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Expert Guide for QR Code AI Art with Stable Diffusion

In this document we will discuss the "Expert" options in the QR Diffusion Generator. Most of them should be used with care, as the default options should be sufficient for the average user.

QR Options

There is just one new setting in Expert mode.

Error Correction

The QR code error correction is a percentage that allows QR codes to be some parts of it are covered or smudged and yet still work just fine.

Normally we recommend "H - High (30%)" level of error correction, but in some cases.

High Error Correction example
High Error Correction example

If you have long QR code data and QR code is complex, lowering the error correction makes the QR code simpler in shape. The AI QR codes based on the simpler input QR code will be more creative and easier to read.

Low QR code Error Correction example
Low QR code Error Correction example

ControlNet Options


In the expert mode you can select the ControlNet model which is responsible for baking the QR code into the image while generating. There are number of models available, while the default yields the most stable results.

QR Guidance Range

Guidance Range
Guidance Range

Select a start and end point of when the ControlNet is active in the process of generating the image. ControlNet is baking the QR code in the image being generated. Normally you want it to be active during most of the image-generation process, but sometimes you can experiement and have the generator ignore the ControlNet for either the start or end of the generation process.

Stable Diffusion Options

Sampler Method


CFG Scale

CFG scale (classifier-free guidance scale) or guidance scale is a parameter that controls how much the image generation process follows the text prompt. The higher the value, the more the image looks like the given text input.

Denoising Strength

Lower Denoising Strength will make your generated images look similar to your input image.

Higher Denoising Strength increases variation and reduces the influence of your input image on your output image.


Seed is an integer number that when entered, it produces similar images for the same seed. When no seed is entered, the generator chooses a random seed.

It does not work the same way when ControlNet is involved, so this setting does not have a real effect in our case and it is not really relevant for QR code generation with ControlNet.