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python 批量修改 labelImg 生成的xml文件的方法

作者:Miscellaneous0712

这篇文章主要介绍了python 批量修改 labelImg 生成的xml文件的方法,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面随着小编来一起学习学习吧

概述

自己在用labelImg打好标签后,想只用其中几类训练,不想训练全部类别,又不想重新打标生成.xml文件,因此想到这个办法:直接在.xml文件中删除原有的不需要的标签类及其属性。

打标时标签名出现了大小写(工程量大时可能会手滑),程序中有改写标签值为小写的过程,因为我做py-faster-rcnn 训练时,标签必须全部为小写。

以如下的.xml文件为例,我故意把标签增加了大写

<annotation verified="yes">
 <filename>test.jpg</filename>
 <path>C:\Users\yasin\Desktop\test</path>
 <source>
 <database>Unknown</database>
 </source>
 <size>
 <width>400</width>
 <height>300</height>
 <depth>3</depth>
 </size>
 <segmented>0</segmented>
 <object>
 <name>People</name>
 <pose>Unspecified</pose>
 <truncated>0</truncated>
 <difficult>0</difficult>
 <bndbox>
  <xmin>80</xmin>
  <ymin>69</ymin>
  <xmax>144</xmax>
  <ymax>89</ymax>
 </bndbox>
 </object>
 <object>
 <name>CAT</name>
 <pose>Unspecified</pose>
 <truncated>0</truncated>
 <difficult>0</difficult>
 <bndbox>
  <xmin>40</xmin>
  <ymin>69</ymin>
  <xmax>143</xmax>
  <ymax>16</ymax>
 </bndbox>
 </object>
 <object>
 <name>dog</name>
 <pose>Unspecified</pose>
 <truncated>0</truncated>
 <difficult>0</difficult>
 <bndbox>
  <xmin>96</xmin>
  <ymin>82</ymin>
  <xmax>176</xmax>
  <ymax>87</ymax>
 </bndbox>
 </object> 
</annotation>

具体实现

假如我们只想保留图片上的people和cat类,其他都删除,代码如下:

from xml.etree.ElementTree import ElementTree
from os import walk, path

def read_xml(in_path):
  tree = ElementTree()
  tree.parse(in_path)
  return tree

def write_xml(tree, out_path):
  tree.write(out_path, encoding="utf-8", xml_declaration=True)

def find_nodes(tree, path):
  return tree.findall(path)

def del_node_by_target_classes(nodelist, target_classes_lower, tree_root):
  for parent_node in nodelist:
    children = parent_node.getchildren()
    if (parent_node.tag == "object" and children[0].text.lower() not in target_classes_lower):
      tree_root.remove(parent_node)
    elif (parent_node.tag == "object" and children[0].text.lower() in target_classes_lower):
      children[0].text = children[0].text.lower()

def get_fileNames(rootdir):
  data_path = []
  prefixs = []
  for root, dirs, files in walk(rootdir, topdown=True):
    for name in files:
      pre, ending = path.splitext(name)
      if ending != ".xml":
        continue
      else:
        data_path.append(path.join(root, name))
        prefixs.append(pre)

  return data_path, prefixs

if __name__ == "__main__":
  # get all the xml paths, prefixes if not used here
  paths_xml, prefixs = get_fileNames("/home/yasin/old_labels/")

  target_classes = ["PEOPLE", "CAT"] # target flags you want to keep

  target_classes_lower = []
  for i in range(len(target_classes)):
    target_classes_lower.append(target_classes[i].lower()) # make sure your target is lowe-case

  # print(target_classes_lower)
  for i in range(len(paths_xml)):
    # rename and save the corresponding xml
    tree = read_xml(paths_xml[i])
    
    # get tree node
    tree_root = tree.getroot()

    # get parent nodes
    del_parent_nodes = find_nodes(tree, "./")
    
    # get target classes and delete
    target_del_node = del_node_by_target_classes(del_parent_nodes, target_classes_lower, tree_root)
    
    # save output xml, 000001.xml
    write_xml(tree, "/home/yasin/new_labels/{}.xml".format("%06d" % i))

按照上述代码,示例.xml变为如下.xml,可以看出我们删除了除people和cat类的类别(即dog类),并把保留类别的打标改成了小写:

<?xml version='1.0' encoding='utf-8'?>
<annotation verified="yes">
 <filename>test.jpg</filename>
 <path>C:\Users\yasin\Desktop\test</path>
 <source>
 <database>Unknown</database>
 </source>
 <size>
 <width>400</width>
 <height>300</height>
 <depth>3</depth>
 </size>
 <segmented>0</segmented>
 <object>
 <name>people</name>
 <pose>Unspecified</pose>
 <truncated>0</truncated>
 <difficult>0</difficult>
 <bndbox>
  <xmin>80</xmin>
  <ymin>69</ymin>
  <xmax>144</xmax>
  <ymax>89</ymax>
 </bndbox>
 </object>
 <object>
 <name>cat</name>
 <pose>Unspecified</pose>
 <truncated>0</truncated>
 <difficult>0</difficult>
 <bndbox>
  <xmin>40</xmin>
  <ymin>69</ymin>
  <xmax>143</xmax>
  <ymax>16</ymax>
 </bndbox>
 </object>
</annotation>

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持脚本之家。

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