🧹 more cleanup - remove unused code

supervision/tracker/byte_tracker/core.py

@@ -3,7 +3,6 @@ from typing import List, Tuple
 import numpy as np
 
 from supervision import Detections
-from supervision.detection.utils import box_iou_batch
 from supervision.tracker.byte_tracker import matching
 from supervision.tracker.byte_tracker.basetrack import BaseTrack, TrackState
 from supervision.tracker.byte_tracker.kalman_filter import KalmanFilter
@@ -164,41 +163,6 @@ def detections2boxes(detections: Detections) -> np.ndarray:
     )
 
 
-# converts List[strack] into format that can be consumed by match_detections_with_tracks function
-def tracks2boxes(tracks: List[STrack]) -> np.ndarray:
-    return np.array([track.tlbr for track in tracks], dtype=float)
-
-
-# matches our bounding boxes with predictions
-def match_detections_with_tracks(
-    detections: Detections, tracks: List[STrack]
-) -> Detections:
-    """
-    Match bounding boxes from detections with existing strack objects.
-
-    Parameters:
-        detections (Detections): An object representing the detected bounding boxes.
-        tracks (List[strack]): A list of strack objects to match with the detections.
-
-    Returns:
-        Detections: An object representing the matched tracker IDs for the detections.
-    """
-    if not np.any(detections.xyxy) or len(tracks) == 0:
-        return np.empty((0,))
-
-    tracks_boxes = tracks2boxes(tracks=tracks)
-    iou = box_iou_batch(tracks_boxes, detections.xyxy)
-    track2detection = np.argmax(iou, axis=1)
-
-    tracker_ids = [None] * len(detections)
-
-    for tracker_index, detection_index in enumerate(track2detection):
-        if iou[tracker_index, detection_index] != 0:
-            tracker_ids[detection_index] = tracks[tracker_index].track_id
-
-    return tracker_ids
-
-
 class ByteTrack:
     """
     Initialize the ByteTrack object.
@@ -254,7 +218,7 @@ class ByteTrack:
 
         return detections
 
-    def update_with_numpy(self, output_results) -> List[STrack]:
+    def update_with_numpy(self, output_results: np.ndarray) -> List[STrack]:
         """
         Update a matched strack. It uses the numpy results.