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Install Ubuntu on your RK3588 device. (tested on Ubuntu 20.04 and OrangePi5/Firefly ROC RK3588S devices)
For installing Ubuntu on Firefly you can use their manual[1][2].
For installing Ubuntu on OrangePi you can use their manual.
Or use ours README's for them (select the one below).
OrangePi Firefly -
Install ffmpeg package for WebUI:
sudo apt-get update sudo apt-get install -y ffmpeg
And dependencies for WebUI:
sudo apt-get update # General dependencies sudo apt-get install -y python-dev pkg-config # Library components sudo apt-get install libavformat-dev libavcodec-dev libavdevice-dev \ libavutil-dev libswscale-dev libswresample-dev libavfilter-dev
Open .bashrc in nano text editor:
nano ~/.bashrc
At the end of file add next line:
export LD_PRELOAD=$LD_PRELOAD:/usr/lib/aarch64-linux-gnu/libffi.so.7
Save and close nano with sortcuts ctrl-o, Enter, ctrl-x
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For installing docker on RK3588 device you can use official docker docs or check our README_DOCKER.md
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At first you need download docker image:
docker pull deathk9t/yolov5_rk3588:latest
Then you can run container with:
docker run --privileged --name [container-name] -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix -v /dev/:/dev --network host -it deathk9t/yolov5_rk3588:latest
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You can build docker image by yourself usning Dockerfile:
docker build -t [name-docker-image:tag] .
Then you can run container with:
docker run --privileged --name [container-name] -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix -v /dev/:/dev --network host -it [name-docker-image:tag]
Install miniconda
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-aarch64.sh
bash Miniconda3-latest-Linux-aarch64.sh
Then rerun terminal session:
source ~/.bashrc
Create conda env with python3.9
conda create -n <env-name> python=3.9
And then activate conda env
conda activate <env-name>
Clone repository:
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
In created conda enviroment also install requirements from the same directory
pip install -r install/requirements.txt
Then go to the install dir for building and installing cython_bbox
cd install/cython_bbox
python3 setup.py build
python3 setup.py install
main.py
runs inference with WebUI. You can turn on/off some options in config file or using Settings page at webUI.
python3 main.py
Or run it using bash script:
source run.sh
For see WebUI write to browser address bar next (localhost - device's ip):
localhost:8080
You also can set autostart for running this.
Before it deactivate conda env:
conda deactivate
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For Orange Pi
source install/autostart/orangepi_autostart.sh
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For Firefly:
source install/autostart/firefly_autostart.sh
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Install Python3 and pip3
sudo apt-get update sudo apt-get install python3 python3-dev python3-pip
Install dependent libraries
sudo apt-get update sudo apt-get install libxslt1-dev zlib1g zlib1g-dev libglib2.0-0 libsm6 libgl1-mesa-glx libprotobuf-dev gcc git
Install RKNN-Toolkit2,such as rknn_toolkit2-1.4.0_22dcfef4-cp38-cp38-linux_x86_64.whl
pip install resources/HostPC/converter/install/rknn_toolkit2-1.4.0_22dcfef4-cp38-cp38-linux_x86_64.whl
For convert your .onnx model to .rknn run onnx2rknn.py like:
cd resources/HostPC/converter/convert/ python3 onnx2rknn.py \ --input <path-to-your-onnx-model> \ --output <path-where-save-rknn-model> \ --dataset <path-to-txt-file-with-calibration-images-names>