Hardware accelerated OpenCV, Deepstream, Torch & Tensorrt Ubuntu 20.04 docker images for Jetson Nano containing any python version you need up until the latest 3.12
| Python Version | Dockerhub Image Name | Size |
|---|---|---|
Python3.12 |
jayfalls/l4t-20.04:full-cp312 |
Unkwnown |
Python3.12 |
jayfalls/l4t-20.04:base-cp312 |
Unkwnown |
Python3.11 |
jayfalls/l4t-20.04:full-cp311 |
3.28GB |
Python3.11 |
jayfalls/l4t-20.04:base-cp311 |
1.09GB |
Python3.10 |
jayfalls/l4t-20.04:full-cp310 |
Unkwnown |
Python3.10 |
jayfalls/l4t-20.04:base-cp310 |
Unkwnown |
note: Make sure to run the container on the latest L4T host system (r32.7.1). Running on older JetPack releases (e.g. r32.6.1) can cause driver issues, since L4T drivers are passed into the container
If an image with your desired python version doesn't exist in the docker hub, or you are running an older jetpack release, then you'll need to build it manually
Building Ubuntu 20.04 Images with Custom Python Versions
You can contribute in the following ways
- Create an issue
- Open a Pull request
- Are there python versions I haven't exported to? Open an issue to let me know!
note: I do not have a lot of free time, so I'm not sure if I'll support this fully, as such don't expect too much from me please. The license is MIT, so you can continue it on your own repo if I don't support.
note: If you see the error
ImportError: "/path": cannot allocate memory in static TLS block, you can run export LD_PRELOAD="/path":${LD_PRELOAD} before running your script, then please submit it as an issue so I can put the fix into the build process