labelimg标注的yolo格式和VOC格式数据进行互换

素颜马尾好姑娘i 2022-10-17 13:44 269阅读 0赞

### 文章目录 ###

*  数据格式介绍
 *   *  1.VOC数据格式
     *  2.yolo数据格式
 *  yolo格式转化为VOC格式代码
 *  VOC格式转化为YOLO格式

--------------------

# 数据格式介绍 #

## 1.VOC数据格式 ##

VOC数据格式，会直接把每张图片标注的标签信息保存到一个*XML文件*中。

xml中的关键信息说明：

*  图片名字
 *  每个目标的标定框坐标：即左上角的坐标和右下角的坐标
 *  xmin ymin xmax ymax

## 2.yolo数据格式 ##

YOLO数据格式，会直接把每张图片标注的标签信息保存到一个txt文件中。

0 0.521000 0.235075 0.362000 0.450249
    0 0.213000 0.645522 0.418000 0.519900
    0 0.794000 0.665423 0.376000 0.470149

txt中信息说明：

*  每一行代表标注的一个目标
 *  第一个数代表标注目标的标签
 *  后面的四个数代表标注框的中心坐标和标注框的相对宽和高（进行归一化）
 *  五个数据从左到右以此为：class\_index,x\_center,y\_center,W,h.(后四个数据都是归一化的）。

# yolo格式转化为VOC格式代码 #

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   # 读取读片的路径个图片名字，存储到xml标签文件中
            self.classes = ["shirt", "non_shirt", "western_style_clothes", "coat", "down_filled_coat",
                            "cotton", "sweater", "silk_scarf", "tie", "bow_tie"]
    
        # 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))
    
            # 把从xmls标签文件中提取的类别写入到'./Annotations/classes.txt'文件中
            # if writer:
            #     with open('./Annotations/classes.txt', 'w') as f:
            #         for label in all_names:
            #             f.write(label + '\n')
    
            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)
    
            # # 读取每张图片，获取图片的尺寸信息（shape）
            # imgs = os.listdir(self.imgs_path)
            # for img_name in imgs:
            #     img = cv2.imread(os.path.join(self.imgs_path, img_name))
            #     height, width, depth = img.shape
            #     # print(height, width, depth)   # 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）
            #
            # # 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_name in txts:
            #     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(' ')
            #             print(object)  # ['2', '0.506667', '0.553333', '0.490667', '0.658667']
    
            # 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.shape
                    print(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folder
                    folder = 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：JPEGImages
                    folderContent = 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filename
                    filename = 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.jpg
                    filenameContent = 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width
                    width = xmlBuilder.createElement("width")  # size子标签width
                    widthContent = 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height
                    height = xmlBuilder.createElement("height")  # size子标签height
                    heightContent = 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depth
                    depth = xmlBuilder.createElement("depth")  # size子标签width
                    depthContent = 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 + 1
                        y_center = float(object_info[2])*height_img + 1
                        xminVal = 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__':
        txts_path1 = './Annotations_txt'
        xmls_path1 = './Annotations_xml'
        imgs_path1 = './JPEGImages'
    
        yolo2voc_obj1 = YOLO2VOCConvert(txts_path1, xmls_path1, imgs_path1)
        labels = yolo2voc.search_all_classes()
        print('labels: ', labels)
        yolo2voc_obj1.yolo2voc()

# VOC格式转化为YOLO格式 #

__Author__ = "Shliang"
    __Email__ = "shliang0603@gmail.com"
    
    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   # 读取读片的路径个图片名字，存储到xml标签文件中
            self.classes = ["shirt", "non_shirt", "western_style_clothes", "coat", "down_filled_coat",
                            "cotton", "sweater", "silk_scarf", "tie", "bow_tie"]
    
        # 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))
    
            # 把从xmls标签文件中提取的类别写入到'./Annotations/classes.txt'文件中
            # if writer:
            #     with open('./Annotations/classes.txt', 'w') as f:
            #         for label in all_names:
            #             f.write(label + '\n')
    
            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)
    
            # # 读取每张图片，获取图片的尺寸信息（shape）
            # imgs = os.listdir(self.imgs_path)
            # for img_name in imgs:
            #     img = cv2.imread(os.path.join(self.imgs_path, img_name))
            #     height, width, depth = img.shape
            #     # print(height, width, depth)   # 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）
            #
            # # 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_name in txts:
            #     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(' ')
            #             print(object)  # ['2', '0.506667', '0.553333', '0.490667', '0.658667']
    
            # 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.shape
                    print(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folder
                    folder = 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：JPEGImages
                    folderContent = 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filename
                    filename = 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.jpg
                    filenameContent = 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width
                    width = xmlBuilder.createElement("width")  # size子标签width
                    widthContent = 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height
                    height = xmlBuilder.createElement("height")  # size子标签height
                    heightContent = 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depth
                    depth = xmlBuilder.createElement("depth")  # size子标签width
                    depthContent = 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 + 1
                        y_center = float(object_info[2])*height_img + 1
                        xminVal = 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__':
        txts_path1 = './Annotations_txt'
        xmls_path1 = './Annotations_xml'
        imgs_path1 = './JPEGImages'
    
        yolo2voc_obj1 = YOLO2VOCConvert(txts_path1, xmls_path1, imgs_path1)
        labels = yolo2voc.search_all_classes()
        print('labels: ', labels)
        yolo2voc_obj1.yolo2voc()