Python 生成VOC格式的标签实例

常用目标检测模型基本都是读取的PASCAL VOC格式的标签，下面代码用于生成VOC格式的代码，根据需要修改即可：

from lxml import etree, objectify

def gen_txt(filename, h, w, c):
E = objectify.ElementMaker(annotate=False)
anno_tree = E.annotation(
E.folder('VOC_OPEN_IMAGE'),
E.filename(filename),
E.source(
E.database('The VOC2007 Database'),
E.annotation('PASCAL VOC2007'),
E.image('flickr'),
E.flickrid("341012865")
),
E.size(
E.width(w),
E.height(h),
E.depth(c)
),
E.segmented(0),
E.object(
E.name('1'),
E.pose('left'),
E.truncated('1'),
E.difficult('0'),
E.bndbox(
E.xmin('0'),
E.ymin('0'),
E.xmax('0'),
E.ymax('0')
)
),
)
etree.ElementTree(anno_tree).write('ann/'+filename[:-4]+".xml", pretty_print=True)

补充知识： python对PASCAL VOC标注数据进行统计

用于统计训练数据中的类别，以及所有目标的个数：

# coding:utf-8
import xml.etree.cElementTree as ET
import os
from collections import Counter
import shutil

# Counter({'towCounter({'tower': 3074, 'windpower': 2014, 'thermalpower': 689, 'hydropower': 261, 'transformer': 225})
# total_num: 6263

def count(pathdir,despath):
category = []
path = pathdir + '/XML/'
for index,xml in enumerate(os.listdir(path)):
# print(str(index) + ' xml: '+ xml)
root = ET.parse(os.path.join(path, xml))
objects = root.findall('object')

# ==================select images which has a special object=============
for obj in objects:
obj_label = obj.find('name').text
if obj_label == 'transformer':
print(xml)
imgfile = pathdir + 'JPEG/' + xml.replace('xml', 'jpg')
img_despath = despath + xml.replace('xml', 'jpg')
# if not os.path.exists(img_despath):
shutil.copyfile(imgfile, img_despath)

# ==================select images which has a special object=============

category += [ob.find('name').text for ob in objects]
print(Counter(category))
total_num = sum([value for key, value in Counter(category).items()])
print('total_num:',total_num)

if __name__ == '__main__':
# pathdirs = list(set(os.listdir('./')) ^ set(['tools','count.py']))
# print(pathdirs)
# for pathdir in pathdirs:
pathdir = '/summer/Desktop/power_traindata/'
despath = '/transformer/'
count(pathdir,despath)

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