https://github.com/mountchicken/resnet18-cifar10
ResNet18 on CIFAR10 reachs 95.09% Accuracy on TestSet
https://github.com/mountchicken/resnet18-cifar10
accuracy95 cifar-10 resnet-18
Last synced: 4 months ago
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ResNet18 on CIFAR10 reachs 95.09% Accuracy on TestSet
- Host: GitHub
- URL: https://github.com/mountchicken/resnet18-cifar10
- Owner: Mountchicken
- Created: 2021-02-05T01:43:08.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2022-02-13T00:33:08.000Z (over 3 years ago)
- Last Synced: 2025-05-12T13:09:31.344Z (5 months ago)
- Topics: accuracy95, cifar-10, resnet-18
- Language: Python
- Homepage:
- Size: 13.7 KB
- Stars: 12
- Watchers: 1
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ResNet18-CIFAR10
ResNet18 on CIFAR10 reachs 95.09% Accuracy on TestSet
## 项目结构
### 文件
- `ResNet18.py`: 定义模型
- `Mydataset.py`:定义数据集以及dataloader，初次运行时请修改其中的`DATASET_PATH`以读取CIFAR10数据集
- `Train.py`: 训练模型，初次运行时请修改其中的`SAVED_PATH`指定模型保存地址
- `Test.py`: 测试模型在训练集准确率
- `ConfusuinMatrix.py`: 绘制单个模型的混淆矩阵
- `Predict.py`: 用以预测单幅图像
- `main_gui.py,widget.ui,ui_widget.py`: GUI封装代码
### 文件夹
- `Models`: 存放预训练的模型参数
## 如何使用
### 如何使用tensorboard进行调参训练
- `pip install tensorboard`
- 在`Train.py`中修改 `TestParameters`，往列表中加入训练参数，代码会自动对所有可能的训练参数进行训练
- 训练结束后，在Anaconda Prompt中执行命令行 ` tensorboard --logdir=runs`
### 如何启动GUI
- `pip install PyQt5`
- `pip install PyQt5-tools`
- 运行文件`main_gui.py`
## 权重下载
[百度云：提取码eh6h](https://pan.baidu.com/s/1VgOpetLpongi74olRT6I5Q)
## 联系方式
- mountchicken@outlook.com