install.sh

#!/bin/bash

# Fail if any sub-command fails
set -e

function append_to_bashrc {
	# Appends $1 to .bashrc if it has not already been added and the script is not running as part of a Github action
	if ! grep -qF "$1" ~/.bashrc && [[ -z "${GITHUB_ACTION}" ]]; then
		echo "$1" >> ~/.bashrc
	fi
}


# Default value for ROS_DISTRO is noetic
ROS_DISTRO=${ROS_DISTRO:-noetic}

if [[ -z "${GITHUB_ACTION}" ]] && [[ -z "${TWIZY_ONBOARD}" ]]; then # If running on local computer which is not the Twizy's on-board computer
	echo "Would you like to run tensorflow using Nvidia CUDA? This is highly recommended if you have a Nvidia GPU. Answering yes will install some extra dependencies and requires a restart after completed installation."
	select result in yes no; do
		case $result in
			yes) install_cuda=1; break;;
			no) install_cuda=0; break;;
		esac
	done
else # If running as Github action
	install_cuda=1
fi

if [[ ! -z "${GITHUB_ACTION}" ]]; then # If running as Github action
	# Create symlinks to clone location
	mkdir -p ~
	ln -s "${GITHUB_WORKSPACE}" ~/autonomous-twizy
fi

# Install ROS according to http://wiki.ros.org/noetic/Installation/Ubuntu
sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=1 sudo apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654
sudo apt-get update
if [[ -z "${GITHUB_ACTION}" ]]; then # If running on local computer 
	sudo apt-get install -y ros-$ROS_DISTRO-desktop-full
else # If running as Github action
	sudo apt-get install -y ros-$ROS_DISTRO-ros-base
fi
append_to_bashrc "source /opt/ros/$ROS_DISTRO/setup.bash"
source /opt/ros/$ROS_DISTRO/setup.bash

# Install rosdep and ROS packages
sudo apt-get install -y python3-rosdep
[ -f /etc/ros/rosdep/sources.list.d/20-default.list ] || sudo rosdep init
rosdep update
rosdep install -i --from-path ~/autonomous-twizy/src --rosdistro $ROS_DISTRO -y

# Install Kvaser's canlib according to https://www.kvaser.com/canlib-webhelp/section_install_linux.html#Installing-the-driver
sudo apt-get install -y build-essential
cd /tmp
wget --content-disposition "https://www.kvaser.com/downloads-kvaser/?utm_source=software&utm_ean=7330130980754&utm_status=latest"
tar xvzf linuxcan.tar.gz
cd linuxcan
make
sudo make uninstall
sudo make install

# Install python packages not indexed by rosdep
sudo apt-get install -y python3-pip
pip3 install -U canlib
pip3 install -U opencv-python tensorflow yolov4
# sbp at the time of writing requires a newer version of numpy than provided by rosdep, so override with a manuall install of numpy with pip3
# It is also important to install numpy after tensorflow, as tensorflow otherwise installs another version of numpy
# virtualenv would be great...
pip3 install -U sbp==3.4.6 numpy==1.20.2

if [[ -z "${GITHUB_ACTION}" ]] && [[ -z "${TWIZY_ONBOARD}" ]]; then # If running on local computer which is not the Twizy's on-board computer
	# Install webots according to https://www.cyberbotics.com/doc/guide/installation-procedure#installing-the-debian-package-with-the-advanced-packaging-tool-apt
	wget -qO- https://cyberbotics.com/Cyberbotics.asc | sudo apt-key add -
	sudo apt-add-repository 'deb https://cyberbotics.com/debian/ binary-amd64/'
	sudo apt-get update
	sudo apt-get install -y webots
	append_to_bashrc "export WEBOTS_HOME=/usr/local/webots"
fi

if [[ ! -z "${install_cuda}" ]]; then
	cd /tmp
	
	# This next bit is taken from https://gist.github.com/Laurence-Cullen/1156168009b320cd391767ca9bf1ce9c
	
	# Add NVIDIA package repositories
	wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
	sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
	sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub
	sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /"
	sudo apt-get update

	wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu2004/x86_64/nvidia-machine-learning-repo-ubuntu2004_1.0.0-1_amd64.deb

	sudo apt-get install -y ./nvidia-machine-learning-repo-ubuntu2004_1.0.0-1_amd64.deb
	sudo apt-get update

	# Install NVIDIA driver
	sudo apt-get install -y --no-install-recommends nvidia-driver-450
	# Reboot. Check that GPUs are visible using the command: nvidia-smi

	wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/libnvinfer7_7.1.3-1+cuda11.0_amd64.deb
	sudo apt-get install -y ./libnvinfer7_7.1.3-1+cuda11.0_amd64.deb
	sudo apt-get update

	sudo apt-get install -y --allow-downgrades --no-install-recommends cuda-11-0 libcudnn8=8.0.5.39-1+cuda11.0 libcudnn8-dev=8.0.5.39-1+cuda11.0
fi

if [[ ! -z "${TWIZY_ONBOARD}" ]]; then # If running on the Twizy's on-board computer
	append_to_bashrc "export TWIZY_ONBOARD=1"
else # If not running on the Twizy's on-board computer
	append_to_bashrc "export TWIZY_ONBOARD=0"
fi

# Automatically source the workspace's setup.bash in new shells
append_to_bashrc "[ -f ~/autonomous-twizy/devel/setup.bash ] && source ~/autonomous-twizy/devel/setup.bash"

if [[ -z "${GITHUB_ACTION}" ]]; then # If running on a local computer
	echo -e "\n\nInstallation completed!"
	echo -e "\nThe repository has been cloned to ~/autonomous-twizy/src, and the catkin workspace is located at ~/autonomous-twizy."
	if [[ ! -z "${install_cuda}" ]]; then
		echo -e "\nPLEASE REBOOT YOUR COMPUTER NOW FOR NVIDIA CUDA DRIVERS TO KICK IN!"
		echo -e "After rebooting, optionally run"
		echo -e "\n    nvidia-smi\n"
		echo -e "to check that GPUs are visible to the driver\n"
	else
		echo -e "\nFinally, please run"
		echo -e "\n    source ~/.bashrc\n"
	fi
fi