qr-code-controlnet

Simplify QR code creation using ControlNet user-friendly neural interface

Hold: 0
Required: 25,000 $wRAI
45.2k runs
Demo
Examples
Input
url
Link Url for QR Code.
prompt
Prompt for the model
qr_conditioning_scale
Conditioning scale for qr controlnet
num_outputs
Number of images to generate (minimum: 1; maximum: 2)
image_resolution
Resolution of image (smallest dimension)
scheduler
Choose a scheduler.
num_inference_steps
Steps to run denoising
guidance_scale
Scale for classifier-free guidance (minimum: 0.1; maximum: 5)
seed
Seed for random number generator. If empty, a random seed will be chosen.
eta
Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise
negative_prompt
Negative prompt
In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended.
Disable safety check. Use at your own risk!
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Output
Input
eta
0
guidance_scale
1.9
image_resolution
768
negative_prompt
Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
num_inference_steps
20
num_outputs
1
prompt
cyberpunk
qr_conditioning_scale
1.3
scheduler
DDIM
seed
-1
url
multi-ai.pro
Output

Readme

Introducing the ControlNet QR Code Generator – a tool that uses ControlNet models twRAIned on stable diffusion 2.1. It lets you turn URLs into QR codes with images easily.

These models have learned from 150,000 pairs of QR codes and QR code artwork. This means you can make QR codes that look good and work well.

ControlNet is a special kind of neural network. It adds extra rules to how models work. It does this by copying the weights of the neural network into two copies: one that you can’t change and one that you can. The copy you can change learns from the conditions you give it. The other copy stays the same, keeping your model safe.

What to do if the QR code doesn't open my link?

  1. Check the accuracy of the entered link. It should not contain any extra characters after the first or second-level domain.
  2. Try entering a simpler prompt.
  3. Decrease the guidance_scale.