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DefTruth 89181042f5 Add yolox c++/pybind and model_zoo demo (#21) 
* update .gitignore

* Added checking for cmake include dir

* fixed missing trt_backend option bug when init from trt

* remove un-need data layout and add pre-check for dtype

* changed RGB2BRG to BGR2RGB in ppcls model

* add model_zoo yolov6 c++/python demo

* fixed CMakeLists.txt typos

* update yolov6 cpp/README.md

* add yolox c++/pybind and model_zoo demo

* move some helpers to private

* fixed CMakeLists.txt typos

* add normalize with alpha and beta

* add version notes for yolov5/yolov6/yolox

* add copyright to yolov5.cc

* revert normalize

* fixed some bugs in yolox
2022-07-19 09:55:07 +08:00
..
cpp
Add yolox c++/pybind and model_zoo demo (#21)
2022-07-19 09:55:07 +08:00
api.md
add yolov6 c++ and yolov6 pybind (#16)
2022-07-14 16:12:28 +08:00
README.md
Add yolox c++/pybind and model_zoo demo (#21)
2022-07-19 09:55:07 +08:00
yolov6.py
Add yolox c++/pybind and model_zoo demo (#21)
2022-07-19 09:55:07 +08:00

README.md

YOLOv6部署示例

当前支持模型版本为：YOLOv6 v0.1.0

本文档说明如何进行YOLOv6的快速部署推理。本目录结构如下

.
├── cpp                 # C++ 代码目录
│   ├── CMakeLists.txt  # C++ 代码编译CMakeLists文件
│   ├── README.md       # C++ 代码编译部署文档
│   └── yolov6.cc       # C++ 示例代码
├── README.md           # YOLOv6 部署文档
└── yolov6.py           # Python示例代码

安装FastDeploy

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

# 安装fastdeploy-python工具
pip install fastdeploy-python

# 安装vision-cpu模块
fastdeploy install vision-cpu

Python部署

执行如下代码即会自动下载YOLOv6模型和测试图片

python yolov6.py

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

DetectionResult: [xmin, ymin, xmax, ymax, score, label_id]
11.772949,229.269287, 792.933838, 748.294189, 0.954794, 5
667.140381,396.185455, 807.701721, 881.810120, 0.900997, 0
223.271011,405.105743, 345.740723, 859.328552, 0.898938, 0
50.135777,405.863129, 245.485519, 904.153809, 0.888936, 0
0.000000,549.002869, 77.864723, 869.455017, 0.614145, 0

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