根据log绘制loss、accuracy的变化图

1、caffe train --solver=solver.prototxt 2>&1 | tee mylog.log

2、caffe_root/tools/extra/parse_log.py mylog.log ./

3、python脚本：

import pandas as pdimport numpy as npimport matplotlib.pyplot as plttrain_log = pd.read_csv("mylog.txt.train")test_log = pd.read_csv("mylog.txt.test")test_log["loss"][0] = test_log["loss"][1]_, ax1 = plt.subplots(figsize=(15, 10))#ax1 = ax[0]ax2 = ax1.twinx()ax1.plot(train_log["NumIters"], train_log["loss"], alpha=0.4)ax1.plot(test_log["NumIters"], test_log["loss"], 'g')ax2.plot(test_log["NumIters"], test_log["accuracy"], 'r')ax2.plot(train_log["NumIters"], test_log["LearningRate"] * 10, 'b')ax1.set_xlabel('iteration')ax1.set_ylabel('train loss')ax2.set_ylabel('test accuracy')plt.show()