greg (@greg_ash) header
greg (@greg_ash) profile picture

computer graphics, sometimes music. writing code @nianticlabs and https://teapaw.org/t.co/fdyk8D7rug

London
Joined July 2015
Photo by greg (@greg_ash)Photo by greg (@greg_ash)Photo by greg (@greg_ash)Photo by greg (@greg_ash)Photo by greg (@greg_ash)Photo by greg (@greg_ash)Photo by greg (@greg_ash)Photo by greg (@greg_ash)Photo by greg (@greg_ash)
hippopotamoose
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i've released a new beta version of bauble. there's still a lot to do, but it's Mostly Usable now! i'm especially excited about the new interactive documentation page: bauble.studio/help/
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Anyone else just permutating the order of transformation matrices, and randomly wrapping them in inverse() and transpose() until they eventually work? Or do people actually get this right the first time?
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Wrote a bytebeat synthesizer in pure OCaml 💪😤
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i saw this first thing this morning now you have to
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Parameters (sound on). Sound, lines, and dots seeking a relationship. Experiment with additive synthesis affected by various parameters also mapped to visual representation. Sound and visual written in GLSL. Some reverb added. #generativeart #generativeart
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“No computer scientist, as far as I know, has ever actually come up with ‘being fun’ as a criterion for what to do with a computer or how to do it. And yet, It’s pretty clear that if something isn’t fun to do it’s not going to happen.” - Miller Puckette youtube.com/watch?v=ZLACjtOp…
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Were you ever frustrated with jagged edges in AR?! 💔 No more! ✨ 📢 Introducing our #CVPR2023 paper (and code!): Virtual Occlusions Through Implicit Depth❤️🎉 nianticlabs.github.io/implic… arxiv.org/abs/2305.07014 [1/10]
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🧵1/ We’re very excited about SimpleRecon! It brings together state-of-the-art depth accuracy and competitive 3D scene reconstruction which makes it perfect for resource-constrained environments! We used @rerun to dig into its inner workings. #computervision #AI #ML
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<graphics geek warning> Watching the space scenes in the Martian on an OLED TV should be an ideal viewing experience with the true black backgrounds, but in every shot that panned, I couldn’t stop fixating on the incorrect twinkling of all the stars. This is almost always caused by something linearly interpolating pixels that are in a gamma encoded color space. The 0-255 pixel values that you find everywhere aren’t linear — 64 is not twice the photons of 32. It is close enough that you usually won’t notice, but high contrast star fields and line drawings are the worst case. en.wikipedia.org/wiki/Gamma_… There are so many places this can go wrong. I assume the movie master is rendered correctly, but any resampling to a different resolution will probably do it wrong. I was watching in 4K, but 3840x2160 is not the native theatrical resolution. There is an @FFmpeg option to do gamma correct resizing, but it isn’t the default because it is quite a bit slower. Lossy compression can also mess up the subtle fractional pixel values, but star fields should not be challenging to compress. A fixed bit rate should be nearly lossless in “easy” scenes like that, but an adaptive one can drop it to a trickle and make the errors perceptible. A 4K video decoded to a 4K buffer sent to a 4K TV should not involve any resampling, but it is easy for a half pixel offset to slip in somewhere, and GPUs don’t offer a gamma correct YUV textures sampling mode. If you need resampling (as in a VR screen) the best practice is to copy the YUV video to an sRGB texture, then draw that. Any color space transform for the various “vivid” / “cinematic” / whatever modes that gets done in the media device or TV also have to be done in linear space to avoid issues. I tend to rail against these abuses of the pixels, but if you must do it, at least do it right. The same with any motion interpolation or other features on the TV. At the very end, the display panel must actually accurately reproduce the gamma curve everything else in the pipeline expected. There are legitimate subtleties here, like 2.2 vs sRGB, but sometimes things are deliberately distorted to “punch up” unknowing content. So many problems vanish if you just work in 12+ bit linear space, but so far, it has generally been better on net to spend memory/GPU/display bandwidth on higher resolution or frame rates. It is creeping in, but it will be many years yet before end to end linear is common.
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greg retweeted
0b5vr GLSL Techno Live Set 7 minutes of GLSL techno journey with a VJ graphics. in a 64KB WebGL Intro. Appeared in the Revision 2023 PC 64K Intro Compo. youtu.be/3lOptjAeA2w
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WIP grass.
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Another sketch - this time combining both the curl noise sampling and here geometric surface walking. It gives a very nebular or constellation feel to it ✨🦀 gkjohnson.github.io/three-sk… #threejs #webgl #generative #art #spacecrab
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greg retweeted
vec3 p=vec3(0,0,3),v=vec3(FC.xy*2.-r,r.y);for(float T,d,i,n=fsnoise(ceil(FC.y/r+t/.3));i++<2e2;p-=v/length(v)*d)T+=d=min(length(max(abs(p*rotate3D(n*t,tan(r.yxy+n)))+n-1.,-n*n*.8))-n*n,1.-p.y),i>1e2?d+=1e-5,v=fract(cos(t+sqrt(FC.x*FC.y*vec3(9,7,5)))*5e3),o.g=T:T=0.; #GLSL
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greg retweeted
DiffusioNeRF: Regularizing Neural Radiance Fields with Denoising Diffusion Models abs: arxiv.org/abs/2302.12231
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Almost there, @Sonic_Pi v5 Tech Preview 1 with support for live coding Hydra visuals will be dropping for Patreon supporters imminently. (Hydra example by Nelson Vera)
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Teaching my dad, at the age of 70, how to use a TB303 in under 2 and a half minutes... Added some 909, reverb and distortion 'n' he was off! #acid #tb303 #dads
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The Continuity of Splines is now on YouTube!! it has been a year in the making, goodness ;-;🎉 I hope you'll like it ❤ ❱ youtu.be/jvPPXbo87ds
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A little piece I wrote for today’s i newspaper about why - I think - you don’t see more girls doing maths. In short: it’s death by a thousand cuts. inews.co.uk/opinion/hannah-f…
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Binary search for SDF raycasting. tldr; don't, stick to traditional raymarching! iquilezles.org/articles/bina…
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