Fi?VddlmZddlZddlZddlmZmZmZddl m Z GddeZ y))AnyN) BaseSolutionSolutionAnnotatorSolutionResults)colorscPeZdZdZdeddffd ZdejdefdZ xZ S) TrackZoneaA class to manage region-based object tracking in a video stream. This class extends the BaseSolution class and provides functionality for tracking objects within a specific region defined by a polygonal area. Objects outside the region are excluded from tracking. Attributes: region (np.ndarray): The polygonal region for tracking, represented as a convex hull of points. line_width (int): Width of the lines used for drawing bounding boxes and region boundaries. names (list[str]): List of class names that the model can detect. boxes (list[np.ndarray]): Bounding boxes of tracked objects. track_ids (list[int]): Unique identifiers for each tracked object. clss (list[int]): Class indices of tracked objects. Methods: process: Process each frame of the video, applying region-based tracking. extract_tracks: Extract tracking information from the input frame. display_output: Display the processed output. Examples: >>> tracker = TrackZone() >>> frame = cv2.imread("frame.jpg") >>> results = tracker.process(frame) >>> cv2.imshow("Tracked Frame", results.plot_im) kwargsreturnNc t|di|gd}tjt j |j xs|tj|_d|_y)zInitialize the TrackZone class for tracking objects within a defined region in video streams. Args: **kwargs (Any): Additional keyword arguments passed to the parent class. ))Kr )5r )r)r r)dtypeN) super__init__cv2 convexHullnparrayregionint32mask)selfr default_region __class__s a/var/www/pod-logistic/pod-ai/venv/lib/python3.12/site-packages/ultralytics/solutions/trackzone.pyrzTrackZone.__init__&sL "6"EnnRXXdkk.K^SUS[S[%\]  im0c t||j}|jPtj|dddddf|_t j |j|jgdt j|||j}|j|t j||jgdd|jdz t|j|j|j|jD]7\}}}}|j!||j#||| t%|d 9|j'}|j)|t+|t-|j S) aProcess the input frame to track objects within a defined region. This method initializes the annotator, creates a mask for the specified region, extracts tracks only from the masked area, and updates tracking information. Objects outside the region are ignored. Args: im0 (np.ndarray): The input image or frame to be processed. Returns: (SolutionResults): Contains processed image `plot_im` and `total_tracks` (int) representing the total number of tracked objects within the defined region. Examples: >>> tracker = TrackZone() >>> frame = cv2.imread("path/to/image.jpg") >>> results = tracker.process(frame) ) line_widthNr)rT)r#r#r#)isClosedcolor thickness)track_id)labelr&)plot_im total_tracks)rr"rr zeros_likerfillPolyr bitwise_andextract_tracks polylineszipboxes track_idsclssconfs box_labeladjust_box_labelrresultdisplay_outputrlen) rr annotator masked_frameboxr(clsconfr*s rprocesszTrackZone.process1sC$&cdooF 99  c!Q'l3DI LLT[[M3 7sCdii@  L) cDKK=4Z^ZiZilmZmn),DJJ SWS]S](^  $C3   400dX0NV\]egkVl    ""$ G$wS=PQQr) __name__ __module__ __qualname____doc__rrrndarrayrr@ __classcell__)rs@rr r s52   'R2::'R/'Rrr ) typingrrnumpyrultralytics.solutions.solutionsrrrultralytics.utils.plottingrr rrrrKs) \\-LR LRr