Get Your Jetson Nano Working
- 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 libhdf5-serial-dev hdf5-tools nano
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
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.
This will take a while. Go grab a coffee, or watch a movie. Once the compilation is complete, you are almost done. Only a few more steps to go.
# Install OpenCV sudo make install sudo ldconfig
The final step is to correctly link the built
OpenCV native library to your virtualenv.
The native library should now be installed in a location that looks like
# Go to the folder where OpenCV's native library is built cd /usr/local/lib/python3.6/site-packages/cv2/python-3.6 # Rename mv cv2.cpython-36m-xxx-linux-gnu.so cv2.so # Go to your virtual environments site-packages folder cd ~/env/lib/python3.6/site-packages/ # Symlink the native library ln -s /usr/local/lib/python3.6/site-packages/cv2/python-3.6/cv2.so cv2.so
Congratulations ! You are now done compiling OpenCV from source.
A quick check to see if you did everything correctly is
You should see something that looks like
total 48 drwxr-xr-x 10 user user 4096 Jun 16 13:03 . drwxr-xr-x 5 user user 4096 Jun 16 07:46 .. lrwxrwxrwx 1 user user 60 Jun 16 13:03 cv2.so -> /usr/local/lib/python3.6/site-packages/cv2/python-3.6/cv2.so -rw-r--r-- 1 user user 126 Jun 16 07:46 easy_install.py drwxr-xr-x 5 user user 4096 Jun 16 07:47 pip drwxr-xr-x 2 user user 4096 Jun 16 07:47 pip-19.1.1.dist-info drwxr-xr-x 5 user user 4096 Jun 16 07:46 pkg_resources drwxr-xr-x 2 user user 4096 Jun 16 07:46 __pycache__ drwxr-xr-x 6 user user 4096 Jun 16 07:46 setuptools drwxr-xr-x 2 user user 4096 Jun 16 07:46 setuptools-41.0.1.dist-info drwxr-xr-x 4 user user 4096 Jun 16 07:47 wheel drwxr-xr-x 2 user user 4096 Jun 16 07:47 wheel-0.33.4.dist-info
To test the OpenCV installation, run
python and do the following
import cv2 # Should print 4.1.0 print(cv2.__version__)
Step 5: Install Donkeycar Python Code
- Change to a dir you would like to use as the head of your 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