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ModelZoo
SSD_pytorch
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e7a9e883
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# SSD
## 论文
SSD: Single Shot MultiBox Detector
-
https://link.springer.com/chapter/10.1007/978-3-319-46448-0_2
## 模型结构
SSD模型结构包括一个基础卷积网络(如VGG16或ResNet)作为特征提取器,后接多个卷积层,这些层负责生成不同尺度的特征图,以便于检测不同大小的物体。
## 算法原理
SSD通过在每个特征图上直接预测边界框和类别概率,使用多种尺寸的默认框来覆盖图像中的目标,在一个前向传播中完成目标检测,显著提高了检测速度。
## 环境配置
### Docker
```
bash
docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-centos7.6-dtk24.04-py310
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
```
其它非深度学习库参照requirements.txt安装:
```
pip install -r requirements.txt
```
## 数据集
在本测试中可以使用Pascal VOC0712 (2007 + 2012)数据集。
-
数据集下载地址:
-
[
SCNet AIDatasets
](
http://113.200.138.88:18080/aidatasets/voc0712/-/tree/Maintainers?ref_type=heads
)
数据集的目录结构如下(进入VOCdevkit0712/voc2007_2012/VOCdevkit即可):
```
VOC_ROOT
|__ VOC20xx
|_ JPEGImages
|_ Annotations
|_ ImageSets
|_ SegmentationClass
|__ VOC20xx
|_ JPEGImages
|_ Annotations
|_ ImageSets
|_ SegmentationClass
|__ ...
```
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。
## 训练
### 单卡训练
```
bash
python train.py
--config-file
configs/vgg_ssd300_voc0712.yaml
```
### 多卡训练
```
python -m torch.distributed.launch --nproc_per_node=4 train.py --config-file configs/vgg_ssd300_voc0712.yaml SOLVER.WARMUP_FACTOR 0.03333 SOLVER.WARMUP_ITERS 1000
```
## 推理
### 单卡推理
```
bash
python test.py
--config-file
configs/vgg_ssd300_voc0712.yaml
```
### 多卡推理
```
python -m torch.distributed.launch --nproc_per_node=4 test.py --config-file configs/vgg_ssd300_voc0712.yaml
```
## 应用场景
### 算法类别
目标检测
### 热点应用行业
金融,交通,教育
## 源码仓库及问题反馈
https://developer.sourcefind.cn/codes/modelzoo/ssd
## 参考资料
https://github.com/lufficc/SSD
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