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e248781784
* 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 * Add NanoDet-Plus Model support Co-authored-by: Jason <jiangjiajun@baidu.com>
NanoDetPlus部署示例
当前支持模型版本为：NanoDetPlus v1.0.0-alpha-1
本文档说明如何进行NanoDetPlus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
│ └── nanodet_plus.cc # C++ 示例代码
├── README.md # YOLOX 部署文档
└── nanodet_plus.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NanoDetPlus模型和测试图片
python nanodet_plus.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]
5.710144,220.634033, 807.854370, 724.089111, 0.825635, 5
45.646439,393.694061, 229.267044, 903.998413, 0.818263, 0
218.289322,402.268829, 342.083252, 861.766479, 0.709301, 0
698.587036,325.627197, 809.000000, 876.990967, 0.630235, 0