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This is cool, I never even knew there was an app like this. I ought to try it out if I ever come across anything pixelated and censored (nothing I have is).
Nice. Always wondered whether there was such a software, but was too lazy to actually search for it.
We reached the peak of technology, from now on it’s all gonna be downwards
They said the same when mobile phone screens became large enough to watch porn in it.
i see what you did there…
Finally a good use of ai
Jokes aside, there are quite some good uses. Both extreme sides on this topic (those with money who abuse tech, people and planet, as well as those who just want to hate everyone who even dares to suggest that AI could be used positively) are just so god damn loud and obnoxious.
Perhaps AI being useful to uncensor porn ends up being the smallest common denominator we can agree on to be good. 🍆
There is a saying that god gave man a brain abd a penis. And only enough blood to run one at a time. That is unfortunate, but thankfully the brain works tirelessly to activate the latter as much as possible
Yeah, but those are my favorite vegetables: aubergine 🍆.
Seems to only support cpu or cuda, not AMD sadly.
You’ll need a Nvidia (CUDA) GPU and some patience to run the app. If your card has at least 4-6GB of VRAM then it should work out of the box.
For the prepackaged flathub or docker installations.
Great news, you can run this software with an AMD GPU fine, just follow the installation instructions in your link and install pytorch for ROCm. https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html
I have a (rather different!) application that’s released as a Flatpak, and GPU acceleration is CUDA-only there, too. It supports ROCm when compiled locally, but ROCm just can’t work through the sandbox at this point, unfortunately. Not for lack of trying.
If you have an example of a Flatpak where it does work, I’d love to see their manifest so I can learn from it.
@PlantPowerPhysicist @HappyFrog f(l)atpak is workaround, not solution. It should not work in non-default configuration
You do realize people don’t care if it uses extra 200mb of space, if they don’t have to build it from GitHub or break their repos.
That’s pretty much the standard for a lot of video processing applications
I did buy a (secondhand) nvidia card specifically for AI worlkloads because yes, I realised that this is what the AI dev community has settled on, and if I try to avoid nvidia I will be making life very hard for myself.
But that doesn’t change the fact that it still absolutely sucks that nvidia have this dominance in the space, and that it is largely due to what tooling the community has decided to use, rather than any unique hardware capability which nvidia have.
You also could pickup a CPU with a ton of memory bandwidth.
Huh? I can’t speak to “video processing”, but “NVIDIA dominance” isn’t applicable at all for AI, at least generative AI. Pretty much all frameworks for LLM either officially support AMD or have an AMD fork. And literally all image gen frameworks that I am aware of officially support AMD.
I typically see people recommending to buy an AMD GPU over NVIDIA in AI communities…
What AI workloads do you run?
EDIT: Even the app in the OP only supports NVIDIA GPUs for the prepackaged flathub installation. You can run this software with an AMD GPU.
