Converts XML tags to TXT format (voc conversion for yolo convenient training)

将xml标签转换为txt（voc格式转换为yolo方便进行训练）

一、前言

After retrieving someone else's,It doesn't feel as good as mine,Contribute your own code

二、程序

import xml.etree.ElementTree as ET


import os
from os import listdir, getcwd

classes = ["bed", "water horse bucket"] # Change your label

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_annotation(image_name,labelPath):
   # in_file = open(os.path.join(labelPath,image_name[:-3] + 'xml')) # xml文件路径


    out_file = open(os.path.join(labelPath+'TXT',image_name[:-3] + 'txt'), 'w')  # 转换后的txt文件存放路径

    in_file = open(os.path.join(labelPath,image_name[:-3] + 'xml'))  # xml文件路径
    xml_text = in_file.read()
    root = ET.fromstring(xml_text)
    in_file.close()
    size = root.find('size')
    w = int(size.find('width').text)
    h = int(size.find('height').text)
   # print(root.iter('object'))
    for obj in root.iter('object'):
        cls = obj.find('name').text
        if cls not in classes:
            print(cls)
            continue
        cls_id = classes.index(cls)
        xmlbox = obj.find('bndbox')
        b = (float(xmlbox.find('xmin').text), float(xmlbox.find('xmax').text), float(xmlbox.find('ymin').text),
             float(xmlbox.find('ymax').text))
        bb = convert((w, h), b)
        #print(bb)
        out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')


wd = getcwd()

if __name__ == '__main__':
    imgNmae=input('Enter the absolute address of the image folder：')
    labelPath=input('输入xmlThe absolute address of the marked folder：')
    #imgNmae='E:\数据集\新建文件夹//bed//bed\data\img'
    #labelPath='E:\数据集\新建文件夹//bed/bed\data\labels'
    if not os.path.isdir(labelPath+'TXT'):
        os.mkdir(labelPath+'TXT')
    for image_path in os.listdir(imgNmae):  # 每一张图片都对应一个xml文件这里写xml对应的图片的路径
        #image_name = image_path.split('\\')[-1]
        print(image_path)
        convert_annotation(image_path,labelPath)

三、Run through the demo

1、修改classesfor your datasetclasses

2、运行：Enter the absolute address of the image and annotation folder

四、结果如下：