Stable Diffusion is a generative AI model that creates photorealistic images from text and image prompts. Launched by Stability AI in 2022, it's notable for its accessibility and user-friendliness. Users can run it on consumer-grade GPUs and have control over key hyperparameters like the number of denoising steps and noise application. The model operates on a reduced-definition latent space instead of pixel space, which significantly lowers processing requirements, allowing it to run on desktops or laptops with GPUs.
Key components of Stable Diffusion include a variational autoencoder, forward and reverse diffusion processes, a noise predictor (U-Net), and text conditioning. The variational autoencoder compresses and decompresses images for manipulation in latent space. Forward diffusion adds Gaussian noise to images, and reverse diffusion iteratively removes this noise. The noise predictor, crucial for denoising, uses the ResNet model for computer vision. Text prompts are analyzed by a CLIP tokenizer and fed into the model to guide image generation.
Stable Diffusion's capabilities extend beyond text-to-image generation; it can perform image-to-image conversion, create graphics and artwork, edit and retouch photos, and even create videos and animations. Its processing efficiency and broad availability mark it as a significant improvement in text-to-image model generation.
Stable Diffusion XL is an advanced AI model for image generation. It excels in creating detailed images from brief text prompts and can incorporate text directly into the images. This model enhances the quality of image composition and face generation, resulting in highly realistic and visually striking outcomes.
SDXL offers several ways to modify the images
- Inpainting - Edit inside the image
- Outpainting - Extend the image outside of the original image
- Image-to-image - Prompt a new image using a sourced image