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Jetson Nano emmc module for ubuntu20.04 env

Hardware and Software Spec

Hardware

  1. Board : Jetson Nano Development 4GB
  2. HostPC : Ubuntu 20.04
  3. Camera : Luxonis OAK-D-W
  4. ssd : 256GB nvme M.2

Software

  1. OS : Ubuntu 20.04
  2. Middle OS : ROS noetic
  3. Python Version : 3.8.10
  4. Jetpack 4.6.6
  5. L4T : 32.7.6
  6. CUDA : 10.2.300
  7. cuDNN : 8.2.1.32
  8. TensorRT : 8.2.1.9
  9. Python Binding TensorRT : 8.0

Install

flashing Jetson nano emmc module

  1. Host PC : Ubuntu20.04

  2. Download Jetson Linux Archive

  1. Invite https://developer.nvidia.com/embedded/linux-tegra-r3276
  2. Download Driver Package(BSP) for Jetson Nano
    ->https://developer.nvidia.com/downloads/embedded/l4t/r32_release_v7.6/t210/jetson-210_linux_r32.7.6_aarch64.tbz2
  3. Download Sample Root Filesystem
    -> https://developer.nvidia.com/downloads/embedded/l4t/r32_release_v7.6/t210/tegra_linux_sample-root-filesystem_r32.7.6_aarch64.tbz2
  1. Flash Jetson module
  1. cd /Download
  2. mkdir Jetson_project
  3. mv Jetson-210_Linux_R32.7.6_aarch64.tbz2 ./Jetson_project
  4. mv Tegra_Linux_Sample-Root-Filesystem_R32.7.6_aarch64.tbz2 ./Jetson_project
  5. tar xf Jetson-210_Linux_R32.7.6_aarch64.tbz2
  6. cd Linux_for_Tegra/rootfs/
  7. sudo tar xpf ../../Tegra_Linux_Sample-Root-Filesystem_R32.7.6_aarch64.tbz2
  8. cd ..
  9. sudo ./apply_binaries.sh
  10. sudo ./flash.sh jetson-nano-emmc mmcblk0p1

Jetson Nano boot for Nvme (https://wiki.seeedstudio.com/reComputer_Jetson_Memory_Expansion/)

  1. connect nvme ssd on board && boot
  2. Ctrl + F && disks
  3. Format Disk
  4. Partitioning : Compatible with...hard disks > 2TB(GPT) && Click Format..
  5. click on the mdiddle + to add a disk character
  6. click on Next
  7. Volume Name : SSD && Type Internal disk for use with Linux systems only (Ext4) && Create
  8. git clone https://github.com/limengdu/rootOnNVMe.git
  9. cd rootOnNVMe/
  10. ./copy-rootfs-ssd.sh
  11. ./setup-service.sh
  12. sudo reboot now

Jetpack build

  1. host pc install Docker image
  2. https://developer.nvidia.com/sdk-manager, Docker Image Ubuntu 18.04 Download
  3. cd Download
  4. docker load < <(tar -c .)
  5. jetpack_docker install (command more -> https://docs.nvidia.com/sdk-manager/docker-containers/index.html)
    -> docker run -it --rm --privileged -v /dev/bus/usb:/dev/bus/usb/ -v /dev:/dev -v /media/$USR:/media/nvidia:slave --network host sdkmanager:2.2.0.12021-Ubuntu_18.04 --cli
  6. Login NVIDIA Developer
  7. Install
  8. Jetson
  9. Uncheck Host Machine(press spacebar), Target Hardware
  10. Jetson Nano modules
  11. Do you want to show all release versions? | y
  12. JetPack 4.6.6 | select
  13. DeepStream 6.0.1 Uncheck
  14. Do you want to customize the install settings | y
  15. Do you want to flash Jetson Module? | n
  16. Download folder : (/home/nvidia/Downloads/nvidia/sdkm_downloads)
  17. Target HW image folder: (/home/nvidia/nvidia/nvidia_sdk)
  18. Accept the terms and conditions of all license agreements: | move 2 & enter
  19. Install JetPack 4.6.6 now | enter
  20. Allow usage data collection? | No
  21. space bar && unchech Jetson OS && enter
  22. Install
  23. Connect via | Ethernet cable (turn on Jetson Nano and connect same network on hostpc)
  24. Enter SSH connection detail to Jetson Nano Modules: | IPv4
  25. IP address: | Jetson Nano IP ex) 111.111.111.51
  26. Username: | Jetson Nano Name ex) jmnano
  27. Password: | Jetson Nano Password ex) 1234
  28. Proxy mode: | Do not set proxy
  29. enter

Update Ubuntu20.04 (https://qengineering.eu/install-ubuntu-20.04-on-jetson-nano.html)

  1. sudo vim /etc/update-manager/release-upgrades -> change line Prompt=nomal
  2. sudo apt-get update
  3. sudo apt-get dist-upgrade
  4. sudo reboot
  5. sudo do-release-upgrade
  6. almost questions enter y, not to use chrominum but auto install
  7. sudo vim /etc/gdm3/custom.conf -> change uncomment | WaylandEnable=false
  8. sudo vim /etc/X11/xorg.conf -> chagne uncommnet | Driver "nvidia"
  9. sudo vim /erc/update-manager/release-upgrades -> change Prompt=never

Ubuntu 20.04 start_settings

  1. sudo rm -rf /usr/share/vulkan/icd.d
  2. sudo apt-get update | maybe this time show error for chrominium use chatgpt how to delete chrominium (https://chatgpt.com/share/67496421-4744-800b-807b-7ab39b2b5af1)
  3. sudo apt-get upgrade
  4. sudo apt-get autoremove
  5. sudo rm /usr/share/applications/vpi1_demos\
  6. cd /usr/share/nvpmodel_indicator
  7. sudo mv nv_logo.svg no_logo.svg

Install gcc & clang

  1. sudo apt-get install gcc-8 g++-8
  2. sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-9 9
  3. sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-8 8
  4. sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-9 9
  5. sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-8 8
  6. sudo update-alternatives --config gcc
  7. sudo update-alternatives --config g++
  8. sudo apt-get install clang-8

Setting gnome Interface

Uninstall lightdm

  1. sudo apt-get purge lightdm
  2. sudo apt-get autoremove

Install gnome-desktop

  1. sudo dpkg-reconfigure gdm3
  2. sudo apt install ubuntu-gnome-desktop
  3. sudo apt install gnome-tweaks
  4. Alt + F2, r
  5. sudo apt install --reinstall gnome-control-center

Jetson nano add swap memory

  1. git clone https://github.com/JetsonHacksNano/installSwapfile
  2. cd installSwapfile
  3. if you want to 8GB more Change number -> vim ./installSwapfile.sh -> SWAPSIZE = 8 (defalut 6)
  4. ./installSwapfile.sh

Install Opencv with CUDA

  1. uninstall opencv * use Chatgpt
  2. wget https://github.com/Qengineering/Install-OpenCV-Jetson-Nano/raw/main/OpenCV-4-8-0.sh
  3. sudo chmod 755 ./OpenCV-4-8-0.sh
  4. vim ./OpenCV-4-8-0.sh -> delete v4l2ucp | use vim search : esc, /v4l2ucp and delete -> change Cmake command (Using gcc 8 version)
   # Set GCC-8 as default compiler for this build
CC=/usr/bin/gcc-8 CXX=/usr/bin/g++-8 cmake -D CMAKE_BUILD_TYPE=RELEASE \
  -D CMAKE_INSTALL_PREFIX=/usr \
  -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \
  -D EIGEN_INCLUDE_PATH=/usr/include/eigen3 \
  -D WITH_OPENCL=OFF \
  -D CUDA_ARCH_BIN=${ARCH} \
  -D CUDA_ARCH_PTX=${PTX} \
  -D WITH_CUDA=ON \
  -D WITH_CUDNN=ON \
  -D WITH_CUBLAS=ON \
  -D ENABLE_FAST_MATH=ON \
  -D CUDA_FAST_MATH=ON \
  -D OPENCV_DNN_CUDA=ON \
  -D ENABLE_NEON=ON \
  -D WITH_QT=OFF \
  -D WITH_OPENMP=ON \
  -D BUILD_TIFF=ON \
  -D WITH_FFMPEG=ON \
  -D WITH_GSTREAMER=ON \
  -D WITH_TBB=ON \
  -D BUILD_TBB=ON \
  -D BUILD_TESTS=OFF \
  -D WITH_EIGEN=ON \
  -D WITH_V4L=ON \
  -D WITH_LIBV4L=ON \
  -D WITH_PROTOBUF=ON \
  -D OPENCV_ENABLE_NONFREE=ON \
  -D INSTALL_C_EXAMPLES=OFF \
  -D INSTALL_PYTHON_EXAMPLES=OFF \
  -D PYTHON3_PACKAGES_PATH=/usr/lib/python3/dist-packages \
  -D OPENCV_GENERATE_PKGCONFIG=ON \
  -D BUILD_EXAMPLES=OFF \
  -D CMAKE_CXX_FLAGS="-march=native -mtune=native" \
  -D CMAKE_C_FLAGS="-march=native -mtune=native" ..
  1. ./OpenCV-4-8-0.sh

TensorRT Python Bindings (https://elinux.org/Jetson/L4T/TRT_Customized_Example#TensorRT_Python_Bindings)

  1. sudo apt install zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev libsqlite3-dev libbz2-dev -y
  2. wget https://www.python.org/ftp/python/3.8.10/Python-3.8.10.tar.xz
  3. tar xvf Python-3.8.10.tar.xz Python-3.8.10/
  4. mkdir build-python-3.8.10
  5. cd build-python-3.8.10/
  6. ../Python-3.8.10/configure --enable-optimizations
  7. make -j $(nproc)
  8. sudo -H make altinstall
  9. cd ../
  10. sudo apt-get install -y protobuf-compiler libprotobuf-dev openssl libssl-dev libcurl4-openssl-dev
  11. mkdir python3.8
  12. mkdir python3.8/include
  13. wget http://launchpadlibrarian.net/449197644/libpython3.8-dev_3.8.0-3~18.04_arm64.deb -O libpython3.8-dev_3.8.0-3~18.04_arm64.deb
  14. ar x libpython3.8-dev_3.8.0-3~18.04_arm64.deb
  15. tar -xvf data.tar.xz
  16. cp ./usr/include/aarch64-linux-gnu/python3.8/pyconfig.h python3.8/include/
  17. cp -r Python-3.8.10/Include/* python3.8/include/
  18. git clone https://github.com/pybind/pybind11.git
  19. git clone -b release/8.0 https://github.com/NVIDIA/TensorRT.git
  20. cd TensorRT
  21. git submodule update --init --recursive
  22. cd python/
  23. TRT_OSSPATH=${PWD}/.. EXT_PATH=${PWD}/../.. TARGET=aarch64 PYTHON_MINOR_VERSION=8 ./build.sh
  24. python3.8 -m pip install build/dist/tensorrt-8.0.1.6-cp38-none-linux_aarch64.whl | if you want to install venv, active venv and command this

Install Torch & TorchVision (https://qengineering.eu/install-pytorch-on-jetson-nano.html)

torch

  1. sudo apt-get install python3-pip libjpeg-dev libopenblas-dev libopenmpi-dev libomp-dev
  2. if you want to install torch for venv active and follow --------host python command-------- --------venv python command--------
  3. sudo -H pip3 install future | pip3 install future
  4. sudo pip3 install -U --user wheel mock pillow | pip3 install -U wheel mock pillow
  5. sudo -H pip3 install testresources | pip3 install testresources
  6. sudo -H pip3 install setuptools==58.3.0 | pip3 install setuptools==58.3.0
  7. sudo -H pip3 install Cython | pip3 install Cython
  8. sudo -H pip3 install gdown | pip3 install gdown
  9. gdown https://drive.google.com/uc?id=1e9FDGt2zGS5C5Pms7wzHYRb0HuupngK1
  10. sudo -H pip3 install torch-1.13.0a0+git7c98e70-cp38-cp38-linux_aarch64.whl | pip3 install torch-1.13.0a0+git7c98e70-cp38-cp38-linux_aarch64.whl
  11. rm torch-1.13.0a0+git7c98e70-cp38-cp38-linux_aarch64.whl

torchvision

  1. sudo apt-get install libjpeg-dev zlib1g-dev libpython3-dev
  2. sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev
  3. if you want to install torch for venv active and follow --------host python command-------- --------venv python command--------
  4. sudo pip3 install -U pillow | pip3 install -U pillow
  5. gdown https://drive.google.com/uc?id=19UbYsKHhKnyeJ12VPUwcSvoxJaX7jQZ2
  6. sudo -H pip3 install torchvision-0.14.0a0+5ce4506-cp38-cp38-linux_aarch64.whl | pip3 install torchvision-0.14.0a0+5ce4506-cp38-cp38-linux_aarch64.whl
  7. rm torchvision-0.14.0a0+5ce4506-cp38-cp38-linux_aarch64.whl

torch Install test

  1. python3
  2. import torch
  3. torch.cuda.is_available() -> True

Install YOLOv8 or YOLOv11

  1. pip install ultralytics

Install ROS noetic(https://wiki.ros.org/noetic/Installation/Ubuntu)

  1. sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
  2. sudo apt install curl -y
  3. curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | sudo apt-key add -
  4. sudo apt update
  5. sudo apt install ros-noetic-desktop-full
  6. source /opt/ros/noetic/setup.bash
  7. echo "source /opt/ros/noetic/setup.bash" >> ~/.bashrc
  8. source ~/.bashrc
  9. sudo apt install python3-rosdep python3-rosinstall python3-rosinstall-generator python3-wstool build-essential -y
  10. sudo apt install python3-rosdep -y
  11. sudo rosdep init
  12. rosdep update

Install Luxonis Camera for ROS

  1. sudo wget -qO- https://raw.githubusercontent.com/luxonis/depthai-ros/main/install_dependencies.sh | sudo bash
  2. sudo apt install python3-rosdep
  3. sudo rosdep init
  4. rosdep update
  5. mkdir -p dai_ws/src
  6. cd dai_ws/src
  7. git clone --branch noetic https://github.com/luxonis/depthai-ros.git
  8. cd ..
  9. rosdep install --from-paths src --ignore-src -r -y
  10. source /opt/ros/noetic/setup.bash
  11. catkin_make
  12. source devel/setup.bash

Install Luxonis Camera for Python

  1. git clone https://github.com/luxonis/depthai-python.git
  2. cd depthai-python/examples
  3. python3 install_requirements.py

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