在python中将labelme格式改成yolo格式的代码

在Python中，将LabelMe标注数据转换成YOLO所需的格式通常需要编写一些脚本或者利用特定的工具库，例如`xmltodict`用于解析XML标签标记文件，`pandas`处理数据结构，然后手动创建YOLO所需的txt文件。以下是一个简化的示例，假设你已经有一个LabelMe XML文件：

import xml.etree.ElementTree as ET
import pandas as pd

# 解析XML文件
def parse_xml(xml_path):
    tree = ET.parse(xml_path)
    root = tree.getroot()
    objects = []

    for obj in root.findall('object'):
        label = obj.find('name').text
        bbox = [int(float(x)) for x in obj.find('bndbox').attrib.values()]
        objects.append([label] + bbox)

    return objects

# 将数据转换成DataFrame
def convert_to_df(objects):
    df = pd.DataFrame(objects, columns=['class', 'xmin', 'ymin', 'xmax', 'ymax'])
    return df

# 转换并保存到YOLO格式
def save_yolo_format(df, output_path):
    df[['x', 'y']] = df[['xmin', 'ymin']].apply(lambda row: (row[0]/df['width'], row[1]/df['height']), axis=1)
    df[['w', 'h']] = df[['xmax', 'ymax']].apply(lambda row: (row[0]-row[1], row[3]-row[2]), axis=1)
    df[['x', 'y', 'w', 'h']] = df[['x', 'y', 'w', 'h']].astype(int)
    df.drop(['xmin', 'ymin', 'xmax', 'ymax'], axis=1, inplace=True)
    df.to_csv(output_path, header=False, index=False)

# 示例用法
xml_file = "your_labelme.xml"
output_txt = "your_output.txt"

objects = parse_xml(xml_file)
df = convert_to_df(objects)
save_yolo_format(df, output_txt)