xml_yolo.py
将annotation和img的文件自动转换成yolov5数据集格式的labels,并且自动划分为train和val,目前发现的最好用的,上传到这里方便自己以后下载。转载于https://blog.csdn.net/didiaopao/article/details/120022845
将annotation和img的文件自动转换成yolov5数据集格式的labels,并且自动划分为train和val,目前发现的最好用的,上传到这里方便自己以后下载。转载于https://blog.csdn.net/didiaopao/article/details/120022845
将labelimg标注好的xml和原图片划分为yolov5格式的数据集。首先创建一个文件夹paper_data下面三个子文件夹1.images 2.Annotations 3. ImageSets/Main三个文件夹,这两个程序放在paper_data里面和其他三个子文件夹同一级。转载于https://blog.csdn.net/qq_36756866/article/details/109111065?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522163583584216780264054953%2522%252C%2522scm%2522%253A%252220140713.130102334..%2522%257D&request_id=163583584216780264054953&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~top_positive~default-2-109111065.pc_search_result_control_group&utm_term=yolov5%E8%AE%AD%E7%BB%83%E8%87%AA%E5%B7%B1%E7%9A%84%E6%95%B0%E6%8D%AE%E9%9B%86&spm=1018.2226.3001.4187。上传这里方便自己以后查找使用
转载于https://blog.csdn.net/qq_42911028/article/details/120027337?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522163581882716780357246029%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=163581882716780357246029&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~first_rank_ecpm_v1~rank_v31_ecpm-4-120027337.pc_search_result_control_group&utm_term=yolov%E5%B0%86%E6%95%B0%E6%8D%AE%E9%9B%86%E4%B8%BA%E5%88%92%E5%88%86%E8%AE%AD%E7%BB%83%E9%9B%86%E5%92%8C%E9%AA%8C%E8%AF%81%E9%9B%86&spm=1018.2226.3001.4187。将转换好的txt标注文件和jpg图片自动按照比例划分成为数据集。使用前需要先修改好python代码的地址,然后创建好train、val、test三个文件夹,每个文件夹下都包含了images和labels。按照文件要求创建好文件夹运行即可。上传到这里方便自己以后下载
转载于https://blog.csdn.net/BruceBorgia/article/details/118805278?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522163581600516780261931218%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=163581600516780261931218&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~first_rank_ecpm_v1~rank_v31_ecpm-1-118805278.pc_search_result_control_group&utm_term=labelimg%E6%A0%87%E6%B3%A8%E7%9A%84%E5%9B%BE%E7%89%87%E8%BD%AC%E6%8D%A2%E6%88%90yolov5&spm=1018.2226.3001.4187。使用前需要创Annotations和labels文件夹和该python文件放在一块,Annotations保存labelimg标注好的xml文件,使用后labels文件夹内会生成对应的yolov5所需的txt文件,也要记得修改classes改成自己的瑕疵类别。上传到这里方便自己以后下载
转载于https://blog.csdn.net/sxfd91307/article/details/94980559?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522162737166216780366525358%2522%252C%2522scm%2522%253A%252220140713.130102334..%2522%257D&request_id=162737166216780366525358&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~baidu_landing_v2~default-1-94980559.pc_search_result_before_js&utm_term=%E5%B0%86voc%E6%95%B0%E6%8D%AE%E9%9B%86%E8%BD%AC%E6%8D%A2%E6%88%90yolo&spm=1018.2226.3001.4187,方便自己以后查找使用