lllyasviel / lllyasviel/ControlNet
Character consistency
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 34.1k
- Forks
- 3k
- PR merge metrics
- No merged PRs in 30d
Description
Spoiler alert: I'm a noob
ControlNet is the first real method to control SD. I was thinking if with this method there would be a way to teach the network to keep the generated character. I'll give you an example:
dog with blue fur => save subject => riding a motorcycle
I know there are already methods to teach the network about the subject, like dreambooth etc.
but I thought since the network already knows the subject 'cause he created it in the first place, isn't there a way theorically to tell the network to keep overall subject traits without training it and waste time.
This imho would unleash the power of SD. Ranging from creating storyboard, to notime character design creation
Ps. sorry for my bad english
Contributor guide
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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
The issue discusses ControlNet, Stable Diffusion, and DreamBooth but names no files, tests, or entry points. Start by reviewing how ControlNet handles conditioning and how existing subject-preservation methods work. Done would require a concrete approach and reproducible criteria for preserving a generated character without additional training.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100