def __init__(self, mean=None, std=None, *args, **kwargs):
        """ Initializer for the RegressBoxes layer.

        Args
            mean: The mean value of the regression values which was used for normalization.
            std: The standard value of the regression values which was used for normalization.
        """
        if mean is None:
            mean = np.array([0, 0, 0, 0])
        if std is None:
            std = np.array([0.2, 0.2, 0.2, 0.2])

        if isinstance(mean, (list, tuple)):
            mean = np.array(mean)
        elif not isinstance(mean, np.ndarray):
            raise ValueError('Expected mean to be a np.ndarray, list or tuple. Received: {}'.format(type(mean)))

        if isinstance(std, (list, tuple)):
            std = np.array(std)
        elif not isinstance(std, np.ndarray):
            raise ValueError('Expected std to be a np.ndarray, list or tuple. Received: {}'.format(type(std)))

        self.mean = mean
        self.std  = std
        super(RegressBoxes, self).__init__(*args, **kwargs)
 Initializer for the RegressBoxes layer.

        Args
            mean: The mean value of the regression values which was used for normalization.
            std: The standard value of the regression values which was used for normalization.
        
keras_retinanet/layers/_misc.py