8
submitted 20 hours ago by K22@lemmy.ml to c/astrophotography@lemmy.world

Building on Papillon's original guide on the PixInsight forum, I've put together a consolidated and maintained version on GitLab:

https://gitlab.com/K-22/pixinsight_rocm_linux_instructions


What it covers

The guide walks through building TensorFlow 2.19.1 with ROCm 7.2 support inside a Docker container and configuring PixInsight to use it. The Docker approach keeps the build clean and reproducible — no build dependencies on your host. Also includes performance tuning and troubleshooting.

Tested with

  • AMD Radeon RX 9070 XT (RDNA4 / gfx1201)
  • Ubuntu 24.04 and CachyOS (Arch-based)
  • ROCm 7.2, TensorFlow 2.19.1

Should work with older AMD generations (RDNA3, RDNA2, etc.) by adjusting the target architecture flag — the guide explains how.

Contributions welcome

AMD GPU support on Linux is a moving target. If you've tested a different GPU, found a distro-specific fix, or have a better configuration — open an issue or MR on the repo. Even just confirming it worked on your setup helps.


Full credit to Papillon for the original guide. This repo is just an effort to make it easier to find, maintain, and extend.

Clear skies.

[-] K22@lemmy.ml 1 points 3 days ago

Haha, I’ll take that as a compliment! Not sure my code flows quite like Hafez’s poetry yet, but AI definitely helped with it. As for latency: It’s snappy. Since it runs locally as a Docker container and bypasses the heavy native UI, network latency is basically zero.

The dashboard just polls the reverse-engineered API directly. The Ugreen endpoints respond very quickly, so the CPU/RAM and network traffic statistics update in near real-time.

11
submitted 3 days ago by K22@lemmy.ml to c/opensource@lemmy.ml

geteilt von: https://lemmy.ml/post/44811675

Hi everyone! 👋

I’m looking for contributors to help grow this project—if you’re interested in collaborating, reviewing code, or adding features, feel free to jump in!

I built NAS Monitor because the native Ugreen UI isn't the most efficient when you just want a quick, real-time overview of your system.

Full disclosure: I built this entirely with the help of AI! It’s been a fascinating experiment, but now I'd love to get some real human developers on board to help refine it.

What it does: It’s a simple, self-hosted dashboard that runs via Docker. It gives you a clean look at your: CPU & RAM usage Disk health Network traffic (without all the extra clicks!)

🛠 Bonus for Devs (API Docs): Since Ugreen doesn't have an official API, I managed to reverse-engineer their internal one (with AI assistance) and included the complete API documentation in the repository. If you're looking to build your own tools for Ugreen NASync devices, this should save you a lot of time!

🔗 Links:

17
submitted 3 days ago by K22@lemmy.ml to c/selfhosted@lemmy.world

geteilt von: https://lemmy.ml/post/44811675

Hi everyone! 👋

I’m looking for contributors to help grow this project—if you’re interested in collaborating, reviewing code, or adding features, feel free to jump in!

I built NAS Monitor because the native Ugreen UI isn't the most efficient when you just want a quick, real-time overview of your system.

Full disclosure: I built this entirely with the help of AI! It’s been a fascinating experiment, but now I'd love to get some real human developers on board to help refine it.

What it does: It’s a simple, self-hosted dashboard that runs via Docker. It gives you a clean look at your: CPU & RAM usage Disk health Network traffic (without all the extra clicks!)

🛠 Bonus for Devs (API Docs): Since Ugreen doesn't have an official API, I managed to reverse-engineer their internal one (with AI assistance) and included the complete API documentation in the repository. If you're looking to build your own tools for Ugreen NASync devices, this should save you a lot of time!

🔗 Links:

3
submitted 3 days ago by K22@lemmy.ml to c/homelab@lemmy.ml

Hi everyone! 👋

I’m looking for contributors to help grow this project—if you’re interested in collaborating, reviewing code, or adding features, feel free to jump in!

I built NAS Monitor because the native Ugreen UI isn't the most efficient when you just want a quick, real-time overview of your system.

Full disclosure: I built this entirely with the help of AI! It’s been a fascinating experiment, but now I'd love to get some real human developers on board to help refine it.

What it does: It’s a simple, self-hosted dashboard that runs via Docker. It gives you a clean look at your: CPU & RAM usage Disk health Network traffic (without all the extra clicks!)

🛠 Bonus for Devs (API Docs): Since Ugreen doesn't have an official API, I managed to reverse-engineer their internal one (with AI assistance) and included the complete API documentation in the repository. If you're looking to build your own tools for Ugreen NASync devices, this should save you a lot of time!

🔗 Links:

K22

joined 4 days ago