darknet/scripts/log_parser/log_parser.py

114 lines
3.4 KiB
Python

# -*- coding: utf-8 -*-
# @Time : 2018/4/25 20:28
# @Author : Adesun
# @Site : https://github.com/Adesun
# @File : log_parser.py
import argparse
import logging
import os
import platform
import re
import sys
# set non-interactive backend default when os is not windows
if sys.platform != 'win32':
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
def get_file_name_and_ext(filename):
(file_path, temp_filename) = os.path.split(filename)
(file_name, file_ext) = os.path.splitext(temp_filename)
return file_name, file_ext
def show_message(message, stop=False):
print(message)
if stop:
sys.exit(0)
def parse_args():
parser = argparse.ArgumentParser(description="training log parser by DeepKeeper ")
parser.add_argument('--source-dir', dest='source_dir', type=str, default='./',
help='the log source directory')
parser.add_argument('--save-dir', dest='save_dir', type=str, default='./',
help='the directory to be saved')
parser.add_argument('--csv-file', dest='csv_file', type=str, default="",
help='training log file')
parser.add_argument('--log-file', dest='log_file', type=str, default="",
help='training log file')
parser.add_argument('--show', dest='show_plot', type=bool, default=False,
help='whether to show')
return parser.parse_args()
def log_parser(args):
if not args.log_file:
show_message('log file must be specified.', True)
log_path = os.path.join(args.source_dir, args.log_file)
if not os.path.exists(log_path):
show_message('log file does not exist.', True)
file_name, _ = get_file_name_and_ext(log_path)
log_content = open(log_path).read()
iterations = []
losses = []
fig, ax = plt.subplots()
# set area we focus on
ax.set_ylim(0, 8)
major_locator = MultipleLocator()
minor_locator = MultipleLocator(0.5)
ax.yaxis.set_major_locator(major_locator)
ax.yaxis.set_minor_locator(minor_locator)
ax.yaxis.grid(True, which='minor')
pattern = re.compile(r"([\d].*): .*?, (.*?) avg")
# print(pattern.findall(log_content))
matches = pattern.findall(log_content)
# print(type(matches[0]))
counter = 0
log_count = len(matches)
if args.csv_file != '':
csv_path = os.path.join(args.save_dir, args.csv_file)
out_file = open(csv_path, 'w')
else:
csv_path = os.path.join(args.save_dir, file_name + '.csv')
out_file = open(csv_path, 'w')
for match in matches:
counter += 1
if log_count > 200:
if counter % 200 == 0:
print('parsing {}/{}'.format(counter, log_count))
else:
print('parsing {}/{}'.format(counter, log_count))
iteration, loss = match
iterations.append(int(iteration))
losses.append(float(loss))
out_file.write(iteration + ',' + loss + '\n')
ax.plot(iterations, losses)
plt.xlabel('Iteration')
plt.ylabel('Loss')
plt.tight_layout()
# saved as svg
save_path = os.path.join(args.save_dir, file_name + '.svg')
plt.savefig(save_path, dpi=300, format="svg")
if args.show_plot:
plt.show()
if __name__ == "__main__":
args = parse_args()
log_parser(args)