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Introduction to Stable Diffusion's parameters

(10th November 2022)

Sta­ble Dif­fu­sion is an im­age gen­er­ation net­work, which was re­leased to the pub­lic in 2022. It is based on a dif­fu­sion pro­cess, in which the model gets a noisy im­age as an in­put and it tries to gen­er­ate a noise-free im­age as an out­put. This pro­cess can be guided by de­scrib­ing the tar­get im­age in plain En­glish (aka txt2img), and op­tion­ally even giv­ing it a tar­get im­age (aka. img2img). This ar­ti­cle doesn't de­scribe how the model works and how to run it your­self, in­stead this is more of a tu­to­rial on how var­ious pa­ram­eters af­fect the re­sult­ing im­age. Non-tech­ni­cal peo­ple can use these im­age gen­er­at­ing AIs via web­pages such as Ar­tis­tic.wtf (my and my friend's pro­ject), Craiyon.com, Mid­jour­ney.com and others.

Languages: Python PyTorch
Tags: Computer Vision Autoencoder Stable Diffusion