Img2img Tutorial for Stable Diffusion.

Sebastian Kamph
30 Jun 202323:09

TLDRThis tutorial delves into the intricacies of image-to-image functionality within Stable Fusion, showcasing how to transform and enhance images using various features and tools. The guide emphasizes the importance of denoising strength in determining the extent of changes from one image to another and demonstrates techniques for refining details, such as adding glasses or altering facial features. It also explores methods for upscaling low-resolution images while maintaining or improving detail, all the while encouraging iterative refinement for achieving desired results.


  • 📸 Understanding the basics of Stable Fusion involves recognizing its capability to work with various types of images, including generated images, paintings, and photographs.
  • 🎨 The 'image to image' feature in Stable Fusion allows users to modify and enhance images by adjusting key parameters such as denoising strength, which controls the degree of transformation from the original to the new image.
  • 🖌️ Styles are essential in Stable Fusion and can be customized to achieve desired effects; users are encouraged to explore and download additional styles for more creative options.
  • 🔄 The sampling method and steps play a crucial role in the image generation process, with DPM++ 2M Keras being a recommended setting for general use.
  • 📐 Aspect ratio and resolution are important considerations when generating images, with square formats like 512x512 or 1024x1024 being recommended for beginners.
  • 🔄 Iterative adjustments are key in achieving desired results in Stable Fusion, as there is no one-size-fits-all setting; users should expect to fine-tune parameters like denoising strength for each new attempt.
  • 🎭 The 'inpainting' feature can be used to modify specific parts of an image without altering the entire composition, offering a targeted approach to image enhancement.
  • 👓 Creative applications of Stable Fusion include adding or modifying elements such as glasses or changing hair color, which can be done by painting on the image and allowing the AI to generate the details.
  • 🚀 Upscaling images in Stable Fusion can introduce more detail and improve resolution, but it requires careful management of GPU resources and understanding of resize modes.
  • 🛠️ The process of generating images with Stable Fusion is an iterative one, often involving multiple attempts and adjustments to achieve the most satisfying results.
  • 📚 Tutorials and guides are valuable resources for users new to Stable Fusion, providing insights into best practices and advanced techniques for image generation and manipulation.

Q & A

  • What is the main focus of the tutorial?

    -The main focus of the tutorial is to teach users how to work with image-to-image features in Stable Fusion, including tips and tricks for using various tools and settings effectively.

  • What types of images can be used with Stable Fusion?

    -Stable Fusion can work with a variety of image types, including generated images, photographs, and paintings.

  • What is the significance of the denoising strength setting in image-to-image features?

    -The denoising strength setting determines how much of the first image will be transferred into the second image, affecting the level of change between the two images.

  • What is the recommended denoising strength value for most users according to the tutorial?

    -The recommended denoising strength value for most users is between 0.4 and 0.6, depending on the desired level of detail and change in the output image.

  • How can users adjust the image to achieve a more realistic outcome?

    -Users can adjust the denoising strength and iteratively work on the image, using features like image-to-image, inpaint, and sketch to refine and add details as needed.

  • What is the purpose of the 'in painting' feature in Stable Fusion?

    -The 'in painting' feature allows users to focus on specific parts of an image for improvement or modification without altering the entire image.

  • How can users upscale a low-resolution image while retaining or introducing more detail?

    -Users can input a low-resolution image into image-to-image with a higher denoising strength and a larger output resolution to upscale and introduce more detail.

  • What are some of the different resize modes available in Stable Fusion?

    -Different resize modes include crop and resize, resize, and resize and fill. These determine how the image is adjusted when changing its scale, whether by cropping part of the image, simply resizing, or filling in the edges with additional content.

  • What is the role of the 'paint sketch' feature in image manipulation?

    -The 'paint sketch' feature allows users to paint directly onto an image with specific colors, which the AI then uses to generate a detailed and colored section of the image based on the user's input.

  • How can users ensure that their generated images maintain the desired composition?

    -Users can maintain the desired composition by carefully adjusting the denoising strength and using iterative refinement, ensuring that the key elements of the composition are retained while still allowing for the introduction of new details or changes.

  • What are some best practices for working with Stable Fusion based on the tutorial?

    -Some best practices include starting with the right denoising strength value, iterating on the image for refinement, using the right tools for specific tasks like 'in painting' or 'paint sketch', and understanding the impact of different settings and modes when resizing or upscaling images.



🎨 Introduction to Image Manipulation with Stable Fusion

This paragraph introduces viewers to an image tutorial on Stable Fusion, a tool for generating and manipulating images. The speaker explains the basic concept of Stable Fusion, highlighting its versatility in handling various types of images and its ability to generate new images based on color and composition. The tutorial begins with a discussion on the new camera setup and moves on to demonstrate how to use the tool effectively, including tips and tricks for enhancing the user's experience.


🖌️ Utilizing Denoise Strength for Image Transformation

In this paragraph, the focus is on the denoising strength setting within the image-to-image feature of Stable Fusion. The speaker elaborates on the importance of this setting, which controls the degree of transformation from the original to the new image. By adjusting the denoising strength, users can achieve a balance between retaining the original image's features and introducing new details. The paragraph also discusses the use of different sampling methods and the impact of the setting on the final output, emphasizing the need for iteration and experimentation to achieve desired results.


👓 Enhancing Images with Inpainting and Sketching

This paragraph delves into the features of inpainting and sketching within Stable Fusion. The speaker demonstrates how to use these features to modify specific parts of an image, such as adding glasses or changing the color of the eyes. The process involves painting over the desired area and allowing the AI to generate the details. The paragraph also covers the use of different settings and the impact on the quality and accuracy of the generated features, highlighting the importance of finding the right balance between denoising strength and the level of detail.


🚀 Iterative Image Refinement and Resolution Upscaling

The speaker discusses the iterative process of refining an image using Stable Fusion. This involves making adjustments, generating new images, and selecting the most promising results to further develop. The paragraph also touches on the technique of upscaling images to increase their resolution while maintaining or enhancing detail. The speaker provides practical advice on using the resize feature and the implications of different resizing modes, emphasizing the potential for significant GPU resource usage at higher resolutions.


📚 Conclusion and Future Tutorials

In the concluding paragraph, the speaker wraps up the tutorial by summarizing the key points discussed and encouraging viewers to apply what they've learned. The speaker invites feedback and questions from the audience and expresses openness to addressing them in future videos. There's also a teaser for upcoming content, inviting viewers to suggest topics for future tutorials and to engage with the content by leaving comments and questions.



💡Stable Fusion

Stable Fusion is a generative AI tool that creates images based on given inputs. It is the main focus of the video, where the user is taught how to use it effectively. The video provides various tips and tricks for using Stable Fusion to generate and modify images, such as changing the denoising strength to alter the level of detail and making adjustments to the image's composition.

💡Image to Image

Image to Image is a feature within Stable Fusion that allows users to transform one image into another while retaining certain aspects of the original. This process involves adjusting settings like denoising strength to control the extent of changes made to the initial image. The video emphasizes the importance of this feature in achieving desired results in image generation.

💡Denoising Strength

Denoising Strength is a crucial setting in Stable Fusion's Image to Image feature that determines the degree to which the original image's details are preserved or altered in the generated image. A lower value retains more of the original image, while a higher value introduces more changes and detail. It is a balancing act between maintaining the essence of the input and creating a new, detailed output.


In the context of Stable Fusion, Styles refer to pre-defined sets of parameters or filters that influence the appearance and characteristics of the generated images. Users can load different styles to achieve various visual effects and aesthetic outcomes. The video instructs viewers on where to find and download additional styles to enhance their image generation experience.

💡Sampling Method

Sampling Method refers to the technique used by Stable Fusion to select data points from the input image to create the output image. Different sampling methods, such as DPM plus plus 2m Keras, can be chosen to influence the quality and appearance of the generated images. The choice of sampling method can affect the level of detail and the overall success of the image transformation.


Inpainting is a feature within Stable Fusion that allows users to modify specific parts of an image without affecting the rest. This process involves painting over the area to be changed, and the AI fills in the details based on the input. It is used for making localized adjustments, such as changing the color of lips or adding glasses to a portrait.


Sketch refers to the process of creating a rough or simplified version of an image, often for the purpose of emphasizing certain features or for artistic expression. In the context of the video, sketching is used to make quick modifications to an image, such as adding red to the lips or painting glasses onto a face, which the AI then interprets and incorporates into the final image.


Upscaling is the process of increasing the resolution of an image, typically to enhance its detail and quality. In the video, upscaling is discussed as a way to improve low-resolution images generated by Stable Fusion, using features like 'resize' to achieve a higher resolution without losing essential details.

💡迭代 (Iteration)

迭代, or iteration, is the process of repeating the image generation and modification steps to gradually refine and improve the output. This involves making small adjustments and observing the results, using feedback to guide further changes. The video emphasizes the importance of iteration in achieving desired outcomes with Stable Fusion, as there is no perfect setting that works for every image.

💡AI (Artificial Intelligence)

AI, or Artificial Intelligence, is the technology behind Stable Fusion that enables the creation and modification of images based on user inputs. AI algorithms analyze the input data and generate new images or modify existing ones according to the parameters set by the user. The video highlights the capabilities of AI in transforming images and the creative potential it offers.


Introduction to image-to-image tutorial in stable Fusion

Explanation of the difference between a camera and a sock

Demonstration of using various image sources with stable Fusion

Discussion on the importance of denoising strength in image-to-image

Adjusting sampling method for better results

Using different models and resolutions in stable Fusion

Illustration of how denoising strength affects image transformation

Practical example of changing an image's features using denoising strength

Introduction to image-to-image sketch and impaint sketch

Method of adding details to an image using inpainting

Technique of iterating on an image for improved results

Use of in paint sketch for more controlled image adjustments

Process of upscaling low-resolution images for higher detail

Explanation of different resize modes in image scaling

Final thoughts and conclusion of the image-to-image tutorial