🏠 Jetson Packages Family

A collection of AWESOME Tools tailored to NVIDIA Jetson Devices

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CopyRight 2020-2022 Hikari AI. All rights reserved.

Collaborator: Kevin Yu (@yqlbu), Shi Kun (@kunish)

This repo aims to give you clear instructions on how to install packages on AArch64(ARM) Platform, especially in Jetson family. All the packages have been tested on Jetson AGX Xavier and Jetson Nano.

Feel free to check out my site hikariai.net for more cutting-edge information about Microservices and Edge Computing

Pre-Commit

This repo uses pre-commit for managing and maintaining multi-language preo-commit hooks.

Dependencies Installation

Before performing any installation, you may need to install the following basic dependencies

$ sudo apt-get install -y nano curl
# python3
$ sudo apt-get install -y python3-pip python3-dev python3-setuptools
# python2
$ sudo apt-get install -y python-pip python-dev python-setuptools
$ sudo apt-get install -y libcanberra-gtk0 libcanberra-gtk-module

Notes: If you wish to set python3 as your default python compiler and pip package manager, please do the following:

# python
$ sudo rm -rf /usr/bin/python && sudo ln -s /usr/bin/python3 /usr/bin/python
$ which python
# pip
$ sudo rm -rf /usr/bin/pip && sudo ln -s /usr/bin/pip3 /usr/bin/pip
$ which pip

Python-pip

# pip3
$ pip3 install -U pip
$ pip3 install setuptools wheel cython

Set CUDA Path

If you have not set CUDA Path yet, you might need to do so.

Setup with script

$ wget -qO- https://github.com/yqlbu/jetson-packages-family/raw/master/set_cuda.sh | bash -

Setup manually

$ echo "export PATH=/usr/local/cuda/bin:\${PATH}" >> ${HOME}/.bashrc
$ echo "export LD_LIBRARY_PATH=/usr/local/cuda/lib64:\${LD_LIBRARY_PATH}" >> ${HOME}/.bashrc
$ echo "export CPATH=$CPATH:/usr/local/cuda/targets/aarch64-linux/include" >> ${HOME}/.bashrc
$ echo "export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/cuda/targets/aarch64-linux/lib" >> {HOME}/.bashrc
$ source ~/.bashrc

Boot From SSD (Xavier Only)

Compared with Jetson Nano, an important feature comes with Jetson Xavier NX and Jetson AGX Xavier is that they come with the M.2 Key M connector. According to the third-party testing, the reading speed from my SSD is 7 times faster than the SD card. Thus, to boot from SSD will surely boost the performance of Jetson Xavier.

Guide to setup

Jetsonhacks RootOnNVMe repo

Fan Control

A script that can control the PWM fan with the change of the CPU temperature of any Jetson Machine (Jetson Nano, Jetson TX1, TX2, Jetson Xavier)

Guide to setup

Packages List

• Pytorch
• Tensorflow
• Machine Learning
  • Scikit Learn
  • Scipy
  • Matplotlib
  • Pycuda
  • Jupyter Lab
  • Pillow
  • Pandas
  • Numpy
  • Seaborn
  • ONNX
• LLVM
• Numba
• Jetson Stats
• NeoVim Server
• VSCode
• CodeServer
• Archiconda3
• OpenCV
• Pycharm
• Lazygit
• Lsd
• Ctop
• Cointop
• Gotop
• Bashtop
• Httpie
• Ranger
• Neofetch
• Docker
• Dlib
• LabelImg
• Qt5
• Kubernetes
• Nomachine

Pytorch

PyTorch v1.8.0 (JetPack 4.4 +)

Python 3.6 - torch-1.8.0-cp36-cp36m-linux_aarch64.whl

$ wget https://nvidia.box.com/shared/static/p57jwntv436lfrd78inwl7iml6p13fzh.whl -O torch-1.8.0-cp36-cp36m-linux_aarch64.whl
$ sudo apt-get install python3-pip libopenblas-base libopenmpi-dev
$ pip3 install Cython
$ pip3 install numpy torch-1.8.0-cp36-cp36m-linux_aarch64.whl

Torchvision v0.5.0 (compatible with PyTorch v1.4.0)

$ sudo apt-get install libjpeg-dev zlib1g-dev libpython3-dev libavcodec-dev libavformat-dev libswscale-dev
$ git clone --branch <version> https://github.com/pytorch/vision torchvision   # see below for version of torchvision to download
$ cd torchvision
$ export BUILD_VERSION=0.x.0  # where 0.x.0 is the torchvision version
$ python3 setup.py install --user
$ cd ../  # attempting to load torchvision from build dir will result in import error
$ pip install 'pillow<7' # always needed for Python 2.7, not needed torchvision v0.5.0+ with Python 3.6

Verfication

$ python3 -c "import torch ; print(torch.__version__)"

To install other versions of PyTorch and Torchvision, please visit site HERE

Tensorflow

Python 3.6 + JetPack 4.5

sudo apt-get install libhdf5-serial-dev hdf5-tools libhdf5-dev zlib1g-dev zip libjpeg8-dev liblapack-dev libblas-dev gfortran
sudo apt-get install python3-pip
sudo pip3 install -U pip testresources setuptools==49.6.0
sudo pip3 install -U numpy==1.16.1 future==0.18.2 mock==3.0.5 h5py==2.10.0 keras_preprocessing==1.1.1 keras_applications==1.0.8 gast==0.2.2 futures protobuf pybind11
# TF-2.x
$ sudo pip3 install --pre --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v45 tensorflow
# TF-1.15
$ sudo pip3 install --pre --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v45 ‘tensorflow<2’

If you meet error when installing h5py, please run this command to solve the dependency:

$ sudo apt-get install libhdf5-serial-dev hdf5-tools

To install other versions of Tensorflow, checkout the sites below:

Jetson Xavier: HERE

Jetson Nano: HERE

Machine Learning

Python3 v3.6.9

• Scikit Learn
• Scipy
• Matplotlib
• Pycuda
• Jupyter Lab
• Pillow
• Pandas
• Numpy
• Seaborn

Scikit-learn

$ pip3 install scikit-learn

Scipy

$ apt-get install libatlas-base-dev gfortran
$ pip3 install -U scipy --user

Matplotlib

$ sudo apt install libfreetype6-dev -y
$ sudo apt install python3-matplotlib -y

Pycuda

pip3 install -U pycuda --user

Jupyter Lab

# install jupyter
$ pip3 install jupyterlab
$ pip3 install --upgrade --force jupyter-console

# export environment path
$ echo 'export PATH=$PATH:~/.local/bin' >> ~/.bashrc
$ source ~/.bashrc

# check installation version
$ jupyter lab -V

Install with Docker

$ docker run --name jupyterlab -d \
  -e TZ=Asia/Shanghai \
  -p 8888:8888 \
  -v /appdata/jupyterlab:/opt/app/data \
  hikariai/jupyterlab:latest

Run the app

$ jupyter lab --ip=* --port=8888 --no-browser --notebook-dir=/opt/app/data \
  --allow-root --NotebookApp.token='' --NotebookApp.password='' \
  --LabApp.terminado_settings='{"shell_command": ["/bin/bash"]}'

Usage Guide: https://github.com/yqlbu/jetson_lab

Pillow

$ pip3 install -U pillow --user

Pandas

$ pip3 install -U pandas --user

Numpy

$ pip3 install -U numpy --user

Seaborn

$ pip3 install -U seaborn --user

ONNX

ONNX v1.4.1 (Python3.6.9 + JetPack 4.3/4.4/4.5)

$ sudo apt install protobuf-compiler libprotoc-dev
$ pip install onnx==1.4.1

LLVM

LLVM v3.9 (Python3.6 + JetPack 4.3/4.4/4.5)

$ sudo apt-get install llvm-3.9
$ export LLVM_CONFIG=/usr/lib/llvm-3.9/bin/llvm-config
$ cd ~
$ wget https://github.com/numba/llvmlite/archive/v0.16.0.zip
$ unzip v0.16.0.zip
$ cd llvmlite-0.16.0
$ sudo chmod 777 -R /usr/local/lib/python3.6/dist-packages/
$ python3 setup.py install

Numba

Numba v0.31 (Python3.6 + JetPack 4.3/4.4/4.5)

**Notes: Numba requires **LLVM** pre-built, so please check out the instructions for LLVM and have it installed before installing Numba.

$ pip3 install numba==0.31 --user

Jetson Stats

Jetson-stats is a package to monitoring and control your NVIDIA Jetson [Xavier NX, Nano, AGX Xavier, TX1, TX2] Works with all NVIDIA Jetson ecosystem.

$ sudo -H pip install -U jetson-stats
$ sudo jtop

NeoVim Server

NeoVim Server is a containerized IDE-like text editor that runs on a web server.

Docs: https://github.com/yqlbu/neovim-server/wiki

Font Install:

$ mkdir -p ~/.local/share/fonts
$ cd ~/.local/share/fonts && curl -fLo "Droid Sans Mono for Powerline Nerd Font Complete.otf" https://github.com/ryanoasis/nerd-fonts/raw/master/patched-fonts/DroidSansMono/complete/Droid%20Sans%20Mono%20Nerd%20Font%20Complete.otf

Quick Install:

$ docker run -d \
    --name nvim-server \
    -p 6080:3000 \
    -p 8090:8090 \
    -v ~/workspace:/workspace \
    -v /appdata/nvim-server:/config \
    -e TZ=Asia/Shanghai \
    -e USER=<USER> \
    -e SECRET=<PASSWORD> \
    hikariai/nvim-server:latest

Wait for a couple seconds until the container finishes its bootstrap process, then visit http://localhost:6080/wetty

VS Code for aarch64

Visual Studio Code is a code editor redefined and optimized for building and debugging modern web and cloud applications.

$ curl -s https://packagecloud.io/install/repositories/swift-arm/vscode/script.deb.sh | sudo bash
$ sudo apt-get install -y code-oss

Code Server

Code-server is a Visual Studio Code instance running on a remote server accessible through any web browser. It allows you to code anywhere and on any device such as a tablet or laptop with a consistent integrated development environment (IDE)

Installation Guide: [HERE

Archiconda3

Archiconda3 is a distribution of conda for 64 bit ARM. Anaconda is a free and open-source distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. Like Virtualenv, Anaconda also uses the concept of creating environments so as to isolate different libraries and versions.

$ cd ${HOME}
$ curl -fsSL https://github.com/Archiconda/build-tools/releases/download/0.2.3/Archiconda3-0.2.3-Linux-aarch64.sh | sudo bash -
$ cd ~
$ sudo chown -R $USER archiconda3/
$ export "PATH=~/archiconda3/bin:$PATH" >> ~/.bashrc
$ conda config --add channels conda-forge
$ conda -V
$ conda update conda
$ conda -V

To prevent conda from activating the base environment by default

$ conda config --set auto_activate_base false
$ export "PATH=/bin:/usr/bin:$PATH" >> ~/.bashrc
$ source ~/.bashrc

Please checkout site HERE for usage guide.

OpenCV

OpenCV v4.1.1 (Python2.7/3.6+ JetPack4.3/4.4/4.5)

# purge old-version
$ sudo apt-get purge libopencv*
# install
$ sudo bash <(wget -qO- https://github.com/yqlbu/jetson-packages-family/raw/master/OpenCV/install_opencv4.1.1_jetson.sh)

Notes: You may modify the script to install custom version of OpenCV

$ wget https://github.com/yqlbu/jetson-packages-family/raw/master/OpenCV/install_opencv4.1.1_jetson.sh

Pycharm

PyCharm is an integrated development environment (IDE) used in computer programming, specifically for the Python language. It is developed by the Czech company JetBrains.

PyCharm Professional

$ cd ~
$ sudo apt-get update && sudo apt-get install -y openjdk-8-jdk
$ wget https://download.jetbrains.com/python/pycharm-professional-2019.3.4.tar.gz?_ga=2.42966822.2056165753.1586158936-1955479096.1586158936 -O pycharm-professional-2019.3.4.tar.gz
$ tar -xzf pycharm-professional-2019.3.4.tar.gz && cd pycharm-2019.3.4/bin
$ sudo chmod +x pycharm.sh && mv pycharm.sh pycharm
$ sudo rm -rf pycharm-professional-2019.3.4.tar.gz
$ cd ~
$ echo 'export PATH=/home/'$USER'/pycharm-2019.3.4/bin:$PATH' >> .bashrc

PyCharm Community

$ cd ~
$ sudo apt-get update && sudo apt-get install -y openjdk-8-jdk
$ wget https://download.jetbrains.com/python/pycharm-community-2019.3.4.tar.gz?_ga=2.42966822.2056165753.1586158936-1955479096.1586158936 -O pycharm-community-2019.3.4.tar.gz
$ tar -xzf pycharm-community-2019.3.4.tar.gz && cd pycharm-2019.3.4/bin
$ sudo chmod +x pycharm.sh && mv pycharm.sh pycharm
$ sudo rm -rf pycharm-community-2019.3.4.tar.gz
$ cd ~
$ echo 'export PATH=/home/'$USER'/pycharm-2019.3.4/bin:$PATH' >> .bashrc

run

$ pycharm

Notes: You may find other versions HERE

Lazygit

Lazygit is a simple terminal UI for git commands, written in Go with the gocui library.

$ sudo add-apt-repository ppa:lazygit-team/release
$ sudo apt-get update
$ sudo apt-get install lazygit

Ranger

Ranger is a console file manager with VI key bindings. It provides a minimalistic and nice curses interface with a view on the directory hierarchy. It ships with rifle, a file launcher that is good at automatically finding out which program to use for what file type.

$ pip install ranger-fm

(Optional) Install ranger devicons

$ git clone https://github.com/alexanderjeurissen/ranger_devicons ~/.config/ranger/plugins/ranger_devicons
$ echo "default_linemode devicons" >> $HOME/.config/ranger/rc.conf

Sample config is available HERE

Lsd

Lsd is the next gen ls command

Download the latest .deb package from the release page and install it via:

sudo dpkg -i lsd_0.20.1_arm64.deb # adapt version number and architecture

Ctop

Ctop is a Top-like interface for container metrics. Ctop provides a concise and condensed overview of real-time metrics for multiple containers.

# echo "deb http://packages.azlux.fr/debian/ buster main" | sudo tee /etc/apt/sources.list.d/azlux.list
# wget -qO - https://azlux.fr/repo.gpg.key | sudo apt-key add -
# sudo apt update
# sudo apt install docker-ctop

Cointop

Cointop is is a fast and lightweight interactive terminal based UI application for tracking and monitoring cryptocurrency coin stats in real-time.

Docs: HERE

$ curl -o- https://raw.githubusercontent.com/miguelmota/cointop/master/install.sh | bash

Gotop

Gotop A terminal based graphical activity monitor inspired by gtop and vtop

# install
$ curl -fsSL git.io/gotop.sh | sudo bash
# uninstall 
sudo rm -f /usr/local/bin/gotop

Bashtop

Bashtop Resource monitor that shows usage and stats for processor, memory, disks, network and processes.

$ sudo add-apt-repository ppa:bashtop-monitor/bashtop
$ sudo apt update
$ sudo apt install bashtop

Httpie

Httpie is a command-line HTTP client. Its goal is to make CLI interaction with web services as human-friendly as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers. The http & https commands allow for creating and sending arbitrary HTTP requests. They use simple and natural syntax and provide formatted and colorized output.

$ apt install httpie -y

Neofetch

Neofetch is a cross-platform, simple shell script that scans for your system’s information and displays it in a terminal, together with an ASCII image or any desired image next to the output.

$ sudo add-apt-repository ppa:dawidd0811/neofetch
$ sudo apt-get update
$ sudo apt-get install neofecth

Docker

Docker is basically a container engine which uses the Linux Kernel features like namespaces and control groups to create containers on top of an operating system and automates application deployment on the container. Docker uses Copy-on-write union file system for its backend storage.

$ sudo wget -qO- https://get.docker.com/ | sh
$ sudo usermod -aG docker $USER
$ sudo systemctl enable docker
$ sudo systemctl status docker

Docker Default Runtime

To enable access to the CUDA compiler (nvcc) during docker build operations, add "default-runtime": "nvidia" to your /etc/docker/daemon.json configuration file before attempting to build the containers:

{
  "runtimes": {
    "nvidia": {
      "path": "nvidia-container-runtime",
      "runtimeArgs": []
    }
  },
  "features": {
    "buildkit": true
  },
  "default-runtime": "nvidia"
}

Restart Docker Daemon

$ sudo systemctl restart docker

Verify if the default runtime is set to nvidia:

$ docker info | grep nvidia

Docker-compose

Docker Compose is a tool for defining and running multi-container Docker applications. With Compose, you use a YAML file to configure your application’s services. Then, with a single command, you create and start all the services from your configuration.

$ sudo apt-get update
$ sudo apt-get install -y python3 python3-pip libffi-dev libssl-dev
$ sudo pip3 install docker-compose
$ docker-compose -v

L4T-Docker

NVIDIA L4T-Docker

Official Repo: https://github.com/NVIDIA/nvidia-docker

Install NVIDIA-Docker Runtime

$ sudo apt install -y nvidia-docker2
$ sudo systemctl daemon-reload
$ sudo systemctl restart docker
$ docker info | grep nvidia

Custom L4T-Docker Image is available HERE

Dlib

DLib is an open source C++ library implementing a variety of machine learning algorithms, including classification, regression, clustering, data transformation, and structured prediction. ... K-Means clustering, Bayesian Networks, and many others.

Dlib v19.18

$ cd ~
$ wget https://raw.githubusercontent.com/yqlbu/face_recognizer/master/setup.sh
$ sudo chmod +x setup.sh
$ ./setup.sh

LabelImg

LabelImg is a graphical image annotation tool and label object bounding boxes in images.

$ sudo apt-get install pyqt4-dev-tools
$ sudo apt-get install python-lxml
$ sudo apt-get install python-qt4
$ sudo apt install libcanberra-gtk-module libcanberra-gtk3-module
$ git clone https://github.com/tzutalin/labelImg.git
$ cd labelImg
$ make qt4py2
$ python labelImg.py

Qt5

Qt is used for developing graphical user interfaces (GUIs) and multi-platform applications that run on all major desktop platforms and most mobile or embedded platforms. Most GUI programs created with Qt have a native-looking interface, in which case Qt is classified as a widget toolkit.

$ sudo apt-get install qt5-default qtcreator -y
$ sudo apt-get install pyqt5*
$ sudo apt install python3-pyqt5.qtsql

Kubernetes

Kubernetes has rapidly become a key ingredient in edge computing. With Kubernetes, companies can run containers at the edge in a way that maximizes resources, makes testing easier, and allows DevOps teams to move faster and more effectively as these organizations consume and analyze more data in the field.

K3S is a lightweight Kubernetes distribution developed by Rancher Labs, perfect for Edge Computing use cases where compute resources may be somewhat limited.

Installation and usage guide is available at HERE

Nomachine

Nomachine ARMv8 (compatible with Jetson Devices)

NoMachine is a free, cross-platform, serverless remot e desktop tool that lets you setup a remote desktop server on your computer using the NX video protocol. The client can be used to connect to the server from anywhere in the world.

Official Website: HERE

Change Resolution

The desktop resolution is typically determined by the capabilities of the display that is attached to Jetson. If no display is attached, a default resolution of 640x480 is selected. To use a different resolution, edit /etc/X11/xorg.conf and append the following lines:

Section "Screen"
   Identifier    "Default Screen"
   Monitor       "Configured Monitor"
   Device        "Tegra0"
   SubSection "Display"
       Depth    24
       Virtual 1280 800 # Modify the resolution by editing these values
   EndSubSection
EndSection

Update Logs

Dec-18-2022

Updated

• Add gotop installation guide
• Drop python2 support
• Update code-server installation guide

Aug-27-2021

Updated

• Use pip3 to install docker-compose

Aug-02-2021

Added

• Update Logs section

Updated

• Archiconda3 to v0.2.3

License

MIT License (C) Kevin Yu