View source for NPU SDK1.5.2/zh

[[NPU_SDK1.5.2|English]]

==New version RKNPU2 SDK==
Link to → [[NPU/zh|NPU]]
==How to test NPU==
===OS===
Tested on the following OS:
====Debian11 (bullseye)====
* rk3588-sd-debian-bullseye-desktop-6.1-arm64-20240116.img.gz
* rk3568-sd-debian-bullseye-desktop-6.1-arm64-20231113.img.gz
====Ubuntu20 (focal)====
* rk3588-sd-ubuntu-focal-desktop-6.1-arm64-20240116.img.gz
===install rknpu===
<syntaxhighlight lang="text">
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/
</syntaxhighlight>

===check rknn version===
<syntaxhighlight lang="text">
strings /usr/bin/rknn_server |grep 'build@'
strings /usr/lib/librknnrt.so |grep 'librknnrt version:'
</syntaxhighlight>

===run rknn_yolov5_demo===
<syntaxhighlight lang="text">
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
</syntaxhighlight>
Transfer the generated out.jpg to PC to view the result:
<syntaxhighlight lang="text">
scp out.jpg xxx@YourIP:/tmp/
</syntaxhighlight>
[[File:Rknn_yolov5_demo_out.jpg|640px]]

===install rknn_toolkit on debian11===
====install rknn_toolkit====
<syntaxhighlight lang="text">
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/
</syntaxhighlight>

====run python demo====
<syntaxhighlight lang="text">
$ 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
</syntaxhighlight>

===install rknn_toolkit on ubuntu===
====build python3.9 from source====
<syntaxhighlight lang="text">
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
</syntaxhighlight>

====install rknn_toolkit====
<syntaxhighlight lang="text">
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/
</syntaxhighlight>

====run python demo====
<syntaxhighlight lang="text">
$ 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
</syntaxhighlight>
==Doc==
https://github.com/rockchip-linux/rknpu2/tree/master/doc
==Other==
===查看NPU占有率===
<syntaxhighlight lang="text">
cat /sys/kernel/debug/rknpu/load
</syntaxhighlight>
===设置NPU频率===
<syntaxhighlight lang="text">
echo userspace > /sys/class/devfreq/fdab0000.npu/governor
echo 800000000 > /sys/class/devfreq/fdab0000.npu/min_freq
echo 1000000000 > /sys/class/devfreq/fdab0000.npu/max_freq
</syntaxhighlight>
===查看NPU频率===
<syntaxhighlight lang="text">
cat /sys/class/devfreq/fdab0000.npu/cur_freq
</syntaxhighlight>