Initial commit: Infrared Equipment Fault Detection HTTP Service

- Add FastAPI microservice for infrared equipment fault detection
- Add dual pyproject.toml: local development and Docker deployment
- Add MANUAL_SETUP.md for manual file placement instructions
- Add Dockerfile for containerized deployment
- Add sample .env.example for PROJECT_ROOT configuration
- Configure gitignore for weights, lib, venv, and environment files
This commit is contained in:
SkyLi
2026-03-28 20:28:32 +08:00
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# 手动部署说明
由于网络限制,权重文件和 whl 包需要手动放置到本地目录。
## 必需文件
### 1. whl 包
- **文件名**: `infrared_data-0.1.0-py3-none-any.whl`
- **存放路径**: `lib/infrared_data-0.1.0-py3-none-any.whl`
- **下载地址**: 联系项目维护者获取
### 2. 模型权重文件
- **文件名**: `best.pt`
- **存放路径**: `weights/best.pt`
- **下载地址**: 联系项目维护者获取
## 目录结构
```
.
├── lib/
│ └── infrared_data-0.1.0-py3-none-any.whl
├── weights/
│ └── best.pt
├── src/
│ ├── __init__.py
│ ├── config.py
│ └── main.py
├── tests/
├── pyproject.toml
└── Dockerfile
```
## 安装步骤
```bash
# 1. 放置上述文件到对应目录
# 2. 创建 .env 文件(包含项目路径)
# 注意:此文件包含绝对路径,每个开发者需要根据实际路径修改
cp .env.example .env # 或手动创建
# 3. 创建虚拟环境并安装依赖
set -a && source .env && uv sync
# 4. 启动服务
set -a && source .env && INFERENCE_DEVICE=cpu uv run uvicorn src.main:app --host 0.0.0.0 --port 8000
```
## 验证
```bash
# 健康检查
curl http://localhost:8000/health
# 测试推理
curl -X POST http://localhost:8000/infer -F "image=@your_image.jpg"
```