# 将图片和标注数据按比例切分为 训练集和测试集
import shutil
import random
import os
import argparse
# 检查文件夹是否存在
def mkdir(path):
if not os.path.exists(path):
os.makedirs(path)
def main(image_dir, txt_dir, save_dir):
# 创建文件夹
mkdir(save_dir)
images_dir = os.path.join(save_dir, 'images')
labels_dir = os.path.join(save_dir, 'labels')
img_train_path = os.path.join(images_dir, 'train')
img_test_path = os.path.join(images_dir, 'test')
img_val_path = os.path.join(images_dir, 'val')
label_train_path = os.path.join(labels_dir, 'train')
label_test_path = os.path.join(labels_dir, 'test')
label_val_path = os.path.join(labels_dir, 'val')
mkdir(images_dir);
mkdir(labels_dir);
mkdir(img_train_path);
mkdir(img_test_path);
mkdir(img_val_path);
mkdir(label_train_path);
mkdir(label_test_path);
mkdir(label_val_path);
# 数据集划分比例,训练集75%,验证集15%,测试集15%,按需修改
train_percent = 0.8
val_percent = 0.1
test_percent = 0.1
total_txt = os.listdir(txt_dir)
num_txt = len(total_txt)
list_all_txt = range(num_txt) # 范围 range(0, num)
num_train = int(num_txt * train_percent)
num_val = int(num_txt * val_percent)
num_test = num_txt - num_train - num_val
train = random.sample(list_all_txt, num_train)
# 在全部数据集中取出train
val_test = [i for i in list_all_txt if not i in train]
# 再从val_test取出num_val个元素,val_test剩下的元素就是test
val = random.sample(val_test, num_val)
print("训练集数目:{}, 验证集数目:{},测试集数目:{}".format(len(train), len(val), len(val_test) - len(val)))
for i in list_all_txt:
name = total_txt[i][:-4]
srcImage = os.path.join(image_dir, name + '.jpg')
srcLabel = os.path.join(txt_dir, name + '.txt')
if i in train:
dst_train_Image = os.path.join(img_train_path, name + '.jpg')
dst_train_Label = os.path.join(label_train_path, name + '.txt')
shutil.copyfile(srcImage, dst_train_Image)
shutil.copyfile(srcLabel, dst_train_Label)
elif i in val:
dst_val_Image = os.path.join(img_val_path, name + '.jpg')
dst_val_Label = os.path.join(label_val_path, name + '.txt')
shutil.copyfile(srcImage, dst_val_Image)
shutil.copyfile(srcLabel, dst_val_Label)
else:
dst_test_Image = os.path.join(img_test_path, name + '.jpg')
dst_test_Label = os.path.join(label_test_path, name + '.txt')
shutil.copyfile(srcImage, dst_test_Image)
shutil.copyfile(srcLabel, dst_test_Label)
if __name__ == '__main__':
"""
python split_datasets.py --image-dir my_datasets/color_rings/imgs --txt-dir my_datasets/color_rings/txts --save-dir my_datasets/color_rings/train_data
"""
parser = argparse.ArgumentParser(description='split datasets to train,val,test params')
parser.add_argument('--image-dir', type=str,default='D:/ultralytics-main/data', help='image path dir')
parser.add_argument('--txt-dir', type=str,default='D:/ultralytics-main/data/txt' , help='txt path dir')
parser.add_argument('--save-dir', default='D:/ultralytics-main/data/split',type=str, help='save dir')
args = parser.parse_args()
image_dir = args.image_dir
txt_dir = args.txt_dir
save_dir = args.save_dir
main(image_dir, txt_dir, save_dir)
没有合适的资源?快使用搜索试试~ 我知道了~
YOLOv8实例分割制作自己的数据集代码
![preview](https://csdnimg.cn/release/downloadcmsfe/public/img/white-bg.ca8570fa.png)
共10个文件
xml:5个
py:3个
iml:1个
![preview-icon](https://csdnimg.cn/release/downloadcmsfe/public/img/scale.ab9e0183.png)
![star](https://csdnimg.cn/release/downloadcmsfe/public/img/star.98a08eaa.png)
温馨提示
对数据集进行转换和划分。该文件包含两个代码文件,分别为json2txt.py和split.py。 使用方法: 1.下载labelme,对数据进行标注。 2.对数据集进行转换和划分。注意:在数据标注的时候将图片和json文件放在不同的文件夹里。如下图所示,另外新建两个文件夹txt 和split。 3.新建json2txt.py文件,修改文件路径为自己的路径。 4.新建split.py,修改文件路径为自己的路径。 5.新建seg.yaml文件 ,按照下列格式创建 我一般写成绝对路径,方便一点。 6.然后开始训练即可。
资源推荐
资源详情
资源评论
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![rar](https://img-home.csdnimg.cn/images/20210720083606.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![docx](https://img-home.csdnimg.cn/images/20210720083331.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![rar](https://img-home.csdnimg.cn/images/20210720083606.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![apk](https://img-home.csdnimg.cn/images/20210720083646.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![7z](https://img-home.csdnimg.cn/images/20210720083312.png)
![txt](https://img-home.csdnimg.cn/images/20210720083642.png)
收起资源包目录
![package](https://csdnimg.cn/release/downloadcmsfe/public/img/package.f3fc750b.png)
![folder](https://csdnimg.cn/release/downloadcmsfe/public/img/folder.005fa2e5.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![folder](https://csdnimg.cn/release/downloadcmsfe/public/img/folder.005fa2e5.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![folder](https://csdnimg.cn/release/downloadcmsfe/public/img/folder.005fa2e5.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
![file-type](https://csdnimg.cn/release/download/static_files/pc/images/minetype/UNKNOWN.png)
共 10 条
- 1
资源评论
![avatar-default](https://csdnimg.cn/release/downloadcmsfe/public/img/lazyLogo2.1882d7f4.png)
- qq_373696192024-05-28#内容详尽 #注释完整
![avatar](https://profile-avatar.csdnimg.cn/806f08fbc8b340bc9a603244936f1032_m0_51530640.jpg!1)
![avatar-vip](https://csdnimg.cn/release/downloadcmsfe/public/img/user-vip.1c89f3c5.png)
AICurator
- 粉丝: 6103
- 资源: 115
上传资源 快速赚钱
我的内容管理 展开
我的资源 快来上传第一个资源
我的收益
登录查看自己的收益我的积分 登录查看自己的积分
我的C币 登录后查看C币余额
我的收藏
我的下载
下载帮助
![voice](https://csdnimg.cn/release/downloadcmsfe/public/img/voice.245cc511.png)
![center-task](https://csdnimg.cn/release/downloadcmsfe/public/img/center-task.c2eda91a.png)
安全验证
文档复制为VIP权益,开通VIP直接复制
![dialog-icon](https://csdnimg.cn/release/downloadcmsfe/public/img/green-success.6a4acb44.png)