Base abstract class for the long-term tracker:
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#include <opencv2/tracking/tracker.hpp>
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template<typename _Tp > |
static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
| Loads algorithm from the file.
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template<typename _Tp > |
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
| Loads algorithm from a String.
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template<typename _Tp > |
static Ptr< _Tp > | read (const FileNode &fn) |
| Reads algorithm from the file node.
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Base abstract class for the long-term tracker:
virtual cv::Tracker::~Tracker |
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virtual |
Python: |
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| retval | = | cv.Tracker.init( | image, boundingBox | ) |
Initialize the tracker with a known bounding box that surrounded the target.
- Parameters
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image | The initial frame |
boundingBox | The initial bounding box |
- Returns
- True if initialization went succesfully, false otherwise
virtual bool cv::Tracker::initImpl |
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const Mat & |
image, |
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const Rect2d & |
boundingBox |
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protectedpure virtual |
virtual void cv::Tracker::read |
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const FileNode & |
fn | ) |
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pure virtual |
Reads algorithm parameters from a file storage.
Reimplemented from cv::Algorithm.
Python: |
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| retval, boundingBox | = | cv.Tracker.update( | image | ) |
Update the tracker, find the new most likely bounding box for the target.
- Parameters
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image | The current frame |
boundingBox | The bounding box that represent the new target location, if true was returned, not modified otherwise |
- Returns
- True means that target was located and false means that tracker cannot locate target in current frame. Note, that latter does not imply that tracker has failed, maybe target is indeed missing from the frame (say, out of sight)
virtual bool cv::Tracker::updateImpl |
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const Mat & |
image, |
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Rect2d & |
boundingBox |
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protectedpure virtual |
virtual void cv::Tracker::write |
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FileStorage & |
fs | ) |
const |
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pure virtual |
Stores algorithm parameters in a file storage.
Reimplemented from cv::Algorithm.
The documentation for this class was generated from the following file: