python:批量统计xml中各类目标的数量案例

之前写了一个matlab的，越用越觉得麻烦，如果不同数据集要改类别数目，而且运行速度慢。所以重新写了一个Python的，直接读取xml文件夹路径就可以，不用预先知道类别，直接能够检测出所有类别的目标名称及其对应的数量。

分享出来给大家。

代码如下：

# -*- coding:utf-8 -*-
import os
import xml.etree.ElementTree as ET
import numpy as np
np.set_printoptions(suppress=True, threshold=np.nan)
import matplotlib
from PIL import Image

def parse_obj(xml_path, filename):
 tree=ET.parse(xml_path+filename)
 objects=[]
 for obj in tree.findall('object'):
 obj_struct={}
 obj_struct['name']=obj.find('name').text
 objects.append(obj_struct)
 return objects

def read_image(image_path, filename):
 im=Image.open(image_path+filename)
 W=im.size[0]
 H=im.size[1]
 area=W*H
 im_info=[W,H,area]
 return im_info

if __name__ == '__main__':
 xml_path='C:/Users/nansbas/Desktop/hebin/03/'
 filenamess=os.listdir(xml_path)
 filenames=[]
 for name in filenamess:
 name=name.replace('.xml','')
 filenames.append(name)
 recs={}
 obs_shape={}
 classnames=[]
 num_objs={}
 obj_avg={}
 for i,name in enumerate(filenames):
 recs[name]=parse_obj(xml_path, name+ '.xml' )
 for name in filenames:
 for object in recs[name]:
 if object['name'] not in num_objs.keys():
  num_objs[object['name']]=1
 else:
  num_objs[object['name']]+=1
 if object['name'] not in classnames:
  classnames.append(object['name'])
 for name in classnames:
 print('{}:{}个'.format(name,num_objs[name]))
 print('信息统计算完毕。')

补充知识：Python对目标检测数据集xml文件操作（统计目标种类、数量、面积、比例等&修改目标名字）

1. 根据xml文件统计目标种类以及数量

# -*- coding:utf-8 -*-
#根据xml文件统计目标种类以及数量
import os
import xml.etree.ElementTree as ET
import numpy as np
np.set_printoptions(suppress=True, threshold=np.nan)
import matplotlib
from PIL import Image

def parse_obj(xml_path, filename):
 tree=ET.parse(xml_path+filename)
 objects=[]
 for obj in tree.findall('object'):
 obj_struct={}
 obj_struct['name']=obj.find('name').text
 objects.append(obj_struct)
 return objects

def read_image(image_path, filename):
 im=Image.open(image_path+filename)
 W=im.size[0]
 H=im.size[1]
 area=W*H
 im_info=[W,H,area]
 return im_info

if __name__ == '__main__':
 xml_path='/home/dlut/网络/make_database/数据集——合集/VOCdevkit/VOC2018/Annotations/'
 filenamess=os.listdir(xml_path)
 filenames=[]
 for name in filenamess:
 name=name.replace('.xml','')
 filenames.append(name)
 recs={}
 obs_shape={}
 classnames=[]
 num_objs={}
 obj_avg={}
 for i,name in enumerate(filenames):
 recs[name]=parse_obj(xml_path, name+ '.xml' )
 for name in filenames:
 for object in recs[name]:
  if object['name'] not in num_objs.keys():
   num_objs[object['name']]=1
  else:
   num_objs[object['name']]+=1
  if object['name'] not in classnames:
   classnames.append(object['name'])
 for name in classnames:
 print('{}:{}个'.format(name,num_objs[name]))
 print('信息统计算完毕。')

2.根据xml文件统计目标的平均长度、宽度、面积以及每一个目标在原图中的占比

# -*- coding:utf-8 -*-
#统计
# 计算每一个目标在原图中的占比
# 计算目标的平均长度、
# 计算平均宽度，
# 计算平均面积、
# 计算目标平均占比

import os
import xml.etree.ElementTree as ET
import numpy as np

#np.set_printoptions(suppress=True, threshold=np.nan) #10,000,000
np.set_printoptions(suppress=True, threshold=10000000) #10,000,000
import matplotlib
from PIL import Image

def parse_obj(xml_path, filename):
 tree = ET.parse(xml_path + filename)
 objects = []
 for obj in tree.findall('object'):
  obj_struct = {}
  obj_struct['name'] = obj.find('name').text
  bbox = obj.find('bndbox')
  obj_struct['bbox'] = [int(bbox.find('xmin').text),
        int(bbox.find('ymin').text),
        int(bbox.find('xmax').text),
        int(bbox.find('ymax').text)]
  objects.append(obj_struct)
 return objects

def read_image(image_path, filename):
 im = Image.open(image_path + filename)
 W = im.size[0]
 H = im.size[1]
 area = W * H
 im_info = [W, H, area]
 return im_info

if __name__ == '__main__':
 image_path = '/home/dlut/网络/make_database/数据集——合集/VOCdevkit/VOC2018/JPEGImages/'
 xml_path = '/home/dlut/网络/make_database/数据集——合集/VOCdevkit/VOC2018/Annotations/'
 filenamess = os.listdir(xml_path)
 filenames = []
 for name in filenamess:
  name = name.replace('.xml', '')
  filenames.append(name)
 print(filenames)
 recs = {}
 ims_info = {}
 obs_shape = {}
 classnames = []
 num_objs={}
 obj_avg = {}
 for i, name in enumerate(filenames):
  print('正在处理 {}.xml '.format(name))
  recs[name] = parse_obj(xml_path, name + '.xml')
  print('正在处理 {}.jpg '.format(name))
  ims_info[name] = read_image(image_path, name + '.jpg')
 print('所有信息收集完毕。')
 print('正在处理信息......')
 for name in filenames:
  im_w = ims_info[name][0]
  im_h = ims_info[name][1]
  im_area = ims_info[name][2]
  for object in recs[name]:
   if object['name'] not in num_objs.keys():
    num_objs[object['name']] = 1
   else:
    num_objs[object['name']] += 1
   #num_objs += 1
   ob_w = object['bbox'][2] - object['bbox'][0]
   ob_h = object['bbox'][3] - object['bbox'][1]
   ob_area = ob_w * ob_h
   w_rate = ob_w / im_w
   h_rate = ob_h / im_h
   area_rate = ob_area / im_area
   if not object['name'] in obs_shape.keys():
    obs_shape[object['name']] = ([[ob_w,
            ob_h,
            ob_area,
            w_rate,
            h_rate,
            area_rate]])
   else:
    obs_shape[object['name']].append([ob_w,
             ob_h,
             ob_area,
             w_rate,
             h_rate,
             area_rate])
  if object['name'] not in classnames:
   classnames.append(object['name']) # 求平均

 for name in classnames:
  obj_avg[name] = (np.array(obs_shape[name]).sum(axis=0)) / num_objs[name]
  print('{}的情况如下：*******\n'.format(name))
  print(' 目标平均W={}'.format(obj_avg[name][0]))
  print(' 目标平均H={}'.format(obj_avg[name][1]))
  print(' 目标平均area={}'.format(obj_avg[name][2]))
  print(' 目标平均与原图的W比例={}'.format(obj_avg[name][3]))
  print(' 目标平均与原图的H比例={}'.format(obj_avg[name][4]))
  print(' 目标平均原图面积占比={}\n'.format(obj_avg[name][5]))
 print('信息统计计算完毕。')

3.修改xml文件中某个目标的名字为另一个名字

#修改xml文件中的目标的名字，
import os, sys
import glob
from xml.etree import ElementTree as ET

# 批量读取Annotations下的xml文件
# per=ET.parse(r'C:\Users\rockhuang\Desktop\Annotations\000003.xml')
xml_dir = r'/home/dlut/网络/make_database/数据集——合集/VOCdevkit/VOC2018/Annotations'
xml_list = glob.glob(xml_dir + '/*.xml')
for xml in xml_list:
 print(xml)
 per = ET.parse(xml)
 p = per.findall('/object')

 for oneper in p: # 找出person节点
  child = oneper.getchildren()[0] # 找出person节点的子节点
  if child.text == 'PinNormal': #需要修改的名字
   child.text = 'normal bolt' #修改成什么名字
  if child.text == 'PinDefect': #需要修改的名字
   child.text = 'defect bolt-1' #修改成什么名字

 per.write(xml)
 print(child.tag, ':', child.text)

以上这篇python:批量统计xml中各类目标的数量案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我们。