https://github.com/jintao-huang/efficientnet_pytorch
实现风格与torchvision.models中的网络类似
https://github.com/jintao-huang/efficientnet_pytorch
efficientnet pytorch
Last synced: 5 days ago
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实现风格与torchvision.models中的网络类似
- Host: GitHub
- URL: https://github.com/jintao-huang/efficientnet_pytorch
- Owner: Jintao-Huang
- License: apache-2.0
- Created: 2020-05-14T08:47:07.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2021-05-30T12:34:46.000Z (over 4 years ago)
- Last Synced: 2025-01-12T21:33:30.154Z (9 months ago)
- Topics: efficientnet, pytorch
- Language: Python
- Homepage:
- Size: 965 KB
- Stars: 11
- Watchers: 2
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# efficientnet_pytorch
实现风格与`torchvision.models`中其他网络的类似
(The implementation style is similar to other networks in `torchvision.models`)
## Reference
1. 论文(paper):
[https://arxiv.org/pdf/1905.11946.pdf](https://arxiv.org/pdf/1905.11946.pdf)
2. 代码参考(reference code):
[https://github.com/lukemelas/EfficientNet-PyTorch](https://github.com/lukemelas/EfficientNet-PyTorch)
3. 使用的预训练模型来源(Source of the pre-training model used):
[https://github.com/lukemelas/EfficientNet-PyTorch](https://github.com/lukemelas/EfficientNet-PyTorch)
由于我对模型进行了调整，所以我修改了原预训练模型的state_dict的key值，并进行了发布.
Since I adjusted the model, I modified the state_dict key value of the original pretraining model and release it.
权重见 release. 或在百度云中下载:
链接：[https://pan.baidu.com/s/1HzAZZoJNIoii7uDsnPExHQ](https://pan.baidu.com/s/1HzAZZoJNIoii7uDsnPExHQ)
提取码：4sb5
4. labels_map.txt来源(Source of labels_map.txt):
[https://github.com/lukemelas/EfficientNet-PyTorch/blob/master/examples/simple/labels_map.txt](https://github.com/lukemelas/EfficientNet-PyTorch/blob/master/examples/simple/labels_map.txt)
## 使用方式(How to use)
#### 1. 预测图片(Predict images)
```
python3 std_pred_image.py
```
#### 2. 简单的训练例子(Simple training examples)
```
python3 train_example.py
```
#### 3. train
```
python3 make_dataset.py
python3 train.py
python3 pred_image.py
```
## 性能
见`docs/`文件夹
## 运行环境(environment)
torch 1.8.1
torchvision 0.9.0