数据集的标签格式为xml格式，转为yolo的训练格式：

1.创建一个格式转化的.py文件将下面代码复制：

import os
import glob
import xml.etree.ElementTree as ET
 
 
def get_classes(classes_path):
    with open(classes_path, encoding='utf-8') as f:
        class_names = f.readlines()
    class_names = [c.strip() for c in class_names]
    print("Classes loaded:", class_names)
    return class_names, len(class_names)
 
 
def convert(size, box):
    dw = 1.0 / size[0]
    dh = 1.0 / size[1]
    x = (box[0] + box[1]) / 2.0
    y = (box[2] + box[3]) / 2.0
    w = box[1] - box[0]
    h = box[3] - box[2]
    x = x * dw
    w = w * dw
    y = y * dh
    h = h * dh
    return (x, y, w, h)
 
 
def convert_xml_to_yolo(xml_root_path, txt_save_path, classes_path):
    print("XML root path:", xml_root_path)
    print("TXT save path:", txt_save_path)
    print("Classes path:", classes_path)
 
    if not os.path.exists(txt_save_path):
        os.makedirs(txt_save_path)
    print("Directory created:", txt_save_path)
 
    xml_paths = glob.glob(os.path.join(xml_root_path, '*.xml'))
    print("XML files found:", xml_paths)
 
    classes, _ = get_classes(classes_path)
 
    for xml_id in xml_paths:
        print("Processing file:", xml_id)
        txt_id = os.path.join(txt_save_path, os.path.basename(xml_id)[:-4] + '.txt')
        txt = open(txt_id, 'w')
        xml = open(xml_id, encoding='utf-8')
        tree = ET.parse(xml)
        root = tree.getroot()
        size = root.find('size')
        w = int(size.find('width').text)
        h = int(size.find('height').text)
        for obj in root.iter('object'):
            difficult = 0
            if obj.find('difficult') is not None:
                difficult = obj.find('difficult').text
            cls = obj.find('name').text
            print("Class found:", cls)
            if cls not in classes or int(difficult) == 1:
                continue
            cls_id = classes.index(cls)
            xmlbox = obj.find('bndbox')
            b = (int(float(xmlbox.find('xmin').text)), int(float(xmlbox.find('xmax').text)),
                 int(float(xmlbox.find('ymin').text)), int(float(xmlbox.find('ymax').text)))
            box = convert((w, h), b)
            txt.write(str(cls_id) + ' ' + ' '.join([str(a) for a in box]) + '\n')
        txt.close()
        print("TXT file created:", txt_id)
if __name__ == '__main__':
    # 用户输入XML文件路径和TXT文件存放路径
    xml_root_path = r"D:\CVproject\ultralytics-main\datatrans\labels"
    txt_save_path = r"D:\CVproject\ultralytics-main\datatrans\txt"
    classes_path = r"D:\CVproject\ultralytics-main\datatrans\labels.txt"
    convert_xml_to_yolo(xml_root_path, txt_save_path, classes_path)

2.使用方法

xml_root_path里边复制你的xml文件夹的绝对路径

txt_save_path里边复制你转换后的标签的存放地址

classes_path里边复制你的数据集类别的说明文件的存放地址（第三步细讲）
xml_root_path = r"D:\CVproject\ultralytics-main\datatrans\Annotations"
txt_save_path = r"D:\CVproject\ultralytics-main\datatrans\txt1"
classes_path = r"D:\CVproject\ultralytics-main\datatrans\labels.txt"

3.labels.txt

这个文件需要你自己创建一个txt文件，名字要用这个labels别换，里边的内容放你的数据集的标签，一个类别一行，注意大小写，不要有多余的标点符号

如果你的标签里类别的首字母大小写不一，那就回出错，处理方法请看我的另外一篇博客！！！！