Local Image Generation : With open models and open-source tools

Will Kurt is the author of Get Programming with Haskell and Bayesian Statistics the Fun Way. He also writes the Count Bayesie blog. He has done AI and machine learning work for over a decade.

• INTRODUCTION 0 CREATOR, NOT CONSUMER PART 1: GETTING STARTED 1 MAKING OUR FIRST IMAGE: "A DAMN FINE CUP OF COFFEE" 2 EASIER IMAGE GENERATION WITH STABLE DIFFUSION WEBUI 3 PROGRAMMING STABLE DIFFUSION WITH HUGGING FACE DIFFUSERS 4 UNDERSTANDING HOW STABLE DIFFUSION WORKS PART 2: CREATING BETTER IMAGES 5 USING CUSTOM CHECKPOINTS FOR BETTER IMAGES 6 IMPROVING IMAGES WITH SAMPLERS 7 CREATING HIGH RESOLUTION IMAGES 8 BUILDING ADVANCED WORKFLOWS WITH COMFYUI PART 3: ADVANCED TECHNIQUES 9 BETTER IMAGE GENERATION WITH FLUX 10 THE FLUX WORKFLOW 11 DEEPER CUSTOMIZATION USING LORA 12 USING CONTROLNETS PART 4: CREATING YOUR OWN MODELS 13 TRAINING A FLUX LORA 14 CHECKPOINT MERGING 15 FINE-TUNING STABLE DIFFUSION  APPENDIX APPENDIX A: INSTALLING STABLE DIFFUSION

“This is one of the few resources you can find that enable you to learn how to start and become proficient in image creation, without relying on paid services like Midjourney.” Riccardo Marotti, Head of Software Engineering, Expert Lab Service  “This book is the perfect introduction to image generation with Stable Diffusion.” Cosimo Attanasi, Senior Software Developer and Process Automation Engineer, ERSistemi S.p.A.