Using Stable Diffusion with Python
Andrew Zhu (Shudong Zhu)
Venduto da PBShop.store UK, Fairford, GLOS, Regno Unito
Venditore AbeBooks dal 11 giugno 1999
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Aggiungere al carrelloVenduto da PBShop.store UK, Fairford, GLOS, Regno Unito
Venditore AbeBooks dal 11 giugno 1999
Condizione: Nuovo
Quantità: Più di 20 disponibili
Aggiungere al carrelloNew Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Codice articolo L0-9781835086377
Master AI image generation by leveraging GenAI tools and techniques such as diffusers, LoRA, textual inversion, ControlNet, and prompt design in this hands-on guide, with key images printed in color
Stable Diffusion is a game-changing AI tool that enables you to create stunning images with code. The author, a seasoned Microsoft applied data scientist and contributor to the Hugging Face Diffusers library, leverages his 15+ years of experience to help you master Stable Diffusion by understanding the underlying concepts and techniques.
You’ll be introduced to Stable Diffusion, grasp the theory behind diffusion models, set up your environment, and generate your first image using diffusers. You'll optimize performance, leverage custom models, and integrate community-shared resources like LoRAs, textual inversion, and ControlNet to enhance your creations. Covering techniques such as face restoration, image upscaling, and image restoration, you’ll focus on unlocking prompt limitations, scheduled prompt parsing, and weighted prompts to create a fully customized and industry-level Stable Diffusion app. This book also looks into real-world applications in medical imaging, remote sensing, and photo enhancement. Finally, you'll gain insights into extracting generation data, ensuring data persistence, and leveraging AI models like BLIP for image description extraction.
By the end of this book, you'll be able to use Python to generate and edit images and leverage solutions to build Stable Diffusion apps for your business and users.
If you're looking to gain control over AI image generation, particularly through the diffusion model, this book is for you. Moreover, data scientists, ML engineers, researchers, and Python application developers seeking to create AI image generation applications based on the Stable Diffusion framework can benefit from the insights provided in the book.
(N.B. Please use the Read Sample option to see further chapters)
Andrew Zhu is an experienced Microsoft Applied Data Scientist with over 15 years of experience in the tech field. He is a highly regarded writer known for his ability to explain complex concepts in machine learning and AI in an engaging and informative manner. Andrew frequently contributes articles to Toward Data Science and other prominent tech publishers. He has authored the book "Microsoft Workflow Foundation 4.0 Cookbook," which has received a 4.5-star review. Andrew has a strong command of programming languages such as C/C++, Java, C#, and Javascript, with his current focus primarily on Python. With a passion for AI and Automation, Andrew resides in WA, US, with his family, which includes two boys.
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