1. voc转yolo
import xml.etree.ElementTree as ET
import pickle
import os
from os import listdir, getcwd
from os.path import join
sets = ['trainval','test']
classes = [ 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog',
'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor' ] # voc的20个类别
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('./model/dataset/VOCdevkit/VOC2007/Annotations/%s.xml' % (image_id))
#填原来voc数据集xml标注数据文件所在路径
out_file = open('./labels/test/%s.txt' % (image_id), 'w')
#填转换后的yolov5需要labels文件所在路径
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'):
difficult = obj.find('difficult').text
cls = obj.find('name').text
if cls not in classes or int(difficult) == 1:
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')
# if __name__ == "__main__":
wd = getcwd()
for image_set in sets:
if not os.path.exists('./labels/'):
os.makedirs('./labels/')
#创建转换后labels存放文件路径
image_ids = open('./model/dataset/VOCdevkit/VOC2007/ImageSets/Main/%s.txt' % (image_set)).read().strip().split()
#list_file = open('./%s.txt' % (image_set), 'w')
for image_id in image_ids:
#list_file.write('dataset/VOCdevkit/VOC2007/JPEGImages/%s.jpg\n' % (image_id))
convert_annotation(image_id)
list_file.close()以上代码可以将voc格式的xml注释文件转换成yolov5格式的labels注释文件，只需要将路径改为自己的，直接运行即可。
2.yolo转voc
import os
import glob
from PIL import Image
voc_annotations = 'voc_test/Annotations/'
yolo_txt = 'yolo_test/labels/'
img_path = 'yolo_test/images/'
labels = [ 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog',
'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor' ] # label for datasets
# 图像存储位置
src_img_dir = img_path
# 图像的txt文件存放位置
src_txt_dir = yolo_txt
src_xml_dir = voc_annotations
img_Lists = glob.glob(src_img_dir + '/*.jpg')
img_basenames = []
for item in img_Lists:
img_basenames.append(os.path.basename(item))
img_names = []
for item in img_basenames:
temp1, temp2 = os.path.splitext(item)
img_names.append(temp1)
for img in img_names:
im = Image.open((src_img_dir + '/' + img + '.jpg'))
width, height = im.size
# 打开txt文件
gt = open(src_txt_dir + '/' + img + '.txt').read().splitlines()
print(gt)
if gt:
# 将主干部分写入xml文件中
xml_file = open((src_xml_dir + '/' + img + '.xml'), 'w')
xml_file.write('<annotation>\n')
xml_file.write(' <folder>VOC2007</folder>\n')
xml_file.write(' <filename>' + str(img) + '.jpg' + '</filename>\n')
xml_file.write(' <size>\n')
xml_file.write(' <width>' + str(width) + '</width>\n')
xml_file.write(' <height>' + str(height) + '</height>\n')
xml_file.write(' <depth>3</depth>\n')
xml_file.write(' </size>\n')
# write the region of image on xml file
for img_each_label in gt:
spt = img_each_label.split(' ') # 这里如果txt里面是以逗号‘，’隔开的，那么就改为spt = img_each_label.split(',')。
print(f'spt:{spt}')
xml_file.write(' <object>\n')
xml_file.write(' <name>' + str(labels[int(spt[0])]) + '</name>\n')
xml_file.write(' <pose>Unspecified</pose>\n')
xml_file.write(' <truncated>0</truncated>\n')
xml_file.write(' <difficult>0</difficult>\n')
xml_file.write(' <bndbox>\n')
center_x = round(float(spt[1].strip()) * width)
center_y = round(float(spt[2].strip()) * height)
bbox_width = round(float(spt[3].strip()) * width)
bbox_height = round(float(spt[4].strip()) * height)
xmin = str(int(center_x - bbox_width / 2))
ymin = str(int(center_y - bbox_height / 2))
xmax = str(int(center_x + bbox_width / 2))
ymax = str(int(center_y + bbox_height / 2))
xml_file.write(' <xmin>' + xmin + '</xmin>\n')
xml_file.write(' <ymin>' + ymin + '</ymin>\n')
xml_file.write(' <xmax>' + xmax + '</xmax>\n')
xml_file.write(' <ymax>' + ymax + '</ymax>\n')
xml_file.write(' </bndbox>\n')
xml_file.write(' </object>\n')
xml_file.write('</annotation>')yolo格式的txt文件转换成 voc的xml格式代码见上图，改路径直接运行（这个参考了Yolo标准数据集格式转Voc数据集_YANJINING-CSDN博客_yolo数据集转voc）
版权声明：本文为CSDN博主「kkcodeer」的原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/weixin_42148914/article/details/121931849
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