lllyasviel / lllyasviel/ControlNet
How to generate fixed results?
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- Dominant language
- Python
- Stars
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Description
I noticed that in the training tutorial, it is mentioned that the results of label cannot be generated exactly because of stable diffusion. If I have requirements like image inpainting and image super-resolution, can I modify controlNet to a model that can generate stable results? Do you have any suggestions for modification?
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the training tutorial section about stable diffusion and fixed results, then review the ControlNet training and model-modification guidance. Determine whether image inpainting and image super-resolution require modifying ControlNet and document a concrete, supported direction or limitations for producing stable results.
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Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100