64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
import os.path
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from lxml import etree
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import xml.etree.ElementTree as ET
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import cv2
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import numpy as np
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import xml.etree.ElementTree as ET
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def remove_vest_objects(root):
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"""
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递归地从XML树中删除所有name='Vest'的object标签及其子标签
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:param root: XML树的根元素
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"""
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# 收集要删除的elements列表，因为不能在迭代时直接修改列表
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to_remove = []
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for elem in root.findall('.//object'):
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if elem.get('name') == 'Vest':
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to_remove.append(elem)
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# 逆序删除，因为删除会影响列表的索引
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for elem in reversed(to_remove):
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elem.getparent().remove(elem)
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# 解析XML文件
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def save_PH(path, save_path):
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all_xml_name = os.listdir(path)
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all_xml_path = [os.path.join(path, t) for t in all_xml_name]
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for i in range(len(all_xml_path)):
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xml = all_xml_path[i]
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tree = ET.parse(xml)
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root = tree.getroot()
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j = 0
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while j < len(root):
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f = 0
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if root[j].tag == 'object':
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for child in root[j]:
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if child.tag == 'name' and child.text not in ['Person', 'Helmet']:
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del root[j]
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f = 1
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break
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if f == 0:
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j += 1
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tree.write(os.path.join(save_path, all_xml_name[i]), encoding='utf-8', xml_declaration=False)
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if __name__ == '__main__':
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path = 'E:/haotian/YOLO安全帽手套检测数据集(含1000张图片)+对应voc、coco和yolo三种格式标签+划分脚本+训练教程/datasets/Annotations'
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save_path = 'E:/haotian/YOLO安全帽手套检测数据集(含1000张图片)+对应voc、coco和yolo三种格式标签+划分脚本+训练教程/datasets/Annotaions_PH'
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save_PH(path, save_path)
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