List page: Stable diffusion
Tag specific RSS FeedExploring stable diffusion guidance.
(Stable diffusion)The guidance scale parameter controls how strongly the generation process is guided towards the prompt. A value of 0 is equivalent to no guidance, and the image is completely unrelated to the prompt (it can however, still be an interesting image). Increasing the guidance scale increases how closely the image resembles the prompt, but reduces consistency and tends to lead to an overstaturated and oversharpened image.
... read more.Exploring step counts in stable diffusion.
(AI, ML and if statements ) (Stable diffusion)TLDR: The step count has very litle effect on image content, and increasing it has rapidly deminishing returns over 20 steps.
... read more.Smooth prompt interpolation with stable diffusion. [SD part 3]
(AI, ML and if statements ) (Stable diffusion)You have probably seen smooth animations made with stable diffusion like this: https://www.youtube.com/watch?v=Bo3VZCjDhGI But how was it done?
The answer is very simple, by running multiple prompts on the same image, the noise predictions can be combined to create an intermediate image. Changing the relative weights of the prompts, but keeping the initial latents (seed value) the same, a series of intermediate images can be created.
... read more.Stable diffusion, in code. [SD part 2]
(AI, ML and if statements ) (Stable diffusion)If you have not read the last post, I would highly recommend you read it first.
Full disclosure, I will be using pre-trained models from the internet for unet, CLIP TextEncoder, and vae.
... read more.Just how does stable diffusion actually work? [SD part 1]
(AI, ML and if statements ) (Stable diffusion)Stable Diffusion is a newish (Dec 20, 2021) image generation model. It can generate quickly generate highly detailed images with a concise text prompt:
... read more.