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Ruff format docstring Python code (#15792)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-08-25 01:08:07 +08:00 • committed by GitHub
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ultralytics/trackers/utils/matching.py
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@ -121,7 +121,7 @@ def embedding_distance(tracks: list, detections: list, metric: str = "cosine") -
Compute the embedding distance between tracks and detections using cosine metric
>>> tracks = [STrack(...), STrack(...)] # List of track objects with embedding features
>>> detections = [BaseTrack(...), BaseTrack(...)] # List of detection objects with embedding features
>>> cost_matrix = embedding_distance(tracks, detections, metric='cosine')
>>> cost_matrix = embedding_distance(tracks, detections, metric="cosine")
"""
cost_matrix = np.zeros((len(tracks), len(detections)), dtype=np.float32)