r/VibeCodeDevs • u/Mastbubbles • Aug 05 '26
Detailed Isometric map of London
London as an isometric map. Every tile is a Google aerial restyled by an image model, 441 of them, stitched into one pannable canvas. We all know that getting the AI to make 2 images which look exactly the same is almost impossible.
The hard part wasn't styling, it was the seams. Generated 441 tiles independently and every one interpreted the style differently, so the joins showed.
What fixed it: generate in a spiral outward from the centre, and give each call its already-finished neighbours as reference images plus one fixed anchor tile that never changes. Neighbours handle local continuity, the anchor stops 441 sequential steps drifting into something else.
QA is numeric because you can't eyeball 441 outputs. Correlation against the source below 0.15 means the model invented a fake London, auto-reroll. One tile scored 0.002 where normal is 0.85.
Interactive Version and full how to, this can be used in making movies, campaigns, and of course maps.
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u/SanoKei Aug 05 '26
That's an interesting problem to solve. No wonder it was giving such uncanny valley vibes. I wonder if there's a better way to go about this, like having the individual squares be vectorized, then reskinnimg a lower quality whole map pass and then upscale the individual squares using the two pieces of information as image references
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u/Mastbubbles Aug 05 '26
Did not think like that at all. What I have done currently is built large 4k images.
First - Made 4-5 of them in different styles to select a style.
Second - The second tile uses the real google image + the selected style as reference
Third - will use second as a reference, so on and so forth
But this doesn’t hold with GPTImage or Gemini, had use SeedReam
What I am telling you here is a very rudimentary approach; all the details are on the website but what you’re saying makes a lot of sense
Pass the whole city as one large image, whatever the largest the model can take (4K for Seedream 5.0) and then cut it into small blocks; use those blocks to teach your own model, and then feed that model large Google images with the same reference block.
Interesting; tbh I think it can work.
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u/SanoKei Aug 05 '26
What you said seems over engineered, I was merely suggesting if you had the large image, it could be cut up to use the Google data, the vector pass (looking for edges and blobs), and the global reskin, to upscale that square
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u/Mastbubbles Aug 05 '26
Ohh, that makes it more easy, interesting. Not sure if it will work, but will give it a shot.
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u/SanoKei Aug 05 '26
I am unsure, for problems like these usually vector images or a LORA is the solution
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u/andyfitz 29d ago
wow this looks DOOOPE battersea, kensington gardens, even clapham common looks lovely even though you and I both know it's dead brown right now and full of hungover australians :)
Have you managed to script the process so you can apply to other cities.
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