update pyproject.yaml

fix blur issue in Wan 2.2 14B
add wan 2.2 5B
2025-11-23 01:11:08 +08:00 · 2025-11-23 00:46:25 +08:00 · 2025-11-17 16:09:45 +08:00 · 2025-11-17 16:05:42 +08:00 · 2025-11-17 16:04:51 +08:00 · 2025-11-17 16:04:48 +08:00
102 changed files with 11472 additions and 340 deletions
@@ -7,14 +7,18 @@ on:
    paths:
      - "pyproject.toml"

+permissions:
+  issues: write
+
 jobs:
  publish-node:
    name: Publish Custom Node to registry
    runs-on: ubuntu-latest
+    if: ${{ github.repository_owner == 'scraed' }}
    steps:
      - name: Check out code
        uses: actions/checkout@v4
      - name: Publish Custom Node
-        uses: Comfy-Org/publish-node-action@main
+        uses: Comfy-Org/publish-node-action@v1
        with:
          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} ## Add your own personal access token to your Github Repository secrets and reference it here.
@@ -98,3 +98,5 @@ cookiecutter-pypackage-env/
 # vscode settings
 .history/
 *.code-workspace
+.vscode/
+/.vscode
@@ -5,4 +5,8 @@
    "/PATH/TO/ComfyUI/",
    "/PATH/TO/ComfyUI/custom_nodes/"
  ],
+  "cursorpyright.analysis.extraPaths": [
+    "/PATH/TO/ComfyUI/",
+    "/PATH/TO/ComfyUI/custom_nodes/"
+  ],
 }
@@ -1,55 +1,80 @@
-# LanPaint (Thinking mode Inpaint)
+<div align="center">

-Unlock precise inpainting without additional training. LanPaint lets the model "think" through multiple iterations before denoising, aiming for seamless and accurate results. We encourage you to try it out and share your feedback through issues or discussions, as your input will help us enhance the algorithm's performance and stability.
+# 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)
+[![Hugging Face](https://img.shields.io/badge/Hugging%20Face-yellow?logo=huggingface&logoColor=white)](https://huggingface.co/charrywhite/LanPaint)
+[![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>
+
+
+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), accepted by TMLR. The repository is for ComfyUI extension. Local Python benchmark code is published here: [LanPaintBench](https://github.com/scraed/LanPaintBench).
+
+**🎬 NEW: LanPaint now supports video inpainting and outpainting based on Wan 2.2!**
+
+<div align="center">
+
+| Original Video | Mask (edit T-shirt text) | Inpainted Result |
+|:--------------:|:----:|:----------------:|
+| ![Original](https://github.com/scraed/LanPaint/blob/master/examples/Original_No_Mask-example18.gif) | ![Mask](https://github.com/scraed/LanPaint/blob/master/examples/Example_18/Masked_Load_Me_in_Loader.png) | ![Result](https://github.com/scraed/LanPaint/blob/master/examples/Inpainted_81frames_Drag_Me_to_ComfyUI_example18.gif) |
+
+*Video Inpainting Example: 81 frames with temporal consistency*
+
+</div>
+
+Check our latest [Wan 2.2 Video Examples](#video-examples-beta), [Wan 2.2 Image Examples](#example-wan22-inpaintlanpaint-k-sampler-5-steps-of-thinking), and 
+[Qwen Image Edit 2509](#example-qwen-edit-2509-inpaint) support.
+  
+
+## Table of Contents
+- [Features](#features)
+- [Quickstart](#quickstart)
+- [How to Use Examples](#how-to-use-examples)
+- [Video Examples (Beta)](#video-examples-beta)
+  - [Wan 2.2 Video Inpainting](#wan-22-video-inpainting)
+  - [Wan 2.2 5B Video Inpainting](#wan-22-5b-video-inpainting)
+  - [Wan 2.2 Video Outpainting](#wan-22-video-outpainting)
+  - [Resource Consumption](#resource-consumption)
+- [Image Examples](#image-examples)
+  - [Hunyuan T2I](#example-hunyuan-t2i-inpaintlanpaint-k-sampler-5-steps-of-thinking)
+  - [Wan 2.2 T2I](#example-wan22-inpaintlanpaint-k-sampler-5-steps-of-thinking)
+  - [Wan 2.2 T2I with reference](#example-wan22-partial-inpaintlanpaint-k-sampler-5-steps-of-thinking)
+  - [Qwen Image Edit 2509](#example-qwen-edit-2509-inpaint)
+  - [Qwen Image Edit 2508](#example-qwen-edit-2508-inpaint)
+  - [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](#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-)
+- [FAQ](#faq)
+- [Updates](#updates)
+- [ToDo](#todo)
+- [Citation](#citation)

 ## Features

- 🎨 **Zero-Training Inpainting** - Works immediately with ANY SD model, even custom models you've trained yourself
- 🛠️ **Simple Integration** - Same workflow as standard ComfyUI KSampler
- 🚀 **Quality Enhancements** - High quality and seamless inpainting
+- **Universal Compatibility** – Works instantly with almost any model (**SD 1.5, XL, 3.5, Flux, HiDream, Qwen-Image, Wan2.2 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.  
+- **No Workarounds** – Generates 100% new content (no blending or smoothing) without relying on partial denoising.  
+- **Beyond Inpainting** – You can even use it as a simple way to generate consistent characters. 

-## Example Results
-All examples use random seed 0 to ensure fair comparison.
-### Example 1: Basket to Basket Ball (LanPaint K Sampler, It is fast).
-![Inpainting Result 1](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_04.jpg)  
-[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_1) 
-[Model Used in This Example](https://civitai.com/models/1188071?modelVersionId=1408658) 
-### Example 2: White Shirt to Blue Shirt (LanPaint K Sampler (Advanced), it is slower.)
-![Inpainting Result 2](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_05.jpg)  
-[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_2)
-[Model Used in This Example](https://civitai.com/models/1188071?modelVersionId=1408658)
-### Example 3: Smile to Sad (LanPaint K Sampler (Advanced))
-![Inpainting Result 3](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_06.jpg)  
-[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_3)
-[Model Used in This Example](https://civitai.com/models/133005/juggernaut-xl)
-### Example 4: Damage Restoration (LanPaint K Sampler (Advanced))
-![Inpainting Result 3](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_07.jpg)  
-[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_4)
-[Model Used in This Example](https://civitai.com/models/133005/juggernaut-xl)
-### Example 5: Huge Damage Restoration (LanPaint K Sampler (Advanced))
-![Inpainting Result 3](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_08.jpg)  
-[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_5)
-[Model Used in This Example](https://civitai.com/models/133005/juggernaut-xl) (The key is increase LanPaint_stepsize to 0.5)
-
-**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).  
-
-Compare and explore the results from each method!
-
-![WorkFlow](https://github.com/scraed/LanPaint/blob/master/Example.JPG)  
+**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).

 ## Quickstart

-1. **Install ComfyUI**: Follow the official [ComfyUI installation guide](https://docs.comfy.org/get_started) to set up ComfyUI on your system.  
+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.
 2. **Install ComfyUI-Manager**: Add the [ComfyUI-Manager](https://github.com/ltdrdata/ComfyUI-Manager) for easy extension management.  
 3. **Install LanPaint Nodes**:  
   - **Via ComfyUI-Manager**: Search for "[LanPaint](https://registry.comfy.org/publishers/scraed/nodes/LanPaint)" in the manager and install it directly.  
@@ -62,6 +87,230 @@ Compare and explore the results from each method!

 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!

+
+## **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)**
+
+## Video Examples (Beta)
+
+LanPaint now supports video inpainting with Wan 2.2, enabling you to seamlessly inpaint masked regions across video frames while maintaining temporal consistency.
+
+**Note:** LanPaint supports video inpainting for longer sequences (e.g., 81 frames), but processing time increases significantly (please check the [Resource Consumption](#resource-consumption) section for details) and performance may become unstable. For optimal results and stability, we recommend limiting video inpainting to **40 frames or fewer**.
+
+### Wan 2.2 Video Inpainting 
+
+*Example: Wan2.2 t2v 14B, 480p video (11:6), 40 frames, LanPaint K Sampler, 2 steps of thinking*
+
+| Original Video | Mask (Add a white hat) | Inpainted Result |
+|:--------------:|:----:|:----------------:|
+| ![Original Video](https://github.com/scraed/LanPaint/blob/master/examples/Original_No_Mask_example17.gif) | ![Mask](https://github.com/scraed/LanPaint/blob/master/examples/Example_17/Masked_Load_Me_in_Loader.png) | ![Inpainted Result](https://github.com/scraed/LanPaint/blob/master/examples/Inpainted_40frames_Drag_Me_to_ComfyUI_example17.gif) |
+
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_17)
+
+You need to follow the ComfyUI version of [Wan2.2 T2V workflow](https://docs.comfy.org/tutorials/video/wan/wan2_2) to download and install the T2V model.
+
+### Wan 2.2 5B Video Inpainting 
+
+Similar to Wan 2.2 14B with slightly different workflow. [View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_17)
+
+### Wan 2.2 Video Outpainting
+
+Extend your videos beyond their original boundaries with LanPaint's video outpainting capability based on Wan 2.2. This feature allows you to expand the canvas of your videos while maintaining coherent motion and context.
+
+*Example: Wan2.2 t2v 14B, 480p video (1:1 outpaint to 11:6), 40 frames, LanPaint K Sampler, 2 steps of thinking*
+
+| Original Video | Mask (Expand to 880x480) | Outpainted Result |
+|:--------------:|:----:|:-----------------:|
+| ![Original Video](https://github.com/scraed/LanPaint/blob/master/examples/Original_Load_Me_in_Loader_example19.gif) | ![Mask](https://github.com/scraed/LanPaint/blob/master/examples/Mask_Example19_.png) | ![Outpainted Result](https://github.com/scraed/LanPaint/blob/master/examples/Outpainted_40frames_Drag_Me_to_ComfyUI_example19.gif) |
+
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_19)
+
+You need to follow the ComfyUI version of [Wan2.2 T2V workflow](https://docs.comfy.org/tutorials/video/wan/wan2_2) to download and install the T2V model.
+
+### Resource Consumption
+
+
+<table>
+<thead>
+<tr>
+<th align="left">Processing Mode</th>
+<th align="left">Resolution</th>
+<th align="left">Frames Processed</th>
+<th align="left">VRAM Required</th>
+<th align="left">Total Runtime (20 steps)</th>
+</tr>
+</thead>
+<tbody>
+<tr style="background-color: #e8f4f8;">
+<td><strong>Inpainting</strong></td>
+<td>880×480 (11:6)</td>
+<td>40 frames</td>
+<td>39.8 GB</td>
+<td><strong>05:37 min</strong></td>
+</tr>
+<tr style="background-color: #e8f4f8;">
+<td><strong>Inpainting</strong></td>
+<td>480×480 (1:1)</td>
+<td>40 frames</td>
+<td>38.0 GB</td>
+<td><strong>05:35 min</strong></td>
+</tr>
+<tr style="background-color: #e8f4f8;">
+<td><strong>Outpainting</strong></td>
+<td>880×480 (11:6)</td>
+<td>40 frames</td>
+<td>40.2 GB</td>
+<td><strong>05:36 min</strong></td>
+</tr>
+<tr style="background-color: #fff4e6;">
+<td><strong>Inpainting</strong></td>
+<td>880×480 (11:6)</td>
+<td>81 frames</td>
+<td>43.3 GB</td>
+<td><strong>16:23 min</strong></td>
+</tr>
+<tr style="background-color: #fff4e6;">
+<td><strong>Inpainting</strong></td>
+<td>480×480 (1:1)</td>
+<td>81 frames</td>
+<td>39.8 GB</td>
+<td><strong>14:25 min</strong></td>
+</tr>
+<tr style="background-color: #fff4e6;">
+<td><strong>Outpainting</strong></td>
+<td>880×480 (11:6)</td>
+<td>81 frames</td>
+<td>42.6 GB</td>
+<td><strong>13:46 min</strong></td>
+</tr>
+</tbody>
+</table>
+
+<sub>**Test Platform**: All tests were conducted on an NVIDIA RTX Pro 6000.<br>
+**Model Used**: `wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors` and `wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors`.<br>
+**Processing Steps**:  20 sampling steps x 2 (LanPaint steps of thinking).</sub>
+
+**Note:** To further reduce VRAM requirements, we recommend loading CLIP on CPU.
+
+## Image Examples
+
+### Example Hunyuan T2I: InPaint(LanPaint K Sampler, 5 steps of thinking)
+We are excited to announce that LanPaint now supports inpainting with Hunyuan text to image generation.
+
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_20)
+
+
+You need to follow the ComfyUI version of [Hunyuan workflow](https://docs.comfy.org/tutorials/video/hunyuan-video#hunyuan-text-to-video-workflow) to download and install the model.
+
+### Example Wan2.2: InPaint(LanPaint K Sampler, 5 steps of thinking)
+We are excited to announce that LanPaint now supports Wan2.2 text to image generation with Wan2.2 T2V model.
+
+![Inpainting Result 45](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_45.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_15)
+
+
+You need to follow the ComfyUI version of [Wan2.2 T2V workflow](https://docs.comfy.org/tutorials/video/wan/wan2_2) to download and install the T2V model.
+
+### Example Wan2.2: Partial InPaint(LanPaint K Sampler, 5 steps of thinking)
+Sometimes we don't want to inpaint completely new content, but rather let the inpainted image reference the original image. One option to achieve this is to inpaint with an edit model like Qwen Image Edit. Another option is to perform a partial inpaint: allowing the diffusion process to start at some middle steps rather than from 0.
+
+![Inpainting Result 46](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_46.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_16)
+
+
+You need to follow the ComfyUI version of [Wan2.2 T2V workflow](https://docs.comfy.org/tutorials/video/wan/wan2_2) to download and install the T2V model.
+
+### Example Qwen Edit 2509: InPaint
+Check our latest updated [Mased Qwen Edit Workflow](https://github.com/scraed/LanPaint/tree/master/examples/Example_14) for Qwen Image Edit 2509. Download the model at [Qwen Image Edit 2509 Comfy](https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/tree/main/split_files/diffusion_models).
+
+![Qwen Result 3](https://github.com/scraed/LanPaint/blob/master/examples/LanPaintQwen_04.jpg) 
+
+### Example Qwen Edit 2508: InPaint
+![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.
+
+
+
+### Example Qwen Image: InPaint(LanPaint K Sampler, 5 steps of thinking)
+
+![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.)
+
+![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.
+
+### Example HiDream: InPaint (LanPaint K Sampler, 5 steps of thinking)
+![Inpainting Result 8](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_11.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_8)
+
+You need to follow the ComfyUI version of [HiDream workflow](https://docs.comfy.org/tutorials/image/hidream/hidream-i1) to download and install the model.
+
+### Example HiDream: OutPaint(LanPaint K Sampler, 5 steps of thinking)
+![Inpainting Result 8](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_13(1).jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_10)
+
+You need to follow the ComfyUI version of [HiDream workflow](https://docs.comfy.org/tutorials/image/hidream/hidream-i1) to download and install the model. Thanks [Amazon90](https://github.com/Amazon90) for providing this example.
+
+### Example SD 3.5: InPaint(LanPaint K Sampler, 5 steps of thinking)
+![Inpainting Result 8](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_12.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_9)
+
+You need to follow the ComfyUI version of [SD 3.5 workflow](https://comfyui-wiki.com/en/tutorial/advanced/stable-diffusion-3-5-comfyui-workflow) to download and install the model.
+
+### Example Flux: InPaint(LanPaint K Sampler, 5 steps of thinking)
+![Inpainting Result 7](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_10.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_7)
+[Model Used in This Example](https://huggingface.co/Comfy-Org/flux1-dev/blob/main/flux1-dev-fp8.safetensors) 
+(Note: Prompt First mode is disabled on Flux. As it does not use CFG guidance.)
+
+### Example SDXL 0: Character Consistency (Side View Generation) (LanPaint K Sampler, 5 steps of thinking)
+![Inpainting Result 6](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_09.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_6)
+[Model Used in This Example](https://civitai.com/models/1188071?modelVersionId=1408658) 
+
+(Tricks 1: You can emphasize the character by copy it's image multiple times with Photoshop. Here I have made one extra copy.)
+
+(Tricks 2: Use prompts like multiple views, multiple angles, clone, turnaround. Use LanPaint's Prompt first mode (does not support Flux))
+
+(Tricks 3: Remeber LanPaint can in-paint: Mask non-consistent regions and try again!)
+
+
+### Example SDXL 1: Basket to Basket Ball (LanPaint K Sampler, 2 steps of thinking).
+![Inpainting Result 1](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_04.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_1) 
+[Model Used in This Example](https://civitai.com/models/1188071?modelVersionId=1408658) 
+### Example SDXL 2: White Shirt to Blue Shirt (LanPaint K Sampler, 5 steps of thinking)
+![Inpainting Result 2](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_05.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_2)
+[Model Used in This Example](https://civitai.com/models/1188071?modelVersionId=1408658)
+### Example SDXL 3: Smile to Sad (LanPaint K Sampler, 5 steps of thinking)
+![Inpainting Result 3](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_06.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_3)
+[Model Used in This Example](https://civitai.com/models/133005/juggernaut-xl)
+### Example SDXL 4: Damage Restoration (LanPaint K Sampler, 5 steps of thinking)
+![Inpainting Result 4](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_07.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_4)
+[Model Used in This Example](https://civitai.com/models/133005/juggernaut-xl)
+### Example SDXL 5: Huge Damage Restoration (LanPaint K Sampler, 20 steps of thinking)
+![Inpainting Result 5](https://github.com/scraed/LanPaint/blob/master/examples/InpaintChara_08.jpg)  
+[View Workflow & Masks](https://github.com/scraed/LanPaint/tree/master/examples/Example_5)
+[Model Used in This Example](https://civitai.com/models/133005/juggernaut-xl)
+
+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).
+
+
 ## Usage

 **Workflow Setup**  
@@ -71,53 +320,116 @@ Same as default ComfyUI KSampler - simply replace with LanPaint KSampler nodes.
 - LanPaint requires binary masks (values of 0 or 1) without opacity or smoothing. To ensure compatibility, set the mask's **opacity and hardness to maximum** in your mask editor. During inpainting, any mask with smoothing or gradients will automatically be converted to a binary mask.
 - LanPaint relies heavily on your text prompts to guide inpainting - explicitly describe the content you want generated in the masked area. If results show artifacts or mismatched elements, counteract them with targeted negative prompts.

-### Basic Sampler
+## Basic Sampler
 ![Samplers](https://github.com/scraed/LanPaint/blob/master/Nodes.JPG)  
-**LanPaint KSampler**  
+
+- LanPaint KSampler: The most basic and easy to use sampler for inpainting.
+- LanPaint KSampler (Advanced): Full control of all parameters.
+
+### LanPaint KSampler
 Simplified interface with recommended defaults:

- Steps: 50+ recommended
- LanPaint NumSteps: 1-10 (complexity of edits)
- Built-in parameter presets
+- Steps: 20 - 50. More steps will give more "thinking" and better results.
+- LanPaint NumSteps: The turns of thinking before denoising. Recommend 5 for most of tasks ( which means 5 times slower than sampling without thinking). Use 10 for more challenging tasks. 
+- LanPaint Prompt mode: Image First mode and Prompt First mode. Image First mode focuses on the image, inpaint based on image context (maybe ignore prompt), while Prompt First mode focuses more on the prompt. Use Prompt First mode for tasks like character consistency. (Technically, it Prompt First mode change CFG scale to negative value in the BIG score to emphasis prompt, which will costs image quality.)

-**LanPaint KSampler (Advanced)**  
+### LanPaint KSampler (Advanced)
 Full parameter control:
-## Key Parameters
+**Key Parameters**

 | Parameter | Range | Description |
 |-----------|-------|-------------|
-| `Steps` | 0-100 | Total steps of diffusion sampling. Higher means better inpainting. Recommend 50. |
-| `LanPaint_NumSteps` | 0-20 | Reasoning iterations per denoising step ("thinking depth"). Easy task: 1-2. Hard task: 5-10 |
-| `LanPaint_Lambda` | 0.1-50 | Content alignment strength (higher = stricter). Recommend 6.0 |
-| `LanPaint_StepSize` | 0.1-1.0 | The StepSize of each thinking step. Recommend 0.1 for most cases, 0.5 for some difficult cases. |
-| `LanPaint_cfg_BIG` | 0-20 | CFG scale used when aligning masked and unmasked region (higher = better alignment). Recommend 8 for seamless inpaint (i.e limbs, faces), 0-1 for character consistency (i.e multiple view) |
+| `Steps` | 0-100 | Total steps of diffusion sampling. Higher means better inpainting. Recommend 20-50. |
+| `LanPaint_NumSteps` | 0-20 | Reasoning iterations per denoising step ("thinking depth"). Easy task: 2-5. Hard task: 5-10 |
+| `LanPaint_Lambda` | 0.1-50 | Content alignment strength (higher = stricter). Recommend 4.0 - 10.0 |
+| `LanPaint_StepSize` | 0.1-1.0 | The StepSize of each thinking step. Recommend 0.1-0.5. |
+| `LanPaint_Beta` | 0.1-2.0 | The StepSize ratio between masked / unmasked region. Small value can compensate high lambda values. Recommend 1.0 |
+| `LanPaint_Friction` | 0.0-100.0 | The friction of Langevin dynamics. Higher means more slow but stable, lower means fast but unstable. Recommend 10.0 - 20.0|
+| `LanPaint_EarlyStop` | 0-10 | Stop LanPaint iteration before the final sampling step. Helps to remove artifacts in some cases. Recommend 1-5|
+| `LanPaint_PromptMode` | Image First / Prompt First | Image First mode focuses on the image context, maybe ignore prompt. Prompt First mode focuses more on the prompt. |

 For detailed descriptions of each parameter, simply hover your mouse over the corresponding input field to view tooltips with additional information.

-
+### LanPaint Mask Blend
+This node blends the original image with the inpainted image based on the mask. It is useful if you want the unmasked region to match the original image pixel perfectly.

 ## LanPaint KSampler (Advanced) Tuning Guide
 For challenging inpainting tasks:  

-1️⃣ **Primary Adjustments**:
- Increase **steps**, **LanPaint_StepSize**，**LanPaint_NumSteps** (thinking iterations), and **LanPaint_cfg_BIG** (guidance scale).
+1️⃣ **Boost Quality**
+Increase **total number of sampling steps** (very important!), **LanPaint_NumSteps** (thinking iterations) or **LanPaint_Lambda** if the inpainted result does not meet your expectations.
  
-2️⃣ **Secondary Tweaks**:  
- Boost **LanPaint_Lambda** (spatial constraint strength) or **LanPaint_StepSize** (denoising aggressiveness).
+2️⃣ **Boost Speed**
+Decrease **LanPaint_NumSteps** to accelerate generation! If you want better results but still need fewer steps, consider:
+    - **Increasing LanPaint_StepSize** to speed up the thinking process.
+    - **Decreasing LanPaint_Friction** to make the Langevin dynamics converges more faster.
    
-3️⃣ **Balance Speed vs Stability**:  
- Reduce **LanPaint_Friction** to prioritize faster results with fewer "thinking" steps (*may risk instability*).  
- Increase **LanPaint_Tamed** (noise normalization onto a sphere) or **LanPaint_Alpha** (constraint the friction of underdamped Langevin dynamics) to suppress artifacts.
+3️⃣ **Fix Unstability**:  
+If you find the results have wired texture, try
+- Reduce **LanPaint_Friction** to make the Langevin dynamics more stable. 
+- Reduce **LanPaint_StepSize** to use smaller step size.
+- Reduce **LanPaint_Beta** if you are using a high lambda value.

 ⚠️ **Notes**:  
- Optimal parameters vary depending on the **model** and the **size of the inpainting area**.  
- For effective tuning, **fix the seed** and adjust parameters incrementally while observing the results. This helps isolate the impact of each setting.  
+- 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.

-## Contribute
+## Community Showcase [](#community-showcase-)

- 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).
+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!
+
+## FAQ
+[Working togather with crop&stitch](https://github.com/scraed/LanPaint/issues/46)
+
+## 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.~~ Check our local Python benchmark code [LanPaintBench](https://github.com/scraed/LanPaintBench).
+
+## Citation
+
+```
+@misc{zheng2025lanpainttrainingfreediffusioninpainting,
+      title={Lanpaint: Training-Free Diffusion Inpainting with Exact and Fast Conditional Inference}, 
+      author={Candi Zheng and Yuan Lan and Yang Wang},
+      year={2025},
+      eprint={2502.03491},
+      archivePrefix={arXiv},
+      primaryClass={eess.IV},
+      url={https://arxiv.org/abs/2502.03491}, 
+}
+```

-Help us improve LanPaint! 🚀 **Report bugs**, share **example cases**, or contribute your **personal parameter settings** to benefit the community. 



@@ -0,0 +1,786 @@
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+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
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+          "links": [
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+      "title": "CLIP Text Encode (Positive Prompt)",
+      "properties": {
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+        "ver": "0.3.26",
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+        "cute anime girl with massive fluffy fennec ears and a big fluffy tail blonde messy long hair blue eyes wearing a maid outfit with a long black gold leaf pattern dress and a white apron mouth open placing a fancy black forest cake with candles on top of a dinner table of an old dark Victorian mansion lit by candlelight with a bright window to the foggy forest and very expensive stuff everywhere there are paintings on the walls"
+      ],
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+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
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+          "name": "conditioning",
+          "type": "CONDITIONING",
+          "link": 195
+        }
+      ],
+      "outputs": [
+        {
+          "label": "CONDITIONING",
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "slot_index": 0,
+          "links": [
+            207
+          ]
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+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
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+          "name": "MODEL",
+          "type": "MODEL",
+          "slot_index": 0,
+          "links": [
+            197
+          ]
+        },
+        {
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+          "name": "CLIP",
+          "type": "CLIP",
+          "slot_index": 1,
+          "links": [
+            194,
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+          ]
+        },
+        {
+          "label": "VAE",
+          "name": "VAE",
+          "type": "VAE",
+          "slot_index": 2,
+          "links": [
+            200,
+            203
+          ]
+        }
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+      "properties": {
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+          "type": "MODEL",
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+        {
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+          "type": "CONDITIONING",
+          "link": 207
+        },
+        {
+          "name": "negative",
+          "type": "CONDITIONING",
+          "link": 210
+        },
+        {
+          "name": "latent_image",
+          "type": "LATENT",
+          "link": 186
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "slot_index": 0,
+          "links": [
+            187
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "LanPaint",
+        "ver": "56bd6c04e89124cd06682b304245d6ddf8b20522",
+        "Node name for S&R": "LanPaint_KSampler"
+      },
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+        0,
+        "fixed",
+        30,
+        1,
+        "euler",
+        "simple",
+        1,
+        5,
+        "Image First",
+        "LanPaint KSampler. Recommend steps 50, LanPaint NumSteps 1-20 depending on the difficulty of task. LanPaint_EndSigma = 3.0 for anime style, 0.6 for realistic style. For more information, visit https://github.com/scraed/LanPaint",
+        "🖼️ Image Inpainting"
+      ]
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+      "inputs": [
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+          "type": "IMAGE",
+          "link": 188
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": 203
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "slot_index": 0,
+          "links": [
+            216
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.23",
+        "Node name for S&R": "VAEEncode"
+      },
+      "widgets_values": []
+    },
+    {
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+      "type": "SaveImage",
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+      "mode": 0,
+      "inputs": [
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+          "name": "images",
+          "type": "IMAGE",
+          "link": 103
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.23"
+      },
+      "widgets_values": [
+        "ComfyUI"
+      ]
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+    {
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+      "type": "LanPaint_MaskBlend",
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+          "link": 218
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+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": 220
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+        {
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+          "type": "IMAGE",
+          "links": [
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+      "properties": {
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+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.23"
+      },
+      "widgets_values": [
+        "ComfyUI"
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+          "link": 187
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+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": 200
+        }
+      ],
+      "outputs": [
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+          "name": "IMAGE",
+          "type": "IMAGE",
+          "slot_index": 0,
+          "links": [
+            103,
+            218
+          ]
+        }
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+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.23",
+        "Node name for S&R": "VAEDecode"
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+      "widgets_values": []
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+    },
+    "groupNodes": {}
+  },
+  "version": 0.4
+}
@@ -0,0 +1,735 @@
+{
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+          "type": "CONDITIONING",
+          "slot_index": 0,
+          "links": [
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+          ]
+        }
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+        "Node name for S&R": "CLIPTextEncode"
+      },
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+          "type": "CONDITIONING",
+          "slot_index": 0,
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+        }
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+        "ver": "0.3.23"
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+          "type": "IMAGE",
+          "slot_index": 0,
+          "links": [
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+        }
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+      },
+      "widgets_values": [
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+        "image"
+      ]
+    },
+    {
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+      },
+      "widgets_values": [
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+        },
+        {
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+        },
+        {
+          "name": "latent_image",
+          "type": "LATENT",
+          "link": 186
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "slot_index": 0,
+          "links": [
+            187
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "LanPaint",
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+      },
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+        30,
+        5,
+        "euler",
+        "karras",
+        1,
+        5,
+        "Image First",
+        "LanPaint KSampler. For more info, visit https://github.com/scraed/LanPaint. If you find it useful, please give a star ⭐️!"
+      ]
+    },
+    {
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+      "type": "LanPaint_MaskBlend",
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+        {
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+        },
+        {
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+      ],
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+          "type": "IMAGE",
+          "links": [
+            188
+          ]
+        }
+      ],
+      "properties": {
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+        "ver": "4d3d5d17f0105b673df92da5b084cce567c9c712",
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+        {
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+        }
+      ],
+      "outputs": [
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+          "name": "LATENT",
+          "type": "LATENT",
+          "slot_index": 0,
+          "links": [
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+          ]
+        }
+      ],
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+      ],
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+          "type": "LATENT",
+          "slot_index": 0,
+          "links": [
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+        }
+      ],
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+    }
+  ],
+  "links": [
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+      "title": "Mask image for inpainting.",
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+      "color": "#3f789e",
+      "font_size": 24,
+      "flags": {}
+    },
+    {
+      "id": 2,
+      "title": "Convert Latents for LanPaint",
+      "bounding": [
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+        714.343505859375,
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+      "color": "#3f789e",
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+      "flags": {}
+    },
+    {
+      "id": 3,
+      "title": "Load Model and Set Prompts",
+      "bounding": [
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+      "font_size": 24,
+      "flags": {}
+    },
+    {
+      "id": 4,
+      "title": "Inpaint with the LanPaint KSampler",
+      "bounding": [
+        960.8922729492188,
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+      "color": "#3f789e",
+      "font_size": 24,
+      "flags": {}
+    },
+    {
+      "id": 5,
+      "title": "LanPaint OutPut",
+      "bounding": [
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+    },
+    {
+      "id": 11,
+      "title": "LanPaint",
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+      ],
+      "color": "#3f789e",
+      "font_size": 24,
+      "flags": {}
+    },
+    {
+      "id": 13,
+      "title": "Paste back the original to preserve it exactly, if you want",
+      "bounding": [
+        1491.586181640625,
+        984.3547973632812,
+        749.66455078125,
+        637.360595703125
+      ],
+      "color": "#3f789e",
+      "font_size": 24,
+      "flags": {}
+    }
+  ],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.6209213230591556,
+      "offset": [
+        850.0803535605011,
+        86.6432096141053
+      ]
+    },
+    "frontendVersion": "1.25.10",
+    "node_versions": {
+      "comfy-core": "0.3.18",
+      "LanPaint": "0f509469ed2cd60c6032f739e282aad5dfc06166"
+    }
+  },
+  "version": 0.4
+}
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"

 [project]
 name = "LanPaint"
-version = "0.0.8"
+version = "1.4.4"
 description = "Achieve seamless inpainting results without needing a specialized inpainting model."
 authors = [
  {name = "LanPaint", email = "czhengac@connect.ust.hk"}
@@ -0,0 +1,181 @@
+import torch
+from .utils import *
+from functools import partial
+
+class LanPaint():
+    def __init__(self, Model, NSteps, Friction, Lambda, Beta, StepSize, IS_FLUX = False, IS_FLOW = False):
+        self.n_steps = NSteps
+        self.chara_lamb = Lambda
+        self.IS_FLUX = IS_FLUX
+        self.IS_FLOW = IS_FLOW
+        self.step_size = StepSize
+        self.inner_model = Model
+        self.friction = Friction
+        self.chara_beta = Beta
+        self.img_dim_size = None
+
+    def add_none_dims(self, array):
+        # Create a tuple with ':' for the first dimension and 'None' repeated num_nones times
+        index = (slice(None),) + (None,) * (self.img_dim_size-1)
+        return array[index]
+    def remove_none_dims(self, array):
+        # Create a tuple with ':' for the first dimension and 'None' repeated num_nones times
+        index = (slice(None),) + (0,) * (self.img_dim_size-1)
+        return array[index]
+    def __call__(self, x, latent_image, noise, sigma, latent_mask, current_times, model_options, seed, n_steps=None):
+        self.img_dim_size = len(x.shape)
+        self.latent_image = latent_image
+        self.noise = noise
+        if torch.mean(torch.abs(self.noise)) < 1e-8:
+            self.noise = torch.randn_like(self.noise)
+        if n_steps is None:
+            n_steps = self.n_steps
+        return self.LanPaint(x, sigma, latent_mask, current_times, n_steps, model_options, seed, self.IS_FLUX, self.IS_FLOW)
+    def LanPaint(self, x, sigma, latent_mask, current_times, n_steps, model_options, seed, IS_FLUX, IS_FLOW):
+        VE_Sigma, abt, Flow_t = current_times
+
+        
+        step_size = self.step_size * (1 - abt)
+        step_size = self.add_none_dims(step_size)
+        # self.inner_model.inner_model.scale_latent_inpaint returns variance exploding x_t values
+        # This is the replace step
+        def scale_latent_inpaint(x, sigma, noise, latent_image):
+            return self.inner_model.inner_model.model_sampling.noise_scaling(sigma.reshape([sigma.shape[0]] + [1] * (len(noise.shape) - 1)), noise, latent_image)
+
+        x = x * (1 - latent_mask) +  scale_latent_inpaint(x=x, sigma=sigma, noise=self.noise, latent_image=self.latent_image)* latent_mask
+        
+
+
+        if IS_FLUX or IS_FLOW:
+            x_t = x * ( self.add_none_dims(abt)**0.5 + (1-self.add_none_dims(abt))**0.5 )
+        else:
+            x_t = x / ( 1+self.add_none_dims(VE_Sigma)**2 )**0.5 # switch to variance perserving x_t values
+
+        ############ LanPaint Iterations Start ###############
+        # after noise_scaling, noise = latent_image + noise * sigma, which is x_t in the variance exploding diffusion model notation for the known region.
+        args = None
+        for i in range(n_steps):
+            score_func = partial( self.score_model, y = self.latent_image, mask = latent_mask, abt = self.add_none_dims(abt), sigma = self.add_none_dims(VE_Sigma), tflow = self.add_none_dims(Flow_t), model_options = model_options, seed = seed )
+            x_t, args = self.langevin_dynamics(x_t, score_func , latent_mask, step_size , current_times, sigma_x = self.add_none_dims(self.sigma_x(abt)), sigma_y = self.add_none_dims(self.sigma_y(abt)), args = args)  
+        if IS_FLUX or IS_FLOW:
+            x = x_t / ( self.add_none_dims(abt)**0.5 + (1-self.add_none_dims(abt))**0.5 )
+        else:
+            x = x_t * ( 1+self.add_none_dims(VE_Sigma)**2 )**0.5 # switch to variance perserving x_t values
+        ############ LanPaint Iterations End ###############
+        # out is x_0
+        out, _ = self.inner_model(x, sigma, model_options=model_options, seed=seed)
+        out = out * (1-latent_mask) + self.latent_image * latent_mask
+        return out
+
+    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
+            x_0, x_0_BIG = self.inner_model(x, self.remove_none_dims(tflow), model_options=model_options, seed=seed)
+        else:
+            x = x_t * ( 1+sigma**2 )**0.5 # switch to variance exploding
+            x_0, x_0_BIG = self.inner_model(x, self.remove_none_dims(sigma), model_options=model_options, seed=seed)
+
+        score_x = -(x_t - x_0)
+        score_y =  - (1 + lamb) * ( x_t - y )  + lamb * (x_t - x_0_BIG)  
+        return score_x * (1 - mask) + score_y * mask
+    def sigma_x(self, abt):
+        # the time scale for the x_t update
+        return abt**0
+    def sigma_y(self, abt):
+        beta = self.chara_beta * abt ** 0
+        return beta
+
+    def langevin_dynamics(self, x_t, score, mask, step_size, current_times, sigma_x=1, sigma_y=0, args=None):
+        # prepare the step size and time parameters
+        with torch.autocast(device_type=x_t.device.type, dtype=torch.float32):
+            step_sizes = self.prepare_step_size(current_times, step_size, sigma_x, sigma_y)
+            sigma, abt, dtx, dty, Gamma_x, Gamma_y, A_x, A_y, D_x, D_y = step_sizes
+        # print('mask',mask.device)
+        if torch.mean(dtx) <= 0.:
+            return x_t, args
+        # -------------------------------------------------------------------------
+        # 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)
+        A = A_x * (1-mask) + A_y * mask
+        D = D_x * (1-mask) + D_y * mask
+        dt = dtx * (1-mask) + dty * mask
+        Gamma = Gamma_x * (1-mask) + Gamma_y * mask
+
+
+        def Coef_C(x_t):
+            x0 = self.x0_evalutation(x_t, score, sigma, args)
+            C = (abt**0.5 * x0  - x_t )/ (1-abt) + A * x_t
+            return C
+        def advance_time(x_t, v, dt, Gamma, A, C, D):
+            dtype = x_t.dtype
+            with torch.autocast(device_type=x_t.device.type, dtype=torch.float32):
+                osc = StochasticHarmonicOscillator(Gamma, A, C, D )
+                x_t, v = osc.dynamics(x_t, v, dt )
+            x_t = x_t.to(dtype)
+            v = v.to(dtype)
+            return x_t, v
+        if args is None:
+            #v = torch.zeros_like(x_t)
+            v = None
+            C = Coef_C(x_t)
+            #print(torch.squeeze(dtx), torch.squeeze(dty))
+            x_t, v = advance_time(x_t, v, dt, Gamma, A, C, D)
+        else:
+            v, C = args
+
+            x_t, v = advance_time(x_t, v, dt/2, Gamma, A, C, D)
+
+            C_new = Coef_C(x_t)
+            v = v + Gamma**0.5 * ( C_new - C) *dt
+
+            x_t, v = advance_time(x_t, v, dt/2, Gamma, A, C, D)
+
+            C = C_new
+  
+        return x_t, (v, C)
+
+    def prepare_step_size(self, current_times, step_size, sigma_x, sigma_y):
+        # -------------------------------------------------------------------------
+        # Unpack current times parameters (sigma and abt)
+        sigma, abt, flow_t = current_times
+        sigma = self.add_none_dims(sigma)
+        abt = self.add_none_dims(abt)
+        # Compute time step (dtx, dty) for x and y branches.
+        dtx = 2 * step_size * sigma_x
+        dty = 2 * step_size * sigma_y
+        
+        # -------------------------------------------------------------------------
+        # Define friction parameter Gamma_hat for each branch.
+        # Using dtx**0 provides a tensor of the proper device/dtype.
+
+        Gamma_hat_x = self.friction **2 * self.step_size * sigma_x / 0.1 * sigma**0
+        Gamma_hat_y = self.friction **2 * self.step_size * sigma_y / 0.1 * sigma**0
+        #print("Gamma_hat_x", torch.mean(Gamma_hat_x).item(), "Gamma_hat_y", torch.mean(Gamma_hat_y).item())
+        # adjust dt to match denoise-addnoise steps sizes
+        Gamma_hat_x /= 2.
+        Gamma_hat_y /= 2.
+        A_t_x = (1) / ( 1 - abt ) * dtx / 2
+        A_t_y =  (1+self.chara_lamb) / ( 1 - abt ) * dty / 2
+
+
+        A_x = A_t_x / (dtx/2)
+        A_y = A_t_y / (dty/2)
+        Gamma_x = Gamma_hat_x / (dtx/2)
+        Gamma_y = Gamma_hat_y / (dty/2)
+
+        #D_x = (2 * (1 + sigma**2) )**0.5
+        #D_y = (2 * (1 + sigma**2) )**0.5
+        D_x = (2 * abt**0 )**0.5
+        D_y = (2 * abt**0 )**0.5
+        return sigma, abt, dtx/2, dty/2, Gamma_x, Gamma_y, A_x, A_y, D_x, D_y
+
+
+
+    def x0_evalutation(self, x_t, score, sigma, args):
+        x0 = x_t + score(x_t)
+        return x0
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
scraed	3f4a5cdb5a	update pyproject.yaml	2025-11-23 01:11:08 +08:00
scraed	e0ce52b1be	fix blur issue in Wan 2.2 14B	2025-11-23 00:46:25 +08:00
scraed	2c8f4baec0	add wan 2.2 5B	2025-11-17 16:09:45 +08:00
scraed	daf1bdf4be	update version	2025-11-17 16:05:42 +08:00
scraed	f4d4dfdd61	Merge branch 'master' of https://github.com/scraed/LanPaint	2025-11-17 16:04:51 +08:00
scraed	6d624e7e1e	support Wan 2.2 5B	2025-11-17 16:04:48 +08:00
scraed	e0940059e6	Update README.md	2025-11-10 13:37:49 +08:00
scraed	76ce20b51f	version change	2025-10-26 23:29:23 +08:00
scraed	29ed0b3da5	Add kwargs to CFGGuider_LanPaint sampling methods Updated the outer_sample and inner_sample method calls in CFGGuider_LanPaint to accept and forward arbitrary keyword arguments (kwargs). This allows for greater flexibility and compatibility with future changes or additional parameters.	2025-10-26 23:28:35 +08:00
scraed	3d5aa3a3fa	Add Hunyuan supports Added new example workflows for Hunyuan, including images and JSON workflow files. Updated README with Hunyuan T2I inpainting instructions and links. Increased default LanPaint step size to 0.2 in nodes and advanced sampler, and refactored scale_latent_inpaint logic in lanpaint.py for improved compatibility.	2025-10-16 15:59:13 +08:00
charrywhite	6109df6591	Upload a 41frames outpaint workflows	2025-10-03 22:32:19 +08:00
scraed	536716a7b9	typo fix	2025-10-03 09:59:01 +08:00
scraed	ece228ab10	Bump version to 1.4.0 in pyproject.toml Updated the project version from 1.3.3 to 1.4.0 to prepare for a new release.	2025-10-02 23:24:21 +08:00
charrywhite	c048230250	Update Original Video (Fix to 40 frames, fps=12)	2025-10-02 21:48:44 +08:00
charrywhite	aa885d9fa6	Update README.md	2025-10-02 21:33:37 +08:00
charrywhite	80d55a47b0	Add 81 frames example	2025-10-02 21:31:19 +08:00
charrywhite	79db1765e3	Add video inpainting (Beta)	2025-10-02 21:13:43 +08:00
charrywhite	929328d08d	Update README.md	2025-09-27 00:42:43 +08:00
scraed	c12897040b	Update README with inpainting result image Replaced the workflow & masks link with an inpainting result image to better showcase the output of the project.	2025-09-24 18:49:34 +08:00
scraed	48b9a59ca3	Update README with new model support and examples Added references to Wan2.2 and Qwen Image Edit 2509 support, and included a link to workflow and mask examples for improved documentation.	2025-09-24 18:48:46 +08:00
scraed	d55f8c61d0	Add Qwen Image Edit 2509 example to README Introduced a new section for Qwen Image Edit 2509 inpainting example, including workflow and model download links, and an example image. Updated the table of contents to reference the new example.	2025-09-24 18:43:41 +08:00
scraed	a097b9c9b2	Update LanPaintQwen_04.jpg example image Replaces the existing LanPaintQwen_04.jpg in the examples directory with a new version. This may reflect updated content or improved image quality.	2025-09-24 18:40:25 +08:00
scraed	70cc94cc6a	update readme	2025-09-24 18:30:04 +08:00
scraed	e653f45103	Support 2509	2025-09-24 18:27:11 +08:00
scraed	c9c237c2de	Add WAN 2.2 partial inpaint workflow template	2025-09-18 16:55:48 +08:00
scraed	c5aa0116d5	Add Example 16 for partial inpainting with reference Added a new example (Example 16) demonstrating partial inpainting using reference images. Updated README with instructions and links for the new example, and added related images to the examples directory.	2025-09-18 15:40:22 +08:00
scraed	1820d88594	fix link	2025-09-17 15:59:35 +08:00
scraed	c265bcc989	Add Wan2.2 inpainting example and bump version Added a new example for Wan2.2 inpainting with image and workflow links in the README. Updated project version to 1.3.2 in pyproject.toml.	2025-09-17 15:55:28 +08:00
scraed	b8973c570b	Support Wan 2.2 Txt 2 Img	2025-09-17 15:46:11 +08:00
scraed	1b50a90424	qwen edit resize fix	2025-09-07 13:07:17 +08:00
charrywhite	dab41249da	Update README.md	2025-08-30 11:15:11 +08:00
charrywhite	b2b2b21bf1	Update README.md	2025-08-30 11:14:53 +08:00
scraed	099d4137a9	Clarify speed improvement suggestions Reworded instructions for boosting speed in README.	2025-08-26 12:10:11 +08:00
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
scraed	7aeb6e535f	Add Qwen image support and new inpainting examples Updated the README to announce Qwen image support and provide usage instructions. Added new example images and workflow files for Qwen inpainting in the examples directory.	2025-08-08 14:09:53 +08:00
scraed	eda0f19944	Generalize dimension handling in LanPaint and fix mask reshape Refactored LanPaint to dynamically handle tensors with varying numbers of dimensions by introducing add_none_dims and remove_none_dims utility methods. Updated all relevant tensor broadcasting to use these methods, improving flexibility. Also fixed reshape_mask in nodes.py to use the last two dimensions for resizing, ensuring correct mask shape.	2025-08-08 13:42:24 +08:00
scraed	e20c8f20ce	update version	2025-06-21 14:13:09 +08:00
scraed	89b9010b35	Fix indentation error in sample method Corrected an indentation issue in the sample method of LanPaint_SamplerCustomAdvanced to ensure proper execution of the end_at_step check.	2025-06-21 14:09:11 +08:00
scraed	ee0c65656e	simplify custom sampler	2025-06-21 13:18:25 +08:00
scraed	48b1dd4be6	Merge branch 'master' into pr/33	2025-06-21 13:10:05 +08:00
scraed	9d304cd5a3	update readme	2025-06-21 13:03:30 +08:00
scraed	61c19ac31d	update algorithm with better outpaint	2025-06-21 12:56:36 +08:00
Bagier	1ca6e53090	adjust info names	2025-06-20 08:31:51 +07:00
Bagier	520932cee0	add invalid value check	2025-06-19 20:49:20 +07:00
Bagier	37612bb399	Logic fix	2025-06-19 20:12:50 +07:00
Bagier	0e6cb45081	re-add lanpaint info	2025-06-19 19:25:59 +07:00
Bagier	0a5e36d55e	add advanced custom sampler	2025-06-19 19:15:58 +07:00
Bagier	b319f772cb	fix parameter update error	2025-06-19 19:00:41 +07:00
Bagier	340376ad18	Add custom sampler variation	2025-06-19 16:14:26 +07:00
scraed	dbfc1585fc	Merge branch 'master' of https://github.com/scraed/LanPaint	2025-06-16 20:03:31 +08:00
scraed	c3ae2c644d	update coefficients	2025-06-16 20:03:25 +08:00
scraed	c7017373c9	Update pyproject.toml	2025-06-08 17:59:04 +08:00
scraed	850f707eb6	Remove redundant comment	2025-06-08 17:58:40 +08:00
scraed	62870f060a	Update README.md	2025-06-06 13:05:50 +08:00
scraed	a91cefacf0	Update README.md	2025-06-06 13:05:16 +08:00
scraed	4265f71a85	Update README.md	2025-06-05 18:15:21 +08:00
scraed	4189ba80c2	add error message	2025-06-05 17:10:07 +08:00
scraed	23ad6e47fd	add new masked blend node	2025-06-05 16:21:46 +08:00
scraed	4d3d5d17f0	Update README.md	2025-06-05 01:22:09 +08:00
scraed	b86f3b7112	update version	2025-06-05 01:14:57 +08:00
scraed	96b7f3eecd	fix sigma batch error	2025-06-05 01:11:04 +08:00
scraed	e472574783	update readme	2025-06-04 21:33:58 +08:00
scraed	0b799be8ec	support more sampler	2025-06-04 21:28:51 +08:00
scraed	82da0b4142	Merge branch 'master' of https://github.com/scraed/LanPaint	2025-06-04 20:04:58 +08:00
scraed	c66155e783	add early stop	2025-06-04 20:04:53 +08:00
scraed	d802f2f2b0	Update README.md fix typo	2025-06-04 14:34:10 +08:00
scraed	6153a450c9	Update README.md	2025-06-04 14:33:07 +08:00
scraed	493658d23a	Update README.md	2025-06-04 14:28:11 +08:00
scraed	7de1054b39	Update README.md	2025-06-04 09:06:39 +08:00
scraed	574d9906ec	Update README.md	2025-06-03 20:54:12 +08:00
scraed	61d4ecef75	Update README.md	2025-06-03 18:41:24 +08:00
scraed	5eb2d8ef48	Update README.md	2025-06-03 17:19:52 +08:00
scraed	b668bcc42c	Update README.md	2025-06-03 13:11:47 +08:00
scraed	05386f98d3	replace outdated flux picture	2025-06-03 11:49:40 +08:00
scraed	ad5704d25f	correct tricks for consistency	2025-06-03 11:06:35 +08:00
scraed	2ab72851b9	update summary img	2025-06-03 10:29:54 +08:00
scraed	14f7907c70	update version	2025-06-03 10:19:41 +08:00
scraed	5adce4ecdd	update readme	2025-05-28 18:11:30 +08:00
scraed	2fd945e69b	update readme and pictures	2025-05-28 18:04:52 +08:00
scraed	1bd6932cae	change to ve notation and update examples	2025-05-28 17:22:15 +08:00
scraed	59b31303c8	update examples	2025-05-27 10:44:15 +08:00
scraed	f906bd9cc9	reduce parameters	2025-05-22 15:01:36 +08:00
scraed	31e4909438	switch to sampler alg	2025-05-22 10:14:58 +08:00
scraed	6775e6ac37	1-a schedule and shared A	2025-05-17 19:06:43 +08:00
scraed	49b35bcb28	fix Zcoef asymp bug	2025-05-14 15:55:18 +08:00
scraed	13bd3182bf	switch to separate file	2025-05-13 19:14:46 +08:00
scraed	bb3e0078d4	switch to new new alg	2025-05-13 18:33:08 +08:00
scraed	5fc4cf2092	remove y time truncate	2025-05-12 22:34:44 +08:00
scraed	3f8e2b833c	change y update alg	2025-05-12 22:27:56 +08:00
scraed	0f546f09b6	add truncate time step	2025-05-12 16:38:35 +08:00
scraed	99ac3ee06d	Create utils.py	2025-05-12 11:40:05 +08:00
scraed	505fbfb7fc	fix tamed bug	2025-05-12 09:49:12 +08:00
scraed	aa541edaea	change default lambda schedule to const	2025-05-03 23:16:07 +08:00
scraed	5382fbba21	remove redundant time step schedule	2025-05-03 22:31:59 +08:00
scraed	82a6798e29	change parameter range	2025-05-03 22:28:25 +08:00
scraed	3b7c79f431	add lamb schedule	2025-05-03 01:01:02 +08:00
scraed	ae31ac7e70	complete migration to new alg formula	2025-05-02 22:31:37 +08:00
scraed	2a67dd353f	update epxm1Dx	2025-05-02 21:14:54 +08:00
scraed	2d0f458695	update eps	2025-05-02 13:50:19 +08:00
scraed	6f2deeda51	separate ld	2025-05-02 00:38:58 +08:00
scraed	76cd0a5c1d	sort tamed	2025-05-01 21:08:45 +08:00
scraed	f90636d4c0	create hidream img	2025-04-23 22:05:02 +08:00
scraed	dc4ef3aed4	Update README.md	2025-04-22 08:55:51 +08:00
scraed	eca581ee79	Update README.md	2025-04-17 15:38:32 +08:00
scraed	75a91710f2	Update pyproject.toml	2025-04-16 23:50:17 +08:00
scraed	f8eea61264	Update README.md	2025-04-16 23:48:58 +08:00
scraed	e42d3b0426	Update README.md	2025-04-16 23:32:46 +08:00
scraed	ee567b14e8	Update Example for Hidream	2025-04-16 23:21:55 +08:00
scraed	10a790974c	Merge branch 'master' of https://github.com/scraed/LanPaint	2025-04-16 23:12:18 +08:00
scraed	00d2eb9885	Update hidream example	2025-04-16 23:12:13 +08:00
scraed	b1139f285a	Update Citationn	2025-04-16 22:58:40 +08:00
scraed	eb69a21cf2	Update README.md for hidream support	2025-04-16 22:26:05 +08:00
scraed	c863ade839	update version	2025-04-16 22:25:05 +08:00
scraed	b07ed256c7	Primary support for Hidream	2025-04-16 22:24:18 +08:00
scraed	612cfb51f2	Merge pull request #19 from ComfyNodePRs/update-publish-yaml Update Github Action for Publishing to Comfy Registry	2025-04-11 20:42:47 +08:00
scraed	aa9319f7cf	Update README.md	2025-03-22 21:26:08 +08:00
scraed	a92d19d4f8	Updates dates	2025-03-22 21:23:12 +08:00
scraed	478b077c69	Update pyproject.toml	2025-03-22 21:18:12 +08:00
scraed	3015d6f0ef	Update README.md	2025-03-22 21:17:17 +08:00
scraed	55cd84be93	Update README.md for flux and tease mode	2025-03-22 21:16:40 +08:00
scraed	758eae62c3	add flux example	2025-03-22 21:08:23 +08:00
scraed	58f8d01acf	Merge branch 'master' of https://github.com/scraed/LanPaint	2025-03-22 20:14:27 +08:00
scraed	1684b616f1	Merge pull request #16 from charrywhite/master Add preview hood in KSamplerX0Inpaint	2025-03-22 20:10:07 +08:00
scraed	65f98f7c48	disable CFG BIG for Flux	2025-03-22 20:05:30 +08:00
charrywhite	5d8e40a669	Add preview hood in KSamplerX0Inpaint	2025-03-22 19:57:59 +08:00
scraed	ff1fb62d1a	Merge branch 'master' of https://github.com/scraed/LanPaint	2025-03-22 19:46:42 +08:00
scraed	b7d37ef121	flux support and parameter change add flux support and eliminate parameters a and b	2025-03-22 19:46:40 +08:00
scraed	29c9d877be	Update ToDo	2025-03-19 23:10:21 +08:00
scraed	6c1375c35f	update control net support in readme	2025-03-13 23:10:49 +08:00
scraed	8c04ba410b	More intuitive how it works	2025-03-13 22:29:46 +08:00
scraed	a5c08aa0a4	Update how it works	2025-03-13 17:45:32 +08:00
scraed	cefc2c43d3	add version requirement in README.md	2025-03-13 10:15:36 +08:00
scraed	62c5934a1a	Update README.md	2025-03-12 17:10:47 +08:00
scraed	9ae04abb14	Update README.md	2025-03-12 10:15:22 +08:00
scraed	8446a1a735	Update README.md	2025-03-12 09:55:46 +08:00
scraed	439cc8371a	Update tuning guide	2025-03-12 08:58:42 +08:00
scraed	0b6adec240	Update README.md	2025-03-11 23:46:52 +08:00
scraed	32dd4f23ff	Update README.md	2025-03-11 22:49:04 +08:00
scraed	ef927e6a9a	Update README.md	2025-03-11 12:14:01 +08:00
scraed	142595b8ac	Update README.md	2025-03-11 12:13:20 +08:00
scraed	26dd8dcf8e	Update README.md	2025-03-11 12:08:09 +08:00
scraed	c4e8ca9fb9	Update README.md	2025-03-11 10:54:51 +08:00
scraed	6073fb9846	Update README.md	2025-03-11 10:53:10 +08:00
scraed	de01bc07d7	Update README.md	2025-03-11 10:49:02 +08:00
scraed	492114f14c	Update README.md	2025-03-11 09:39:26 +08:00
charrywhite	47f4fea033	Update README.md	2025-03-11 09:24:02 +08:00
scraed	3dd2c28db3	Update README.md	2025-03-11 01:43:51 +08:00
scraed	f58cfeb0ca	Update README.md	2025-03-11 01:39:21 +08:00
scraed	df43f9f078	Update README.md	2025-03-11 01:13:51 +08:00
scraed	3eebbf9ffd	Update pyproject.toml	2025-03-11 01:09:45 +08:00
scraed	3fcf3e11ac	Update nodes.py	2025-03-11 01:08:40 +08:00
scraed	a9aff269a7	Update README.md	2025-03-11 01:06:16 +08:00
scraed	22cce34f79	Merge branch 'master' of https://github.com/scraed/LanPaint	2025-03-11 01:00:36 +08:00
scraed	95e566ca23	update nodes image	2025-03-11 01:00:09 +08:00
scraed	bd318e4666	Update README.md	2025-03-11 00:52:47 +08:00
scraed	733cbc704f	Update README.md	2025-03-11 00:49:56 +08:00
charrywhite	96ef5e4926	Update README.md add more description for lanpaint	2025-03-11 00:46:04 +08:00
scraed	bf554c1170	Merge branch 'master' of https://github.com/scraed/LanPaint	2025-03-11 00:45:26 +08:00
scraed	3dc4adeade	update example 6 picture	2025-03-11 00:45:06 +08:00
scraed	dd41680dd7	Update README.md	2025-03-11 00:40:21 +08:00
scraed	3fb85ab403	major update node functions and examples	2025-03-11 00:36:46 +08:00
snomiao	34d36e3c93	chore(publish): update workflow for node publishing - Add permissions for issue writing in the workflow - Set condition to run job only for 'scraed' repository owner - Update action version from 'main' to 'v1' for stability and consistency	2025-03-04 04:12:56 +00:00