An old Jetson Nano for AI?

[Sergei Grichine]

I've been playing with my old Jetson Nano (B01), trying to put it to work on anything AI related.

Anybody who has an old Nano and wants to dust it off - welcome to the club ;-)

https://github.com/slgrobotics/articubot_one/wiki/Notes-and-Status

Best Regards,

-- Sergei

[Sampsa Ranta]

I was able recently able to get accelerated YoloV11 to work with my 4GB Jetson Nano Developer kit for interference camera frames. Worked fine like 11FPS.

It actually supports Jetpack 4.6.7 and nvidia-docker2.. I was working with Jetson Nano on Duckietown Duckiebot platform.

Here is how it looked,

https://youtu.be/0tYwmjO-zfQ

The thing with Jetson Nano Jetpack is, it's not GPU there.. It's an embedded platform with software stack only built for the Ubuntu 18.. I got it working when I rebuilt ROS inside a container based on NVidia L4T-cuda image (tho I did most of this work within QEMU).

I recall there was even Ultralytics Docker image I used as baseline on how I did this. There was some benchmark tool for Jetson Nano. Um, they still seem to support Jetpack 4.x,

https://docs.ultralytics.com/guides/nvidia-jetson/

The baseline Docker image was NVidia l4t-cuda that provided the baseline support..

FROM nvcr.io/nvidia/l4t-cuda:10.2.460-runtime

The solution I saw for Jetson Nano was rather weird, as it exported some of the shared libraries from base image into the Docker image and it all had to be Ubuntu 18 based. There was some Python 3.8 package  from some repo I used to get things started with.. My Docker build was incremental and had more layers that built the stuff. This was based on how Duckietown had also built their stuff. 

This was the final Docker image payload to run, the Python code that does yolo interference is also in this repo,

https://github.com/masterhapero/dt-duckpack-yolov11

Starting the interference was very slow and memory intensive and caused camera acquisition pipeline to fail, but once it got running I was able to restart acquisition and get it working..

Cheers for the club!

- Sampsa

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