PASCAL VOC数据集训练集、验证集、测试集的划分和提取

Love The Way You Lie 2023-02-22 07:59 1阅读 0赞

### 1、训练集、验证集、测试集按比例精确划分 ###

#数据集划分
    import os
    import random
     
    root_dir='./park_voc/VOC2007/'
     
    ## 0.7train 0.1val 0.2test
    trainval_percent = 0.8
    train_percent = 0.7
    xmlfilepath = root_dir+'Annotations'
    txtsavepath = root_dir+'ImageSets/Main'
    total_xml = os.listdir(xmlfilepath)
     
    num = len(total_xml)  # 100
    list = range(num)
    tv = int(num*trainval_percent)  # 80
    tr = int(tv*train_percent)  # 80*0.7=56
    trainval = random.sample(list, tv)
    train = random.sample(trainval, tr)
     
    ftrainval = open(root_dir+'ImageSets/Main/trainval.txt', 'w')
    ftest = open(root_dir+'ImageSets/Main/test.txt', 'w')
    ftrain = open(root_dir+'ImageSets/Main/train.txt', 'w')
    fval = open(root_dir+'ImageSets/Main/val.txt', 'w')
     
    for i in list:
        name = total_xml[i][:-4]+'\n'
        if i in trainval:
            ftrainval.write(name)
            if i in train:
                ftrain.write(name)
            else:
                fval.write(name)
        else:
            ftest.write(name)
     
    ftrainval.close()
    ftrain.close()
    fval.close()
    ftest .close()

### 2、训练集、验证集和测试集提取(只给出trian文件的提取方法) ###

# -*- coding:UTF-8 -*-
    import shutil
     
    f_txt = open('D:\dataset\VOCdevkit\split\VOC2007\ImageSets\Main\\trainval.txt', 'r')
    f_train = 'D:\dataset\VOCdevkit\VOC2007\\train'
     
    context = list(f_txt)
    for imagename in context:
        imagename = imagename[0:6]
        imagename = imagename + '.jpg'
        imagepath = 'D:\dataset\VOCdevkit\VOC2007\JPEGImages\\'+ imagename
        shutil.copy(imagepath,f_train)
        # 删除训练集和验证集，剩余图片为测试集
        # os.remove(imagepath)
     
    #处理Annotations同理只需将.jpg改为.xml

参考：[https://www.cnblogs.com/sdu20112013/p/10801383.html][https_www.cnblogs.com_sdu20112013_p_10801383.html]

[https_www.cnblogs.com_sdu20112013_p_10801383.html]: https://www.cnblogs.com/sdu20112013/p/10801383.html