怎么将caltech数据集的txt用python‘转成VOC数据集xml格式

以下是将Caltech数据集的txt文件转换为VOC数据集xml格式的Python代码：

import os
import xml.etree.ElementTree as ET

# 设置类别名称和类别ID对应的字典
classes = {'person': 0, 'cyclist': 1, 'car': 2, 'van': 3, 'bus': 4, 'truck': 5, 'trailer': 6, 'motorcyclist': 7}

# 定义函数将txt文件转换为xml文件
def txt_to_xml(txt_path, xml_path):
    with open(txt_path, 'r') as f:
        # 读取txt文件中的内容
        lines = f.readlines()

        # 创建xml文件的根元素
        root = ET.Element('annotation')

        # 创建文件名子元素
        filename = ET.SubElement(root, 'filename')
        filename.text = os.path.basename(txt_path)[:-4] + '.jpg'

        # 创建文件大小子元素
        size = ET.SubElement(root, 'size')
        width = ET.SubElement(size, 'width')
        height = ET.SubElement(size, 'height')
        depth = ET.SubElement(size, 'depth')
        width.text = '1280'
        height.text = '720'
        depth.text = '3'

        # 循环处理每个物体的信息
        for line in lines:
            line = line.strip().split(' ')
            classname = line[0]
            classid = classes[classname]
            x1, y1, w, h = [int(float(i)) for i in line[1:]]
            x2 = x1 + w
            y2 = y1 + h

            # 创建物体子元素
            object = ET.SubElement(root, 'object')
            name = ET.SubElement(object, 'name')
            pose = ET.SubElement(object, 'pose')
            truncated = ET.SubElement(object, 'truncated')
            difficult = ET.SubElement(object, 'difficult')
            bndbox = ET.SubElement(object, 'bndbox')
            xmin = ET.SubElement(bndbox, 'xmin')
            ymin = ET.SubElement(bndbox, 'ymin')
            xmax = ET.SubElement(bndbox, 'xmax')
            ymax = ET.SubElement(bndbox, 'ymax')

            name.text = classname
            pose.text = 'Unspecified'
            truncated.text = '0'
            difficult.text = '0'
            xmin.text = str(x1)
            ymin.text = str(y1)
            xmax.text = str(x2)
            ymax.text = str(y2)

        # 将xml文件保存到指定路径
        tree = ET.ElementTree(root)
        tree.write(xml_path)

# 循环处理Caltech数据集中所有txt文件
for root, dirs, files in os.walk('caltech/data/annotations'):
    for filename in files:
        if filename.endswith('.txt'):
            txt_path = os.path.join(root, filename)
            xml_path = os.path.join('caltech/data/annotations/xml', filename[:-4] + '.xml')
            txt_to_xml(txt_path, xml_path)

需要注意的是，上述代码中的路径都是相对路径，需要根据实际情况进行修改。此外，上述代码中默认图片的大小为1280x720，如需修改可以在代码中相应位置进行修改。