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Author SHA1 Message Date
scraed 2f7967a584 update version 2025-08-25 11:37:54 +08:00
scraed e28e115297 add example workflow jsons 2025-08-25 11:37:31 +08:00
scraed f2cc70fed3 Update inpainted example image
Replaces the InPainted_Drag_Me_to_ComfyUI.png file in Example_14 with a new version. This may reflect updated visual content or corrections to the example image.
2025-08-25 11:11:09 +08:00
scraed b8e140f7aa Comment out unused model_sigmas initialization
The initialization of model_sigmas in KSamplerX0Inpaint was commented out to remove warning. Also remove group nodes from example workflow
2025-08-22 10:34:51 +08:00
scraed e6f61e806c Bump version to 1.3.0 in pyproject.toml
Updated the project version from 1.2.0 to 1.3.0 to reflect new changes or improvements in the LanPaint package.
2025-08-22 00:26:46 +08:00
scraed ba506f2654 Add new Qwen edit example and update README
Added Example_14 images and LanPaintQwen_03.jpg to showcase the masked Qwen edit workflow. Updated README with new example references and instructions for using the ComfyUI Qwen Image Edit workflow.
2025-08-22 00:17:40 +08:00
scraed 986dee6bd9 Merge branch 'master' of https://github.com/scraed/LanPaint 2025-08-21 18:12:18 +08:00
scraed e514553120 fix performance issue 2025-08-21 18:12:11 +08:00
scraed 40d7f0854e Update README.md 2025-08-18 23:07:02 +08:00
charrywhite a5e3af84f9 Update README.md 2025-08-18 18:18:21 +08:00
charrywhite 598ca776eb Update README.md 2025-08-18 18:10:50 +08:00
charrywhite b36584b2a7 Update README.md 2025-08-18 18:07:49 +08:00
charrywhite 082c549b24 Update README.md 2025-08-18 18:05:21 +08:00
charrywhite 453b6c090e Update README.md 2025-08-18 17:45:27 +08:00
charrywhite 07229ecbcd Update README.md
reorganize readme
2025-08-18 17:36:02 +08:00
charrywhite 76cf0ff5fe Update README.md 2025-08-18 17:25:21 +08:00
scraed e1f84469f1 Merge branch 'master' of https://github.com/scraed/LanPaint 2025-08-18 17:20:03 +08:00
charrywhite 1fa77b0d1e Update README.md 2025-08-18 17:19:20 +08:00
scraed cd62e71467 Update LanPaintQwen_01.jpg example image
Replaces the existing LanPaintQwen_01.jpg in the examples directory with a new version.
2025-08-18 17:19:02 +08:00
charrywhite deaf2cec2a Update README.md 2025-08-18 17:18:01 +08:00
scraed 587a941607 Update README.md 2025-08-18 15:44:21 +08:00
scraed 7bdbab75e6 Update LanPaintQwen_01.jpg 2025-08-18 15:35:01 +08:00
scraed b77c25677f Fix swapped links for Qwen workflows in README
Corrected the example links for Qwen Inpaint and Outpaint workflows to point to their respective directories.
2025-08-18 15:30:29 +08:00
scraed bf5b607238 update readme 2025-08-18 15:29:21 +08:00
scraed ad77fb7836 Merge branch 'master' of https://github.com/scraed/LanPaint 2025-08-18 15:27:19 +08:00
scraed 3f8eb2552f Update README and add new Qwen inpainting examples
Enhanced README with details and links for Qwen Image workflows and added new example images for Qwen inpainting and outpainting in Example_12 and Example_13 directories. Also included a sample result image for Qwen inpainting.
2025-08-18 15:27:12 +08:00
scraed 238e49e31f Update README.md 2025-08-15 15:34:36 +08:00
18 changed files with 3908 additions and 68 deletions
+86 -62
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@@ -1,13 +1,47 @@
# LanPaint (Thinking mode Inpaint)
<div align="center">
Unlock precise inpainting without additional training. LanPaint lets the model "think" through multiple iterations before denoising, enabling you to invest more computation time for superior quality.
![Inpainting Result 13](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_13.jpg)
# LanPaint: Universal Inpainting Sampler with "Think Mode"
[![arXiv](https://img.shields.io/badge/Arxiv-2502.03491-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2502.03491)
[![Python Benchmark](https://img.shields.io/badge/🐍-Python_Benchmark-3776AB?logo=python)](https://github.com/scraed/LanPaintBench)
[![ComfyUI Extension](https://img.shields.io/badge/ComfyUI-Extension-7B5DFF)](https://github.com/comfyanonymous/ComfyUI)
[![Blog](https://img.shields.io/badge/📝-Blog-9cf)](https://scraed.github.io/scraedBlog/)
[![GitHub stars](https://img.shields.io/github/stars/scraed/LanPaint)](https://github.com/scraed/LanPaint/stargazers)
</div>
This is the official implementation of ["Lanpaint: Training-Free Diffusion Inpainting with Exact and Fast Conditional Inference"](https://arxiv.org/abs/2502.03491).
Universally applicable inpainting ability for every model. LanPaint sampler lets the model "think" through multiple iterations before denoising, enabling you to invest more computation time for superior inpainting quality.
This is the official implementation of ["Lanpaint: Training-Free Diffusion Inpainting with Exact and Fast Conditional Inference"](https://arxiv.org/abs/2502.03491). The repository is for ComfyUI extension. Local Python benchmark code is published here: [LanPaintBench](https://github.com/scraed/LanPaintBench).
![Qwen Result 2](https://github.com/scraed/LanPaint/blob/master/examples/LanPaintQwen_03.jpg)
Check [Mased Qwen Edit Workflow](https://github.com/scraed/LanPaint/tree/master/examples/Example_14). You need to follow the ComfyUI version of [Qwen Image Edit workflow](https://docs.comfy.org/tutorials/image/qwen/qwen-image-edit) to download and install the model.
![Qwen Result 1](https://github.com/scraed/LanPaint/blob/master/examples/LanPaintQwen_01.jpg)
Also check [Qwen Inpaint Workflow](https://github.com/scraed/LanPaint/tree/master/examples/Example_13) and [Qwen Outpaint Workflow](https://github.com/scraed/LanPaint/tree/master/examples/Example_12). You need to follow the ComfyUI version of [Qwen Image workflow](https://docs.comfy.org/tutorials/image/qwen/qwen-image) to download and install the model.
## Table of Contents
- [Features](#features)
- [Quickstart](#quickstart)
- [How to Use Examples](#how-to-use-examples)
- [Examples](#examples)
- [Qwen Image](#example-qwen-image-inpaintlanpaint-k-sampler-5-steps-of-thinking)
- [HiDream](#example-hidream-inpaint-lanpaint-k-sampler-5-steps-of-thinking)
- [SD 3.5](#example-sd-35-inpaintlanpaint-k-sampler-5-steps-of-thinking)
- [Flux](#example-flux-inpaintlanpaint-k-sampler-5-steps-of-thinking)
- [SDXL Examples](#example-sdxl-0-character-consistency-side-view-generation-lanpaint-k-sampler-5-steps-of-thinking)
- [Usage](#usage)
- [Basic Sampler](#basic-sampler)
- [Advanced Sampler](#lanpaint-ksampler-advanced)
- [Tuning Guide](#lanpaint-ksampler-advanced-tuning-guide)
- [Community Showcase](#community-showcase-)
- [Updates](#updates)
- [ToDo](#todo)
- [Citation](#citation)
## Features
- **Universal Compatibility** – Works instantly with almost any model (SD 1.5, XL, 3.5, Flux, HiDream, or custom LoRAs) and ControlNet.
- **Universal Compatibility** – Works instantly with almost any model (**SD 1.5, XL, 3.5, Flux, HiDream, Qwen-Image or custom LoRAs**) and ControlNet.
![Inpainting Result 13](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_13.jpg)
- **No Training Needed** – Works out of the box with your existing model.
- **Easy to Use** – Same workflow as standard ComfyUI KSampler.
- **Flexible Masking** – Supports any mask shape, size, or position for inpainting/outpainting.
@@ -16,17 +50,6 @@ This is the official implementation of ["Lanpaint: Training-Free Diffusion Inpai
**Warning**: LanPaint has degraded performance on distillation models, such as Flux.dev, due to a similar [issue with LORA training](https://medium.com/@zhiwangshi28/why-flux-lora-so-hard-to-train-and-how-to-overcome-it-a0c70bc59eaf). Please use low flux guidance (1.0-2.0) to mitigate this [issue](https://github.com/scraed/LanPaint/issues/30).
## How It Works
LanPaint uses Langevin Dynamics as "thinking" steps, which digs deeper into the diffusion process and allows the model to generate more consistent results.
LanPaint introduces "BIG score" that creates a **two-way alignment** between masked and unmasked areas. It continuously evaluates:
- *"Does the new content make sense with the existing elements?"*
- *"Do the existing elements support the new creation?"*
Based on this evaluation, LanPaint iteratively updates the noise in both the masked and unmasked regions.
LanPaint also implements an accurate, robust, and fast Langevin dynamics solver.
## Quickstart
1. **Install ComfyUI**: Follow the official [ComfyUI installation guide](https://docs.comfy.org/get_started) to set up ComfyUI on your system. Or ensure your ComfyUI version > 0.3.11.
@@ -43,28 +66,15 @@ LanPaint also implements an accurate, robust, and fast Langevin dynamics solver.
Once installed, you'll find the LanPaint nodes under the "sampling" category in ComfyUI. Use them just like the default KSampler for high-quality inpainting!
## Updates
- 2025/08/08
- Add Qwen image support
- 2025/06/21
- Update the algorithm with enhanced stability and outpaint performance.
- Add outpaint example
- Supports Sampler Custom (Thanks to [MINENEMA](https://github.com/MINENEMA))
- 2025/06/04
- Add more sampler support.
- Add early stopping to advanced sampler.
- 2025/05/28
- Major update on the Langevin solver. It is now much faster and more stable.
- Greatly simplified the parameters for advanced sampler.
- Fix performance issue on Flux and SD 3.5
- 2025/04/16
- Added Primary HiDream support
- 2025/03/22
- Added Primary Flux support
- Added Tease Mode
- 2025/03/10
- LanPaint has received a major update! All examples now use the LanPaint K Sampler, offering a simplified interface with enhanced performance and stability.
## **How to Use Examples:**
1. Navigate to the **example** folder (i.e example_1), download all pictures.
2. Drag **InPainted_Drag_Me_to_ComfyUI.png** into ComfyUI to load the workflow.
3. Download the required model (i.e clicking **Model Used in This Example**).
4. Load the model in ComfyUI.
5. Upload **Masked_Load_Me_in_Loader.png** to the **"Load image"** node in the **"Mask image for inpainting"** group (second from left), or the **Prepare Image** node.
7. Queue the task, you will get inpainted results from LanPaint. Some example also gives you inpainted results from the following methods for comparison:
- **[VAE Encode for Inpainting](https://comfyanonymous.github.io/ComfyUI_examples/inpaint/)**
- **[Set Latent Noise Mask](https://comfyui-wiki.com/en/tutorial/basic/how-to-inpaint-an-image-in-comfyui)**
## Examples
@@ -74,6 +84,7 @@ We are excited to announce that LanPaint now supports Qwen Image, providing powe
![Inpainting Result 14](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_14.jpg)
[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_11)
You need to follow the ComfyUI version of [Qwen Image workflow](https://docs.comfy.org/tutorials/image/qwen/qwen-image) to download and install the model.
The following examples utilize a random seed of 0 to generate a batch of 4 images for variance demonstration and fair comparison. (Note: Generating 4 images may exceed your GPU memory; please adjust the batch size as necessary.)
@@ -138,24 +149,6 @@ You need to follow the ComfyUI version of [SD 3.5 workflow](https://comfyui-wiki
Check more for use cases like inpaint on [fine tuned models](https://github.com/scraed/LanPaint/issues/12#issuecomment-2938662021) and [face swapping](https://github.com/scraed/LanPaint/issues/12#issuecomment-2938723501), thanks to [Amazon90](https://github.com/Amazon90).
## **How to Use These Examples:**
1. Navigate to the **example** folder (i.e example_1) by clicking **View Workflow & Masks**, download all pictures.
2. Drag **InPainted_Drag_Me_to_ComfyUI.png** into ComfyUI to load the workflow.
3. Download the required model from Civitai by clicking **Model Used in This Example**.
4. Load the model into the **"Load Checkpoint"** node.
5. Upload **Original_No_Mask.png** to the **"Load image"** node in the **"Original Image"** group (far left).
6. Upload **Masked_Load_Me_in_Loader.png** to the **"Load image"** node in the **"Mask image for inpainting"** group (second from left).
7. Queue the task, you will get inpainted results from three methods:
- **[VAE Encode for Inpainting](https://comfyanonymous.github.io/ComfyUI_examples/inpaint/)** (middle),
- **[Set Latent Noise Mask](https://comfyui-wiki.com/en/tutorial/basic/how-to-inpaint-an-image-in-comfyui)** (second from right),
- **LanPaint** (far right).
8. You also get an output from "masked blend" node, which copy the original image and paste onto the unmasked part of output. It is useful if you want unmasked region to match original picture pixel perfectly.
Compare and explore the results from each method!
![WorkFlow](https://github.com/scraed/LanPaint/blob/master/Example.JPG)
## Usage
**Workflow Setup**
@@ -218,14 +211,45 @@ If you find the results have wired texture, try
⚠️ **Notes**:
- For effective tuning, **fix the seed** and adjust parameters incrementally while observing the results. This helps isolate the impact of each setting. Better to do it with a batche of images to avoid overfitting on a single image.
## Community Showcase [](#community-showcase-)
Discover how the community is using LanPaint! Here are some user-created tutorials:
- [Ai绘画进阶148-三大王炸!庆祝高允贞出道6周年!T8即将直播?当AI绘画学会深度思考?!万能修复神器LanPaint,万物皆可修!-T8 Comfyui教程](https://www.youtube.com/watch?v=Z4DSTv3UPJo)
- [Ai绘画进阶151-真相了!T8竟是个AI?!LanPaint进阶(二),人物一致性,多视角实验性测试,新参数讲解,工作流分享-T8 Comfyui教程](https://www.youtube.com/watch?v=landiRhvF3k)
- [重绘和三视图角色一致性解决新方案!LanPaint节点尝试](https://www.youtube.com/watch?v=X0WbXdm6FA0)
- [ComfyUI: HiDream with Perturbation Upscale, LanPaint Inpainting (Workflow Tutorial)](https://www.youtube.com/watch?v=2-mGe4QVIIw&t=2785s)
- [ComfyUI必备LanPaint插件超详细使用教程](https://plugin.aix.ink/archives/lanpaint)
Submit a PR to add your tutorial/video here, or open an [Issue](https://github.com/scraed/LanPaint/issues) with details!
## Updates
- 2025/08/08
- Add Qwen image support
- 2025/06/21
- Update the algorithm with enhanced stability and outpaint performance.
- Add outpaint example
- Supports Sampler Custom (Thanks to [MINENEMA](https://github.com/MINENEMA))
- 2025/06/04
- Add more sampler support.
- Add early stopping to advanced sampler.
- 2025/05/28
- Major update on the Langevin solver. It is now much faster and more stable.
- Greatly simplified the parameters for advanced sampler.
- Fix performance issue on Flux and SD 3.5
- 2025/04/16
- Added Primary HiDream support
- 2025/03/22
- Added Primary Flux support
- Added Tease Mode
- 2025/03/10
- LanPaint has received a major update! All examples now use the LanPaint K Sampler, offering a simplified interface with enhanced performance and stability.
- 2025/03/06:
- Bug Fix for str not callable error and unpack error. Big thanks to [jamesWalker55](https://github.com/jamesWalker55) and [EricBCoding](https://github.com/EricBCoding).
## ToDo
- Try Implement Detailer
- Provide inference code on without GUI.
## Contribute
- 2025/03/06: Bug Fix for str not callable error and unpack error. Big thanks to [jamesWalker55](https://github.com/jamesWalker55) and [EricBCoding](https://github.com/EricBCoding).
- ~~Provide inference code on without GUI.~~ Check our local Python benchmark code [LanPaintBench](https://github.com/scraed/LanPaintBench).
## Citation
File diff suppressed because it is too large Load Diff
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@@ -0,0 +1,806 @@
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+1 -1
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@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "LanPaint"
version = "1.2.0"
version = "1.3.1"
description = "Achieve seamless inpainting results without needing a specialized inpainting model."
authors = [
{name = "LanPaint", email = "czhengac@connect.ust.hk"}
+2 -3
View File
@@ -62,7 +62,6 @@ class LanPaint():
def score_model(self, x_t, y, mask, abt, sigma, tflow, model_options, seed):
lamb = self.chara_lamb
if self.IS_FLUX or self.IS_FLOW:
# compute t for flow model, with a small epsilon compensating for numerical error.
x = x_t / ( abt**0.5 + (1-abt)**0.5 ) # switch to Gaussian flow matching
@@ -92,8 +91,8 @@ class LanPaint():
# -------------------------------------------------------------------------
# Compute the Langevin dynamics update in variance perserving notation
# -------------------------------------------------------------------------
x0 = self.x0_evalutation(x_t, score, sigma, args)
C = abt**0.5 * x0 / (1-abt)
#x0 = self.x0_evalutation(x_t, score, sigma, args)
#C = abt**0.5 * x0 / (1-abt)
A = A_x * (1-mask) + A_y * mask
D = D_x * (1-mask) + D_y * mask
dt = dtx * (1-mask) + dty * mask
+2 -2
View File
@@ -75,8 +75,8 @@ class KSamplerX0Inpaint:
def __init__(self, model, sigmas):
self.inner_model = model
self.sigmas = sigmas
self.model_sigmas = torch.cat( (torch.tensor([0.], device = sigmas.device) , torch.tensor( self.inner_model.model_patcher.get_model_object("model_sampling").sigmas, device = sigmas.device) ) )
self.model_sigmas = torch.tensor( self.model_sigmas, dtype = self.sigmas.dtype )
#self.model_sigmas = torch.cat( (torch.tensor([0.], device = sigmas.device) , torch.tensor( self.inner_model.model_patcher.get_model_object("model_sampling").sigmas, device = sigmas.device) ) )
#self.model_sigmas = torch.tensor( self.model_sigmas, dtype = self.sigmas.dtype )
def __call__(self, x, sigma, denoise_mask, model_options={}, seed=None,**kwargs):
### For 1.5 and XL model
# x is x_t in the notation of variance exploding diffusion model, x_t = x_0 + sigma * noise