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pugworthy 47 minutes ago [-]
Really neat idea - would have loved to have this 15-20 years ago!
I'm curious how it does for non-Earth data. Mars terrain for example.
dvt 2 days ago [-]
On my phone but very interested in this (hence leaving a comment so I can find it later). What’s the variation, can we generate different maps from the same low res seed?
I’m interested in this because “macro maps” can be hand built in a way that may want to preserve gameplay balance while individual games can still feel broadly unique.
joegibbs 2 days ago [-]
Thank you! Yes as well as the input image you can pass in a seed value (otherwise the result is deterministic). I hadn't tried it with pure noise rather than satellite data but it does pretty well: https://jgibbs.dev/assets/terrainsr-noise.png
jauntywundrkind 2 hours ago [-]
can you talk to some about how you trained this? this is such a neat idea!!
joegibbs 11 minutes ago [-]
Mostly through trial and error really, I started off getting a bunch of 100m and 10m satellite data then tried a few different methods. First I tried a bunch of ways to do it as a GAN, but there were too many artifacts and it lacked detail every time. Then I did a diffusion model that worked but took minutes to run, then kept distilling it down from 64 steps to 1 step, which looked basically the same as 64 but was fast. All in all it was about $100 to train.
I'm curious how it does for non-Earth data. Mars terrain for example.
I’m interested in this because “macro maps” can be hand built in a way that may want to preserve gameplay balance while individual games can still feel broadly unique.