lllyasviel / lllyasviel/sd-forge-layerdiffuse
Latent Offset VAE Encoder
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 4.1k
- Forks
- 352
- PR merge metrics
- No merged PRs in 30d
Description
First of all, thanks for your great work. I was very impressed with your approach for dealing with transparency channel.
As I was running some experiments with the released model, I ran into issue with latent offset vae encoder.
Specifically, I ran some tests with SD15 latent offset vae encoder, and it seems like adding original vae latents with the offset encoder output is producing very blurry results.
I am aware that you are working on this part, but was wondering if you could explain what other measure needs to be done for the encoder to work properly.
Thank you.
Contributor guide
No contributing guide indexed for this repository
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 reproducing the reported SD15 latent offset VAE encoder experiment and compare the original VAE latents plus the offset encoder output. The issue names no files or tests; done would require identifying the cause of the blurry results and documenting or correcting the additional measures needed for the encoder to work properly.
Written by the indexing model from the issue text.
Assessment
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100