HTML5 for Flash Developers. This is the definitive tutorial on an essential skill for today's Flash developers. Carefully structured, it helps you to make the transition to HTML5 painless by drawing on your existing Flash abilities wherever possible

Matthew Fisher

As the support for HTML5 within modern web browsers grows, the appeal of HTML5 development, especially for Flash developers, is at an all-time high. From 3D interactive multi-user content to high definition video streaming, HTML5 can deliver it all, to almost all modern web browsers, desktops, and mobile platforms. HTML5 for Flash Developers is a practical, targeted guide for developers with previous experience in developing applications in Flash who would like to add HTML5 development to their skill set. By understanding key aspects that make HTML5 development different from Flash you will be able to integrate your current skill set into the HTML5 development paradigm. Starting with identifying the key technologies that make up the HTML5 development stack and how they are utilized to create HTML5 content, HTML5 for Flash Developers will cover the traditional HTML5 application development flow chapter by chapter, while covering many other common tools that are regularly used in HTML5 today.In addition to understanding and writing dependency-free HTML5 code, you will also learn how to build your HTML5 applications on top of popular libraries and frameworks such as jQuery and CreateJS. This book covers how to prepare all of your content and media for integration into your HTML5 application using applications such as the Miro Video Converter or Adobe Photoshop. You will learn ways to not only continue to use Adobe Flash in your HTML5 application content preparation flow, but also how to port your existing Flash content right over to HTML5.Once you understand what it takes to build HTML5 content, you will finish up by learning how to debug, optimize, and prepare your content for release on the Web.

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

Andrew Zhu (Shudong Zhu), Matthew Fisher

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.