Python读取VOC中的xml目标框实例

代码：

#!/usr/bin/python
# -*- coding: UTF-8 -*-
# get annotation object bndbox location
import os
import cv2
try:
  import xml.etree.cElementTree as ET #解析xml的c语言版的模块
except ImportError:
  import xml.etree.ElementTree as ET
											     
##get object annotation bndbox loc start 
def GetAnnotBoxLoc(AnotPath):#AnotPath VOC标注文件路径
  tree = ET.ElementTree(file=AnotPath) #打开文件，解析成一棵树型结构
  root = tree.getroot()#获取树型结构的根
  ObjectSet=root.findall('object')#找到文件中所有含有object关键字的地方，这些地方含有标注目标
  ObjBndBoxSet={} #以目标类别为关键字，目标框为值组成的字典结构
  for Object in ObjectSet:
    ObjName=Object.find('name').text
    BndBox=Object.find('bndbox')
    x1 = int(BndBox.find('xmin').text)#-1 #-1是因为程序是按0作为起始位置的
    y1 = int(BndBox.find('ymin').text)#-1
    x2 = int(BndBox.find('xmax').text)#-1
    y2 = int(BndBox.find('ymax').text)#-1
    BndBoxLoc=[x1,y1,x2,y2]
    if ObjName in ObjBndBoxSet:
    	ObjBndBoxSet[ObjName].append(BndBoxLoc)#如果字典结构中含有这个类别了，那么这个目标框要追加到其值的末尾
    else:
    	ObjBndBoxSet[ObjName]=[BndBoxLoc]#如果字典结构中没有这个类别，那么这个目标框就直接赋值给其值吧
  return ObjBndBoxSet
##get object annotation bndbox loc end

def display(objBox,pic):
  img = cv2.imread(pic)
  
  for key in objBox.keys():
    for i in range(len(objBox[key])):
      cv2.rectangle(img, (objBox[key][i][0],objBox[key][i][1]), (objBox[key][i][2], objBox[key][i][3]), (0, 0, 255), 2)    
      cv2.putText(img, key, (objBox[key][i][0],objBox[key][i][1]), cv2.FONT_HERSHEY_COMPLEX, 1, (255,0,0), 1)
  cv2.imshow('img',img)
  cv2.imwrite('display.jpg',img)
  cv2.waitKey(0)


if __name__== '__main__':
  pic = r"./VOCdevkit/VOC2007/JPEGImages/000282.jpg"
  ObjBndBoxSet=GetAnnotBoxLoc(r"./VOCdevkit/VOC2007/Annotations/000282.xml")
  print(ObjBndBoxSet)
  display(ObjBndBoxSet,pic)

输出结果：

{'chair': [[335, 263, 484, 373]], 'person': [[327, 104, 476, 300], [232, 57, 357, 374], [3, 32, 199, 374], [58, 139, 296, 374]]}

图示：

补充知识：使用python将voc类型标注xml文件对图片进行目标还原，以及批量裁剪特定类

使用标注工具如labelimg对图片物体进行voc类型标注，会生成xml文件，如何判断别人的数据集做的好不好，可以用以下代码进行目标还原。

import xml.etree.cElementTree as ET
import cv2
import os
import glob

def GetAnnotBoxLoc(AnotPath):
  tree = ET.ElementTree(file=AnotPath)
  root = tree.getroot()
  ObjectSet=root.findall('object')
  ObjBndBoxSet={} 
  for Object in ObjectSet:
    ObjName=Object.find('name').text
    BndBox=Object.find('bndbox')
    x1 = int(BndBox.find('xmin').text)
    y1 = int(BndBox.find('ymin').text)
    x2 = int(BndBox.find('xmax').text)
    y2 = int(BndBox.find('ymax').text)
    BndBoxLoc=[x1,y1,x2,y2]
    if ObjName in ObjBndBoxSet:
    	ObjBndBoxSet[ObjName].append(BndBoxLoc)
    else:
    	ObjBndBoxSet[ObjName]=[BndBoxLoc]
  return ObjBndBoxSet

def GetAnnotName(AnotPath):
  tree = ET.ElementTree(file=AnotPath) 
  root = tree.getroot()
  path=root.find('path').text
  return path

def Drawpic(xml_path,result_path):
  n = 0
  xmls = glob.glob(os.path.join(xml_path, '*.xml'))
  for xml in xmls:
    n = n + 1
    box=GetAnnotBoxLoc(xml)
    path=GetAnnotName(xml)
    img = cv2.imread(path)
    for classes in list(box.keys()):
      for boxes in box[classes]:
        if classes == "bad1":
          cv2.rectangle(img,(int(boxes[0]),int(boxes[1])),(int(boxes[2]),int(boxes[3])),(255,0,0),3) #blue
        if classes == "bad2":
          cv2.rectangle(img,(int(boxes[0]),int(boxes[1])),(int(boxes[2]),int(boxes[3])),(0,255,0),3) #green
        if classes == "bad3":
          cv2.rectangle(img,(int(boxes[0]),int(boxes[1])),(int(boxes[2]),int(boxes[3])),(0,0,255),3) #red
    cv2.imwrite(result_path+"/"+str(n)+"_result.jpg", img)
    print(path,"还原成功")

Drawpic("/home/wxy/Dashboard/dataset/VOCdevkit/VOC2012/Annotations","/home/wxy/Dashboard/dataset/VOCdevkit/VOC2012/test")

使用labelimg对图像进行标注，folder目录需要修改一下

import xml.etree.ElementTree as ET
import os

for i in os.listdir('/home/wxy/Dashboard/dataset/VOCdevkit/VOC2012/Annotations'):
  tree = ET.parse('/home/wxy/Dashboard/dataset/VOCdevkit/VOC2012/Annotations'+'/'+i)
  root = tree.getroot()
  print(root.find('folder').text)
  root.find('folder').text = 'VOC2012'
  print(root.find('folder').text)
  tree.write('/home/wxy/Dashboard/dataset/VOCdevkit/VOC2012/Annotations'+'/'+i)

批量裁剪特定类，xml.dom.minidom好像比xml.etree.cElementTree好用啊。

#coding=utf-8
import xml.dom.minidom
import cv2
import os

for name in os.listdir("./Annotations/"):
  dom=xml.dom.minidom.parse("./Annotations/"+name)
  root=dom.documentElement
  object_name=root.getElementsByTagName('name')
  if(object_name[0].firstChild.data == "normal"):
    print(name)
    xmin=root.getElementsByTagName('xmin')
    ymin=root.getElementsByTagName('ymin')
    xmax=root.getElementsByTagName('xmax')
    ymax=root.getElementsByTagName('ymax')

    x_min = int(xmin[0].firstChild.data)
    y_min = int(ymin[0].firstChild.data)
    x_max = int(xmax[0].firstChild.data)
    y_max = int(ymax[0].firstChild.data)

    img=cv2.imread("./JPEGImages/"+name[:-4]+".jpg")
    cropped=img[y_min:y_max,x_min:x_max]
    cv2.imwrite("./cut_jpg/"+name[:-4]+".jpg", cropped)

以上这篇Python读取VOC中的xml目标框实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持呐喊教程。

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