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roboflow--supervision/examples/tracking/ultralytics_example.py
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chore: import upstream snapshot with attribution
2026-07-13 12:06:10 +08:00

56 lines
1.8 KiB
Python

from tqdm import tqdm
from ultralytics import YOLO
import supervision as sv
def main(
source_weights_path: str,
source_video_path: str,
target_video_path: str,
confidence_threshold: float = 0.3,
iou_threshold: float = 0.7,
) -> None:
"""
Video Processing with YOLO and ByteTrack.
Args:
source_weights_path: Path to the source weights file
source_video_path: Path to the source video file
target_video_path: Path to the target video file (output)
confidence_threshold: Confidence threshold for the model
iou_threshold: IOU threshold for the model
"""
model = YOLO(source_weights_path)
tracker = sv.ByteTrack()
box_annotator = sv.BoxAnnotator()
label_annotator = sv.LabelAnnotator()
frame_generator = sv.get_video_frames_generator(source_path=source_video_path)
video_info = sv.VideoInfo.from_video_path(video_path=source_video_path)
with sv.VideoSink(target_path=target_video_path, video_info=video_info) as sink:
for frame in tqdm(frame_generator, total=video_info.total_frames):
results = model(
frame, verbose=False, conf=confidence_threshold, iou=iou_threshold
)[0]
detections = sv.Detections.from_ultralytics(results)
detections = tracker.update_with_detections(detections)
annotated_frame = box_annotator.annotate(
scene=frame.copy(), detections=detections
)
annotated_labeled_frame = label_annotator.annotate(
scene=annotated_frame, detections=detections
)
sink.write_frame(frame=annotated_labeled_frame)
if __name__ == "__main__":
from jsonargparse import auto_cli, set_parsing_settings
set_parsing_settings(parse_optionals_as_positionals=True)
auto_cli(main, as_positional=False)