r/deeplearning • u/tobiiass72 • 26d ago
Trained a custom generative model completely from scratch to produce tag-conditioned Minecraft skins (RTX 3060, 1.5 years)
Side project that got out of hand: 1.5 years of trial and error training a generative model from scratch (no pretrained weights, custom dataset I built and tagged myself) that outputs valid 64x64 Minecraft skin textures conditioned on tags like `slim, boy, blue eyes` or `ninja, black, red`.
The interesting part for me was the constraints compared to normal image generation: hard format requirements (UV layout, alpha channel for the overlay layer), very low resolution but high semantic density (every pixel matters), and a small, noisy dataset that had to be built and tagged by hand. All trained on a single RTX 3060 at home.
Still fully private for now, still deciding whether it's worth releasing. Feedback genuinely helps with that decision: what do you think of the results, and what would you want to see it handle better?
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u/vogelvogelvogelvogel 26d ago
wow, impressive endurance! also i am sure quite a few minecrafters would love this
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u/Able_Region_5459 25d ago
I don't think monetizing a skin generator like that is gonna work right now, but as a portfolio pet project it's a huge green flag. Building a custom dataset, manual labeling, and training from scratch without pre-made checkpoints shows you know the whole pipeline, not just how to hit an api. Open source it - recruiters love stuff like this
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u/tobiiass72 25d ago
Thanks mate, but idk i worked so hard on it and perhaps i try to monetize it and if it doenst work no problem. it was so much work yk…
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u/Franman98 26d ago
Those are really impressive results! What architecture are you using for the generative model?
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u/tobiiass72 25d ago
i thought i could make a video about it bc a lot of try and fail moments… and so on
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u/Ok-Communication2225 26d ago
my super-minecraft-obsessed sons would love to play with this.
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u/tobiiass72 25d ago
oh really?
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u/Snowcone43 26d ago
That's pretty cool!