Mastering SDXL Inpainting: Create Stunning Art with Stable Diffusion and Automatic 1111

AIchemy with Xerophayze
31 Oct 202337:22

TLDRIn this tutorial, Eric from Alchem Zero demonstrates the inpainting process using Stable Diffusion and the SDXL models to create art. He addresses common issues with edges not blending properly and shares tips on using the 1.5 and 2.1 inpainting models for better results. The video guides viewers through selecting the right model, adjusting settings like mask blur and sampling steps, and provides practical examples of inpainting faces, hands, and objects in images to achieve a more realistic and blended outcome.

Takeaways

  • 😀 The video is a tutorial on inpainting with Stable Diffusion and SDXL models, addressing common issues like edges not blending properly.
  • 🤖 Eric, the presenter, discusses the lack of development on inpainting models specifically for SDXL and the issues with the official inpainting model.
  • 🎨 The video showcases the use of the 1.5 and 2.1 inpainting models, recommending the SaaS-T Kai model from Civit AI for its versatility.
  • 🖼️ Eric demonstrates the inpainting process on an old photograph of an aristocratic family, highlighting the importance of selecting the right prompts for the desired outcome.
  • 🔍 The tutorial emphasizes the importance of adjusting the mask blur setting when inpainting to prevent visible edges and improve blending.
  • 👨‍👩‍👧‍👦 The video shows how to deal with different elements like faces, hands, and objects in an image, providing tips for each.
  • 📏 Eric explains how to use the control key and ALT key to adjust the brush size and image zoom during the inpainting process.
  • 🌟 The video suggests increasing the mask blur and sampling steps for better results, especially when working with flat or featureless areas.
  • 🏞️ When adding elements like wall hangings or plants, the tutorial advises simplifying the description and ensuring the AI has enough context to work with.
  • 👷‍♂️ Eric recommends experimenting with different models and settings to find the best combination for inpainting specific parts of an image.
  • 🔧 The video concludes with a reminder to consider the mask blur and context when inpainting to avoid common issues like edges and inconsistencies.

Q & A

  • What is the main topic of the video by Eric from Alchem Zero?

    -The main topic of the video is mastering inpainting with Stable Diffusion and Automatic 1111, specifically addressing issues people have been facing with inpainting using the SDXL models.

  • Why might people be having issues with SDXL inpainting models according to Eric?

    -People might be having issues with SDXL inpainting models because the models might be leaving too much of an edge, causing the inpainted area not to blend properly.

  • What is the official inpainting model for SDXL mentioned in the video?

    -The official inpainting model for SDXL mentioned in the video is one that does not have very good ratings or many downloads, suggesting that users did not resonate with it.

  • Which model does Eric recommend for inpainting in the video?

    -Eric recommends using the 'Sastrartha Kai' model found on Civit AI, as it is a good all-around model that handles realism, fine art, and abstract styles well.

  • What is the purpose of using different prompts in the inpainting process as shown in the video?

    -Using different prompts in the inpainting process helps to guide the AI in generating specific details or aspects of the image, such as faces, clothing, or backgrounds.

  • Why is the mask blur setting important when inpainting with SDXL images?

    -The mask blur setting is important because it helps to alleviate the edge effect around the masked area, allowing for a smoother blend with the surrounding image.

  • What is the significance of the 'only masked' and 'masked padding' settings in the inpainting process?

    -The 'only masked' setting focuses the inpainting process on the masked area, while 'masked padding' determines the width and height area around the masked region, affecting the context available to the AI for inpainting.

  • How does Eric suggest dealing with hands in AI-generated images during the inpainting process?

    -Eric suggests that hands can be challenging for AI image generators, and it might be best to mask them or hide them behind objects. If hands need to be visible, he recommends trying different renderings to see if a satisfactory result can be achieved.

  • What is the role of the 'config scale' and 'dnoise strength' settings in the inpainting process?

    -The 'config scale' setting allows the AI to have more 'imagination' about what's in the masked area, while 'dnoise strength' introduces more randomness, helping the AI to work with less context in the masked area.

  • What advice does Eric give for inpainting flat areas in an image?

    -For inpainting flat areas, Eric advises increasing the mask blur, sampling steps, and 'dnoise strength' to give the AI more room to work and to blend the inpainted area more effectively with the rest of the image.

  • How does Eric handle the issue of AI struggling with straight lines and consistency in inpainting?

    -Eric notes that AI can struggle with straight lines and consistency, especially when the line of sight is broken. He suggests simplifying the inpainting request and ensuring the AI has enough context to understand the scene, which can help in achieving a more accurate result.

Outlines

00:00

🎨 Art Inpainting with Stable Diffusion XL Models

In this video, Eric from Alchem Zero discusses the process of inpainting using Stable Diffusion XL (SDXL) models. He addresses common issues users face, such as edges not blending properly after inpainting. Eric plans to demonstrate his workflow using the SaaStra Kai model from Civit AI, which is praised for its versatility in handling various art styles. The video will cover inpainting faces and clothing in old photographs, with a focus on avoiding common pitfalls like leaving visible edges post-inpainting.

05:01

🖼️ Refining Inpainting Techniques for SDXL Images

Eric continues by explaining the challenges of inpainting with SDXL, particularly the lack of development for specific inpainting models. He decides to test the official inpainting model for SDXL, despite its poor ratings and lack of popularity. The video then proceeds to demonstrate the inpainting process on a family portrait, with an emphasis on adjusting the mask blur setting to reduce edge visibility. Eric also discusses the importance of using the correct model and settings for inpainting faces and suggests trying different models like the RPG artist tool for better results.

10:01

🔍 Adjusting Mask Blur to Improve Inpainting Results

The video script details the process of adjusting the mask blur setting to improve the inpainting results on SDXL images. Eric explains that increasing the mask blur can help blend the edges more effectively, especially when working with higher resolution images. He demonstrates this by inpainting a face and adjusting the settings to achieve a softer, more natural look. The video also touches on the use of different models for inpainting and the importance of selecting the right one for the desired outcome.

15:03

👤 Inpainting Faces and Hands in Aristocratic Portraits

Eric focuses on inpainting specific parts of an aristocratic family portrait, such as faces and hands. He discusses the difficulties in inpainting hands and suggests strategies like hiding them behind objects or using gloves to simplify the process. The video shows how to mask out areas and use prompts to generate more realistic and period-appropriate hands. Eric also emphasizes the importance of working with the AI's capabilities and adjusting settings like mask blur and sampling steps to achieve better results.

20:05

🏞️ Adding Objects to Inpaint Flat Backgrounds

The script describes the process of adding objects, such as a wall hanging photo, to flat backgrounds in SDXL images. Eric explains the challenges of working with flat areas and how to adjust settings like mask blur, sampling steps, and config scale to help the AI generate more appropriate content. He demonstrates how to use the 'fill' option to start with a blank area and blend it into the existing image, aiming for a more seamless integration of new elements.

25:05

🌿 Inpainting Potted Plants and Dealing with AI Limitations

Eric attempts to add potted plants to the scene and discusses the AI's difficulty with maintaining consistency, especially with straight lines and intricate details. He shows how to adjust the inpainting settings to better suit the task and emphasizes the importance of providing the AI with enough context to understand the scene. The video highlights the trial-and-error nature of inpainting and the need to simplify prompts to achieve the desired result.

30:06

📸 Final Touches on Inpainting and Addressing Edge Issues

In the final part of the script, Eric wraps up the inpainting process by focusing on the common issue of edges not blending well. He reiterates the importance of adjusting the mask blur and mask padding to provide the AI with the right amount of context while inpainting. Eric demonstrates how different settings can affect the outcome and offers tips on how to avoid giving the AI too much or too little information. The video concludes with a reminder to consider context when inpainting and to experiment with settings to achieve the best results.

Mindmap

Keywords

💡Inpainting

Inpainting refers to the process of filling in missing or corrupted parts of an image, typically using AI algorithms to generate content that blends seamlessly with the original. In the context of this video, inpainting is a central technique used to enhance images generated by the Stable Diffusion model, addressing issues like edges and blending.

💡Stable Diffusion

Stable Diffusion is a type of AI model that generates images from textual descriptions. It is known for its ability to create realistic and diverse visual content. The video discusses using Stable Diffusion models, specifically the sdxl models, to create art and address challenges in inpainting.

💡SDXL

SDXL likely refers to a variant or extension of the Stable Diffusion model optimized for higher resolution images (e.g., 'XL' could imply 'extra large'). The script mentions using sdxl models for inpainting, indicating a focus on working with larger, more detailed images.

💡Mask Blur

Mask Blur is a parameter in image editing that determines how much the edges of a masked area are blurred, helping to blend the masked area with the rest of the image. The video emphasizes the importance of adjusting mask blur in inpainting to avoid visible edges and achieve a natural look.

💡Aristocratic Family

The term 'aristocratic family' is used in the script to describe the subject of an old photograph that the video aims to recreate or enhance through inpainting. It serves as an example of the type of historical imagery that can be worked on using the discussed techniques.

💡Control Key

In the context of image editing software, the Control key is often used as a modifier key to change the size of a brush or to perform other editing functions. The video mentions using the Control key to adjust the brush size during the inpainting process.

💡Detailer

A detailer in AI image generation refers to a tool or function that automatically enhances the details in an image, such as facial features. The script mentions that the author typically uses a detailer to fix faces, but chooses to manually inpainting faces in this video to demonstrate the process.

💡RPG Artist Tool

The RPG Artist Tool mentioned in the video is likely a specific tool or model used for inpainting, possibly developed by the RPG Artist community. It is highlighted as a useful resource for working with realistic images in the inpainting process.

💡Batch Size

Batch size in AI image generation refers to the number of images processed at one time. The video discusses adjusting the batch size during the inpainting process to manage the variation and quality of the generated images.

💡Denoising Strength

Denoising strength is a parameter that controls the intensity of noise reduction in an image. In the video, adjusting the denoising strength is discussed as a way to influence the randomness and detail in the inpainted areas.

Highlights

Introduction to the video on mastering SDXL inpainting with Stable Diffusion and Automatic 1111.

Discussion on the challenges faced with SDXL inpainting models, particularly issues with edges not blending properly.

Introduction of the official inpainting model for SDXL and its lack of popularity due to poor ratings and downloads.

Recommendation to use the 1.5 or 2.1 inpainting models instead of the official SDXL model.

Introduction of the SASTRA Kai model as a favorite for its versatility in handling realism, fine art, and abstract styles.

Demonstration of inpainting process starting with an image of an aristocratic family in an old photograph.

Use of DPM Plus+ 3M SD and SDP Cross 2 samplers for generating realistic images.

Explanation of the process of using prompts and the importance of selecting the right model for inpainting.

Technique of using the control key to change brush size and the ALT key with scroll to change image size in inpainting.

Importance of adjusting mask blur to prevent edges from showing in inpainted areas.

Demonstration of inpainting a face and the use of specific prompts to achieve desired results.

Use of RPG Artist tool and the ZOOYA inpainting model for more realistic results.

Explanation of the settings for inpainting, including mask blur, sampling steps, and noise strength.

Challenges in inpainting hands and the suggestion to mask them or hide them behind objects.

Demonstration of inpainting a photograph of an aristocratic man and adjusting the settings for better blending.

Discussion on the difficulties of inpainting flat areas and the need to increase mask blur and sampling steps.

Technique of adding potted plants to an image and the importance of providing enough context for the AI to work with.

Final tips on inpainting, emphasizing the importance of mask blur and providing context for the AI.