Instructions to use Nacholmo/controlnet-qr-pattern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nacholmo/controlnet-qr-pattern with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Nacholmo/controlnet-qr-pattern") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
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Conditioning only 15% of the pixels closest to black, so as not to affect the luminance of the rest of the image. ̶I̶t̶ ̶g̶o̶e̶s̶ ̶1̶5̶0̶0̶ ̶s̶t̶e̶p̶s̶ ̶s̶o̶ ̶f̶a̶r̶ ̶a̶n̶d̶ ̶i̶s̶ ̶q̶u̶i̶t̶e̶ ̶p̶r̶o̶m̶i̶s̶i̶n̶g̶
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### The concept seems to work, now I have to improve the dataset and do the training again,
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1500.ckpt is the automatic1111 controlnet extension compatible weight, 1500.yaml is also important.
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## 1.5k steps cherry picked examples (not scannable yet)
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Conditioning only 15% of the pixels closest to black, so as not to affect the luminance of the rest of the image. ̶I̶t̶ ̶g̶o̶e̶s̶ ̶1̶5̶0̶0̶ ̶s̶t̶e̶p̶s̶ ̶s̶o̶ ̶f̶a̶r̶ ̶a̶n̶d̶ ̶i̶s̶ ̶q̶u̶i̶t̶e̶ ̶p̶r̶o̶m̶i̶s̶i̶n̶g̶
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### The concept seems to work, now I have to improve the dataset and do the training again, tomorrow I think I will.
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Also I want to make a Preprocessor to have a blur slider. 1500.ckpt is the automatic1111 controlnet extension compatible weight, 1500.yaml is also important.
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## 1.5k steps cherry picked examples (not scannable yet)
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