Stable Diffusion Demo and Tutorial

Fractal Labs
22 Aug 202313:07

TLDRIn this informative video, Alexis Mercedes from Fractal Labs introduces Stable Diffusion, a locally-hosted generative AI tool, and guides viewers through its setup and various use cases. The video offers a detailed tutorial on installing the software, modifying settings for enhanced performance, and creating images based on text prompts. It also explores features like image-to-image editing and upscaling, and discusses the potential and challenges of such powerful AI tools in terms of user experience and future regulations.


  • πŸš€ Alexis Mercedes, the project manager of Fractal Labs, introduces Stable Diffusion, a locally hosted generative AI tool.
  • πŸ“š A step-by-step tutorial is provided for setting up, demoing, and exploring Stable Diffusion's use cases with a UX analysis.
  • πŸ’» To begin, download Python 3.10.6 and Git, ensuring Python is added to the system path during installation.
  • 🌐 Automatic 1111 serves as the browser interface for interacting with Stable Diffusion on a personal computer.
  • πŸ›  Optimizations can be made for Nvidia GPU users to accelerate image generation through modifications in the Web UI-user.bat file.
  • πŸ–ΌοΈ Stable Diffusion's basic function is text-to-image generation, with varying results depending on the prompt.
  • 🎨 The tool also supports image-to-image functions, including in-painting and sketch-in-painting for creative adjustments.
  • πŸ“ˆ Unique features of Stable Diffusion include upscaling images and background removal, enhancing user capabilities.
  • πŸ”§ Extensions like d4m for animations and Dreamboat for training custom models showcase the tool's versatility and extensibility.
  • πŸ“ The UX analysis highlights the challenges of using powerful applications with complex user experience designs.
  • 🌟 Fractal Labs emphasizes the importance of creating apps with exquisite design, incorporating AI and machine learning in a seamless and secure manner.

Q & A

  • Who is the speaker in the video and what is their role?

    -The speaker in the video is Alexis Mercedes, the project manager of Fractal Labs, an app development team focused on improving user experience of cutting-edge software.

  • What is the main topic of the video?

    -The main topic of the video is the demonstration and tutorial on setting up and using Stable Diffusion, a locally hosted generative AI tool.

  • What are the steps to install Python for the Stable Diffusion setup?

    -To install Python for the Stable Diffusion setup, download Python 3.10.6 from, and during installation, ensure to check the box to add Python to the system path.

  • What is the purpose of installing Git along with Python?

    -Git is installed to facilitate the cloning of the repository needed for the Stable Diffusion setup, and it is set up with default settings during the installation process.

  • What is Automatic 1111 and how does it relate to Stable Diffusion?

    -Automatic 1111 is a browser interface built upon the Radio Library. It serves as the web interface to interact with the locally hosted Stable Diffusion program on a personal computer.

  • How does one enable the use of Nvidia GPU with Stable Diffusion?

    -To enable the use of an Nvidia GPU with Stable Diffusion, a modification is made to the Web UI-user.bat file by adding '--transformers' in the command line arguments.

  • What is the basic function of Stable Diffusion?

    -The basic function of Stable Diffusion is to generate images from text prompts, often referred to as text-to-image functionality.

  • What are some of the unique features of Stable Diffusion compared to other text-to-image AI tools?

    -Stable Diffusion offers unique features such as image-to-image generation, including in-painting and sketch-in-painting, upscaling of images, background removal, and the ability to train custom models with extensions.

  • What challenges does the user experience (UX) analysis of Stable Diffusion present?

    -The UX analysis of Stable Diffusion presents challenges such as the lack of a standalone app, the need for community standards due to the open-source nature of the tool, and the potential difficulty in learning how to use more powerful applications with excellent user experience design.

  • What is the speaker's suggestion for improving Stable Diffusion's user experience?

    -The speaker suggests that built-in instructions, such as explanations that pop up upon hovering over feature names, could improve the user experience of Stable Diffusion.

  • How does the speaker view the future of Stable Diffusion and its development?

    -The speaker sees the future of Stable Diffusion as one with infinite extensions due to its open-source nature, rapid development, and a community of users constantly creating new features and improvements.



🌟 Introduction to Stable Diffusion and Setup Process

This paragraph introduces the viewer to Alexis Mercedes, the project manager of Fractal Labs, who is passionate about improving user experience with cutting-edge software. The main theme revolves around the local hosting of generative AI, specifically Stable Diffusion, which allows users to bypass web app restrictions. Alexis provides a step-by-step tutorial on setting up Stable Diffusion, starting from downloading Python 3.10.6, installing Git, and using the command prompt to clone the repository. The paragraph also touches on the optional modification for enabling xformers to accelerate image generation on Nvidia GPUs. The process concludes with running the web UI user file and accessing the local host URL in a web browser to get Stable Diffusion up and running.


🎨 Capabilities and UX Analysis of Stable Diffusion

This paragraph delves into the capabilities of Stable Diffusion, highlighting its strengths in creating images in styles like synthwave and mimicking certain artists. It discusses the hit-or-miss nature of generating realistic images and provides a comparison with other similar tools. Alexis demonstrates text-to-image functionality with various prompts and showcases the tool's ability to improve outputs based on additional information provided by the user. The paragraph also explores image-to-image functions, including in-painting and sketch-in-painting, which allow users to modify existing images or add their drawings. The unique features of upscaling and background removal are mentioned, as well as the potential for animations through an extension. The UX analysis points out that Stable Diffusion is not a standalone app, which presents a challenge for user experience, but also emphasizes the benefits of ownership, such as the absence of community standards and the potential for infinite extensions due to its open-source nature. The paragraph concludes with a reflection on the importance of excellent user experience design in powerful applications and a brief mention of the role of government policies in AI development.


πŸ€– Future of AI and the Role of Fractal Labs

In this final paragraph, the focus shifts to the broader context of AI and its future, particularly in relation to government policies and the role of Fractal Labs. Alexis discusses the potential for Stable Diffusion to be more powerful and dangerous without community restrictions, and suggests improvements such as built-in instructions for features. The open-source nature of Stable Diffusion is highlighted, emphasizing the rapid development and upgrades facilitated by a non-profit community. The paragraph also touches on the challenges of learning powerful applications and the goal of Fractal Labs to create apps with excellent design that incorporate machine learning and AI in a seamless and secure manner. The discussion concludes with a mention of the White House's efforts to create guidance and policies for AI system deployment, and Alexis invites viewers to look forward to more reviews on UX design for cutting-edge software.



πŸ’‘Generative AI

Generative AI refers to artificial intelligence systems that are capable of creating new content, such as images, text, or music. In the context of the video, the focus is on a specific type of Generative AI that can produce images based on textual descriptions. The video discusses the use of Stable Diffusion, a locally hosted generative AI tool, which allows users to generate images on their own computer, bypassing the restrictions of web-based applications.

πŸ’‘Stable Diffusion

Stable Diffusion is a generative AI tool that enables users to generate images from text descriptions. It is distinguished by being hosted locally on a user's computer, which offers more flexibility and control compared to web-based AI tools. The video provides a tutorial on setting up and using Stable Diffusion, highlighting its capabilities and potential applications.

πŸ’‘Local Hosting

Local hosting refers to the practice of running a software or application on a personal computer or a private server, rather than relying on a web-based service. In the video, local hosting of Stable Diffusion is emphasized as it allows users to bypass the rules and restrictions that come with using online platforms, providing greater freedom and control over the AI tool.


Python is a widely-used high-level programming language known for its readability and ease of use. In the context of the video, Python is the programming language on which the Stable Diffusion tool operates. It facilitates the processes necessary for the AI to function, even though the user may not directly interact with Python but rather uses it as a background process.


Git is a distributed version control system that allows developers to track changes in the code and collaborate on projects. In the video, Git is used to download and manage the source code of Stable Diffusion from its online repository to the user's local computer.

πŸ’‘Automatic 1111

Automatic 1111 is a browser interface built on top of the Radio Library, which is used to interact with locally hosted AI tools like Stable Diffusion. It serves as the user's point of interaction with the AI, allowing them to input text prompts and view the generated images in a web browser.


Text-to-Image is a functionality of generative AI tools like Stable Diffusion that converts textual descriptions into visual images. This feature is central to the video's demonstration, showcasing the AI's ability to interpret and create images based on the provided text prompts.


Censorship refers to the suppression or prohibition of speech or images considered offensive or inappropriate by a governing body or other authority. In the context of the video, the discussion around censorship addresses the limitations faced by AI tools when they are hosted on web platforms that enforce community standards, which may restrict the content that can be generated.


Image-to-Image is a feature of generative AI tools that allows users to modify existing images by adding or changing elements based on a textual prompt. This functionality is showcased in the video, demonstrating how Stable Diffusion can adjust an image according to the user's specifications.


In-Painting is a feature that enables users to edit images by adding or modifying elements directly onto the image. Unlike image-to-image, which generates a new image based on the prompt, in-painting uses the existing image as a canvas to incorporate the user's changes. This is highlighted in the video as a unique capability of Stable Diffusion.

πŸ’‘UX Analysis

UX Analysis refers to the evaluation and critique of a product's user experience design. It involves assessing how intuitive, efficient, and enjoyable a product is to use. In the video, the speaker provides a UX analysis of Stable Diffusion, discussing its strengths and areas for improvement in terms of user experience.

πŸ’‘Open Source

Open source refers to a type of software licensing where the source code is made publicly available, allowing users to view, modify, and distribute the software freely. In the context of the video, Stable Diffusion being open source is highlighted as a key advantage, enabling a community of users to continuously develop and improve the tool with new features and extensions.


Alexis Mercedes is the project manager of Fractal Labs, an app development team focused on improving user experience for cutting-edge software.

The video provides a tutorial on setting up and using Stable Diffusion, a locally hosted generative AI tool.

To start with Stable Diffusion, download Python 3.10.6 from and ensure to add Python to your system path during installation.

Git should be installed with all default settings to facilitate the process of using Stable Diffusion.

Automatic 1111 is a browser interface built upon the Radio Library, used to interact with Stable Diffusion hosted on your personal computer.

The process involves cloning a repository and navigating through folders to launch Stable Diffusion via a local host URL.

Enabling Xformers can accelerate image generation if you have an Nvidia GPU.

Stable Diffusion's basic function is text-to-image, with varying results depending on the prompt.

The tool is capable of creating images in styles like synthwave or mimicking certain artists, but generating realistic images can be hit or miss.

Stable Diffusion also offers image-to-image functionality, which includes in-painting and sketch-in-painting.

In painting allows you to replace parts of an image, while sketch allows adding your own drawings to the input.

Stable Diffusion can upscale images and remove backgrounds, offering unique features for image manipulation.

Extensions like d4m enable animations and Dreamboat allows training your own models for customized outputs.

The UX analysis suggests that while powerful, the tool is not a standalone app and lacks built-in instructions for features.

Ownership of the tool means following no community standards, which can be seen as both an advantage and a potential risk.

Stable Diffusion is open source, leading to rapid development and upgrades due to its non-profit nature.

The challenge of learning powerful applications is to balance that power with intuitive user experience design.

Fractal Labs is committed to creating apps with excellent design, incorporating machine learning and AI in a seamless and secure manner.

Government policies on artificial intelligence are expected to shift, with the White House working on guidance and protocols for federal departments.