Get Your Jetson Nano Working
Step 1: Flash Operating System
Download our pre-built image Download Jetson Nano donkey car 3.2 image
You can skip directly
Visit the official Nvidia Jetson Nano Getting Started Guide. Work through the Prepare for Setup, Writing Image to the microSD Card, and Setup and First Boot instructions, then return here.
Step 2: Install Dependencies
ssh into your vehicle. Use the the terminal for Ubuntu or Mac. Putty for windows.
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install build-essential python3 python3-dev python3-pip python3-pandas python3-opencv python3-h5py libhdf5-serial-dev hdf5-tools nano ntp
Optionally, you can install RPi.GPIO clone for Jetson Nano from here. This is not required for default setup, but can be useful if using LED or other GPIO driven devices.
Step 3: Setup Virtual Env
pip3 install virtualenv
python3 -m virtualenv -p python3 env --system-site-packages
echo "source env/bin/activate" >> ~/.bashrc
source ~/.bashrc
Step 4: Install OpenCV
To install Open CV on the Jetson Nano, you need to build it from source. Building OpenCV from source is going to take some time, so buckle up. If you get stuck, here is another great resource which will help you compile OpenCV.
Note: In some cases Python OpenCV may already be installed in your disc image. If the file exists, you can optionally copy it to your environment rather than build from source. Nvidia has said they will drop support for this, so longer term we will probably be building it. If this works:
mkdir ~/mycar cp /usr/lib/python3.6/dist-packages/cv2.cpython-36m-aarch64-linux-gnu.so ~/mycar/ cd ~/mycar python -c "import cv2"Then you have a working version and can skip this portion of the guide. However, following the swapfile portion of this guide has made performance more predictable and solves memory thrashing.
The first step in building OpenCV is to define swap space on the Jetson Nano. The Jetson Nano has 4GB of RAM. This is not sufficient to build OpenCV from source. Therefore we need to define swap space on the Nano to prevent memory thrashing.
# Allocates 4G of additional swap space at /var/swapfile
sudo fallocate -l 4G /var/swapfile
# Permissions
sudo chmod 600 /var/swapfile
# Make swap space
sudo mkswap /var/swapfile
# Turn on swap
sudo swapon /var/swapfile
# Automount swap space on reboot
sudo bash -c 'echo "/var/swapfile swap swap defaults 0 0" >> /etc/fstab'
# Reboot
sudo reboot
Now you should have enough swap space to build OpenCV. Let's setup the Jetson Nano with the pre-requisites to build OpenCV.
# Update
sudo apt-get update
sudo apt-get upgrade
# Pre-requisites
sudo apt-get install build-essential cmake unzip pkg-config
sudo apt-get install libjpeg-dev libpng-dev libtiff-dev
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev
sudo apt-get install libxvidcore-dev libx264-dev
sudo apt-get install libgtk-3-dev
sudo apt-get install libatlas-base-dev gfortran
sudo apt-get install python3-dev
Now you should have all the pre-requisites you need. So, lets go ahead and download the source code for OpenCV.
# Create a directory for opencv
mkdir -p projects/cv2
cd projects/cv2
# Download sources
wget -O opencv.zip https://github.com/opencv/opencv/archive/4.1.0.zip
wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/4.1.0.zip
# Unzip
unzip opencv.zip
unzip opencv_contrib.zip
# Rename
mv opencv-4.1.0 opencv
mv opencv_contrib-4.1.0 opencv_contrib
Let's get our virtual environment (env) ready for OpenCV.
# Install Numpy
pip install numpy
Now let's setup CMake correctly so it generates the correct OpenCV bindings for our virtual environment.
# Create a build directory
cd projects/cv2
mkdir build
cd build
# Setup CMake
cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D INSTALL_C_EXAMPLES=OFF \
-D OPENCV_ENABLE_NONFREE=ON \
# Contrib path
-D OPENCV_EXTRA_MODULES_PATH=~/projects/cv2/opencv_contrib/modules \
# Your virtual environment's Python executable
# You need to specify the result of echo $(which python)
-D PYTHON_EXECUTABLE=~/env/bin/python \
-D BUILD_EXAMPLES=ON ../opencv
The cmake command should show a summary of the configuration. Make sure that the Interpreter is set to the Python executable associated to your virtualenv. Note: there are several paths in the CMake setup, make sure they match where you downloaded and saved the OpenCV source.
To compile the code from the build folder issue the following command.
mkdir -p ~/projects; cd ~/projects
- Get the latest donkeycar from Github.
git clone https://github.com/autorope/donkeycar
cd donkeycar
git checkout master
pip install -e .[nano]
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v42 tensorflow-gpu==1.13.1+nv19.3
Note: This last command can take some time to compile grpcio.
The native library should now be installed in a location that looks like /usr/local/lib/python3.6/site-packages/cv2/python-3.6/cv2.cpython-36m-xxx-linux-gnu.so.
If you plan to use a USB camera, you will also want to setup pygame:
sudo apt-get install python-dev libsdl1.2-dev libsdl-image1.2-dev libsdl-mixer1.2-dev libsdl-ttf2.0-dev libsdl1.2-dev libsmpeg-dev python-numpy subversion libportmidi-dev ffmpeg libswscale-dev libavformat-dev libavcodec-dev libfreetype6-dev
pip install pygame
Later on you can add the CAMERA_TYPE="WEBCAM" in myconfig.py.