yolo模型(四)绘制PR曲线所用到的reval_voc_py.py代码

在绘制PR曲线时要自己生成一个pkl文件，需要reval_voc_py.py代码来生。现贴出基于python2和python3的代码，按照自己的python版本直接复制即可。拿走不谢~

reval_voc_py.py

#!/usr/bin/env python

# Adapt from ->
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
# <- Written by Yaping Sun

"""Reval = re-eval. Re-evaluate saved detections."""

import os, sys, argparse
import numpy as np
import cPickle

from voc_eval import voc_eval

def parse_args():
    """
    Parse input arguments
    """
    parser = argparse.ArgumentParser(description='Re-evaluate results')
    parser.add_argument('output_dir', nargs=1, help='results directory',
                        type=str)
    parser.add_argument('--voc_dir', dest='voc_dir', default='data/VOCdevkit', type=str)
    parser.add_argument('--year', dest='year', default='2017', type=str)
    parser.add_argument('--image_set', dest='image_set', default='test', type=str)
    parser.add_argument('--classes', dest='class_file', default='data/voc.names', type=str)

    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)

    args = parser.parse_args()
    return args

def get_voc_results_file_template(image_set, out_dir = 'results'):
    filename = 'comp4_det_' + image_