再voc.data中有valid的文件路径 

./darknet detector valid cfg/voc-mask.data cfg/yolov4-mask-test.cfg backup/yolov4-mask_final.weights

会在results中生成 .txt文件

python reval_voc.py --voc_dir VOCdevkit --year 2007 --image_set test --classes data/voc-mask.names testmask

会生成pkl文件 

import pickle as cPickle
import matplotlib.pyplot as plt

fr1= open('/home/xxp/darknet/testmask/v3mask_pr.pkl', 'rb')  # 这里open中第一个参数需要修改成自己生产的pkl文件
inf1 = cPickle.load(fr1)     #使用 load() 方法将该文件中的数据反序列化后输出：
fr1.close()

x1= inf1['rec']
y1= inf1['prec']



fr2= open('/home/xxp/darknet/testmask/v4mask_pr.pkl', 'rb')  # 这里open中第一个参数需要修改成自己生产的pkl文件
inf2 = cPickle.load(fr2)
fr2.close()

x2= inf2['rec']
y2= inf2['prec']


fr3= open('/home/xxp/darknet/testmask/v3-3mask_pr.pkl', 'rb')  # 这里open中第一个参数需要修改成自己生产的pkl文件
inf3 = cPickle.load(fr3)
fr3.close()

x3= inf3['rec']
y3= inf3['prec']

plt.figure()
plt.xlabel('recall')
plt.ylabel('precision')
plt.title('PR cruve')
plt.plot(x1, y1, color="red")
plt.plot(x2, y2, color="blue")
plt.plot(x3, y3, color="green")
plt.show()

print('AP：', inf['ap'])

./darknet detector recall ./cfg/voc-mask.data ./cfg/yolov3-tiny-mask5-test.cfg ./backup/yolov3-tiny-mask5_best.weights

./darknet detector map ./cfg/voc-mask.data ./cfg/yolov3-tiny-mask5-test.cfg ./backup/yolov3-tiny-mask5_best.weights