Files
ieemoo-ai-gift/datasets_preprocess/voc_label_.py
2025-06-21 13:37:38 +08:00

103 lines
3.7 KiB
Python

# 标签xml转txt以及无xml的负样本空txt
import xml.etree.ElementTree as ET
import os, cv2
from os import getcwd
sets = ['train', 'val', 'test']
classes = ['tag', 'bandage', 'word', 'package']
def convert(size, box):
dw = 1. / (size[0])
dh = 1. / (size[1])
x = (box[0] + box[1]) / 2.0 - 1
y = (box[2] + box[3]) / 2.0 - 1
w = box[1] - box[0]
h = box[3] - box[2]
x = x * dw
y = y * dh
w = w * dw
h = h * dh
return x, y, w, h
def convert_annotation(image_id, imgname_list, label_path, Annotation_path, image_path):
out_file = open(label_path + '%s.txt' % (image_id), 'w')
if os.path.exists(Annotation_path + '%s.xml' % (image_id)):
try:
in_file = open(Annotation_path + '%s.xml' % (image_id), encoding='UTF-8')
tree = ET.parse(in_file)
root = tree.getroot()
size = root.find('size')
# if size!=None:
# w = int(size.find('width').text)
# h = int(size.find('height').text)
# else:
img_name = image_id + ".jpg"
img_path = image_path + f"{img_name}"
img_data_ = cv2.imread(img_path)
h, w = img_data_.shape[0], img_data_.shape[1]
for obj in root.iter('object'):
# difficult = obj.find('difficult').text
# difficult = obj.find('Difficult').text
cls = obj.find('name').text
# cls = cls[:13]
# print("cls:", cls, len(cls))
# if cls not in classes or int(difficult) == 1:
# continue
try:
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))
b1, b2, b3, b4 = b
# 标注越界修正
if b2 > w:
b2 = w
if b4 > h:
b4 = h
b = (b1, b2, b3, b4)
bb = convert((w, h), b)
out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')
except Exception as e:
print(e, image_id)
imgname_list.append(image_id)
except Exception as e:
print('error:', e, image_id)
else:
out_file.write('\n')
# abs_path = os.getcwd()
image_path = '/home/lc/data_center/gift/v2/images/' # img实际存放地址
Annotation_path = '/home/lc/data_center/gift/v2/xml/' # xml实际存放地址
label_path = '/home/lc/data_center/gift/v2/labels/' # 保存路径
# wd = getcwd()
imgname_list = []
for image_set in sets:
if not os.path.exists(label_path):
os.makedirs(label_path)
# image_ids = open('data/ImageSets/Main/%s.txt' % (image_set), encoding='gbk').read().strip().split()
# image_ids = open('data/ImageSets/Main_0820/%s.txt' % (image_set)).read().strip().split()
image_ids = open('/home/lc/data_center/gift/yolov10_data/Main/%s.txt' % (image_set)).read().split('\n')
list_file = open('/home/lc/data_center/gift/yolov10_data/%s.txt' % (image_set), 'w')
for image_id in image_ids:
list_file.write(image_path + '%s.jpg\n' % (image_id))
# print(image_id, "Converting...")
convert_annotation(image_id, imgname_list, label_path, Annotation_path, image_path)
list_file.close()
with open('error_img.txt', 'w+') as f:
for i_name in imgname_list:
f.write(i_name + '\n')
print("error imgname_list:", imgname_list)