How to Build a Stable Diffusion Image-to-Image Pipeline

Mark McQuade's blog post explores the use of generative AI, specifically the Stable Diffusion Image-to-Image Pipeline, to enhance computer vision training data. The article details the process of setting up and implementing this pipeline using the Hugging Face Diffusers library, SageMaker Notebooks, and image data from Roboflow. Stable Diffusion, a deep learning model released in 2022, is capable of generating detailed images based on text prompts, inpainting, outpainting, and image-to-image translations. The post guides users through creating a SageMaker notebook, importing necessary libraries, and using a construction safety dataset from Roboflow to generate images with varied backgrounds, thereby improving machine learning models' ability to learn from diverse data. The article highlights the potential of stable diffusion for enterprise applications in computer vision, emphasizing its utility in style transfer, domain adaptation, and generating unique outputs, with future advancements in generative AI anticipated to broaden its use across industries.