]]]) -> retval

Constructor.

Parameters

Source file#

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