a yµÿfGã@s8dZddlmZddlZGdd„dƒZGdd„dƒZdS)zKModule defines the base classes and structures for object tracking in YOLO.é)Ú OrderedDictNc@s eZdZdZdZdZdZdZdS)Ú TrackStatea Enumeration class representing the possible states of an object being tracked. Attributes: New (int): State when the object is newly detected. Tracked (int): State when the object is successfully tracked in subsequent frames. Lost (int): State when the object is no longer tracked. Removed (int): State when the object is removed from tracking. Examples: >>> state = TrackState.New >>> if state == TrackState.New: >>> print("Object is newly detected.") réééN)Ú__name__Ú __module__Ú __qualname__Ú__doc__ÚNewZTrackedÚLostÚRemoved©rrúZ/var/www/html/django/DPS/env/lib/python3.9/site-packages/ultralytics/trackers/basetrack.pyr s rc@sheZdZdZdZdd„Zedd„ƒZedd„ƒZ d d „Z d d „Z d d„Z dd„Z dd„Zedd„ƒZdS)Ú BaseTracka{ Base class for object tracking, providing foundational attributes and methods. Attributes: _count (int): Class-level counter for unique track IDs. track_id (int): Unique identifier for the track. is_activated (bool): Flag indicating whether the track is currently active. state (TrackState): Current state of the track. history (OrderedDict): Ordered history of the track's states. features (List): List of features extracted from the object for tracking. curr_feature (Any): The current feature of the object being tracked. score (float): The confidence score of the tracking. start_frame (int): The frame number where tracking started. frame_id (int): The most recent frame ID processed by the track. time_since_update (int): Frames passed since the last update. location (Tuple): The location of the object in the context of multi-camera tracking. Methods: end_frame: Returns the ID of the last frame where the object was tracked. next_id: Increments and returns the next global track ID. activate: Abstract method to activate the track. predict: Abstract method to predict the next state of the track. update: Abstract method to update the track with new data. mark_lost: Marks the track as lost. mark_removed: Marks the track as removed. reset_id: Resets the global track ID counter. Examples: Initialize a new track and mark it as lost: >>> track = BaseTrack() >>> track.mark_lost() >>> print(track.state) # Output: 2 (TrackState.Lost) rcCsRd|_d|_tj|_tƒ|_g|_d|_d|_ d|_ d|_ d|_ t jt jf|_dS)zî Initializes a new track with a unique ID and foundational tracking attributes. Examples: Initialize a new track >>> track = BaseTrack() >>> print(track.track_id) 0 rFN)Ztrack_idZ is_activatedrr ÚstaterÚhistoryÚfeaturesZ curr_featureZscoreZ start_frameÚframe_idZtime_since_updateÚnpÚinfÚlocation©ÚselfrrrÚ__init__Ds zBaseTrack.__init__cCs|jS)zEReturns the ID of the most recent frame where the object was tracked.)rrrrrÚ end_frameZszBaseTrack.end_framecCstjd7_tjS)zIIncrement and return the next unique global track ID for object tracking.r©rÚ_countrrrrÚnext_id_szBaseTrack.next_idcGst‚dS)z\Activates the track with provided arguments, initializing necessary attributes for tracking.N©ÚNotImplementedError)rÚargsrrrÚactivateeszBaseTrack.activatecCst‚dS)zSPredicts the next state of the track based on the current state and tracking model.NrrrrrÚpredictiszBaseTrack.predictcOst‚dS)zaUpdates the track with new observations and data, modifying its state and attributes accordingly.Nr)rr!ÚkwargsrrrÚupdatemszBaseTrack.updatecCs tj|_dS)zAMarks the track as lost by updating its state to TrackState.Lost.N)rr rrrrrÚ mark_lostqszBaseTrack.mark_lostcCs tj|_dS)zFMarks the track as removed by setting its state to TrackState.Removed.N)rr rrrrrÚ mark_removeduszBaseTrack.mark_removedcCs dt_dS)z7Reset the global track ID counter to its initial value.rNrrrrrÚreset_idyszBaseTrack.reset_idN)rrr r rrÚpropertyrÚ staticmethodrr"r#r%r&r'r(rrrrrs"  r)r Ú collectionsrÚnumpyrrrrrrrÚs