Python 统计数据集标签的类别及数目操作

看了大神统计voc数据集标签框后，针对自己标注数据集，灵活应用 ，感谢！

import reimport osimport xml.etree.ElementTree as ETclass1 = ’answer’class2 = ’hand’class3 = ’write’class4 = ’music’class5 = ’phone’’’’class6 = ’bus’class7 = ’car’class8 = ’cat’class9 = ’chair’class10 = ’cow’class11 = ’diningtable’class12 = ’dog’class13 = ’horse’class14 = ’motorbike’class15 = ’person’class16 = ’pottedplant’class17 = ’sheep’class18 = ’sofa’class19 = ’train’class20 = ’tvmonitor’’’’annotation_folder = ’/home/.../train/’#改为自己标签文件夹的路径#annotation_folder = ’/home/.../VOC2007/Annotations/’list = os.listdir(annotation_folder) def file_name(file_dir):L = []for root, dirs, files in os.walk(file_dir):for file in files:if os.path.splitext(file)[1] == ’.xml’:L.append(os.path.join(root, file))return L total_number1 = 0total_number2 = 0total_number3 = 0total_number4 = 0total_number5 = 0’’’total_number6 = 0total_number7 = 0total_number8 = 0total_number9 = 0total_number10 = 0total_number11 = 0total_number12 = 0total_number13 = 0total_number14 = 0total_number15 = 0total_number16 = 0total_number17 = 0total_number18 = 0total_number19 = 0total_number20 = 0’’’total = 0total_pic=0 pic_num1 = 0pic_num2 = 0pic_num3 = 0pic_num4 = 0pic_num5 = 0’’’pic_num6 = 0pic_num7 = 0pic_num8 = 0pic_num9 = 0pic_num10 = 0pic_num11 = 0pic_num12 = 0pic_num13 = 0pic_num14 = 0pic_num15 = 0pic_num16 = 0pic_num17 = 0pic_num18 = 0pic_num19 = 0pic_num20 = 0’’’ flag1 = 0flag2 = 0flag3 = 0flag4 = 0flag5 = 0’’’flag6 = 0flag7 = 0flag8 = 0flag9 = 0flag10 = 0flag11 = 0flag12 = 0flag13 = 0flag14 = 0flag15= 0flag16 = 0flag17 = 0flag18 = 0flag19 = 0flag20 = 0’’’ xml_dirs = file_name(annotation_folder) for i in range(0, len(xml_dirs)):print(xml_dirs[i])#path = os.path.join(annotation_folder,list[i])#print(path) annotation_file = open(xml_dirs[i]).read() root = ET.fromstring(annotation_file)#tree = ET.parse(annotation_file)#root = tree.getroot() total_pic = total_pic + 1for obj in root.findall(’object’):label = obj.find(’name’).textif label == class1:total_number1=total_number1+1flag1=1total = total + 1#print('bounding box number:', total_number1)if label == class2:total_number2=total_number2+1flag2=1total = total + 1if label == class3:total_number3=total_number3+1flag3=1total = total + 1if label == class4:total_number4=total_number4+1flag4=1total = total + 1if label == class5:total_number5=total_number5+1flag5=1total = total + 1’’’if label == class6:total_number6=total_number6+1flag6=1total = total + 1if label == class7:total_number7=total_number7+1flag7=1total = total + 1if label == class8:total_number8=total_number8+1flag8=1total = total + 1if label == class9:total_number9=total_number9+1flag9=1total = total + 1if label == class10:total_number10=total_number10+1flag10=1total = total + 1if label == class11:total_number11=total_number11+1flag11=1total = total + 1if label == class12:total_number12=total_number12+1flag12=1total = total + 1if label == class13:total_number13=total_number13+1flag13=1total = total + 1if label == class14:total_number14=total_number14+1flag14=1total = total + 1if label == class15:total_number15=total_number15+1flag15=1total = total + 1if label == class16:total_number16=total_number16+1flag16=1total = total + 1if label == class17:total_number17=total_number17+1flag17=1total = total + 1if label == class18:total_number18=total_number18+1flag18=1total = total + 1if label == class19:total_number19=total_number19+1flag19=1total = total + 1if label == class20:total_number20=total_number20+1flag20=1total = total + 1’’’ if flag1==1:pic_num1=pic_num1+1#print('pic number:', pic_num1)flag1=0if flag2==1:pic_num2=pic_num2+1flag2=0if flag3==1:pic_num3=pic_num3+1flag3=0if flag4==1:pic_num4=pic_num4+1flag4=0if flag5==1:pic_num5=pic_num5+1flag5=0’’’if flag6==1:pic_num6=pic_num6+1flag6=0if flag7==1:pic_num7=pic_num7+1flag7=0if flag8==1:pic_num8=pic_num8+1flag8=0if flag9==1:pic_num9=pic_num9+1flag9=0if flag10==1:pic_num10=pic_num10+1flag10=0if flag11==1:pic_num11=pic_num11+1flag11=0if flag12==1:pic_num12=pic_num12+1flag12=0if flag13==1:pic_num13=pic_num13+1flag13=0if flag14==1:pic_num14=pic_num14+1flag14=0if flag15==1:pic_num15=pic_num15+1flag15=0if flag16==1:pic_num16=pic_num16+1flag16=0if flag17==1:pic_num17=pic_num17+1flag17=0if flag18==1:pic_num18=pic_num18+1flag18=0if flag19==1:pic_num19=pic_num19+1flag19=0if flag20==1:pic_num20=pic_num20+1flag20=0’’’ print(class1,pic_num1,total_number1)print(class2,pic_num2,total_number2)print(class3,pic_num3, total_number3)print(class4,pic_num4, total_number4)print(class5,pic_num5, total_number5)’’’print(class6,pic_num6, total_number6)print(class7,pic_num7, total_number7)print(class8,pic_num8, total_number8)print(class9,pic_num9, total_number9)print(class10,pic_num10, total_number10)print(class11,pic_num11,total_number11)print(class12,pic_num12,total_number12)print(class13,pic_num13, total_number13)print(class14,pic_num14, total_number14)print(class15,pic_num15, total_number15)print(class16,pic_num16, total_number16)print(class17,pic_num17, total_number17)print(class18,pic_num18, total_number18)print(class19,pic_num19, total_number19)print(class20,pic_num20, total_number20)’’’ print('total', total_pic, total)

补充：【数据集处理】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）

# -*- coding:utf-8 -*-#根据xml文件统计目标种类以及数量import osimport xml.etree.ElementTree as ETimport numpy as npnp.set_printoptions(suppress=True, threshold=np.nan)import matplotlibfrom 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。’)

# -*- 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 osimport xml.etree.ElementTree as ETimport numpy as np#np.set_printoptions(suppress=True, threshold=np.nan) #10,000,000np.set_printoptions(suppress=True, threshold=10000000) #10,000,000import matplotlibfrom PIL import Imagedef 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’).textbbox = 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 objectsdef 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_infoif __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。’)

#修改xml文件中的目标的名字，import os, sysimport globfrom xml.etree import ElementTree as ET# 批量读取Annotations下的xml文件# per=ET.parse(r’C:UsersrockhuangDesktopAnnotations000003.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)

修改为：

以上为个人经验，希望能给大家一个参考，也希望大家多多支持好吧啦网。