# enginex-bi_series-image-classification
## Quickstart
### 启动服务
修改docker.sh的脚本中$mountpath为本地的模型挂载路径
然后运行./docker.sh
当打印出以下内容时表示模型load成功
```
2026-04-08 06:22:55 /workspace/transformers_server.py INFO model loaded successfully
INFO:     Application startup complete.
INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
```

### 运行测试
执行 python3 test.py
打印出以下内容, 图片分类的top5 labels:
```
status_code: 200
response:
{"labels":[282,281,761,285,612]}
```