Step1：
新建一个YOLOMark2VOC文件夹，在文件夹下新建2个文件夹YOLOMarkFile和VOCFile
YOLOMarkFile：下面新建2个文件夹images和labels，用于放置YOLOMark标注结果
VOCFile：下面新建1个文件夹Annatations，用于接受转换后的xml文件。

Step2：
将YOLOMark标注的labels放入 YOLOMark2VOC/YOLOMarkFile/labels
将原图放入 YOLOMark2VOC/YOLOMarkFile/images

Step3：
在YOLOMark2VOC文件夹建一个YOLOMark2VOC.py文件如下

import os
import xml.etree.ElementTree as ET
from xml.dom.minidom import Document
import cv2'''
import xml
xml.dom.minidom.Document().writexml()
def writexml(self,writer: Any,indent: str = "",addindent: str = "",newl: str = "",encoding: Any = None) -> None
'''class YOLO2VOCConvert:def __init__(self, txts_path, xmls_path, imgs_path):self.txts_path = txts_path   # 标注的yolo格式标签文件路径self.xmls_path = xmls_path   # 转化为voc格式标签之后保存路径self.imgs_path = imgs_path   # 读取读片的路径各图片名字，存储到xml标签文件中self.classes = ['forklift_pallet']# 从所有的txt文件中提取出所有的类别， yolo格式的标签格式类别为数字 0,1,...# writer为True时，把提取的类别保存到'./Annotations/classes.txt'文件中def search_all_classes(self, writer=False):# 读取每一个txt标签文件，取出每个目标的标注信息all_names = set()txts = os.listdir(self.txts_path)# 使用列表生成式过滤出只有后缀名为txt的标签文件txts = [txt for txt in txts if txt.split('.')[-1] == 'txt']print(len(txts), txts)# 11 ['0002030.txt', '0002031.txt', ... '0002039.txt', '0002040.txt']for txt in txts:txt_file = os.path.join(self.txts_path, txt)with open(txt_file, 'r') as f:objects = f.readlines()for object in objects:object = object.strip().split(' ')print(object)  # ['2', '0.506667', '0.553333', '0.490667', '0.658667']all_names.add(int(object[0]))# print(objects)  # ['2 0.506667 0.553333 0.490667 0.658667\n', '0 0.496000 0.285333 0.133333 0.096000\n', '8 0.501333 0.412000 0.074667 0.237333\n']print("所有的类别标签：", all_names, "共标注数据集：%d张" % len(txts))return list(all_names)def yolo2voc(self):# 创建一个保存xml标签文件的文件夹if not os.path.exists(self.xmls_path):os.mkdir(self.xmls_path)# 把上面的两个循环改写成为一个循环：imgs = os.listdir(self.imgs_path)txts = os.listdir(self.txts_path)txts = [txt for txt in txts if not txt.split('.')[0] == "classes"]  # 过滤掉classes.txt文件print(txts)# 注意，这里保持图片的数量和标签txt文件数量相等，且要保证名字是一一对应的   (后面改进，通过判断txt文件名是否在imgs中即可)if len(imgs) == len(txts):   # 注意：./Annotation_txt 不要把classes.txt文件放进去map_imgs_txts = [(img, txt) for img, txt in zip(imgs, txts)]txts = [txt for txt in txts if txt.split('.')[-1] == 'txt']print(len(txts), txts)for img_name, txt_name in map_imgs_txts:# 读取图片的尺度信息print("读取图片：", img_name)img = cv2.imread(os.path.join(self.imgs_path, img_name))height_img, width_img, depth_img = img.shapeprint(height_img, width_img, depth_img)   # h 就是多少行（对应图片的高度）， w就是多少列（对应图片的宽度）# 获取标注文件txt中的标注信息all_objects = []txt_file = os.path.join(self.txts_path, txt_name)with open(txt_file, 'r') as f:objects = f.readlines()for object in objects:object = object.strip().split(' ')all_objects.append(object)print(object)  # ['2', '0.506667', '0.553333', '0.490667', '0.658667']# 创建xml标签文件中的标签xmlBuilder = Document()# 创建annotation标签，也是根标签annotation = xmlBuilder.createElement("annotation")# 给标签annotation添加一个子标签xmlBuilder.appendChild(annotation)# 创建子标签folderfolder = xmlBuilder.createElement("folder")# 给子标签folder中存入内容，folder标签中的内容是存放图片的文件夹，例如：JPEGImagesfolderContent = xmlBuilder.createTextNode(self.imgs_path.split('/')[-1])  # 标签内存folder.appendChild(folderContent)  # 把内容存入标签annotation.appendChild(folder)   # 把存好内容的folder标签放到 annotation根标签下# 创建子标签filenamefilename = xmlBuilder.createElement("filename")# 给子标签filename中存入内容，filename标签中的内容是图片的名字，例如：000250.jpgfilenameContent = xmlBuilder.createTextNode(txt_name.split('.')[0] + '.jpg')  # 标签内容filename.appendChild(filenameContent)annotation.appendChild(filename)# 把图片的shape存入xml标签中size = xmlBuilder.createElement("size")# 给size标签创建子标签widthwidth = xmlBuilder.createElement("width")  # size子标签widthwidthContent = xmlBuilder.createTextNode(str(width_img))width.appendChild(widthContent)size.appendChild(width)   # 把width添加为size的子标签# 给size标签创建子标签heightheight = xmlBuilder.createElement("height")  # size子标签heightheightContent = xmlBuilder.createTextNode(str(height_img))  # xml标签中存入的内容都是字符串height.appendChild(heightContent)size.appendChild(height)  # 把width添加为size的子标签# 给size标签创建子标签depthdepth = xmlBuilder.createElement("depth")  # size子标签widthdepthContent = xmlBuilder.createTextNode(str(depth_img))depth.appendChild(depthContent)size.appendChild(depth)  # 把width添加为size的子标签annotation.appendChild(size)   # 把size添加为annotation的子标签# 每一个object中存储的都是['2', '0.506667', '0.553333', '0.490667', '0.658667']一个标注目标for object_info in all_objects:# 开始创建标注目标的label信息的标签object = xmlBuilder.createElement("object")  # 创建object标签# 创建label类别标签# 创建name标签imgName = xmlBuilder.createElement("name")  # 创建name标签imgNameContent = xmlBuilder.createTextNode(self.classes[int(object_info[0])])imgName.appendChild(imgNameContent)object.appendChild(imgName)  # 把name添加为object的子标签# 创建pose标签pose = xmlBuilder.createElement("pose")poseContent = xmlBuilder.createTextNode("Unspecified")pose.appendChild(poseContent)object.appendChild(pose)  # 把pose添加为object的标签# 创建truncated标签truncated = xmlBuilder.createElement("truncated")truncatedContent = xmlBuilder.createTextNode("0")truncated.appendChild(truncatedContent)object.appendChild(truncated)# 创建difficult标签difficult = xmlBuilder.createElement("difficult")difficultContent = xmlBuilder.createTextNode("0")difficult.appendChild(difficultContent)object.appendChild(difficult)# 先转换一下坐标# (objx_center, objy_center, obj_width, obj_height)->(xmin，ymin, xmax,ymax)x_center = float(object_info[1])*width_img + 1y_center = float(object_info[2])*height_img + 1xminVal = int(x_center - 0.5*float(object_info[3])*width_img)   # object_info列表中的元素都是字符串类型yminVal = int(y_center - 0.5*float(object_info[4])*height_img)xmaxVal = int(x_center + 0.5*float(object_info[3])*width_img)ymaxVal = int(y_center + 0.5*float(object_info[4])*height_img)# 创建bndbox标签(三级标签)bndbox = xmlBuilder.createElement("bndbox")# 在bndbox标签下再创建四个子标签(xmin，ymin, xmax,ymax) 即标注物体的坐标和宽高信息# 在voc格式中，标注信息：左上角坐标（xmin, ymin） （xmax, ymax）右下角坐标# 1、创建xmin标签xmin = xmlBuilder.createElement("xmin")  # 创建xmin标签（四级标签）xminContent = xmlBuilder.createTextNode(str(xminVal))xmin.appendChild(xminContent)bndbox.appendChild(xmin)# 2、创建ymin标签ymin = xmlBuilder.createElement("ymin")  # 创建ymin标签（四级标签）yminContent = xmlBuilder.createTextNode(str(yminVal))ymin.appendChild(yminContent)bndbox.appendChild(ymin)# 3、创建xmax标签xmax = xmlBuilder.createElement("xmax")  # 创建xmax标签（四级标签）xmaxContent = xmlBuilder.createTextNode(str(xmaxVal))xmax.appendChild(xmaxContent)bndbox.appendChild(xmax)# 4、创建ymax标签ymax = xmlBuilder.createElement("ymax")  # 创建ymax标签（四级标签）ymaxContent = xmlBuilder.createTextNode(str(ymaxVal))ymax.appendChild(ymaxContent)bndbox.appendChild(ymax)object.appendChild(bndbox)annotation.appendChild(object)  # 把object添加为annotation的子标签f = open(os.path.join(self.xmls_path, txt_name.split('.')[0]+'.xml'), 'w')xmlBuilder.writexml(f, indent='\t', newl='\n', addindent='\t', encoding='utf-8')f.close()if __name__ == '__main__':# 把yolo的txt标签文件转化为voc格式的xml标签文件# yolo格式txt标签文件相对路径txts_path1 = './YOLOMarkFile/labels'# 转化为voc格式xml标签文件存储的相对路径xmls_path1 = './VOCFile/Annotations'# 存放图片的相对路径imgs_path1 = './YOLOMarkFile/images'yolo2voc_obj1 = YOLO2VOCConvert(txts_path1, xmls_path1, imgs_path1)labels = yolo2voc_obj1.search_all_classes()print('labels: ', labels)yolo2voc_obj1.yolo2voc()

Step4:
cd到目录，执行py文件

cd MyModels/A_TransformFormat/YOLOMark2VOC
python3 YOLOMark2VOC.py

运行结果如下：