Difference between revisions of "NPU"
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===install rknn_toolkit on debian11=== | ===install rknn_toolkit on debian11=== |
Revision as of 03:41, 18 January 2024
Contents
1 How to test NPU
1.1 OS
Tested on the following OS:
1.1.1 Debian11 (bullseye)
- rk3588-sd-debian-bullseye-desktop-6.1-arm64-20240116.img.gz
- rk3568-sd-debian-bullseye-desktop-6.1-arm64-20231113.img.gz
1.1.2 Ubuntu20 (focal)
- rk3588-sd-ubuntu-focal-desktop-6.1-arm64-20240116.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 check rknn version
strings /usr/bin/rknn_server |grep 'build@' strings /usr/lib/librknnrt.so |grep 'librknnrt version:'
1.4 run rknn_yolov5_demo
sudo apt-get update sudo apt-get install -y gcc g++ make cmake cd examples/rknn_yolov5_demo ./build-linux_RK3588.sh cd install/rknn_yolov5_demo_Linux ./rknn_yolov5_demo model/RK3588/yolov5s-640-640.rknn model/bus.jpg
Transfer the generated out.jpg to PC to view the result:
scp out.jpg xxx@YourIP:/tmp/
1.5 install rknn_toolkit on debian11
1.5.1 install rknn_toolkit
sudo apt-get update sudo apt-get install -y python3-dev python3-numpy python3-opencv python3-pip cd ~ 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/
1.5.2 run python demo
$ 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
1.6 install rknn_toolkit on ubuntu
1.6.1 build python3.9 from source
sudo apt install build-essential libssl-dev libffi-dev software-properties-common \ libbz2-dev libncurses-dev libncursesw5-dev libgdbm-dev liblzma-dev libsqlite3-dev \ tk-dev libgdbm-compat-dev libreadline-dev wget https://www.python.org/ftp/python/3.9.16/Python-3.9.16.tar.xz tar -xvf Python-3.9.16.tar.xz cd Python-3.9.16/ ./configure --enable-optimizations make -j$(nproc) sudo make install
1.6.2 install rknn_toolkit
pip install --upgrade pip pip install opencv-python cd ~ git clone https://github.com/rockchip-linux/rknn-toolkit2.git (cd rknn-toolkit2 && git checkout tags/v1.5.2 -b v1.5.2) /usr/local/bin/python3.9 -m pip 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/
1.6.3 run python demo
$ cd rknn-toolkit2/rknn_toolkit_lite2/examples/inference_with_lite/ $ python3 test.py --> Load RKNN model done --> Init runtime environment I RKNN: [08:41:08.078] RKNN Runtime Information: librknnrt version: 1.5.2 (c6b7b351a@2023-08-23T15:28:22) I RKNN: [08:41:08.078] RKNN Driver Information: version: 0.9.2 I RKNN: [08:41:08.080] 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 inferenc e type: static_shape 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