Lite2在板端进行简单部署,获得结果后进行画框等后处理等等,也可以使用rknpu2的C/C++ API进行部署,例程参考 rknn_model_zoo仓库。 配套例程有些使用了opencv,所以系统还需安装OpenCV(opencv4),请使用命令: # 鲁班猫板卡系统默认是debianubuntu发行版,直接使用apt安装opencv sudo apt update sudo apt install lib...
推理部署:使得优化后的 RKNN Lite 模型可以在 Rockchip 的开发板或嵌入式设备上进行推理,适合实时应用场景。 RKNN-Toolkit-Lite2仓库链接:https://github.com/airockchip/rknn-toolkit2/tree/master/rknn-toolkit-lite2 RKNPU2 RKNPU2 是 Rockchip 推出的一个跨平台的编程接口,主要用于帮助用户部署使用...
sudo cp ./runtime/RK3588/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/ 同时注意更新sdk版本: 简单的测试代码: importcv2importnumpyasnpimportplatformfromrknnlite.apiimportRKNNLiteINPUT_SIZE=640if__name__=='__main__':#rknn_model = "resnet18_for_rk3588.rknn"rknn_model="yolov5s_for_rk...
git clone https://github.com/Applied-Deep-Learning-Lab/Yolov5_RK3588 And got into repo-dir: cd Yolov5_RK3588 Install RKNN-Toolkit2-Lite,such as rknn_toolkit_lite2-1.4.0-cp39-cp39-linux_aarch64.whl pip install install/rknn_toolkit_lite2-1.4.0-cp39-cp39-linux_aarch64.whl ...
硬件:RK3588S 软件: rknn_toolkit_lite2-1.5.2-cp39-cp39-linux_aarch64.whl rknpu2 升级命令如下: 升级rknpu2 cp rknpu2/runtime/RK3588/Linux/rknn_server/aarch64/usr/bin/rknn_server /usr/bin/rknn_server cp rknpu2/runtime/RK3588/Linux/librknn_api/aarch64/librknnrt.so /usr/lib/lib...
摘要 配置orangepi5pro运行rknn版本的yolov5,使用npu进行目标检测. 关键信息 板卡:orangepi5pro 芯片:RK3588S 环境:rknn2 转换工具:rknn-tool-kit2:1.5.0 系统:ubuntu20.04 原理简介 npu简介 NPU(Neural
譬如RK3588与RK3566、RK3568相同的软件栈。同时，考虑到产业应用实际更关心整体性能，FastDeploy对YOLOv8...
Rockchip RK3588. I have problems with converting yolov5. I tried this: But it is not working for me. In rknn-toolkit I can’t make an onnx file that will be the same format as as example In model-zoo I have different o…
文件中包含内容: 使用平台为RK3588 (1)step1:pt模型转onnx (2)step2: onnx调用做推理 (3)step3: onnx转rknn模型 (4)step4:rknn模型调用 上传者:weixin_43999691时间:2023-10-12 yolo-使用onnxruntime部署yolov5目标检测算法.zip yolo_使用onnxruntime部署yolov5目标检测算法 ...
RKNN-Toolkit-Lite2 provides Python programming interfaces for Rockchip NPU platform (RK3566, RK3568,RK3588, RK3588S) to help users deploy RKNN models and accelerate the implementation of AI applications. For the deployment of the RKNN model, please refer to: ...