def _distance_acc(distances, thr=0.5):
    """Return the percentage below the distance threshold, while ignoring
    distances values with -1.

    Note:
        batch_size: N
    Args:
        distances (np.ndarray[N, ]): The normalized distances.
        thr (float): Threshold of the distances.

    Returns:
        float: Percentage of distances below the threshold. \
            If all target keypoints are missing, return -1.
    """
    distance_valid = distances != -1
    num_distance_valid = distance_valid.sum()
    if num_distance_valid > 0:
        return (distances[distance_valid] < thr).sum() / num_distance_valid
    return -1
Return the percentage below the distance threshold, while ignoring
    distances values with -1.

    Note:
        batch_size: N
    Args:
        distances (np.ndarray[N, ]): The normalized distances.
        thr (float): Threshold of the distances.

    Returns:
        float: Percentage of distances below the threshold.             If all target keypoints are missing, return -1.
    
ppdet/modeling/keypoint_utils.py