xml文件读取与xml文件数据保存(使用YOLO算法的辅助函数)

目前使用yolo系列算法较多，特别是今年yolo4的出现，是我们异常兴奋，但鉴于某些数据集使用xml标注的数据，未能转换成train.txt文件，为此，我写了一份xml文件读取，并将其转换为yolo等训练所需要的格式。希望对读者有些帮助与启示。本博客仅展示代码与结果图片。

 

 

代码如下：

def read_xml(path_xml):
    '''
    :param path_xml: 输入处理xml文件的绝对路径
    :return: 返回xml的label与box，其中label是一维的，并与box一一对应。
    '''
    import xml.etree.ElementTree as ET
    with open( path_xml) as f:
        root = ET.parse(f).getroot()

    boxes = []  # 每张图片的所有box保存在这里boxes，并重新读取图片将重新开始  # We'll store all boxes for this image here.
    labels = []  #每张图片的所有box对应的label保存在这里
    objects = root.findall('object')  # Get a list of all objects in this image.
    # Parse the data for each object.
    for obj in objects:
        class_name = obj.find('name').text
        # Check whether this class is supposed to be included in the dataset.

        # Get the bounding box coordinates.
        bndbox = obj.find('bndbox')
        xmin = int(bndbox.find('xmin').text)  # bndbox.find('xmin').text
        ymin = int(bndbox.find('ymin').text)
        xmax = int(bndbox.find('xmax').text)
        ymax = int(bndbox.find('ymax').text)
        item_dict = {  # 'folder': '',#folder,
            'class_name': class_name,
            'xmin': xmin,
            'ymin': ymin,
            'xmax': xmax,
            'ymax': ymax
                    }
        box = []
        box.append(item_dict['xmin'])
        box.append(item_dict['ymin'])
        box.append(item_dict['xmax'])
        box.append(item_dict['ymax'])
        labels.append(item_dict['class_name'])
        boxes.append(box)

    result=[]
    result.append(labels)
    result.append(boxes)

    return result



def result2txt(data,f):
    labels=data[0]
    boxes=data[1]
    print(labels)
    print(boxes)
    num=len(list(labels))
    for i in range(num):
        s=str(boxes[i][0])+ ','+str(boxes[i][1])+ ','+str(boxes[i][2])+ ','+str(boxes[i][3])+ ','+str(labels[i])+'\t'
        f.write(s)




def readtotxt(write_file,path_xml,img_path=None,classes=None):
    '''
    :param write_file:  将结果写入的文件夹路径，后缀为.txt
    :param path_xml:  xml文件夹的路径
    :param img_path:  将给出图像所在文件夹路径，便于图像读取
    '''
    f = open(write_file, 'w')  # 写入txt文件
    import os
    for name in os.listdir(path_xml):
        path = os.path.join(path_xml, name)
        result = read_xml(path)
        labels = result[0]  # 对应的label列表，与boxes一一对应
        boxes = result[1]
        num = len(list(labels))
        for i in range(num):
            if classes is not None:
                label=classes.index(labels[i])
            else:
                label=labels[i]
            if img_path is not None:
                if i == 0:
                    img, _ = os.path.splitext(name)
                    img_str = str(img_path + '/' + img + '.jpg')
                    s = img_str + '\t' + str(boxes[i][0]) + ',' + str(boxes[i][1]) + ',' + str(
                        boxes[i][2]) + ',' + str(
                        boxes[i][3]) + ',' + str(
                        label) + '\t'
                else:
                    s = str(boxes[i][0]) + ',' + str(boxes[i][1]) + ',' + str(
                        boxes[i][2]) + ',' + str(
                        boxes[i][3]) + ',' + str(
                        label) + '\t'
            else:
                s = str(boxes[i][0]) + ',' + str(boxes[i][1]) + ',' + str(
                    boxes[i][2]) + ',' + str(
                    boxes[i][3]) + ',' + str(
                    label) + '\t'

            print(s)
            f.write(s)
        f.write('\n')

    f.close()  # 关闭文件




if __name__ == "__main__":


    path_xml = './data/train_data/xml'  # 读取文件路径
    path = "./data/train_data/2007_train.txt"
    classes=['aeroplane','bicycle','bird','boat','bottle','bus','car','cat','chair',
'cow','diningtable','dog','horse','motorbike','person','pottedplant','sheep',
'sofa', 'train', 'tvmonitor']

    readtotxt(path, path_xml,img_path='./data/train_data/img',classes=classes)

    # img_path 表示图像存放路径

 

 

 

读取与写入结果如下：