Last update: 20 March 2023
This article will guide you through the process of creating a minimalist Ubuntu-based image for your NVIDIA Jetson Nano board that is tailored to your specific project needs.
While the official image is available for use, it is over 5GB in size and comes pre-installed with unnecessary packages like the Ubuntu desktop and a browser, taking up valuable disk space and memory. Building an image from scratch provides a great opportunity to learn something new and create a clean and minimalistic image.
To download prebuilt images, go to the GitHub release page 👉 here
To be able to decompress the images, you must have lrzip installed.
Once the images are decompressed, follow the section below to flash the image to the SD card.
The default username is
jetson and the password is
Building the jetson image is fairly easy. All you need to have is the following tools installed on your machine.
Start by cloning the repo from github
$ git clone https://github.com/pythops/jetson-nano-image $ cd jetson-nano-image
Then create a new rootfs using the following command:
$ just build-jetson-rootfs
This will create the rootfs in the
You can modify the
Containerfile.rootfsfile to add any tool or configuration that you will need in the final image.
Next, use the following command to build the Jetson image:
$ just build-jetson-image <board> <revision>
Specify the Jetson board you want, which can be either
For the jetson nano you can specify the revision:
300. For example, for the jetson nano board 200 revision, use the following command:
$ just build-jetson-image jetson-nano 200
For the Jetson Nano 2GB, there is no need to provide the revision, so just use the following command:
$ just build-jetson-image jetson-nano-2gb
The Jetson image will be built and saved in the current directory in a file named
To flash the jetson image, just run the following command:
$ sudo just flash-image <jetson image file> <sdcard device>
sdcard device is the name of the sd card identified by your system.
For instance, if your sdard is recognized as
/dev/sda, then replace
sdcard device by /dev/sda
Once you boot the board with the new image, then you can install Nvidia libraries using
$ sudo apt install -y cuda-toolkit-10-2 libcudnn8 libcudnn8-dev
With the new image only 150MB of RAM is used, which leaves you with 3.85 GB for your projects !
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