cnn_tensorflow.py 文件源码

def evaluate(graph, mels, label, mapping):
    """ Check correctness of a file classification """
    logging.info('Evaluating audio classification')
    audio_feature = np.asanyarray(list(mels.flatten()), dtype=np.float32)

    true_result = mapping[label]

    x = graph.get_tensor_by_name('prefix/input:0')
    y = graph.get_tensor_by_name('prefix/softmax_tensor:0')

    with tf.Session(graph=graph) as sess:
        # Note: we didn't initialize/restore anything, everything is stored in the graph_def
        y_out = sess.run(y, feed_dict={
            x: [audio_feature]
        })

        logging.info('true value:' + str(true_result))
        logging.info('predicted value:' + str(y_out[0].argmax()))
        logging.info('predictions:' + str(y_out))
        if y_out[0].argmax() == true_result:
            return True
        else:
            return False