@jschauma It's turtles - I mean - interpreted, multi-paradigm, high-level, general-purpose programming languages all the way down... 🤪

@TomF wow, that is one epic vrchat experience... 👀 I'll have to try it, when I have a few hours to spare... 😳

@paulmelis ,,, and yes, default nerfacto model ... 😁

@paulmelis With my source videos, typically 2-3 minutes long, the ns-process tool usually extracts about 300 images from the video. On occasion I've tried upping the frame count to 500-600 but haven't seen much improvement, and often ended up running out of memory. :) About 300 frames usually works fine for me.

@paulmelis I just use my regular Android phone, a OnePlus 8T, taking video at also very regular Full-HD (1080) resolution. I think the blotchy "clouds" and "fuzzy areas" are an artifact of not having enough image/video coverage of those areas. Not enough image data for the NeRF algorithms to work on. In this case I also had "cloudy" and fuzzy areas but kept them mostly out of view by adjusting the render camera path and camera angles just so... 😉 Also I think taking video of the subject is much easier snd quicker to capture, than taking individual photos of it. You'd need to take hundreds of photos ideally, very time consuming captured individually, but a couple of minutes of video gives you those hundreds of image frames for a lot less effort. Video also provides "good data" i.e. coverage of the background scene while you're walking around the subject, reducing those fuzzy/blotchy areas.

@ZXVintage40 "high-resolution full colour graphics with BEEP sounds, professional level computing..." Gotta love the marketing. 😁 Good times though, Spectrum48K was my first computer as well.

@abdullin like they say: my LLM will be in touch with your LLM shortly... 😉

@abdullin Chat-GPT is pretty good at this kind of email text generation. There's a plugin for Gmail to integrate chat-gpt into Gmail message editor so you can generate message texts or replies to emails directly within gmail editor. I tried that plugin for responding to a request sent to me, trying both "positive can-do" and "negative hostile" response styles and the generated reply messages were really quite good, incorporating request details like task content and deadline dates correctly from original request email. Really quite fun way to "write" emails... If I had that chat-gpt plugin for company email, I'd probably use it every day ... 😅