Class cv::TrackerNano#

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

Collaboration diagram for cv::TrackerNano:

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 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: HonglinChu/SiamTrackers Original repo is here: HonglinChu/NanoTrack Author: HongLinChu, 1628464345@qq.com

Constructor & Destructor Documentation#

TrackerNano()#

cv::TrackerNano::TrackerNano()

~TrackerNano()#

cv::TrackerNano::~TrackerNano()

Member Function Documentation#

create()#

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

Python:

cv.TrackerNano.create([, parameters]) -> retval
cv.TrackerNano.create(backbone, neckhead) -> retval
cv.TrackerNano_create([, parameters]) -> retval
cv.TrackerNano_create(backbone, neckhead) -> retval

Constructor.

Parameters

Source file#

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