SkyLi
356a308f9b
- 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
59 lines
1.3 KiB
Markdown
59 lines
1.3 KiB
Markdown
# 手动部署说明
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由于网络限制，权重文件和 whl 包需要手动放置到本地目录。
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## 必需文件
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### 1. whl 包
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- **文件名**: `infrared_data-0.1.0-py3-none-any.whl`
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- **存放路径**: `lib/infrared_data-0.1.0-py3-none-any.whl`
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- **下载地址**: 联系项目维护者获取
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### 2. 模型权重文件
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- **文件名**: `best.pt`
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- **存放路径**: `weights/best.pt`
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- **下载地址**: 联系项目维护者获取
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## 目录结构
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```
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.
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├── lib/
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│ └── infrared_data-0.1.0-py3-none-any.whl
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├── weights/
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│ └── best.pt
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├── src/
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│ ├── __init__.py
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│ ├── config.py
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│ └── main.py
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├── tests/
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├── pyproject.toml
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└── Dockerfile
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```
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## 安装步骤
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```bash
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# 1. 放置上述文件到对应目录
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# 2. 创建 .env 文件（包含项目路径）
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# 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
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cp .env.example .env # 或手动创建
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# 3. 创建虚拟环境并安装依赖
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set -a && source .env && uv sync
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# 4. 启动服务
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set -a && source .env && INFERENCE_DEVICE=cpu uv run uvicorn src.main:app --host 0.0.0.0 --port 8000
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```
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## 验证
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```bash
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# 健康检查
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curl http://localhost:8000/health
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# 测试推理
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curl -X POST http://localhost:8000/infer -F "image=@your_image.jpg"
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```
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