78 lines
3.3 KiB
Markdown
78 lines
3.3 KiB
Markdown
# LanPaint
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Powerful Training Free Inpainting Tool Works for Every SD Model.
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## Features
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- 🎨 **Zero-Training Inpainting** - Works immediately with ANY SD model, even custom models you've trained yourself
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- 🛠️ **Simple Integration** - Same workflow as standard ComfyUI KSampler
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- 🚀 **Quality Enhancements** - High quality and seamless inpainting
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## Example Results
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### Example 1 (LanPaint K Sampler)
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[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_1)
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### Example 2: (LanPaint K Sampler (Advanced))
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[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_2)
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### Example 3: (LanPaint K Sampler (Advanced))
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[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_3)
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Each example includes:
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- Original masked image
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- Full ComfyUI workflow
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## Quickstart
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1. Install [ComfyUI](https://docs.comfy.org/get_started).
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1. Install [ComfyUI-Manager](https://github.com/ltdrdata/ComfyUI-Manager)
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1. Look up this extension in ComfyUI-Manager. If you are installing manually, clone this repository under `ComfyUI/custom_nodes`.
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1. Restart ComfyUI.
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## Installation
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1. Place `LanPaint_Nodes.py` in your `ComfyUI/custom_nodes` folder
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2. Restart ComfyUI
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3. Use like regular KSampler with inpainting workflows
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## Usage
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**Workflow Setup**
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Same as default ComfyUI KSampler - simply replace with LanPaint KSampler nodes. The inpainting workflow is the same as the [SetLatentNoiseMask](https://comfyui-wiki.com/zh/comfyui-nodes/latent/inpaint/set-latent-noise-mask) inpainting workflow.
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**Note**
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LanPaint only support binary mask (0,1) with no smoothing. Any mask with smooting will be converted to binary mask during inpainting.
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## Advanced Options (Optional)
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Fine-tune results with these key parameters:
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| Parameter | Typical Range | Effect |
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|-----------|---------------|--------|
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| `NumSteps` | 1-10 | Thinking iterations per step |
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| `Lambda` | 4-8 | Content preservation strength |
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| `StepSize` | 0.05-0.2 | Detail refinement intensity |
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## Publishing to Registry
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If you wish to share this custom node with others in the community, you can publish it to the registry. We've already auto-populated some fields in `pyproject.toml` under `tool.comfy`, but please double-check that they are correct.
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You need to make an account on https://registry.comfy.org and create an API key token.
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- [ ] Go to the [registry](https://registry.comfy.org). Login and create a publisher id (everything after the `@` sign on your registry profile).
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- [ ] Add the publisher id into the pyproject.toml file.
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- [ ] Create an api key on the Registry for publishing from Github. [Instructions](https://docs.comfy.org/registry/publishing#create-an-api-key-for-publishing).
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- [ ] Add it to your Github Repository Secrets as `REGISTRY_ACCESS_TOKEN`.
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A Github action will run on every git push. You can also run the Github action manually. Full instructions [here](https://docs.comfy.org/registry/publishing). Join our [discord](https://discord.com/invite/comfyorg) if you have any questions!
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