Using Stable Diffusion with Python

Name: Using Stable Diffusion with Python
Price: 44.99 USD

$44.99

352 pages

Leverage Python to control and automate high-quality AI image generation using Stable Diffusion

bookJune 3rd, 2024

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Created by Andrew Zhu (Shudong Zhu)

Cover image for Using Stable Diffusion with Python

ISBN: 9781835086377

PID: B21263

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Master the art of generating stunning AI artwork with the help of expert guidance and ready-to-run Python code
Get instant access to emerging extensions and open-source models
Leverage the power of community-shared models and LoRA to produce high-quality images that captivate audiences
Purchase of the print or Kindle book includes a free PDF eBook

Table of Contents

22 Chapters

1
Introducing Stable Diffusion
2
Setting Up the Environment for Stable Diffusion
3
Generating Images Using Stable Diffusion
4
Understanding the Theory Behind Diffusion Models
5
Understanding How Stable Diffusion Works
6
Using Stable Diffusion Models
7
Optimizing Performance and VRAM Usage
8
Using Community-Shared LoRAs
9
Using Textual Inversion
10
Overcoming 77-Token Limitations and Enabling Prompt Weighting
11
Image Restore and Super-Resolution
12
Scheduled Prompt Parsing
13
Generating Images with ControlNet
14
Generating Video Using Stable Diffusion
15
Generating Image Descriptions using BLIP-2 and LLaVA
16
Exploring Stable Diffusion XL
17
Building Optimized Prompts for Stable Diffusion
18
Applications - Object Editing and Style Transferring
19
Generation Data Persistence
20
Creating Interactive User Interfaces
21
Diffusion Model Transfer Learning
22
Exploring Beyond Stable Diffusion