OUTPAINTING that works. Impressive results with Automatic1111 Stable Diffusion WebUI.

Next Tech and AI
29 Jul 202413:33

TLDRThis video tutorial showcases how to use Stable Diffusion OutPaint with Automatic1111 Stable Diffusion WebUI to expand images seamlessly. It guides viewers through the installation of ControlNet, the use of the inpainting model, and the adjustment of parameters for outpainting. The video also demonstrates techniques to maintain the original image's integrity while adding new content, and offers tips for creative outpainting results. Finally, it suggests upscaling for increased consistency.

Takeaways

  • 🖼️ Stable Diffusion OutPaint allows expanding images without altering the original prompt.
  • 🔄 Outpainting can be done even after changing the prompt using the right parameters.
  • 🛠️ For outpainting, ControlNet with version 1.1 or newer is required, and the inpaint model should be installed.
  • 🔍 If ControlNet or the inpaint model is missing, it can be updated or downloaded from the provided link.
  • 🎨 The process involves setting the control mode to inpaint and using the pre-processor 'inpaint + lama' for optimal results.
  • 📏 Outpainting can be done by adjusting the image width and using 'resize and fill' mode to add new content.
  • 🔄 Denoising strength between 0.6 and 1.0 can be adjusted to control how much the original image changes during outpainting.
  • 🖌️ A simple method to outpaint involves copying the image to the inpaint tab and drawing a line to indicate the direction of expansion.
  • 📈 Using scripts for outpainting can yield creative results and is less resource-intensive than using ControlNet alone.
  • 🔧 If outpainting results are not as expected, adjusting the script parameters or the direction of outpainting can help achieve the desired outcome.
  • 🖼️ After outpainting, upscaling the image can increase consistency and improve the final result.

Q & A

  • What is outpainting in the context of Stable Diffusion?

    -Outpainting in Stable Diffusion refers to the process of expanding an image beyond its original borders with the help of AI, filling in the new areas with content that is consistent with the original image.

  • How can I check if I have the correct version of ControlNet for outpainting?

    -You can check the version of ControlNet by accessing the extensions tab and looking for updates. If you do not have version 1.1 or newer, you should update or install the latest version.

  • What should I do if the 'inpaint' model is missing in ControlNet?

    -If the 'inpaint' model is missing, you need to download the 'inpaint.pth' file from the provided link in the description and place it in your Stable Diffusion directory under models/ControlNet.

  • Why is it important to match the checkpoint version with the ControlNet version?

    -It is important to match the checkpoint version with the ControlNet version to ensure compatibility and optimal performance. For instance, if you are using ControlNet 1.5, you should use a checkpoint that is also version 1.5.

  • How do I set up the parameters for outpainting in the image to image tab?

    -In the image to image tab, extend the width to your desired size, set the resize mode to 'resize and fill', and adjust the denoising strength to a value between 0.6 and 1.

  • What is the purpose of setting the seed to -1 during outpainting?

    -Setting the seed to -1 generates a random number, which can introduce variability in the outpainting results. However, the script suggests that there isn't much difference in the results.

  • Why is it necessary to enable ControlNet when performing outpainting?

    -Enabling ControlNet is necessary for outpainting because it provides the control mechanism that allows the AI to understand how to fill in the new areas of the image.

  • How can I maintain the original content of the image while outpainting?

    -To maintain the original content while outpainting, you can use the inpainting tab to mask the areas you want to keep and then extend the image using the outpainting script or ControlNet settings.

  • What is the 'poor man's outpainting' mentioned in the script?

    -The 'poor man's outpainting' is a term used to describe an earlier or simpler method of outpainting that may not produce the best results, often resulting in an ugly appearance.

  • How can I increase the consistency of the outpainted image?

    -To increase the consistency of the outpainted image, you can upscale the picture after outpainting, usually two times, to refine the details and improve the overall coherence of the image.

Outlines

00:00

🖼️ OutPainting with Stable Diffusion

This paragraph introduces the concept of expanding images using Stable Diffusion OutPaint. It explains how to use the feature without altering the original prompt and highlights the importance of using the right version of ControlNet for outpainting. The process involves checking for updates, installing the necessary inpainting model, and ensuring compatibility between the ControlNet version and the checkpoint used. The paragraph also covers the initial steps of outpainting, including setting the image width, resize mode, denoising strength, and enabling ControlNet with the inpaint model.

05:04

🖌️ Refining OutPainting Results

The second paragraph discusses refining outpainting results by adjusting the denoising strength to minimize changes to the original image. It introduces the use of the inpaint tab to selectively expand the image and maintain the original content. The paragraph also covers techniques for repairing parts of the image, such as fixing a jacket, and extending the image to add more headroom. Additionally, it mentions the common issue of images being centered when only one side should be extended and suggests using a script for more precise outpainting.

10:05

🎨 Creative OutPainting Techniques

The final paragraph focuses on creative outpainting techniques, such as using scripts to extend the image in a specific direction while maintaining the original content. It explains how to use the inpaint tab to extend the image to the top and discusses the use of noise to generate more creative content. The paragraph also touches on the efficiency of using scripts over ControlNet for memory consumption and suggests upscaling the image for increased consistency as a final step. The video creator encourages viewers to share their experiences and like the video if they found it helpful.

Mindmap

Keywords

💡Outpainting

Outpainting refers to the process of extending the borders of an image to add new content around the existing subject. In the context of the video, it is used to expand an image beyond its original dimensions without altering the central subject. The video demonstrates how to use Stable Diffusion OutPaint to achieve this, showcasing the process of adding content to the left and right of an image.

💡Stable Diffusion

Stable Diffusion is a type of AI model that generates images from textual descriptions. It is highlighted in the video as the tool used for outpainting. The script mentions using Stable Diffusion with ControlNet for effective outpainting, indicating its role as a foundational technology in the process.

💡ControlNet

ControlNet is a specific model within the AI framework used for outpainting. The video emphasizes checking for ControlNet version 1.1 or newer and ensuring it is correctly installed and updated for the best outpainting results. It is integral to the process as it helps in managing how new content is generated around the original image.

💡Inpainting

Inpainting is a technique used to fill in missing or damaged parts of an image. The video script uses the term in relation to outpainting, where the ControlNet inpainting model is employed to add new content to the image borders. It is showcased as a method to repair or extend parts of an image without losing the original content.

💡Denoising Strength

Denoising strength is a parameter that controls the degree to which the original image is altered during the outpainting process. A higher denoising strength can lead to more significant changes to the original image, while a lower value preserves the original content more closely. The video suggests experimenting with this parameter to achieve the desired balance.

💡Resize Mode

Resize mode is a setting that determines how an image is scaled. In the video, 'resize and fill' is mentioned as a crucial setting for outpainting, ensuring that new content is added to the sides of the image while maintaining the original aspect ratio.

💡Seed

The term 'seed' in the video refers to a random number generator seed used to produce unique results in image generation. Setting the seed to -1 generates a random seed, which can lead to varied outpainting results. It is mentioned as a way to introduce variability in the outpainting process.

💡Preprocessor

A preprocessor in the context of the video is a step in the image processing pipeline that prepares the image for further operations. 'Inpaint + lama' is mentioned as the preferred preprocessor for outpainting, suggesting it as an optimal combination for preparing the image before adding new content.

💡Control Mode

Control mode is a setting that determines how the AI model interacts with the image. The video specifies using 'ControlNet' as the control mode for outpainting, indicating that it is the preferred method for guiding the AI in generating new content that aligns with the original image.

💡Script

In the video, a script is a predefined set of instructions that automates the outpainting process. It is suggested as a method to achieve more creative and controlled outpainting results, with the video demonstrating how to use a script to extend the image in a specific direction.

💡Upscaling

Upscaling is the process of increasing the resolution of an image. The video mentions upscaling as a final step after outpainting to enhance the consistency and quality of the image. It is presented as a way to refine the outpainting results for a more polished final product.

Highlights

Stable Diffusion OutPaint allows expanding images without changing the prompt.

Outpainting can be done even after changing the prompt.

Automatic1111 and ControlNet are necessary for outpainting.

Ensure ControlNet version 1.1 or newer for optimal outpainting.

Install ControlNet if it's not already installed.

Use the ControlNet inpainting model for outpainting.

The model control inpaint might need to be added if missing.

Download the inpaint.pth file from the provided link and place it in the Stable Diffusion directory.

Refresh the WebUI to see the inpaint model after copying the file.

Use the correct checkpoint compatible with ControlNet version.

Prepare an image for outpainting and check parameters in the PNG info tab.

Outpainting can extend an image to the left and right by setting width and resize mode.

Denoising strength between 0.6 and 1.0 is recommended for outpainting.

ControlNet should always be enabled for outpainting.

Use the inpaint control mode for better outpainting results.

Upload the same image as an independent control image for outpainting.

The resize mode should be set to resize and fill for outpainting.

Outpainting can change the original image content, which can be adjusted with denoising strength.

Copy the image to the inpaint tab to extend areas without changing the original image.

Increase the brush size to paint a line for outpainting direction.

Inpainting can be used to repair parts of the image after outpainting.

Scripts can be used for outpainting, contrary to popular belief.

Outpainting scripts can extend the image in a specific direction without affecting the original content.

Use the inpaint tab for scripts to handle outpainting.

Outpainting scripts may consume less memory than using ControlNet alone.

Increase picture consistency by upscaling after outpainting.