• A machine learning technique that lets you generate photorealistic images of specific subjects in a variety of different contexts.
• Stable Diffusion knows everything about the general world - what clouds look like, how bald Dwayne “The Rock” Johnson is, and what rainbows are made of. Using Dreambooth, you can teach it what you look like too!

Dream-booth + SD:

• To use Dream-booth, we’ll have to give it some training data: a set of images of ourselves, or whoever we want to generate images of, along with a label (our name) and the class of objects the thing belongs to (human). Dream-booth then fine-tunes a pre-trained text-to-image model to learn to recognize and generate images of the specific subject.

Workflow:

We've got the OG Stable Diffusion model. That's not the special part. What's really going to make it ours is the set of input photos we'll use. Here's a simplified flow of how it'll work:

1. The SD model is trained on a dataset of images that represent one subject (you).
2. Using the input photos, the model extracts the key features and characteristics of the faces in the photos.
3. The model uses the extracted features to generate new, synthesized images that resemble the input photos but have their own unique style and variations based on our text.