ssd_training.py 文件源码

def _l1_smooth_loss(self, y_true, y_pred):
        """Compute L1-smooth loss.

        # Arguments
            y_true: Ground truth bounding boxes,
                tensor of shape (?, num_boxes, 4).
            y_pred: Predicted bounding boxes,
                tensor of shape (?, num_boxes, 4).

        # Returns
            l1_loss: L1-smooth loss, tensor of shape (?, num_boxes).

        # References
            https://arxiv.org/abs/1504.08083
        """
        abs_loss = tf.abs(y_true - y_pred)
        sq_loss = 0.5 * (y_true - y_pred)**2
        l1_loss = tf.where(tf.less(abs_loss, 1.0), sq_loss, abs_loss - 0.5)
        return tf.reduce_sum(l1_loss, -1)