添加了MIT License

LICENSE

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+MIT License
+
+Copyright (c) 2025 C-a-r-r-y
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# MobileNetV2 图像分类项目
+
+本项目使用PyTorch框架实现基于MobileNetV2的图像分类模型。
+
+## 环境要求
+- Python 3.7+
+- PyTorch 1.10+
+- torchvision
+- tqdm
+
+安装依赖：
+```bash
+pip install torch torchvision tqdm
+```
+
+## 数据准备
+1. 创建以下目录结构：
+```
+train_data/
+    1/
+        train/
+        test/
+model/
+    1/
+test_image/
+```
+
+2. 将训练图像放入`train_data/1/train`目录，每个类别一个子目录
+3. 将测试图像放入`train_data/1/test`目录，保持相同的类别结构
+
+## 训练模型
+运行训练脚本：
+```bash
+python train_mobilenetv2.py
+```
+
+训练参数：
+- 训练轮数：20
+- 批量大小：64
+- 学习率：0.0001
+- 优化器：Adam
+- 学习率调度器：ReduceLROnPlateau
+
+## 模型保存
+训练好的模型将保存在`model/1/`目录下，文件名包含训练轮数和准确率。
+
+## 目录结构
+```
+.
+├── train_mobilenetv2.py       # 主训练脚本
+├── pretreatment.ipynb         # 数据预处理notebook
+├── test.ipynb                 # 测试notebook
+├── train_data/                # 训练数据（git忽略）
+│   └── 1/
+│       ├── train/             # 训练图像
+│       └── test/              # 测试图像
+├── model/                     # 保存的模型（git忽略）
+│   └── 1/
+└── test_image/                # 测试图像（git忽略）
+```
+
+## 注意事项
+- 项目使用预训练的MobileNetV2模型
+- 数据增强包括随机裁剪和水平翻转
+- 如果有GPU会自动使用GPU进行训练