1、转化前yolo格式数据集路径结构

2、转化后yolo格式数据集路径结构

3、转化脚本（可以直接复制使用）

import os
import argparse
import shutil
def makdirs(opt,tests_flag):
    images_train = os.path.join(opt.save_root_path, 'images/train')
    images_val = os.path.join(opt.save_root_path ,'images/val')

    label_train = os.path.join(opt.save_root_path, 'labels/train')
    label_val = os.path.join(opt.save_root_path,'labels/val')



    os.makedirs(images_train,exist_ok=True)
    os.makedirs(images_val, exist_ok=True)
    os.makedirs(label_train, exist_ok=True)
    os.makedirs(label_val, exist_ok=True)
    if tests_flag:
        images_test = os.path.join(opt.save_root_path, 'images/test')
        label_test = os.path.join(opt.save_root_path, 'labels/test')
        os.makedirs(images_test, exist_ok=True)
        os.makedirs(label_test, exist_ok=True)
    else:
        images_test, label_test=0,0
    return images_train,images_val,label_train,label_val,images_test,label_test

def transform_dic(opt):
    train_img=[]
    train_label=[]

    val_img=[]
    val_label=[]

    test_img=[]
    test_label=[]

    # if os.listdir(os.path.join(opt.ori_root_path,'train')))
    if os.path.exists(os.path.join(opt.ori_root_path,'train')):
        base_train_images=os.path.join(os.path.join(opt.ori_root_path,'train'),'images')
        base_train_labels = os.path.join(os.path.join(opt.ori_root_path, 'train'), 'labels')
        train_img=[os.path.join(base_train_images,img_name) for img_name in os.listdir(base_train_images)]
        train_label=[os.path.join(base_train_labels,label_name) for label_name in os.listdir(base_train_labels)]

    if os.path.exists(os.path.join(opt.ori_root_path, 'valid')):
        base_val_images=os.path.join(os.path.join(opt.ori_root_path,'valid'),'images')
        base_val_labels = os.path.join(os.path.join(opt.ori_root_path, 'valid'), 'labels')
        val_img=[os.path.join(base_val_images,img_name) for img_name in os.listdir(base_val_images)]
        val_label=[os.path.join(base_val_labels,label_name) for label_name in os.listdir(base_val_labels)]

    if os.path.exists(os.path.join(opt.ori_root_path, 'test')):
        base_test_images = os.path.join(os.path.join(opt.ori_root_path, 'test'), 'images')
        base_test_labels = os.path.join(os.path.join(opt.ori_root_path, 'test'), 'labels')
        test_img = [os.path.join(base_test_images, img_name) for img_name in os.listdir(base_test_images)]
        test_label = [os.path.join(base_test_labels, label_name) for label_name in os.listdir(base_test_labels)]
        tests_flag = True
    else:
        tests_flag = False


    images_train,images_val,label_train,label_val,images_test,label_test = makdirs(opt, tests_flag)
    train_len,val_len,test_len= len(train_img),len(val_img),len(test_img)
    for train_index in range(train_len):
        #在windows里面，split时用'\\',在linux里面，请用'\/'
        shutil.copy2(train_img[train_index],os.path.join(images_train,train_img[train_index].split('\\')[-1]))
        shutil.copy2(train_label[train_index],os.path.join(label_train,train_label[train_index].split('\\')[-1]))
        print(os.path.join(images_train,train_img[train_index].split('\\')[-1]))
    for val_index in range(val_len):
        #在windows里面，split时用'\\',在linux里面，请用'\/'
        shutil.copy2(val_img[val_index],os.path.join(images_val,val_img[val_index].split('\\')[-1]))
        shutil.copy2(val_label[val_index],os.path.join(label_val,val_label[val_index].split('\\')[-1]))
    if len(images_test)!=0 and len(label_test)!=0:
        for test_index in range(test_len):
            #在windows里面，split时用'\\',在linux里面，请用'\/'
            shutil.copy2(test_img[test_index],os.path.join(images_test,test_img[test_index].split('\\')[-1]))
            shutil.copy2(test_label[test_index],os.path.join(label_test,test_label[test_index].split('\\')[-1]))




if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--ori_root_path', nargs='+', type=str, default='./Roadsyolo', help='原始数据')
    parser.add_argument('--save_root_path', nargs='+', type=str, default='./newyolodatas',help='新的数据集保存路径')
    opt = parser.parse_args()
    transform_dic(opt)