在使用yolov5制作数据集时,yolov5使用txt格式的标签,打标签的工具如labelimg使用的是xml格式的标签,需要进行数据集格式的转换:
yolov5保存检测结果的txt标签
python3.8 detect.py --weights '/home/*/**.pt' --source '/home/*/images/*.png' --device 0 --save-txt
import os
import xml.etree.ElementTree as ET
from PIL import Image
import numpy as np
# 图片文件夹,后面的/不能省
img_path = '/home/**/'
# txt文件夹,后面的/不能省
labels_path = '/home/**/'
# xml存放的文件夹,后面的/不能省
annotations_path = '/home/**/'
labels = os.listdir(labels_path)
# 类别
classes = ["**"] #类别名
# 图片的高度、宽度、深度
sh = sw = sd = 0
def write_xml(imgname, sw, sh, sd, filepath, labeldicts):
'''
imgname: 没有扩展名的图片名称
'''
# 创建Annotation根节点
root = ET.Element('Annotation')
# 创建filename子节点,无扩展名
ET.SubElement(root, 'filename').text = str(imgname)
# 创建size子节点
sizes = ET.SubElement(root,'size')
ET.SubElement(sizes, 'width').text = str(sw)
ET.SubElement(sizes, 'height').text = str(sh)
ET.SubElement(sizes, 'depth').text = str(sd)
for labeldict in labeldicts:
objects = ET.SubElement(root, 'object')
ET.SubElement(objects, 'name').text = labeldict['name']
ET.SubElement(objects, 'pose').text = 'Unspecified'
ET.SubElement(objects, 'truncated').text = '0'
ET.SubElement(objects, 'difficult').text = '0'
bndbox = ET.SubElement(objects,'bndbox')
ET.SubElement(bndbox, 'xmin').text = str(int(labeldict['xmin']))
ET.SubElement(bndbox, 'ymin').text = str(int(labeldict['ymin']))
ET.SubElement(bndbox, 'xmax').text = str(int(labeldict['xmax']))
ET.SubElement(bndbox, 'ymax').text = str(int(labeldict['ymax']))
tree = ET.ElementTree(root)
tree.write(filepath, encoding='utf-8')
for label in labels:
with open(labels_path + label, 'r') as f:
img_id = os.path.splitext(label)[0]
contents = f.readlines()
labeldicts = []
for content in contents:
# !!!这里要看你的图片格式了,我这里是png,注意修改
img = np.array(Image.open(img_path + label.strip('.txt') + '.png'))
# 图片的高度和宽度
sh, sw, sd = img.shape[0], img.shape[1], img.shape[2]
content = content.strip('\n').split()
x = float(content[1])*sw
y = float(content[2])*sh
w = float(content[3])*sw
h = float(content[4])*sh
# 坐标的转换,x_center y_center width height -> xmin ymin xmax ymax
new_dict = {'name': classes[int(content[0])],
'difficult': '0',
'xmin': x+1-w/2,
'ymin': y+1-h/2,
'xmax': x+1+w/2,
'ymax': y+1+h/2
}
labeldicts.append(new_dict)
write_xml(img_id, sw, sh, sd, annotations_path + label.strip('.txt') + '.xml', labeldicts)
#[转载链接](https://zhuanlan.zhihu.com/p/383660741)
import os
import xml.etree.ElementTree as ET
from decimal import Decimal
dirpath = '/home/*/' # 原来存放xml文件的目录
newdir = '/home/*/' # 修改label后形成的txt目录
if not os.path.exists(newdir):
os.makedirs(newdir)
for fp in os.listdir(dirpath):
root = ET.parse(os.path.join(dirpath, fp)).getroot()
xmin, ymin, xmax, ymax = 0, 0, 0, 0
sz = root.find('size')
width = float(sz[0].text)
height = float(sz[1].text)
filename = root.find('filename').text
print(fp)
with open(os.path.join(newdir, fp.split('.')[0] + '.txt'), 'a+') as f:
for child in root.findall('object'): # 找到图片中的所有框
sub = child.find('bndbox') # 找到框的标注值并进行读取
sub_label = child.find('name')
xmin = float(sub[0].text)
ymin = float(sub[1].text)
xmax = float(sub[2].text)
ymax = float(sub[3].text)
try: # 转换成yolov的标签格式,需要归一化到(0-1)的范围内
x_center = Decimal(str(round(float((xmin + xmax) / (2 * width)),6))).quantize(Decimal('0.000000'))
y_center = Decimal(str(round(float((ymin + ymax) / (2 * height)),6))).quantize(Decimal('0.000000'))
w = Decimal(str(round(float((xmax - xmin) / width),6))).quantize(Decimal('0.000000'))
h = Decimal(str(round(float((ymax - ymin) / height),6))).quantize(Decimal('0.000000'))
print(str(x_center) + ' ' + str(y_center)+ ' '+str(w)+ ' '+str(h))
#读取需要的标签
#if sub_label.text == 'armor':
f.write(' '.join([str(0), str(x_center), str(y_center), str(w), str(h) + '\n']))
except ZeroDivisionError:
print(' width有问题')
'''有其他标签选用
if sub_label.text == 'xxx':
f.write(' '.join([str(1), str(x_center), str(y_center), str(w), str(h) + '\n']))
if sub_label.text == 'xxx':
f.write(' '.join([str(2), str(x_center), str(y_center), str(w), str(h) + '\n']))'''
# with open(os.path.join(newdir, fp.split('.')[0] + '.txt'), 'a+') as f:
# f.write(' '.join([str(2), str(x_center), str(y_center), str(w), str(h) + '\n']))