In this post, I want to share with you my project on the discovery of “Stable Diffusion”.
Introduction
Stable Diffusion is an advanced artificial intelligence model designed for the generation and transformation of images. It relies on deep learning techniques to creatively and realistically process and modify images. Initially designed to generate images from text descriptions, Stable Diffusion has evolved to also accept images as input. This capability makes Stable Diffusion particularly useful for applications such as photo retouching, AI-assisted artistic creation, and image quality enhancement.
About the Project
This project allows for easy deployment of “Stable Diffusion XL with Controlnet” in the AWS cloud on an EC2.
It automates the creation and configuration of the necessary infrastructure to run “Stable Diffusion XL with Controlnet”.
The installation of Stable Diffusion is manually done once the EC2 is available (with a copy/paste guide).
To limit EC2 costs, a spot instance of type g4dn.xlarge is used (1 NVIDIA T4 GPU 16 GB GDDR6, 4 Intel Cascade Lake vCPUs, 16 GB RAM).
The deployment of Stable Diffusion is carried out with the AUTOMATIC1111 installer.
Architecture
Project Goals
- Image Generation: Generate high-quality images from a prompt.
- Accessibility: Make these technologies accessible and understandable.
- Open Collaboration: Encourage collaboration and knowledge sharing.
> > > > > > > > > > Visit my project on GitLab by clicking here < < < < < < < < < <
This document has been translated from the French version of the blog by the gpt-4-1106-preview model.