Denoising Strength Stable Diffusion: Complete Guide
- Cole B.
Today, I am going to show you exactly how to use the denoising strength stable diffusion setting.
Learning this setting helped me create 100+ beautiful high-resolution images when upscaling and inpainting.
So, if you want to learn how this setting works and take your images to the next level, this guide is for you.
Let’s get started.
What is Denoising Strength in Stable Diffusion?
Denoising strength in stable diffusion is a setting that adds noise to an image before refining with sampling steps.
Increasing the strength will add more noise and result in a more varied picture. For instance, a setting of 1.0 will completely replace the input image with noise and result in an entirely different generated image.
Decreasing the strength will result in a picture similar to the one that is being used as the input image. Having a strength of 0.0 will result in the exact same image as the input image.
Where is Denoising Strength Used?
It is typically used with image generation techniques that use the denoising strength setting and require an input image:
Hires.fix
Hires.fix is a method that increases the resolution of your images while they are being generated.
Denoising strength for this setting impacts how strongly the image is impacted by the upscaler.
In this example, having a value creates a blurry image, while a high value creates an entirely different image.
Img2Img: Upscaling
Img2Img has many different functions within stable diffusion, but I am going to focus on the resizing or the upscaler feature.
For the upscaling images, it works the exact same as hires.fix, the higher the strength, the more varied the image will be from the input image.
For upscaling, using a low value will produce a similar image with some details expanded upon to increase the width and height.
I wouldn’t recommend having a high strength for upscaling.
Img2Img: Inpainting
Inpainting is a tool for editing parts of images in a selected area.
Denoising strength, in this instance, controls how much of the masked or highlighted area is changed.
This is an example of using different amounts with this image of Tom Cruise, having his hair in the masked area.
And we will add the prompt “blonde hair” and generate using various settings:
A lot of denoising is needed to have an effect on inpainting.
This is because the noise needs to be enough to completely replace what is beneath the masked area.
What are the Best Settings for Denoising Strength?
The short answer is that a denoising strength between 0.4 and 0.6 is usually best for most applications. Inpainting, however, requires a higher setting.
The long answer is that it will depend on how much change you want to change the input image and what image-generation techniques you are using.
This is a good example of different strengths for what you are wanting:
- 0.0: No Change
- 0.3: Slight Change
- 0.5: Moderately Changed
- 0.7: Almost completely different
- 1.0: Completely different image
Let Me Know Your Thoughts
Now that I have covered the denoising strength stable diffusion setting.
I want to know what the best setting you found when using it was.
Let me know by leaving a comment below.