June 2024
Intermediate to advanced
352 pages
8h 8m
English
Content preview from Using Stable Diffusion with Python
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Part 3 – Advanced Topics
In Parts 1 and 2, we established a solid foundation for Stable Diffusion, covering its fundamentals, customization options, and optimization techniques. Now, it’s time to venture into more advanced territories, where we’ll explore cutting-edge applications, innovative models, and expert-level strategies to generate remarkable visual content.
The chapters in this part will take you on a thrilling journey through the latest developments in Stable Diffusion. You’ll learn how to generate images with unprecedented control using ControlNet, craft captivating videos with AnimateDiff, and extract insightful descriptions from images using powerful vision-language models such as BLIP-2 and LLaVA. Additionally, you’ll get acquainted ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.