jetson-nano-setup.sh

#!/bin/bash

set -e

if [[ $(/usr/bin/id -u) -ne 0 ]]; then
    echo "You must sudo this script"
    exit
fi

CMAKE_VERSION="3.18.0"
NODE_VERSION="12.18.3"
OPENCV_VERSION="4.4.0"

# The nvpmodel command handles two power options for your Jetson Nano:
#   (1) 5W is mode 1 and
#   (2) 10W is mode  0.
#   The default is the higher wattage mode, but it is always best to force the mode before running the jetson_clocks command.
nvpmodel -m 0
jetson_clocks

# Get rid of extra stuff
apt-get purge -y libreoffice* thunderbird*
apt-get clean

apt-get update
apt-get -y upgrade
apt autoremove -y

# CMAKE
cd ~/Downloads
apt-get install -y git gcc g++ libssl-dev build-essential curl ca-certificates
wget https://github.com/Kitware/CMake/releases/download/v$CMAKE_VERSION/cmake-$CMAKE_VERSION.tar.gz
tar -zxvf cmake-$CMAKE_VERSION.tar.gz
cd cmake-$CMAKE_VERSION
./bootstrap
make -j4
make install

# NodeJS
cd ~/Downloads
wget https://nodejs.org/dist/v$NODE_VERSION/node-v$NODE_VERSION-linux-arm64.tar.gz
tar -xzf node-v$NODE_VERSION-linux-arm64.tar.gz
cd node-v$NODE_VERSION-linux-arm64/
cp -R * /usr/local/
ln -s /usr/local/bin/node /usr/local/bin/nodejs12.x

# Python3.7
cd ~/Downloads
apt-get install -y python3.7-dev
wget https://bootstrap.pypa.io/get-pip.py
python3.7 get-pip.py
alias python3=python3.7
# update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.7 1
# update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.6 2
# update-alternatives --set python3 /usr/bin/python3.7
# echo "Select Python3.7"
# sudo update-alternatives --config python3 # select python3.7 here

# Java
cd ~/Downloads
apt-get install -y openjdk-8-jdk
ln -s /usr/bin/java /usr/bin/java8

# # Cython
# cd ~/Downloads
# wget https://files.pythonhosted.org/packages/3f/61/16a435de52fcda15246597a602aab6132cea50bedeb0919cb8874a068a20/Cython-0.29.20.tar.gz
# tar -xvf Cython-0.29.20.tar.gz
# cd Cython-0.29.20
# python3.7 setup.py install
python3.7 -m pip install Cython

# # Numpy
# cd ~/Downloads
# wget https://github.com/numpy/numpy/releases/download/v1.18.4/numpy-1.18.4.tar.gz
# tar -xvf numpy-1.18.4.tar.gz
# cd numpy-1.18.4
# python3.7 setup.py install
python3.7 -m pip install numpy

# Neo DLR
cd ~/Downloads
git clone https://github.com/neo-ai/neo-ai-dlr
cd neo-ai-dlr
git checkout 862da2de13d8f4fadb52b30baabc30a3c45821c4
git submodule update --init --recursive
mkdir build
cd build
cmake .. -DUSE_CUDA=ON -DUSE_CUDNN=ON -DUSE_TENSORRT=ON
make -j4
cd ../python
python3.7 setup.py install

# OpenCV
cd ~/Downloads
apt-get install -y build-essential pkg-config
apt-get install -y libtbb2 libtbb-dev
apt-get install -y libavcodec-dev libavformat-dev libswscale-dev
apt-get install -y libxvidcore-dev libavresample-dev
apt-get install -y libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev
apt-get install -y libpng-dev libjpeg-dev libopenexr-dev libtiff-dev libwebp-dev
apt-get install -y python-tk libgtk-3-dev
apt-get install -y libgtk-3-dev libcanberra-gtk-module libcanberra-gtk3-module
apt-get install -y libv4l-dev libdc1394-22-dev
apt-get install -y libv4l-dev v4l-utils qv4l2 v4l2ucp libdc1394-22-dev
wget -O opencv-$OPENCV_VERSION.tar.gz https://github.com/opencv/opencv/archive/$OPENCV_VERSION.tar.gz
wget -O opencv_contrib-$OPENCV_VERSION.tar.gz https://github.com/opencv/opencv_contrib/archive/$OPENCV_VERSION.tar.gz
tar -xvf opencv-$OPENCV_VERSION.tar.gz
tar -xvf opencv_contrib-$OPENCV_VERSION.tar.gz
cd opencv-$OPENCV_VERSION
mkdir build
cd build
cmake   -D CMAKE_BUILD_TYPE=RELEASE \
        -D CMAKE_INSTALL_PREFIX=/usr/local \
        -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-$OPENCV_VERSION/modules \
        -D WITH_CUDA=ON \
        -D CUDA_ARCH_BIN=5.3 \
        -D CUDA_ARCH_PTX="" \
        -D WITH_CUBLAS=ON \
        -D ENABLE_FAST_MATH=ON \
        -D CUDA_FAST_MATH=ON \
        -D ENABLE_NEON=ON \
        -D WITH_GSTREAMER=ON \
        -D WITH_LIBV4L=ON \
        -D WITH_QT=OFF \
        -D WITH_OPENGL=OFF \
        -D BUILD_opencv_python2=OFF \
        -D BUILD_opencv_python3=ON \
        -D BUILD_TESTS=OFF \
        -D BUILD_PERF_TESTS=OFF \
        -D BUILD_EXAMPLES=OFF ..

make -j4
make install
ldconfig

adduser --system ggc_user
addgroup --system ggc_group

# Add ggc_user to the video group so it can access CUDA !
usermod -a -G video ggc_user

cd ~/Downloads
wget https://d1onfpft10uf5o.cloudfront.net/greengrass-core/downloads/1.10.2/greengrass-linux-aarch64-1.10.2.tar.gz
tar -xzvf greengrass-linux-aarch64-1.10.2.tar.gz -C /
wget -O /greengrass/certs/root.ca.pem https://www.amazontrust.com/repository/AmazonRootCA1.pem

wget -O greengrassd.service https://gist.githubusercontent.com/teuteuguy/0f2e52cebdf9bcd76b8734b25a793644/raw/08cd29d1ca056b127a4ed27807f3a542f76c9446/greengrassd.service
cp greengrassd.service /lib/systemd/system/
systemctl enable greengrassd.service

# Utilities
# sudo -H pip install -U jetson-stats # enables jtop

# Notes
#
# For Greengrass, the resources needed to attach to the lambda function at minimum are the following:
# /dev/nvhost-ctrl
# /dev/nvhost-ctrl-gpu
# /dev/nvhost-prof-gpu
# /dev/nvmap
# /dev/nvhost-gpu
# /dev/nvhost-as-gpu
#
# the following 2 are optional, to avoid errors showing up, but inference still works without them:
# /dev/nvhost-vic
# /dev/tegra_dc_ctrl

Proposed edit - Add the following 2 lines to install Java and create a symlink for Greengrass:

sudo apt install openjdk-8-jdk
sudo ln -s /usr/bin/java /usr/bin/java8

Done.