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 pd
import numpy as np
import matplotlib.pyplot as plt

train_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()