Emani K.
Atkins.

def best_ppe_match(detections, expected_region, person_box, threshold):
    """Match a PPE detection to the region expected from a person's pose."""
    if expected_region is None or person_box is None:
        return None

    best, best_score = None, 0.0
    for d in detections:
        box = d.get("box")
        if box is None or not center_in_box(box, person_box):
            continue  # PPE must belong to this Roboflow-detected person

        iou = intersection_over_union(box, expected_region)
        containment = intersection_over_detection(box, expected_region)
        score = max(iou, containment)

        # A detection centered in the expected region counts even when
        # the box sizes differ enough to produce a low IoU
        if center_in_box(box, expected_region):
            score = max(score, threshold)

        if score >= threshold and score > best_score:
            best, best_score = {**d, "match_score": round(float(score), 4)}, score
    return best