一图流介绍的比较详细，一般图像检测数据集格式为txt或者xml格式，在使用labelimg进行标注的时候，可以设置获得不同格式的数据集，以满足不同算法训练格式要求：
一般建议使用pascalVoc:即PASCAL VOC数据集格式，关于该数据集的参见：PASCAL VOC
因为这样的数据方便在标注软件中看到对应的框；
对于xml格式数据集，如果要用yolo对其进行使用时候，先将其转化为txt格式，再进行训练，转换代码：
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import copy
from lxml.etree import Element, SubElement, tostring, ElementTree
import xml.etree.ElementTree as ET
import pickle
import os
from os import listdir, getcwd
from os.path import join
classes = ["0", "1", "2", "3"] # 类别
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
def convert(size, box):
dw = 1. / size[0]
dh = 1. / size[1]
x = (box[0] + box[1]) / 2.0
y = (box[2] + box[3]) / 2.0
w = box[1] - box[0]
h = box[3] - box[2]
x = x * dw
w = w * dw
y = y * dh
h = h * dh
return (x, y, w, h)
def convert_annotation(image_id):
in_file = open('./label_xml\%s.xml' % (image_id), encoding='UTF-8')
out_file = open('./label_txt\%s.txt' % (image_id), 'w') # 生成txt格式文件
tree = ET.parse(in_file)
root = tree.getroot()
size = root.find('size')
w = int(size.find('width').text)
h = int(size.find('height').text)
for obj in root.iter('object'):
cls = obj.find('name').text
# print(cls)
if cls not in classes:
continue
cls_id = classes.index(cls)
xmlbox = obj.find('bndbox')
b = (float(xmlbox.find('xmin').text), float(xmlbox.find('xmax').text), float(xmlbox.find('ymin').text),
float(xmlbox.find('ymax').text))
bb = convert((w, h), b)
out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')
xml_path = os.path.join(CURRENT_DIR, './label_xml/')
# xml list
img_xmls = os.listdir(xml_path)
for img_xml in img_xmls:
label_name = img_xml.split('.')[0]
print(label_name)
convert_annotation(label_name)
txt格式的数据不方便进行一些数据增强操作，可以先将其转换成xml格式后再进行相关标注工作或者
增强操作；
#!/user/bin/env python3
# _*_ coding:utf-8 -*_
# using: 将yolo txt label 转换成xml标签
from xml.dom.minidom import Document
import os
import cv2
def makexml(txtPath, xmlPath, picPath): # 读取txt路径，xml保存路径，数据集图片所在路径
dict = {'0': "0", # 字典对类型进行转换
'1': "1",
'2': "2",
'3': "3"}
files = os.listdir(txtPath)
for i, name in enumerate(files):
xmlBuilder = Document()
annotation = xmlBuilder.createElement("annotation") # 创建annotation标签
xmlBuilder.appendChild(annotation)
txtFile=open(txtPath+name)
txtList = txtFile.readlines()
img = cv2.imread(picPath+name[0:-4]+".jpg")
Pheight, Pwidth, Pdepth=img.shape
flag = 0
for i in txtList:
flag += 1
oneline = i.strip().split(" ")
folder = xmlBuilder.createElement("folder") # folder标签
folderContent = xmlBuilder.createTextNode("VOC2007")
folder.appendChild(folderContent)
annotation.appendChild(folder)
if flag == 1:
filename = xmlBuilder.createElement("filename") # filename标签
filenameContent = xmlBuilder.createTextNode(name[0:-4]+".jpg")
filename.appendChild(filenameContent)
annotation.appendChild(filename)
size = xmlBuilder.createElement("size") # size标签
width = xmlBuilder.createElement("width") # size子标签width
widthContent = xmlBuilder.createTextNode(str(Pwidth))
width.appendChild(widthContent)
size.appendChild(width)
height = xmlBuilder.createElement("height") # size子标签height
heightContent = xmlBuilder.createTextNode(str(Pheight))
height.appendChild(heightContent)
size.appendChild(height)
depth = xmlBuilder.createElement("depth") # size子标签depth
depthContent = xmlBuilder.createTextNode(str(Pdepth))
depth.appendChild(depthContent)
size.appendChild(depth)
annotation.appendChild(size)
object = xmlBuilder.createElement("object")
picname = xmlBuilder.createElement("name")
nameContent = xmlBuilder.createTextNode(dict[oneline[0]])
picname.appendChild(nameContent)
object.appendChild(picname)
pose = xmlBuilder.createElement("pose")
poseContent = xmlBuilder.createTextNode("Unspecified")
pose.appendChild(poseContent)
object.appendChild(pose)
truncated = xmlBuilder.createElement("truncated")
truncatedContent = xmlBuilder.createTextNode("0")
truncated.appendChild(truncatedContent)
object.appendChild(truncated)
difficult = xmlBuilder.createElement("difficult")
difficultContent = xmlBuilder.createTextNode("0")
difficult.appendChild(difficultContent)
object.appendChild(difficult)
bndbox = xmlBuilder.createElement("bndbox")
xmin = xmlBuilder.createElement("xmin")
mathData=int(((float(oneline[1]))*Pwidth+1)-(float(oneline[3]))*0.5*Pwidth)
xminContent = xmlBuilder.createTextNode(str(mathData))
xmin.appendChild(xminContent)
bndbox.appendChild(xmin)
ymin = xmlBuilder.createElement("ymin")
mathData = int(((float(oneline[2]))*Pheight+1)-(float(oneline[4]))*0.5*Pheight)
yminContent = xmlBuilder.createTextNode(str(mathData))
ymin.appendChild(yminContent)
bndbox.appendChild(ymin)
xmax = xmlBuilder.createElement("xmax")
mathData = int(((float(oneline[1]))*Pwidth+1)+(float(oneline[3]))*0.5*Pwidth)
xmaxContent = xmlBuilder.createTextNode(str(mathData))
xmax.appendChild(xmaxContent)
bndbox.appendChild(xmax)
ymax = xmlBuilder.createElement("ymax")
mathData = int(((float(oneline[2]))*Pheight+1)+(float(oneline[4]))*0.5*Pheight)
ymaxContent = xmlBuilder.createTextNode(str(mathData))
ymax.appendChild(ymaxContent)
bndbox.appendChild(ymax)
object.appendChild(bndbox)
annotation.appendChild(object)
f = open(xmlPath+name[0:-4]+".xml", 'w')
xmlBuilder.writexml(f, indent='\t', newl='\n', addindent='\t', encoding='utf-8')
f.close()
makexml("./label_txt/","./label_xml/","./image/")
其中：
label_txt: 存放txt格式的文件label_xml: 存放xml格式的文件image: 存放本地图片