To run the application, you have to:
- OpenCV 64-bit installed.
- Optional: Code::Blocks. (
$ sudo apt-get install codeblocks)
Start with the usual
$ sudo apt-get update
$ sudo apt-get upgrade
$ sudo apt-get install cmake wget curl
$ git clone https://github.com/airockchip/rknn-toolkit2.git
We only use a few files.
rknn-toolkit2-master
│
└── rknpu2
│
└── runtime
│
└── Linux
│
└── librknn_api
├── aarch64
│ └── librknnrt.so
└── include
├── rknn_api.h
├── rknn_custom_op.h
└── rknn_matmul_api.h
$ cd ~/rknn-toolkit2-master/rknpu2/runtime/Linux/librknn_api/aarch64
$ sudo cp ./librknnrt.so /usr/local/lib
$ cd ~/rknn-toolkit2-master/rknpu2/runtime/Linux/librknn_api/include
$ sudo cp ./rknn_* /usr/local/include
Or use Cmake.
$ cd *MyDir*
$ mkdir build
$ cd build
$ cmake ..
$ make -j4
onnx导出必须用rknn官网的导，必须要导出４层。
用这两个文件导出你对应的rknn版本。
connx.py
convertrknn.py
模型输出必须保持４层，原因是rknn不支持yolo一层输出，会裁减掉yolo的cfl。
cpp代码运行示例，帧率问题可以进一步改进，要做其他事情暂时只demo了。
./YoloV8_NPU rk3568/v8hand.rknn <你自己的图片路径>