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1 RK3588

1.1 OS

Tested on the following OS:

• rk3588-sd-debian-bullseye-desktop-6.1-arm64-20231116.img.gz

1.2 install rknpu

export GIT_SSL_NO_VERIFY=1
git clone https://github.com/rockchip-linux/rknpu2.git
cd rknpu2
git checkout tags/v1.5.2 -b v1.5.2
sudo cp ./runtime/RK3588/Linux/librknn_api/aarch64/* /usr/lib
sudo cp ./runtime/RK3588/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/

1.3 install rknn_toolkit

sudo apt-get update
sudo apt-get install -y python3-dev python3-numpy python3-opencv python3-pip
git clone https://github.com/rockchip-linux/rknn-toolkit2.git
(cd rknn-toolkit2 && git checkout tags/v1.5.2 -b v1.5.2)
pip3 install ./rknn-toolkit2/rknn_toolkit_lite2/packages/rknn_toolkit_lite2-1.5.2-cp39-cp39-linux_aarch64.whl -i https://pypi.tuna.tsinghua.edu.cn/simple/

1.4 run test

$ cd rknn-toolkit2/rknn_toolkit_lite2/examples/inference_with_lite/
$ python3 test.py
--> Load RKNN model
done
--> Init runtime environment
I RKNN: [08:06:49.416] RKNN Runtime Information: librknnrt version: 1.5.2 (c6b7b351a@2023-08-23T15:28:22)
I RKNN: [08:06:49.416] RKNN Driver Information: version: 0.9.2
I RKNN: [08:06:49.416] RKNN Model Information: version: 6, toolkit version: 1.5.2-source_code(compiler version: 1.5.2 (71720f3fc@2023-08-
21T09:35:42)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inference type: static_s
hape
done
--> Running model
resnet18
-----TOP 5-----
[812]: 0.9996760487556458
[404]: 0.00024927023332566023
[657]: 1.449744013370946e-05
[466 833]: 9.023910024552606e-06
[466 833]: 9.023910024552606e-06
 
done