src/tools/detection_model.py

from ultralytics import YOLO

detection_model_id = "yolo11n.pt"
detection_model = YOLO(detection_model_id)
def run_detection(image_path: str, is_visualize: bool = False):
    """YOLOv11: return list of {box, label, score} for a single image."""
    results = detection_model(image_path)  
    r = results[0] 

    detections = []
    for box in r.boxes:
        # box.xyxy is a 1×4 tensor, box.conf is a 1-element tensor, box.cls likewise
        coords  = box.xyxy.cpu().numpy().flatten().tolist()
        score   = float(box.conf.cpu().numpy().item())
        cls_id  = int(box.cls.cpu().numpy().item())
        detections.append({
            "box": coords,
            "label": r.names[cls_id],
            "score": score,
        })

    if is_visualize:
        r.save()
        r.show()    

    return {"detections": detections}