EfficientDet_PyTorch 目标检测(Object Detection).zip

# EfficientDet_PyTorch 注意事项(NOTICE): 1. 训练请使用SGD优化器(with momentum 0.9). 不要使用Adam. 会造成不收敛. Use SGD optimizer for training(with momentum 0.9). Do not use Adam. It will cause a nonconvergence 2. 有两个分支(branch)，一个是按照论文书写(official)、一个是参考`zylo117`的代码(master)， 并使用了他的预训练模型书写(万分感谢)，请按实际情况选择 There are two branches, one(official) was written according to the paper, the other(master) was written referring to the code of 'Zylo117' and use his pre-training model(thank you very much), please choose according to the actual situation 3. `train_example.py` 的意义是展示模型输入的格式 The meaning of `train_example.py` is to show the format of the model input 4. 自己训练的时候，请使用`EfficientNet`预训练模型(推荐使用official) Use 'EfficientNet' pre-training model when you train yourself (Official is recommended) ## Reference 1. 论文(paper): [https://arxiv.org/pdf/1911.09070.pdf](https://arxiv.org/pdf/1911.09070.pdf) 2. 代码参考(reference code): [https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch](https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch) 3. EfficientNet 主干网代码来源(Backbone code source): [https://github.com/Jintao-Huang/EfficientNet_PyTorch](https://github.com/Jintao-Huang/EfficientNet_PyTorch) 4. 预训练模型来自(The pre-training model comes from): [https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch](https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch) 因为修改了模型，所以我把预训练模型的state_dict进行了重组，并进行发布 (Because I changed the model, I reorganized the state_dict for the pretraining model and release it) 5. VOC0712 数据集链接 链接：[https://pan.baidu.com/s/17iop7UBnSGExW64cip-pYw](https://pan.baidu.com/s/17iop7UBnSGExW64cip-pYw) 提取码：sdvx 权重见 release. 或在百度云中下载: 链接：[https://pan.baidu.com/s/1VrO0eBmSHlB8_haEJ7WbuA](https://pan.baidu.com/s/1VrO0eBmSHlB8_haEJ7WbuA) 提取码：2kq9 ## 使用方式(How to use) #### 1. 预测图片(Predict images) ``` python3 pred_image.py ``` #### 2. 预测视频(Predict video) ``` python3 pred_video.py ``` #### 3. 简单的训练案例(Simple training cases) ``` python3 train_example.py ``` #### 4. 训练 ``` python3 make_dataset.py python3 train.py ``` ## 性能 如果打不开可在`images/`与`docs/`文件夹中查看  #### d0效果   ## 运行环境(environment) torch 1.7.1 torchvision 0.8.2