Hands-on code examples for stable diffusion and Python enable immediate learning and application
Covers advanced techniques like LoRA, textual inversion, and ControlNet for enhanced image generation
Includes access to emerging extensions and open-source models for staying current with developments
Focuses on real-world applications in medical imaging, remote sensing, and photo enhancement
Provides insights into data persistence, prompt optimization, and integration with AI models like BLIP
Summarized by Shop
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 Key Features
Master the art of generating stunning AI artwork with the help of expert guidance and ready-to-run Python code
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Format
Print book
Language
English
Includes
Free PDF ebook
Key features
Code-based instruction, community model access, real-world application coverage
Target audience
Data scientists, ML engineers, Python developers, researchers