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-# SSD
-
-## 环境配置
-
-### Docker
-
-推荐使用docker方式运行，提供拉取的docker镜像：
-
-```bash
-docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-centos7.6-dtk24.04-py310
-#-v挂载工作目录
-docker run -it  --shm-size 80g --network=host --name=SSD --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-centos7.6-dtk24.04-py310 bin/bash
-
-```
-
-安装docker中没有的依赖：
-
-```bash
-cd SSD
-pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
-```
-
-
-## 训练
-
-### 数据集设置
-#### VOC0712
-数据集下载地址：
-[SCNet](http://113.200.138.88:18080/aidatasets/voc0712/-/tree/Maintainers?ref_type=heads)
-
-对于VOC0712数据集，文件结构如下（进入VOCdevkit0712/voc2007_2012/VOCdevkit即可）：
-```
-VOC_ROOT
-|__ VOC2007
-    |_ JPEGImages
-    |_ Annotations
-    |_ ImageSets
-    |_ SegmentationClass
-|__ VOC2012
-    |_ JPEGImages
-    |_ Annotations
-    |_ ImageSets
-    |_ SegmentationClass
-
-在当前项目中，在`SSD/ssd/config/path_catlog.py`中第5行`DATA_DIR = '{数据集所在文件夹}/VOCdevkit0712/voc2007_2012/VOCdevkit'`修改数据集地址。
-```
-### 单DCU训练
-
-```bash
-export LD_LIBRARY_PATH=/opt/hayhal/hydm/lib:/opt/hayhal/lib:/opt/dtk-24.04.1/.hyhal/hydm/lib:$LD_LIBRARY_PATH
-python train.py --config-file configs/vgg_ssd300_voc0712.yaml
-```
-
-### 多DCU训练
-
-```bash
-export NGPUS=4
-python -m torch.distributed.launch --nproc_per_node=$NGPUS train.py --config-file configs/vgg_ssd300_voc0712.yaml SOLVER.WARMUP_FACTOR 0.03333 SOLVER.WARMUP_ITERS 1000
-```
-## 评估
-
-### 单DCU评估
-
-```bash
-python test.py --config-file configs/vgg_ssd300_voc0712.yaml
-```
-
-### 多DCU评估
-
-```bash
-export NGPUS=4
-python -m torch.distributed.launch --nproc_per_node=$NGPUS test.py --config-file configs/vgg_ssd300_voc0712.yaml
-```
-
-## 模型仓库
-### COCO:
-
-| Backbone       | Input Size  |          box AP                  | Model Size |  Download |
-| :------------: | :----------:|   :--------------------------:   | :--------: | :-------: |
-|  VGG16         |     300     |          25.2                    |  262MB     | [model](https://github.com/lufficc/SSD/releases/download/1.2/vgg_ssd300_coco_trainval35k.pth)   |
-|  VGG16         |     512     |          29.0                    |  275MB     | [model](https://github.com/lufficc/SSD/releases/download/1.2/vgg_ssd512_coco_trainval35k.pth)   |
-
-### PASCAL VOC:
-
-| Backbone         | Input Size  |          mAP                     | Model Size | Download  |
-| :--------------: | :----------:|   :--------------------------:   | :--------: | :-------: |
-|  VGG16           |     300     |          77.7                    |   201MB    | [model](https://github.com/lufficc/SSD/releases/download/1.2/vgg_ssd300_voc0712.pth)  |
-|  VGG16           |     512     |          80.7                    |   207MB    | [model](https://github.com/lufficc/SSD/releases/download/1.2/vgg_ssd512_voc0712.pth)  |
-|  Mobilenet V2    |     320     |          68.9                    |   25.5MB   | [model](https://github.com/lufficc/SSD/releases/download/1.2/mobilenet_v2_ssd320_voc0712_v2.pth) |
-|  Mobilenet V3    |     320     |          69.5                    |   29.9MB   | [model](https://github.com/lufficc/SSD/releases/download/1.2/mobilenet_v3_ssd320_voc0712.pth) |
-|  EfficientNet-B3 |     300     |          73.9                    |   97.1MB   | [model](https://github.com/lufficc/SSD/releases/download/1.2/efficient_net_b3_ssd300_voc0712.pth) |
-
-
-
-## 引用
-如果你在研究中使用这个项目，请引用这个项目。
-```text
- of SSD in PyTorch}},
-    year = {2018},
-    howpublished = {\url{https://github.com/lufficc/SSD}}
-}
-```