１．将自己的数据集的文件名统一修改为pascal voc的命名格式： 代码名称：xml_node.py
# coding:utf-8 import os import os.path import xml.etree.ElementTree as ET from xml.etree.ElementTree import Element from w3lib.html import remove_tags findpath ='/media/ymw/LANKEXIN/02facexml' filenames=os.listdir(findpath) s=[] save_path ='/media/ymw/LANKEXIN/02facexml' for file in filenames: tree = ET.parse(os.path.join(findpath, file)) root = tree.getroot() # 为图片改名字01face (1).jpg改成000001.jpg nodename = root[1].text re_nodename = nodename[:-4].replace('02face (', '').replace(')', '') new_num = int(re_nodename) + 1696 new_nodename = str(new_num) new_nodename1 = new_nodename.zfill(6) + '.jpg' # new_nodename1 = re_nodename.zfill(6) + '.jpg' root[1].text = new_nodename1 tree.write(os.path.join(save_path, file))2.将自己的数据集标注格式转化成pascal voc 的标注格式： 代码名字：new_xml.py
# coding:utf-8 import os import os.path import xml.etree.ElementTree as ET from xml.etree.ElementTree import Element findpath = '/media/ymw/LANKEXIN/02facexml' filenames = os.listdir(findpath) s = [] xml_path = '/media/ymw/LANKEXIN/02facexml' for file in filenames: # 依次添加节点（按照pascal voc 的标注格式） tree = ET.parse(os.path.join(findpath, file)) root = tree.getroot() source = Element('source') root.append(source) database = Element('database') database.text = 'The VOC2007 Database' source.append(database) annotation = Element('annotation') annotation.text = 'PASCAL VOC2007' source.append(annotation) image = Element('image') image.text = 'flickr' source.append(image) # 获取bndbox的节点信息 object = root.getchildren()[3] face = object.getchildren()[0] big = face.getchildren()[1] # 将...作为object的子节点添加进去 one = Element('name') one.text = 'cat' object.append(one) two = Element('pose') two.text = 'Unspecified' object.append(two) three = Element('truncated') three.text = '0' object.append(three) four = Element('difficult') four.text = '0' object.append(four) object.append(big) object.remove(face) # bndbox = ET.SubElement(face, 'bndbox') # bndbox.text = big.text nodename2 = root[3].tag root[3].tag = 'object' root[3][4].tag = 'bndbox' # 将修改之后的标注写入到一个新的文件夹 tree.write(os.path.join(xml_path, file))３．从Annotations文件夹产生ImageSets，xml文件生成txt文件： 代码名字：xml2txt.py
# coding:utf-8 import os import random trainval_percent = 0.98 # 作为trainval_percent的比例，在整个数据集，可以修改 train_percent = 0.98 # 用于训练的数据的比例，可以修改 xmlfilepath = '/home/ymw/桌面/xinan/Cat Face/catxml_total' txtsavepath = '/home/ymw/桌面/xinan/Cat Face/cattxt_total/' total_xml = os.listdir(xmlfilepath) num=len(total_xml) list=range(num) tv=int(num*trainval_percent) tr=int(tv*train_percent) trainval= random.sample(list,tv) train=random.sample(trainval,tr) ftrainval = open(txtsavepath+'/trainval.txt', 'w') ftest = open(txtsavepath+'/test.txt', 'w') ftrain = open(txtsavepath+'/train.txt', 'w') fval = open(txtsavepath+'/val.txt', 'w') for i in list: org_name=total_xml[i][:-4]+'\n' re_name=org_name.replace('01face (', '').replace(')', '') name=re_name.zfill(7) if i in trainval: ftrainval.write(name) if i in train: ftrain.write(name) else: fval.write(name) else: ftest.write(name) ftrainval.close() ftrain.close() fval.close() ftest .close()４．可视化数据集检查错误： 代码名字：view.py
# -*- coding: UTF-8 -*- from xml.etree import ElementTree as ET import cv2 import os imgpath = '/home/ymw/PycharmProjects/tf-faster-rcnn-master/data/VOCdevkit2007/VOC2007/JPEGImages' xmlpath = '/home/ymw/桌面/facebig_xml' imgnames = os.listdir(imgpath) for imgname in imgnames: img = cv2.imread(os.path.join(imgpath, imgname)) index = imgname[:-4] xmlname = index + '.xml' tree = ET.parse(os.path.join(xmlpath, xmlname)) root = tree.getroot() bndbox = root.getchildren()[3].getchildren()[4] big_xmin = int(bndbox.getchildren()[0].text) big_ymin = int(bndbox.getchildren()[1].text) big_xmax = int(bndbox.getchildren()[2].text) big_ymax = int(bndbox.getchildren()[3].text) cv2.rectangle(img, (big_xmin, big_ymin), (big_xmax, big_ymax), (0, 0, 255), 2) cv2.imwrite(os.path.join('/home/ymw/PycharmProjects/tf-faster-rcnn-master/data/VOCdevkit2007/VOC2007/viewimgs',imgname), img)５．检查自己的标注是否有坐标值为０（在tf-faster-rcnn中有影响，导致程序报错：total loss = Nan）：
#coding:utf-8 from xml.etree import ElementTree as ET import os import shutil,re xmlpath = '/media/ymw/LANKEXIN/facebig_xml_right' xmlnames = os.listdir(xmlpath) i = 0 a = [] # f = open('/home/ymw/桌面/1.txt', 'w') for xmlname in xmlnames: # f.writelines(xmlname + '\n') tree = ET.parse(os.path.join(xmlpath, xmlname)) root = tree.getroot() small = root.getchildren()[3].getchildren()[0].getchildren()[0] big = root.getchildren()[3].getchildren()[4] # object = tree.findall('object') big_xmin = int(big.getchildren()[0].text) big_ymin = int(big.getchildren()[1].text) big_xmax = int(big.getchildren()[2].text) big_ymax = int(big.getchildren()[3].text) small_xmin = int(small.getchildren()[0].text) small_ymin = int(small.getchildren()[1].text) small_xmax = int(small.getchildren()[2].text) small_ymax = int(small.getchildren()[3].text) if big_xmin > small_xmin: i = i+1 # newpath = '/media/ymw/LANKEXIN/02facexml/02face_cuowu' # os.remove(os.path.join(xmlpath, xmlname)) # xmlnum = xmlname[:-4].replace('02face (', '').replace(')', '') # # print(i) print(xmlname)该段程序会筛选出自己的数据集中坐标值为０的图片名称，ｉ表示个数，xmlname就是所要筛选出来的文件名字。 6.测试集图片可视化处理： 实现将测试机图片copy到data/demo文件夹中替换原本的测试图片，并将所有的测试集图片名称输出到一个列表中，以此完成测试集图片的可视化. 代码名称：copytestimg.py
import os import shutil # img_txtpath是voc数据集中ImageSets中的text.txt,以此找到测试集图片的索引值 img_txtpath ='tf-faster-rcnn-master/data/VOCdevkit2007/VOC2007/ImageSets/Main/test.txt' # dir是.jpg文件所在地址 dir = 'tf-faster-rcnn-master/data/VOCdevkit2007/VOC2007/JPEGImages' # newpath是将测试集图片copy到的目的地 newpath = '/home/ymw/桌面/demo_test' with open(img_txtpath) as f: img_index = [x.strip()+'.jpg' for x in f.readlines()] # 这个是参照pascal_voc.py中读取图片的索引值的处理方法 # 将所有的索引值+'.jpg'都加入到一个列表中,刚好可以放到demo.py中 # print(img_index) for file in img_index: img_path = os.path.join(dir, file) shutil.copy(img_path, newpath) # 实现测试集图片的copy