lllyasviel / lllyasviel/ControlNet
Inpainting Controlnet
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- Dominant language
- Python
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Description
I've trained controlnet for sd2 inpainting model by concatenating control image, masked image and the mask itself.
What do I need to change in inference code to use this model?
size mismatch for input_blocks.0.0.weight: copying a param with shape torch.Size([320, 9, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 4, 3, 3])
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
Start by inspecting the inference code and the checkpoint error for input_blocks.0.0.weight, comparing the trained 9-channel input with the current model's 4-channel input. Done means the trained inpainting ControlNet loads successfully and its inference path accepts the concatenated control image, masked image, and mask.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100