

I’ve played around with Meshroom in the past.
Die they just flip over a fishing boat?
You’re most welcome
I use pinchflat and TubeArchivist to fetch content from YouTube.
While TubeArchivist is great on it’s own when you fetch individual videos or channels that have their content organized in playlists, it has only a web UI which is OK on phone, but unusable on TV.
There is an add-on to synchronize TubeArchivist and jellyfin, but it doesn’t translate too well between how TA and JF organize their data.
I use Pinchflat exclusively to download channels whose content’s order does not necessarily matter. It nicely provides all the metadata to JF and even integrates sponsorblock as chapters into JF.
I have each of these services running as a docker container.
Yes, I use jellyfin exclusively as a frontend for local mirrors of a handful YouTube channels.
Send a bill over 80 hours of freelance work
Only if you read it in a heavy german accent Akzent
Now that you mention it… But since both are equally agreeable, it should be fine either way
Wait, NATO-wave is made by right trolls?
The bestestest deal even!
From what I’ve understood he’s a conservative populist. So interpret that however you want.
And you’re making it easy for them if you don’t give a fuck.
I thought energy in the U.S. was laughably cheap, but those prices are surprisingly expensive compared to my feel-good-all-hydro-and-wind plan at 0,35€/kWh
I’ve just absorbed that into my vocabulary, thank you
At the moment there is no difference between the hosted version to the self-hosted version
So what’s the plan there?
Yeah, you don’t get a game :(
The container itself has been allocated 4 cores and 4 GiB RAM on my PVE host, RAM usage currently sits at 75%. Before I had 2 GiB of RAM allocated, felt like it was slowed down a little bit by running from a HDD then. The host CPU is an i5-9400, so nothing beefy.
Besides Gitlab, I run Home Assistant, a single tenant Nextcloud instance and pfsense on the same host without any troubles. All services combined have 14 GiB Ram allocated, most of that actually goes to HASS since its doing speech recognition and speech synthesis (6GiB)