Machine Learning generated Pokémon graphics sprites #ML #MachineLearning

A new machine learning model generates Pokemon graphics sprites using text input.

clip-guided-diffusion-pokemon is a Cog implementation which generates pixel artwork from a prompt using a diffusion model trained on Pokémon sprites. Original implementation on this colab by @nshepperd1. Thanks Katherine Crowson for the diffusion model design.

The sheet on the left was generated using “two monsters fighting #pixelart” while the one on the right using “a fire pokemon #pixelart”

See more on replicate.ai and GitHub.

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Filed under: Artificial intelligence, graphics, machine learning —
Tags: , , — by Anne Barela

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