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所在平台: Udemy |
课程主页: https://www.udemy.com/course/beginners-guide-to-stable-diffusion/
课程评论：没有评论
课程名称：初学者的稳定扩散指南与Automatic1111 课程概述：这门课程是关于利用生成性人工智能设计图像艺术的全面介绍。稳定扩散是由Stability AI发布的最强大AI工具之一，它为学习生成性人工智能提供了扎实的基础，具备足够技能的用户还可以在生产环境中使用。课程内容包括： - 稳定扩散简介 - 在Windows 10或11上使用Nvidia显卡安装稳定扩散的指南 - 用户界面理解 - 关键功能理解 学到的关键概念包括提示构建、评估和优化。稳定扩散是一种潜在扩散模型，是一种深度生成神经网络。其代码和模型权重已被公开发布，能够在配备至少8GB VRAM的普通消费者硬件上运行。课程还探讨了对于硬件性能较低用户的选项。 稳定扩散是完全免费和开源的，没有商业使用上的限制。它是最灵活的AI图像生成器，用户甚至可以根据自己的数据集训练自己的模型，以生成精确想要的图像。学生还学习了获取宝贵资源的渠道，如第三方检查点和模型，这些资源可提升工作流程并提供创作自由。 稳定扩散是一种深入学习的文字到图像模型，主要用于生成基于文字描述的详细图像。它还可以应用于其他任务，如填图（inpainting）、扩图（outpainting）和在文本提示指导下生成图像之间的转换。稳定扩散的主要应用场景包括： - 文字到图像：经典应用，用户输入文本提示，稳定扩散生成相应图像。 - 图像到图像：调整现有图像。用户提供一张图像和一个提示，稳态扩散利用该图像并向提示方向进行调整。 - 填图：仅在特定蒙版部分调整现有图像。 - 扩图：在现有图像的边界上添加内容。
This course is a complete introduction to the nearly magical art of designing images by the use of generative AI.Stable diffusion is one of the most powerful AI tools released by Stability AI and it provides a thorough basis for learning about generative AI generally, but also it can be used, with sufficient skill, in a production environment.The course includes the following•An Introduction to Stable Diffusion•A guide to Installing Stable Diffusion using an Nvidia Graphics Card on Windows 10 or 11•Understand the user interface•Understanding Key FeaturesKey concepts learned include prompt construction, evalution and optimization.Stable Diffusion is a latent diffusion model, a kind of deep generative neural network. Its code and model weights have been released publicly, and it can run on most consumer hardware equipped with a modest GPU with at least 8 GB VRAM.The course explores options for users with less powerful equipment.Stable Diffusion is entirely free and open-source, with no restrictions on commercial use. It is the most flexible AI image generator that you can even train your own models based on your own dataset to get it to generate exactly the kind of images you wantStudents also learn where to get valuable resources like 3rd party checkpoints and models which can be used to improve the workflow and to provide creative freedom.Stable Diffusion is a deep learning, text-to-image model that is primarily used to generate detailed images conditioned on text descriptions. It can also be applied to other tasks such as inpainting, outpainting, and generating image-to-image translations guided by a text prompt1. The main use cases of stable diffusion include:Text-to-Image: the classic application where you enter a text prompt and Stable Diffusion generates a corresponding image.Image-to-Image: tweak an existing image. You provide an image and a prompt and SD uses your image and tweaks it towards the prompt.Inpainting: tweak an existing image only at specific masked parts.Outpainting: add to an existing image at the border of it.
