The Easy Way to Outpaint in Stable Diffusion! Outpainting that actually Works!

Artificially Intelligent
28 May 202312:03

TLDRIn this tutorial, the YouTuber introduces an innovative method for outpainting using Stable Diffusion, an AI-based image generation tool. Traditional outpainting techniques can be tricky and sometimes result in unwanted images, such as 'naked anime girls'. The proposed method leverages in-painting features to extend the canvas and seamlessly integrate new sections into the original image. The process involves extending the canvas, filling in black areas with a chosen color, and adjusting denoising strength for a natural blend. The video also touches on using scripts for varied denoising scales and latent upscale for overall image enhancement. The YouTuber emphasizes the ease of this method compared to traditional outpainting and suggests further iterations for better results, concluding with a quick demonstration using the azovia RPG artist tools for creating fantasy images.

Takeaways

  • 🖼️ The video introduces an alternative method for outpainting in Stable Diffusion, which involves extending the canvas of an image.
  • 🎨 The traditional outpainting tool is criticized for being difficult to use and sometimes generating inappropriate content.
  • 🖌️ The suggested method uses inpainting for outpainting, which is claimed to be easier and more effective.
  • 🖥️ The process starts by opening Stable Diffusion and selecting the 'Image to Image' tab.
  • 📁 The user is instructed to drag and drop the image they wish to outpaint into the designated box.
  • ✏️ An editing feature allows the user to extend the canvas in the desired direction.
  • 🔍 The script advises against scrolling within the canvas and recommends clicking outside to reset the view.
  • 🛠️ Denoising strength is initially set to zero to create a black extension on the canvas.
  • 🎨 The black area is then filled with color using inpainting techniques.
  • 🔄 An iterative process is suggested to refine the image, adjusting denoising strength and using different models.
  • 📈 The video also mentions using scripts to automate testing of different denoising levels for optimal results.
  • 🌐 The presenter shares a personal preference for not using the inpainting model, finding it unnecessary for their workflow.
  • 🔗 The video concludes with a mention of upscaling for improving image quality, directing viewers to another video for detailed instructions.

Q & A

  • What is outpainting in the context of the video?

    -Outpainting is the process of extending the canvas of an image and adding more content to it, making it appear as if the picture was always larger to begin with.

  • Why does the video suggest using inpainting for outpainting?

    -The video suggests using inpainting for outpainting because the usual outpainting tools are not working as expected, and the creator finds it easier and more effective than traditional methods.

  • How does the process of outpainting using inpainting start?

    -The process starts by opening up Stable Diffusion, clicking on the image-to-image tab, and dragging in the photo that needs to be outpainted.

  • What is the purpose of extending the canvas in the video?

    -The canvas is extended to create a black area where new content can be added, which is then filled in using inpainting techniques.

  • Why is the denoising strength set to zero initially?

    -The denoising strength is set to zero initially to ensure that the new black area added to the canvas is not altered when generating the image.

  • What is the significance of the color palette and brush size in the outpainting process?

    -The color palette is used to choose a color to fill in the black area, and the brush size is adjusted to efficiently cover the area.

  • How does the video suggest iterating to improve the outpainting result?

    -The video suggests iterating by adjusting the denoising strength and using different settings to find the best result for the image.

  • What is the role of the seed in the outpainting process?

    -The seed provides a starting point for the generation process, which can help in achieving a more consistent result when iterating.

  • Why might the video creator prefer inpainting over the dedicated outpainting model?

    -The video creator prefers inpainting over the dedicated outpainting model because they feel it generates better results and is less time-consuming.

  • What is the final step suggested in the video for enhancing the outpainted image?

    -The final step suggested is to upscale the image using advanced sampling methods with higher sampling steps for better quality.

  • How does the video demonstrate using different tools for outpainting?

    -The video demonstrates using different tools for outpainting by showing the process in Stable Diffusion, mentioning other AI generators like Leonardo AI, and discussing various techniques and settings.

Outlines

00:00

🎨 'Outpainting' with Stable Diffusion

The speaker introduces an alternative method to 'outpainting' using Stable Diffusion instead of the traditional open outpainting tool. They explain that outpainting extends the canvas of an image to create the illusion that the picture was originally larger. The tutorial walks through using the 'image to image' tab in Stable Diffusion, editing the canvas to extend it, and setting denoising strength to zero before generating the image. The speaker then sends the extended image to inpainting, discusses techniques for selecting colors and adjusting brush size, and iterates on the image by adjusting denoising strength and mask content settings. They also mention using scripts to automate the testing of different denoising levels for optimal results.

05:05

🖌️ Enhancing Images with Inpainting

The speaker discusses how to enhance images using inpainting techniques in Stable Diffusion. They explain that inpainting can be used to fix or alter parts of an image and demonstrate how to use the color palette and brush size adjustments to fill in black areas of an image. The tutorial covers adjusting denoising strength and mask content settings for inpainting, with a focus on achieving a natural blend between the original and inpainted areas. The speaker also shares a tip for generating multiple variations of an image by adjusting denoising levels and using scripts to automate the process. They conclude with a mention of using advanced sampling methods for final image upscaling.

10:08

🏰 Outpainting with Leonardo AI

The speaker presents a bonus method for outpainting using Leonardo AI, an AI image generator. They describe the process of uploading an image to the AI canvas, adjusting the outpainting box size, and providing a description for the desired outpainted content. The tutorial includes tips on using the guidance scale to refine results and selecting the best outcome from multiple generated images. The speaker concludes by demonstrating how to download the outpainted image, emphasizing the ease of use and the quality of results achievable with Leonardo AI.

Mindmap

Keywords

💡Outpainting

Outpainting is the process of extending the canvas of an image and adding new content to the extended area, making it appear as if the picture was always larger. In the context of the video, the presenter discusses an alternative method to achieve outpainting using 'inpainting' techniques within the Stable Diffusion tool. This is showcased as a solution to the difficulties faced with traditional outpainting methods.

💡Inpainting

Inpainting is a technique used in image editing where missing or damaged parts of an image are filled in or restored. The video describes a creative workaround where inpainting is used to achieve outpainting. This involves editing the canvas to extend the image and then using inpainting to fill in the new areas with content that seamlessly blends with the original image.

💡Stable Diffusion

Stable Diffusion is a tool mentioned in the video that is used for generating images from textual descriptions or editing existing images. The presenter uses Stable Diffusion to demonstrate the outpainting technique. It is highlighted as a user-friendly tool that simplifies the process of image editing without requiring extensive technical knowledge.

💡Canvas Extension

Canvas extension refers to the act of increasing the size of the image canvas to add more space for creative input. In the video, the presenter instructs viewers on how to extend the canvas to the left using Stable Diffusion, which is part of the outpainting process to create more room for adding new visual elements.

💡Denoising Strength

Denoising strength is a parameter in image processing that controls the level of noise reduction applied to an image. In the context of the video, adjusting the denoising strength is crucial for refining the outpainted areas so that they blend naturally with the original image content. The presenter experiments with different denoising strength values to achieve the best results.

💡Seed

A seed in image generation refers to a random number used to produce a specific outcome. In the video, the presenter mentions using a seed to ensure consistency in the image generation process. It helps in maintaining the coherence of the outpainted areas with the original image by providing a reference point for the algorithm.

💡XYZ Plot

An XYZ plot is a method used to test different values of a parameter to see how it affects the output. In the video, the presenter uses an XYZ plot to test various denoising strength values from 0.2 to 0.8, generating 20 variations to find the optimal setting for the outpainting process.

💡Latent Upscale

Latent upscale is a process that improves the quality of an image without necessarily increasing its resolution. The video describes using latent upscale to enhance the overall image quality after the outpainting process. It is mentioned as a step to refine the image before finalizing the outpainted result.

💡Sampling Steps

Sampling steps refer to the number of iterations used in the image generation process to achieve a higher quality result. The presenter in the video suggests increasing the sampling steps during the final upscale to ensure a smoother and more detailed image output after the outpainting and inpainting processes.

💡Upscaling

Upscaling in the context of the video refers to increasing the resolution of an image for better detail and clarity. The presenter mentions upscaling as a separate process from latent upscale, suggesting that viewers can use specific tools to increase the resolution of their images up to 8K for extremely high-quality results.

Highlights

Introduction to an alternative method for outpainting in Stable Diffusion.

Common issues with the default outpainting tool and its unreliability.

Explanation of outpainting as extending the canvas of an image.

The presenter's method involves using inpainting for outpainting purposes.

Step-by-step guide to outpainting using the image-to-image tab in Stable Diffusion.

Editing the canvas to extend it in a desired direction for outpainting.

Recommendation to avoid scrolling inside the canvas to maintain the right size.

Setting denoising strength to zero for initial generation.

Sending the generated image with extended bar to inpaint.

Using a color palette to paint over the black area for inpainting.

Increasing denoising strength and setting mask content to 'fill' for inpainting.

Iterative process of generating images to find the optimal denoising level.

Using scripts to test different denoising levels efficiently.

Latent upscale as a method to improve image quality in one go.

Adjusting CFG scale and denoising strength for better image meshing.

Final upscale process with increased sampling steps for higher quality.

The presenter's preference for using the original model over the inpainting model.

Creating an image using text-to-image and control Nets.

Using inpainting to make adjustments to the generated image.

Outpainting an image by extending the canvas and generating a black bar.

Filling in the black section with color and adjusting denoising for inpainting.

Testing different denoising levels to find the optimal setting.

Using image-to-image generation for further improvements without seeds.

Introduction to Leonardo AI as an alternative to Stable Diffusion for outpainting.

Uploading an image and specifying outpainting details in Leonardo AI.

Generating and selecting the best outpainting result from multiple options.

Downloading the final outpainted image from Leonardo AI.