Civitai Beginners Guide To AI Art // #4 U.I Walkthrough // Easy Diffusion 3.0 & Automatic 1111

20 Feb 202456:54

TLDRThis video guide introduces beginners to AI art creation using Easy Diffusion and Automatic 1111. It covers the user interface, generating the first AI image, and exploring various settings like seed, model, sampler, and CFG scale. The video also touches on using control nets and lauras for more advanced image crafting, emphasizing the importance of experimentation and exploration to master AI art generation.


  • 🌟 Introduction to Easy Diffusion and Automatic 1111 user interfaces for AI art generation.
  • πŸš€ Focus on getting comfortable with the software, starting with the basics before diving into more complex features.
  • πŸ’» Easy Diffusion's interface walkthrough, including launching the software and understanding the generate tab.
  • πŸ› οΈ Explanation of various features in Easy Diffusion such as settings, help, community, and model tools tabs.
  • 🎨 Demonstration of generating the first AI image using the default prompt and understanding the command prompt during the process.
  • 🌐 Discussion on the importance of keeping track of downloaded models and the organization of the model folder.
  • πŸ”„ Explanation of the image settings tab, including parameters like seed, number of images, model selection, and samplers.
  • πŸ”§ Details on advanced settings like control net image, custom V, and samplers for refining image generation.
  • πŸ“Έ Introduction to Automatic 1111's interface, highlighting the model selector, stable diffusion V, and text-to-image tab.
  • πŸ” How to use the control net extension in Automatic 1111 for advanced image manipulation.
  • πŸŽ“ Encouragement for users to experiment with the software and use inspiration from others to improve their AI art generation skills.

Q & A

  • What is the focus of this video in the AI art series?

    -The focus of this video is to familiarize viewers with the user interface of Easy Diffusion and Automatic 1111, and to guide them through generating their first basic AI image.

  • How can users get started with Easy Diffusion on Windows and Mac OS?

    -Users can get started by launching the 'start stable, diffusion, ui.CMD' file in the Easy Diffusion directory on Windows. For Mac OS, the process is similar but involves launching the application through the terminal or by using an alternative method shown in the installation video.

  • What are the main tabs in the Easy Diffusion interface?

    -The main tabs in the Easy Diffusion interface are Generate, Settings, Help and Community, What's New, and Model Tools.

  • What is the purpose of the negative prompt box in Easy Diffusion?

    -The negative prompt box allows users to specify elements or characteristics that they do not want to see in the generated image, helping to refine and control the output.

  • How can users customize the image settings in Easy Diffusion?

    -Users can customize the image settings by adjusting parameters such as the seed, number of images, model, sampler, image size, inference steps, guidance scale, and the use of control nets and lauras.

  • What is the role of the control net extension in Automatic 1111?

    -The control net extension in Automatic 1111 enables users to use control nets, which are additional layers of reference images, to influence the style or specific elements of the generated image.

  • How does the CFG scale in Automatic 1111 affect the generated image?

    -The CFG scale, or Control Flow Guidance scale, determines how closely the generated image adheres to the prompt. Higher values result in images that more closely match the prompt, while lower values allow for more creative freedom.

  • What is the purpose of the image to image tab in Automatic 1111?

    -The image to image tab in Automatic 1111 allows users to refine and improve existing images by using them as a base and applying additional prompts or adjustments.

  • How can users explore and experiment with AI image generation?

    -Users can explore and experiment with AI image generation by using websites like CΓ for inspiration, copying prompts and settings from existing images, and then tweaking and adjusting these parameters to create their own unique outputs.

  • What is the significance of the seed in AI image generation?

    -The seed value determines the output of random number generators. With the same parameters and seed, the same image result can be achieved. Seeds are useful for consistency and for iterating on a specific image that a user likes.



🎨 Introduction to AI Art and Easy Diffusion UI

This paragraph introduces viewers to the basics of AI art and navigating the Easy Diffusion user interface. It emphasizes the importance of getting comfortable with the software, which can be overwhelming for beginners. The video focuses on the Windows version of Easy Diffusion, but notes that the Mac OS version is similar. The speaker shares tips on launching Easy Diffusion on Mac OS and encourages viewers to explore the software's various tabs, such as Generate, Settings, Help and Community, What's New, and Model Tools, to enhance their AI art experience.


πŸ–ŒοΈ Crafting Prompts and Generating AI Images

The speaker delves into the process of crafting prompts and generating AI images using Easy Diffusion. They discuss the default prompt, the function of the image modifier button, and the importance of negative prompts to exclude unwanted elements from the generated images. The paragraph also covers the use of embeddings and the significance of the seed in image generation. The speaker demonstrates how to generate an AI image by clicking 'Make Image' and explains the role of different tabs and settings in refining the AI art process.


πŸ› οΈ Customizing Image Settings and Models

This section focuses on customizing image settings and selecting models in Easy Diffusion. The speaker explains the role of the model dropdown, the impact of different models on image style, and the importance of the control net image for generating images based on specific references. They also discuss advanced settings like CLIP skip and the use of custom V, highlighting how these features can influence the final image. The paragraph emphasizes the importance of experimenting with different samplers to achieve varied visual results.


πŸ“ Adjusting Image Resolution and Inference Steps

The speaker discusses adjusting image resolution and inference steps in Easy Diffusion. They explain that the default resolution for stable diffusion models is 512x512 and that changing the resolution can affect the quality and generation speed of images. The paragraph also covers the inference steps, which determine how many times the software iterates over the image generation process. The speaker demonstrates the effects of varying the number of steps and the guidance scale, which controls how closely the AI adheres to the prompt.


🎨 Exploring Advanced Settings and Output Formats

In this paragraph, the speaker explores advanced settings in Easy Diffusion, such as seamless tiling and output formats like JPEG, PNG, and webp. They discuss the image quality slider and the option to enable Vay tiling for optimizing memory usage. The speaker also covers the render settings, including the live preview function and the option to fix incorrect eyes and faces. They conclude by discussing the upscale feature, which can increase the resolution of the generated image, and the importance of experimenting with different settings to achieve desired results.


πŸ› οΈ Navigating System Settings and Extensions

The speaker guides viewers through the system settings of Easy Diffusion, highlighting core settings such as the theme, autosave images, models folder, and safe filter. They also discuss the importance of configuring the GPU memory usage and the option to use the CPU for image generation. The paragraph covers the autosave settings, the confirmation of dangerous actions, and the profile name. The speaker encourages viewers to explore the extensions tab, emphasizing the need to install the control net extension for advanced image manipulation capabilities.


πŸ”„ Understanding Control Nets and Extensions in Automatic 1111

The speaker introduces the Automatic 1111 user interface, focusing on the control net extension and its importance for image manipulation. They explain how to install the control net extension and the benefits of having a control net folder for organizing control net models. The paragraph also covers the various tabs in Automatic 1111, such as text to image, image to image, extras, PNG info, checkpoint merger, train, settings, and extensions. The speaker emphasizes the importance of the extensions tab for enhancing the functionality of the program.


🎨 Generating Images with Automatic 1111

This section provides a walkthrough of generating images using Automatic 1111. The speaker explains the process of selecting models, entering prompts, and using negative prompts to refine image generation. They demonstrate how to generate an image, discuss the role of the generation tab and its parameters, and explain the importance of the seed for consistency in image generation. The paragraph also covers the use of the control net extension window and the image preview options available in Automatic 1111.


πŸ–ΌοΈ Refining Images with Image to Image Tab

The speaker explores the image to image tab in Automatic 1111, which allows users to refine existing images using control nets and other parameters. They demonstrate how to use a base image and apply new prompts to generate a refined image, highlighting the importance of the denoising strength parameter. The paragraph also discusses the potential outcomes of adjusting the denoising strength and how it influences the final image, showing an example of a dragon cat created by blending a cat image with the concept of a dragon.


🌐 Exploring AI Art and Experimenting with Prompts

The speaker encourages viewers to explore AI art by visiting, finding images they like, and experimenting with the prompts and settings used to generate those images. They suggest using the seed and CFG scale from an existing image as a starting point for creating new AI art. The paragraph emphasizes the importance of continuous experimentation and play as the best way to improve and become more comfortable with AI image generation tools like Easy Diffusion and Automatic 1111.



πŸ’‘AI Art

AI Art refers to the creation of artistic images or visual content using artificial intelligence, particularly in the context of this video, it involves using AI models like Stable Diffusion to generate images based on textual prompts or other input.

πŸ’‘User Interface

The User Interface (UI) is the system through which users interact with the software, including the layout of the screens, buttons, and menus that allow for navigation and function execution.

πŸ’‘Stable Diffusion

Stable Diffusion is an AI model used for generating images from textual descriptions or 'prompts'. It is one of the tools discussed in the video for creating AI Art.


In the context of AI Art, a prompt is a textual description or input that guides the AI model to generate a specific type of image. It serves as the creative direction for the AI.

πŸ’‘Image Modifiers

Image Modifiers are additional instructions or settings that can be applied to alter the characteristics of the AI-generated images, such as style, color, or other visual elements.

πŸ’‘Control Net

A Control Net is a feature in AI Art generation that allows users to use a reference image as a base layer for the AI to build upon, influencing the final output to match certain styles or elements.


A Sampler in AI Art generation refers to the algorithm used by the AI model to produce the final image. Different samplers can result in varying visual styles and levels of detail.

πŸ’‘CFG Scale

CFG Scale, or Control Flow Guidance, is a parameter that determines how closely the AI model adheres to the prompt. Higher values mean the AI will try harder to match the prompt, while lower values allow for more creative freedom.


An Upscaler is a tool or function that increases the resolution of an image, often used in AI Art generation to enhance the quality of the generated images for better viewing or printing.


Extensions in the context of AI Art software like Automatic 1111 are additional features or tools that can be installed to enhance the functionality of the base program, such as enabling Control Nets or other advanced features.


Introduction to the user interface of Easy Diffusion and Automatic 1111 for beginners.

Explanation of the Easy Diffusion interface, including the Generate Tab and its functions.

Demonstration of how to generate the first AI image using Easy Diffusion.

Discussion on the Settings tab in Easy Diffusion and its importance for customization.

Overview of the Model Tools tab and its role in organizing and updating lauras (AI models).

Explanation of the Image Settings and how they affect the generation process in Easy Diffusion.

Introduction to the Automatic 1111 interface and its layout.

Importance of installing the Control Net extension for Automatic 1111.

Demonstration of the Text to Image tab in Automatic 1111 and its functionalities.

Explanation of the Image to Image tab for refining images based on existing references.

Discussion on the use of seeds for consistency in image generation.

Explanation of the CFG scale and its impact on how closely the AI adheres to the prompt.

Introduction to the PNG Info tab for extracting generation information from existing images.

Recommendation to explore for inspiration and to practice image generation.

Emphasis on the importance of experimentation and play for learning AI art generation.