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46 lines
1.4 KiB
Markdown
46 lines
1.4 KiB
Markdown
# YOLOv5部署示例
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本文档说明如何进行[YOLOv5](https://github.com/ultralytics/yolov5)的快速部署推理。本目录结构如下
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```
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.
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├── cpp # C++ 代码目录
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│ ├── CMakeLists.txt # C++ 代码编译CMakeLists文件
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│ ├── README.md # C++ 代码编译部署文档
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│ └── yolov5.cc # C++ 示例代码
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├── README.md # YOLOv5 部署文档
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└── yolov5.py # Python示例代码
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```
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## 安装FastDeploy
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使用如下命令安装FastDeploy，注意到此处安装的是`vision-cpu`，也可根据需求安装`vision-gpu`
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```
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# 安装fastdeploy-python工具
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pip install fastdeploy-python
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# 安装vision-cpu模块
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fastdeploy install vision-cpu
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```
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## Python部署
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执行如下代码即会自动下载YOLOv5模型和测试图片
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```
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python yolov5.py
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```
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执行完成后会将可视化结果保存在本地`vis_result.jpg`，同时输出检测结果如下
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```
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DetectionResult: [xmin, ymin, xmax, ymax, score, label_id]
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223.395142,403.948669, 345.337189, 867.339050, 0.856906, 0
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668.301758,400.781342, 808.441772, 882.534973, 0.829716, 0
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50.210720,398.571411, 243.123367, 905.016602, 0.805375, 0
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23.768242,214.979370, 802.627686, 778.840881, 0.756311, 5
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0.737200,552.281006, 78.617218, 890.945007, 0.363471, 0
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```
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## 其它文档
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- [C++部署](./cpp/README.md)
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- [YOLOv5 API文档](./api.md)
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