segnet_model.py 文件源码

def __softmax_crossentropy(self, scores, targets):
        scores_exp = tf.exp(scores)
        scores_sum = tf.maximum(tf.reduce_sum(scores_exp, axis=3), 1e-10)
        scores_sum = tf.expand_dims(scores_sum, axis=-1)
        scores_normalized = tf.truediv(scores_exp, scores_sum, name="scores_normalized")
        scores_normalized = tf.maximum(scores_normalized, 1e-10)

        cross_entropy = tf.reduce_mean(-tf.reduce_sum(targets * tf.log(scores_normalized), reduction_indices=[3]))
        return cross_entropy