Upload 309 files

custom_nodes/ComfyUI-ReActor/.github/ISSUE_TEMPLATE/bug_report.yml

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+name: Bug Report
+description: You think somethings is broken
+labels: ["bug", "new"]
+
+body:
+  - type: checkboxes
+    attributes:
+      label: First, confirm
+      description: Make sure you use the latest version of the ReActor extension and you have already searched to see if an issue already exists for the bug you encountered before you create a new Issue.
+      options:
+        - label: I have read the [instruction](https://github.com/Gourieff/ComfyUI-ReActor/blob/main/README.md) carefully
+          required: true
+        - label: I have searched the existing issues
+          required: true
+        - label: I have updated the extension to the latest version
+          required: true
+  - type: markdown
+    attributes:
+      value: |
+        *Please fill this form with as much information as possible and *provide screenshots if possible**
+  - type: textarea
+    id: what-did
+    attributes:
+      label: What happened?
+      description: Tell what happened in a very clear and simple way
+    validations:
+      required: true
+  - type: textarea
+    id: steps
+    attributes:
+      label: Steps to reproduce the problem
+      description: Please provide with precise step by step instructions on how to reproduce the bug
+      value: |
+        Your workflow
+    validations:
+      required: true
+  - type: textarea
+    id: sysinfo
+    attributes:
+      label: Sysinfo
+      description: Describe your platform. OS, browser, GPU, what other nodes are also enabled.
+    validations:
+      required: true
+  - type: textarea
+    id: logs
+    attributes:
+      label: Relevant console log
+      description: Please provide cmd/terminal logs from the moment you started UI to the momemt you got an error. This will be automatically formatted into code, so no need for backticks.
+      render: Shell
+    validations:
+      required: true
+  - type: textarea
+    id: misc
+    attributes:
+      label: Additional information
+      description: Please provide with any relevant additional info or context.

custom_nodes/ComfyUI-ReActor/.github/ISSUE_TEMPLATE/config.yml

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+blank_issues_enabled: false
+contact_links:
+  - name: ReActor Node Community Support
+    url: https://github.com/Gourieff/ComfyUI-ReActor/discussions
+    about: Please ask and answer questions here.

custom_nodes/ComfyUI-ReActor/.github/ISSUE_TEMPLATE/feature_request.yml

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+name: Feature request
+description: Suggest an idea for this project
+title: "[Feature]: "
+labels: ["enhancement", "new"]
+
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Feature description
+      description: Describe the feature in a clear and simple way
+      value: 
+  - type: markdown
+    attributes:
+      value: |
+        The best way to propose an idea is to start a new discussion via the [Discussions](https://github.com/Gourieff/ComfyUI-ReActor/discussions) section (choose the "Idea" category)

custom_nodes/ComfyUI-ReActor/.github/workflows/publish_action.yml

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+name: Publish to Comfy registry
+on: 
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+    paths:
+      - "pyproject.toml"
+
+jobs:
+  publish-node:
+    name: Publish Custom Node to registry
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+      - name: Publish Custom Node
+        uses: Comfy-Org/publish-node-action@main
+        with:
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} ## Add your own personal access token to your Github secrets and reference it here.

custom_nodes/ComfyUI-ReActor/.gitignore

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+__pycache__/
+*$py.class
+.vscode/
+example
+input

custom_nodes/ComfyUI-ReActor/LICENSE

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+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
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custom_nodes/ComfyUI-ReActor/README.md

@@ -0,0 +1,482 @@
+<div align="center">
+
+  <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/ReActor_logo_NEW_EN.png?raw=true" alt="logo" width="180px"/>
+
+  ![Version](https://img.shields.io/badge/node_version-0.5.2_beta2-green?style=for-the-badge&labelColor=darkgreen)
+
+  <!--<sup>
+  <font color=brightred>
+
+  ## !!! [Important Update](#latestupdate) !!!<br>Don't forget to add the Node again in existing workflows
+  
+  </font>
+  </sup>-->
+  
+  <a href="https://boosty.to/artgourieff" target="_blank">
+    <img src="https://lovemet.ru/img/boosty.jpg" width="108" alt="Support Me on Boosty"/>
+    <br>
+    <sup>
+      Support This Project
+    </sup>
+  </a>
+
+  <hr>
+  
+  [![Commit activity](https://img.shields.io/github/commit-activity/t/Gourieff/ComfyUI-ReActor/main?cacheSeconds=0)](https://github.com/Gourieff/ComfyUI-ReActor/commits/main)
+  ![Last commit](https://img.shields.io/github/last-commit/Gourieff/ComfyUI-ReActor/main?cacheSeconds=0)
+  [![Opened issues](https://img.shields.io/github/issues/Gourieff/ComfyUI-ReActor?color=red)](https://github.com/Gourieff/ComfyUI-ReActor/issues?cacheSeconds=0)
+  [![Closed issues](https://img.shields.io/github/issues-closed/Gourieff/ComfyUI-ReActor?color=green&cacheSeconds=0)](https://github.com/Gourieff/ComfyUI-ReActor/issues?q=is%3Aissue+state%3Aclosed)
+  ![License](https://img.shields.io/github/license/Gourieff/ComfyUI-ReActor)
+
+  English | [Русский](/README_RU.md)
+
+# ReActor Nodes for ComfyUI<br><sub><sup>-=SFW-Friendly=-</sup></sub>
+
+</div>
+
+### The Fast and Simple Face Swap Extension Nodes for ComfyUI, based on [blocked ReActor](https://github.com/Gourieff/comfyui-reactor-node) - now it has a nudity detector to avoid using this software with 18+ content
+
+> By using this Node you accept and assume [responsibility](#disclaimer)) 
+
+<div align="center">
+
+---
+[**What's new**](#latestupdate) | [**Installation**](#installation) | [**Usage**](#usage) | [**Troubleshooting**](#troubleshooting) | [**Updating**](#updating) | [**Disclaimer**](#disclaimer) | [**Credits**](#credits) | [**Note!**](#note)
+
+---
+
+</div>
+
+<a name="latestupdate">
+
+## What's new in the latest update
+
+### 0.5.2 <sub><sup>BETA1</sup></sub>
+
+- ReSwapper models support. Although Inswapper still has the best similarity, but ReSwapper is evolving - thanks @somanchiu https://github.com/somanchiu/ReSwapper for the ReSwapper models and the ReSwapper project! This is a good step for the Community in the Inswapper's alternative creation!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-03.jpg?raw=true" alt="0.5.2-whatsnew-03" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-04.jpg?raw=true" alt="0.5.2-whatsnew-04" width="100%"/>
+
+You can download ReSwapper models here:
+https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models
+Just put them into the "models/reswapper" directory.
+
+### 0.5.2 <sub><sup>ALPHA3</sup></sub>
+
+- NSFW-detector to not violate [GitHub rules](https://docs.github.com/en/site-policy/acceptable-use-policies/github-misinformation-and-disinformation#synthetic--manipulated-media-tools)
+
+### 0.5.2 <sub><sup>ALPHA2</sup></sub>
+
+- Minor fixes
+
+### 0.5.2 <sub><sup>ALPHA1</sup></sub>
+
+- New node "Unload ReActor Models" - is useful for complex WFs when you need to free some VRAM utilized by ReActor
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-01.jpg?raw=true" alt="0.5.2-whatsnew-01" width="100%"/>
+
+- Support of ORT CoreML and ROCM EPs, just install onnxruntime version you need
+- Install script improvements to install latest versions of ORT-GPU
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-02.jpg?raw=true" alt="0.5.2-whatsnew-02" width="50%"/>
+
+<details>
+	<summary><a>Previous versions</a></summary>
+
+### 0.5.1
+
+- Support of GPEN 1024/2048 restoration models (available in the HF dataset https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models/facerestore_models)
+- ReActorFaceBoost Node - an attempt to improve the quality of swapped faces. The idea is to restore and scale the swapped face (according to the `face_size` parameter of the restoration model) BEFORE pasting it to the target image (via inswapper algorithms), more information is [here (PR#321)](https://github.com/Gourieff/comfyui-reactor-node/pull/321)
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.1-whatsnew-01.jpg?raw=true" alt="0.5.1-whatsnew-01" width="100%"/>
+
+[Full size demo preview](https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.1-whatsnew-02.png)
+
+- Sorting facemodels alphabetically
+- A lot of fixes and improvements
+
+### [0.5.0 <sub><sup>BETA4</sup></sub>](https://github.com/Gourieff/comfyui-reactor-node/releases/tag/v0.5.0)
+
+- Spandrel lib support for GFPGAN
+
+### 0.5.0 <sub><sup>BETA3</sup></sub>
+
+- Fixes: "RAM issue", "No detection" for MaskingHelper
+
+### 0.5.0 <sub><sup>BETA2</sup></sub>
+
+- You can now build a blended face model from a batch of face models you already have, just add the "Make Face Model Batch" node to your workflow and connect several models via "Load Face Model"
+- Huge performance boost of the image analyzer's module! 10x speed up! Working with videos is now a pleasure!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-05.png?raw=true" alt="0.5.0-whatsnew-05" width="100%"/>
+
+### 0.5.0 <sub><sup>BETA1</sup></sub>
+
+- SWAPPED_FACE output for the Masking Helper Node
+- FIX: Empty A-channel for Masking Helper IMAGE output (causing errors with some nodes) was removed
+
+### 0.5.0 <sub><sup>ALPHA1</sup></sub>
+
+- ReActorBuildFaceModel Node got "face_model" output to provide a blended face model directly to the main Node:
+
+Basic workflow [💾](https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/workflows/ReActor--Build-Blended-Face-Model--v2.json)
+
+- Face Masking feature is available now, just add the "ReActorMaskHelper" Node to the workflow and connect it as shown below:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-01.jpg?raw=true" alt="0.5.0-whatsnew-01" width="100%"/>
+
+If you don't have the "face_yolov8m.pt" Ultralytics model - you can download it from the [Assets](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/detection/bbox/face_yolov8m.pt) and put it into the "ComfyUI\models\ultralytics\bbox" directory
+<br>
+As well as ["sam_vit_b_01ec64.pth"](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/sams/sam_vit_b_01ec64.pth) model - download (if you don't have it) and put it into the "ComfyUI\models\sams" directory;
+
+Use this Node to gain the best results of the face swapping process:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-02.jpg?raw=true" alt="0.5.0-whatsnew-02" width="100%"/>
+
+- ReActorImageDublicator Node - rather useful for those who create videos, it helps to duplicate one image to several frames to use them with VAE Encoder (e.g. live avatars):
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-03.jpg?raw=true" alt="0.5.0-whatsnew-03" width="100%"/>
+
+- ReActorFaceSwapOpt (a simplified version of the Main Node) + ReActorOptions Nodes to set some additional options such as (new) "input/source faces separate order". Yes! You can now set the order of faces in the index in the way you want ("large to small" goes by default)!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-04.jpg?raw=true" alt="0.5.0-whatsnew-04" width="100%"/>
+
+- Little speed boost when analyzing target images (unfortunately it is still quite slow in compare to swapping and restoring...)
+
+### [0.4.2](https://github.com/Gourieff/comfyui-reactor-node/releases/tag/v0.4.2)
+
+- GPEN-BFR-512 and RestoreFormer_Plus_Plus face restoration models support
+
+You can download models here: https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models/facerestore_models
+<br>Put them into the `ComfyUI\models\facerestore_models` folder
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.2-whatsnew-04.jpg?raw=true" alt="0.4.2-whatsnew-04" width="100%"/>
+
+- Due to popular demand - you can now blend several images with persons into one face model file and use it with "Load Face Model" Node or in SD WebUI as well;
+
+Experiment and create new faces or blend faces of one person to gain better accuracy and likeness!
+
+Just add the ImpactPack's "Make Image Batch" Node as the input to the ReActor's one and load images you want to blend into one model:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.2-whatsnew-01.jpg?raw=true" alt="0.4.2-whatsnew-01" width="100%"/>
+
+Result example (the new face was created from 4 faces of different actresses):
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.2-whatsnew-02.jpg?raw=true" alt="0.4.2-whatsnew-02" width="75%"/>
+
+Basic workflow [💾](https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/workflows/ReActor--Build-Blended-Face-Model--v1.json)
+
+### [0.4.1](https://github.com/Gourieff/comfyui-reactor-node/releases/tag/v0.4.1)
+
+- CUDA 12 Support - don't forget to run (Windows) `install.bat` or (Linux/MacOS) `install.py` for ComfyUI's Python enclosure or try to install ORT-GPU for CU12 manually (https://onnxruntime.ai/docs/install/#install-onnx-runtime-gpu-cuda-12x)
+- Issue https://github.com/Gourieff/comfyui-reactor-node/issues/173 fix
+
+- Separate Node for the Face Restoration postprocessing (FR https://github.com/Gourieff/comfyui-reactor-node/issues/191), can be found inside ReActor's menu (RestoreFace Node)
+- (Windows) Installation can be done for Python from the System's PATH
+- Different fixes and improvements
+
+- Face Restore Visibility and CodeFormer Weight (Fidelity) options are now available! Don't forget to reload the Node in your existing workflow
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.1-whatsnew-01.jpg?raw=true" alt="0.4.1-whatsnew-01" width="100%"/>
+
+### [0.4.0](https://github.com/Gourieff/comfyui-reactor-node/releases/tag/v0.4.0)
+
+- Input "input_image" goes first now, it gives a correct bypass and also it is right to have the main input first;
+- You can now save face models as "safetensors" files (`ComfyUI\models\reactor\faces`) and load them into ReActor implementing different scenarios and keeping super lightweight face models of the faces you use:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.0-whatsnew-01.jpg?raw=true" alt="0.4.0-whatsnew-01" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.0-whatsnew-02.jpg?raw=true" alt="0.4.0-whatsnew-02" width="100%"/>
+
+- Ability to build and save face models directly from an image:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.0-whatsnew-03.jpg?raw=true" alt="0.4.0-whatsnew-03" width="50%"/>
+
+- Both the inputs are optional, just connect one of them according to your workflow; if both is connected - `image` has a priority.
+- Different fixes making this extension better.
+
+Thanks to everyone who finds bugs, suggests new features and supports this project!
+
+</details>
+
+## Installation
+
+<details>
+	<summary>SD WebUI: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/">AUTOMATIC1111</a> or <a href="https://github.com/vladmandic/automatic">SD.Next</a></summary>
+
+1. Close (stop) your SD-WebUI/Comfy Server if it's running
+2. (For Windows Users):
+   - Install [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) (Community version - you need this step to build Insightface)
+   - OR only [VS C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) and select "Desktop Development with C++" under "Workloads -> Desktop & Mobile"
+   - OR if you don't want to install VS or VS C++ BT - follow [this steps (sec. I)](#insightfacebuild)
+3. Go to the `extensions\sd-webui-comfyui\ComfyUI\custom_nodes`
+4. Open Console or Terminal and run `git clone https://github.com/Gourieff/ComfyUI-ReActor`
+5. Go to the SD WebUI root folder, open Console or Terminal and run (Windows users)`.\venv\Scripts\activate` or (Linux/MacOS)`venv/bin/activate`
+6. `python -m pip install -U pip`
+7. `cd extensions\sd-webui-comfyui\ComfyUI\custom_nodes\ComfyUI-ReActor`
+8. `python install.py`
+9.  Please, wait until the installation process will be finished
+10. (From the version 0.3.0) Download additional facerestorers models from the link below and put them into the `extensions\sd-webui-comfyui\ComfyUI\models\facerestore_models` directory:<br>
+https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models/facerestore_models
+11. Run SD WebUI and check console for the message that ReActor Node is running:
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/uploads/console_status_running.jpg?raw=true" alt="console_status_running" width="759"/>
+
+12.  Go to the ComfyUI tab and find there ReActor Node inside the menu `ReActor` or by using a search:
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/uploads/webui-demo.png?raw=true" alt="webui-demo" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/uploads/search-demo.png?raw=true" alt="webui-demo" width="1043"/>
+
+</details>
+
+<details>
+	<summary>Standalone (Portable) <a href="https://github.com/comfyanonymous/ComfyUI">ComfyUI</a> for Windows</summary>
+
+1. Do the following:
+   - Install [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) (Community version - you need this step to build Insightface)
+   - OR only [VS C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) and select "Desktop Development with C++" under "Workloads -> Desktop & Mobile"
+   - OR if you don't want to install VS or VS C++ BT - follow [this steps (sec. I)](#insightfacebuild)
+2. Choose between two options:
+   - (ComfyUI Manager) Open ComfyUI Manager, click "Install Custom Nodes", type "ReActor" in the "Search" field and then click "Install". After ComfyUI will complete the process - please restart the Server.
+   - (Manually) Go to `ComfyUI\custom_nodes`, open Console and run `git clone https://github.com/Gourieff/ComfyUI-ReActor`
+3. Go to `ComfyUI\custom_nodes\ComfyUI-ReActor` and run `install.bat`
+4. If you don't have the "face_yolov8m.pt" Ultralytics model - you can download it from the [Assets](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/detection/bbox/face_yolov8m.pt) and put it into the "ComfyUI\models\ultralytics\bbox" directory
+<br>
+As well as one or both of "Sams" models from [here](https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models/sams) - download (if you don't have them) and put into the "ComfyUI\models\sams" directory
+5. Run ComfyUI and find there ReActor Nodes inside the menu `ReActor` or by using a search
+
+</details>
+
+## Usage
+
+You can find ReActor Nodes inside the menu `ReActor` or by using a search (just type "ReActor" in the search field)
+
+List of Nodes:
+- ••• Main Nodes •••
+   - ReActorFaceSwap (Main Node)
+   - ReActorFaceSwapOpt (Main Node with the additional Options input)
+   - ReActorOptions (Options for ReActorFaceSwapOpt)
+   - ReActorFaceBoost (Face Booster Node)
+   - ReActorMaskHelper (Masking Helper)
+- ••• Operations with Face Models •••
+  - ReActorSaveFaceModel (Save Face Model)
+  - ReActorLoadFaceModel (Load Face Model)
+  - ReActorBuildFaceModel (Build Blended Face Model)
+  - ReActorMakeFaceModelBatch (Make Face Model Batch)
+- ••• Additional Nodes •••
+  - ReActorRestoreFace (Face Restoration)
+  - ReActorImageDublicator (Dublicate one Image to Images List)
+  - ImageRGBA2RGB (Convert RGBA to RGB)
+
+Connect all required slots and run the query.
+
+### Main Node Inputs
+
+- `input_image` - is an image to be processed (target image, analog of "target image" in the SD WebUI extension);
+  - Supported Nodes: "Load Image", "Load Video" or any other nodes providing images as an output;
+- `source_image` - is an image with a face or faces to swap in the `input_image` (source image, analog of "source image" in the SD WebUI extension);
+  - Supported Nodes: "Load Image" or any other nodes providing images as an output;
+- `face_model` - is the input for the "Load Face Model" Node or another ReActor node to provide a face model file (face embedding) you created earlier via the "Save Face Model" Node;
+  - Supported Nodes: "Load Face Model", "Build Blended Face Model";
+
+### Main Node Outputs
+
+- `IMAGE` - is an output with the resulted image;
+  - Supported Nodes: any nodes which have images as an input;
+- `FACE_MODEL` - is an output providing a source face's model being built during the swapping process;
+  - Supported Nodes: "Save Face Model", "ReActor", "Make Face Model Batch";
+
+### Face Restoration
+
+Since version 0.3.0 ReActor Node has a buil-in face restoration.<br>Just download the models you want (see [Installation](#installation) instruction) and select one of them to restore the resulting face(s) during the faceswap. It will enhance face details and make your result more accurate.
+
+### Face Indexes
+
+By default ReActor detects faces in images from "large" to "small".<br>You can change this option by adding ReActorFaceSwapOpt node with ReActorOptions.
+
+And if you need to specify faces, you can set indexes for source and input images.
+
+Index of the first detected face is 0.
+
+You can set indexes in the order you need.<br>
+E.g.: 0,1,2 (for Source); 1,0,2 (for Input).<br>This means: the second Input face (index = 1) will be swapped by the first Source face (index = 0) and so on.
+
+### Genders
+
+You can specify the gender to detect in images.<br>
+ReActor will swap a face only if it meets the given condition.
+
+### Face Models
+
+Since version 0.4.0 you can save face models as "safetensors" files (stored in `ComfyUI\models\reactor\faces`) and load them into ReActor implementing different scenarios and keeping super lightweight face models of the faces you use.
+
+To make new models appear in the list of the "Load Face Model" Node - just refresh the page of your ComfyUI web application.<br>
+(I recommend you to use ComfyUI Manager - otherwise you workflow can be lost after you refresh the page if you didn't save it before that).
+
+## Troubleshooting
+
+<a name="insightfacebuild">
+
+### **I. (For Windows users) If you still cannot build Insightface for some reasons or just don't want to install Visual Studio or VS C++ Build Tools - do the following:**
+
+1. (ComfyUI Portable) From the root folder check the version of Python:<br>run CMD and type `python_embeded\python.exe -V`
+2. Download prebuilt Insightface package [for Python 3.10](https://github.com/Gourieff/Assets/raw/main/Insightface/insightface-0.7.3-cp310-cp310-win_amd64.whl) or [for Python 3.11](https://github.com/Gourieff/Assets/raw/main/Insightface/insightface-0.7.3-cp311-cp311-win_amd64.whl) (if in the previous step you see 3.11) or [for Python 3.12](https://github.com/Gourieff/Assets/raw/main/Insightface/insightface-0.7.3-cp312-cp312-win_amd64.whl) (if in the previous step you see 3.12) and put into the stable-diffusion-webui (A1111 or SD.Next) root folder (where you have "webui-user.bat" file) or into ComfyUI root folder if you use ComfyUI Portable
+3. From the root folder run:
+   - (SD WebUI) CMD and `.\venv\Scripts\activate`
+   - (ComfyUI Portable) run CMD
+4. Then update your PIP:
+   - (SD WebUI) `python -m pip install -U pip`
+   - (ComfyUI Portable) `python_embeded\python.exe -m pip install -U pip`
+5. Then install Insightface:
+   - (SD WebUI) `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl` (for 3.10) or `pip install insightface-0.7.3-cp311-cp311-win_amd64.whl` (for 3.11) or `pip install insightface-0.7.3-cp312-cp312-win_amd64.whl` (for 3.12)
+   - (ComfyUI Portable) `python_embeded\python.exe -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl` (for 3.10) or `python_embeded\python.exe -m pip install insightface-0.7.3-cp311-cp311-win_amd64.whl` (for 3.11) or `python_embeded\python.exe -m pip install insightface-0.7.3-cp312-cp312-win_amd64.whl` (for 3.12)
+6. Enjoy!
+
+### **II. "AttributeError: 'NoneType' object has no attribute 'get'"**
+
+This error may occur if there's smth wrong with the model file `inswapper_128.onnx`
+
+Try to download it manually from [here](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx)
+and put it to the `ComfyUI\models\insightface` replacing existing one
+
+### **III. "reactor.execute() got an unexpected keyword argument 'reference_image'"**
+
+This means that input points have been changed with the latest update<br>
+Remove the current ReActor Node from your workflow and add it again
+
+### **IV. ControlNet Aux Node IMPORT failed error when using with ReActor Node**
+
+1. Close ComfyUI if it runs
+2. Go to the ComfyUI root folder, open CMD there and run:
+   - `python_embeded\python.exe -m pip uninstall -y opencv-python opencv-contrib-python opencv-python-headless`
+   - `python_embeded\python.exe -m pip install opencv-python==4.7.0.72`
+3. That's it!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/uploads/reactor-w-controlnet.png?raw=true" alt="reactor+controlnet" />
+
+### **V. "ModuleNotFoundError: No module named 'basicsr'" or "subprocess-exited-with-error" during future-0.18.3 installation**
+
+- Download https://github.com/Gourieff/Assets/raw/main/comfyui-reactor-node/future-0.18.3-py3-none-any.whl<br>
+- Put it to ComfyUI root And run:
+
+      python_embeded\python.exe -m pip install future-0.18.3-py3-none-any.whl
+
+- Then:
+
+      python_embeded\python.exe -m pip install basicsr
+
+### **VI. "fatal: fetch-pack: invalid index-pack output" when you try to `git clone` the repository"**
+
+Try to clone with `--depth=1` (last commit only):
+
+     git clone --depth=1 https://github.com/Gourieff/ComfyUI-ReActor
+
+Then retrieve the rest (if you need):
+
+     git fetch --unshallow
+
+## Updating
+
+Just put .bat or .sh script from this [Repo](https://github.com/Gourieff/sd-webui-extensions-updater) to the `ComfyUI\custom_nodes` directory and run it when you need to check for updates
+
+### Disclaimer
+
+This software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.
+
+The developers of this software are aware of its possible unethical applications and are committed to take preventative measures against them. We will continue to develop this project in the positive direction while adhering to law and ethics.
+
+Users of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. **Developers and Contributors of this software are not responsible for actions of end-users.**
+
+By using this extension you are agree not to create any content that:
+- violates any laws;
+- causes any harm to a person or persons;
+- propagates (spreads) any information (both public or personal) or images (both public or personal) which could be meant for harm;
+- spreads misinformation;
+- targets vulnerable groups of people.
+
+This software utilizes the pre-trained models `buffalo_l` and `inswapper_128.onnx`, which are provided by [InsightFace](https://github.com/deepinsight/insightface/). These models are included under the following conditions:
+
+[From insighface license](https://github.com/deepinsight/insightface/tree/master/python-package): The InsightFace’s pre-trained models are available for non-commercial research purposes only. This includes both auto-downloading models and manually downloaded models.
+
+Users of this software must strictly adhere to these conditions of use. The developers and maintainers of this software are not responsible for any misuse of InsightFace’s pre-trained models.
+
+Please note that if you intend to use this software for any commercial purposes, you will need to train your own models or find models that can be used commercially.
+
+### Models Hashsum
+
+#### Safe-to-use models have the following hash:
+
+inswapper_128.onnx
+```
+MD5:a3a155b90354160350efd66fed6b3d80
+SHA256:e4a3f08c753cb72d04e10aa0f7dbe3deebbf39567d4ead6dce08e98aa49e16af
+```
+
+1k3d68.onnx
+
+```
+MD5:6fb94fcdb0055e3638bf9158e6a108f4
+SHA256:df5c06b8a0c12e422b2ed8947b8869faa4105387f199c477af038aa01f9a45cc
+```
+
+2d106det.onnx
+
+```
+MD5:a3613ef9eb3662b4ef88eb90db1fcf26
+SHA256:f001b856447c413801ef5c42091ed0cd516fcd21f2d6b79635b1e733a7109dbf
+```
+
+det_10g.onnx
+
+```
+MD5:4c10eef5c9e168357a16fdd580fa8371
+SHA256:5838f7fe053675b1c7a08b633df49e7af5495cee0493c7dcf6697200b85b5b91
+```
+
+genderage.onnx
+
+```
+MD5:81c77ba87ab38163b0dec6b26f8e2af2
+SHA256:4fde69b1c810857b88c64a335084f1c3fe8f01246c9a191b48c7bb756d6652fb
+```
+
+w600k_r50.onnx
+
+```
+MD5:80248d427976241cbd1343889ed132b3
+SHA256:4c06341c33c2ca1f86781dab0e829f88ad5b64be9fba56e56bc9ebdefc619e43
+```
+
+**Please check hashsums if you download these models from unverified (or untrusted) sources**
+
+<a name="credits">
+
+## Thanks and Credits
+
+<details>
+	<summary><a>Click to expand</a></summary>
+
+<br>
+
+|file|source|license|
+|----|------|-------|
+|[buffalo_l.zip](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/buffalo_l.zip) | [DeepInsight](https://github.com/deepinsight/insightface) | ![license](https://img.shields.io/badge/license-non_commercial-red) |
+| [codeformer-v0.1.0.pth](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/facerestore_models/codeformer-v0.1.0.pth) | [sczhou](https://github.com/sczhou/CodeFormer) | ![license](https://img.shields.io/badge/license-non_commercial-red) |
+| [GFPGANv1.3.pth](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/facerestore_models/GFPGANv1.3.pth) | [TencentARC](https://github.com/TencentARC/GFPGAN) | ![license](https://img.shields.io/badge/license-Apache_2.0-green.svg) |
+| [GFPGANv1.4.pth](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/facerestore_models/GFPGANv1.4.pth) | [TencentARC](https://github.com/TencentARC/GFPGAN) | ![license](https://img.shields.io/badge/license-Apache_2.0-green.svg) |
+| [inswapper_128.onnx](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx) | [DeepInsight](https://github.com/deepinsight/insightface) | ![license](https://img.shields.io/badge/license-non_commercial-red) |
+| [inswapper_128_fp16.onnx](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128_fp16.onnx) | [Hillobar](https://github.com/Hillobar/Rope) | ![license](https://img.shields.io/badge/license-non_commercial-red) |
+
+[BasicSR](https://github.com/XPixelGroup/BasicSR) - [@XPixelGroup](https://github.com/XPixelGroup) <br>
+[facexlib](https://github.com/xinntao/facexlib) - [@xinntao](https://github.com/xinntao) <br>
+
+[@s0md3v](https://github.com/s0md3v), [@henryruhs](https://github.com/henryruhs) - the original Roop App <br>
+[@ssitu](https://github.com/ssitu) - the first version of [ComfyUI_roop](https://github.com/ssitu/ComfyUI_roop) extension
+
+</details>
+
+<a name="note">
+
+### Note!
+
+**If you encounter any errors when you use ReActor Node - don't rush to open an issue, first try to remove current ReActor node in your workflow and add it again**
+
+**ReActor Node gets updates from time to time, new functions appear and old node can work with errors or not work at all**

custom_nodes/ComfyUI-ReActor/README_RU.md

@@ -0,0 +1,491 @@
+<div align="center">
+
+  <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/ReActor_logo_NEW_RU.png?raw=true" alt="logo" width="180px"/>
+
+  ![Version](https://img.shields.io/badge/версия_нода-0.5.2_beta2-green?style=for-the-badge&labelColor=darkgreen)
+  
+  <!--<sup>
+  <font color=brightred>
+
+  ## !!! [Важные изменения](#latestupdate) !!!<br>Не забудьте добавить Нод заново в существующие воркфлоу
+  
+  </font>
+  </sup>-->
+
+  <a href="https://boosty.to/artgourieff" target="_blank">
+    <img src="https://lovemet.ru/img/boosty.jpg" width="108" alt="Поддержать проект на Boosty"/>
+    <br>
+    <sup>
+      Поддержать проект
+    </sup>
+  </a>
+
+  <hr>
+  
+  [![Commit activity](https://img.shields.io/github/commit-activity/t/Gourieff/ComfyUI-ReActor/main?cacheSeconds=0)](https://github.com/Gourieff/ComfyUI-ReActor/commits/main)
+  ![Last commit](https://img.shields.io/github/last-commit/Gourieff/ComfyUI-ReActor/main?cacheSeconds=0)
+  [![Opened issues](https://img.shields.io/github/issues/Gourieff/ComfyUI-ReActor?color=red)](https://github.com/Gourieff/ComfyUI-ReActor/issues?cacheSeconds=0)
+  [![Closed issues](https://img.shields.io/github/issues-closed/Gourieff/ComfyUI-ReActor?color=green&cacheSeconds=0)](https://github.com/Gourieff/ComfyUI-ReActor/issues?q=is%3Aissue+state%3Aclosed)
+  ![License](https://img.shields.io/github/license/Gourieff/ComfyUI-ReActor)
+
+  [English](/README.md) | Русский
+
+# ReActor Nodes для ComfyUI<br><sub><sup>-=Безопасно для работы | SFW-Friendly=-</sup></sub>
+
+</div>
+
+### Ноды (nodes) для быстрой и простой замены лиц на любых изображениях для работы с ComfyUI, основан на [ранее заблокированном РеАкторе](https://github.com/Gourieff/comfyui-reactor-node) - теперь имеется встроенный NSFW-детектор, исключающий замену лиц на изображениях с контентом 18+
+
+> Используя данное ПО, вы понимаете и принимаете [ответственность](#disclaimer)
+
+<div align="center">
+
+---
+[**Что нового**](#latestupdate) | [**Установка**](#installation) | [**Использование**](#usage) | [**Устранение проблем**](#troubleshooting) | [**Обновление**](#updating) | [**Ответственность**](#disclaimer) | [**Благодарности**](#credits) | [**Заметка**](#note)
+
+---
+
+</div>
+
+<a name="latestupdate">
+
+## Что нового в последнем обновлении
+
+### 0.5.2 <sub><sup>BETA1</sup></sub>
+
+- Поддержка моделей ReSwapper. Несмотря на то, что Inswapper по-прежнему даёт лучшее сходство, но ReSwapper развивается - спасибо @somanchiu https://github.com/somanchiu/ReSwapper за эти модели и проект ReSwapper! Это хороший шаг для Сообщества в создании альтернативы Инсваппера!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-03.jpg?raw=true" alt="0.5.2-whatsnew-03" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-04.jpg?raw=true" alt="0.5.2-whatsnew-04" width="100%"/>
+
+Скачать модели ReSwapper можно отсюда:
+https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models
+Сохраните их в директорию "models/reswapper".
+
+### 0.5.2 <sub><sup>ALPHA3</sup></sub>
+
+- NSFW-детектор, чтобы не нарушать [правила GitHub](https://docs.github.com/en/site-policy/acceptable-use-policies/github-misinformation-and-disinformation#synthetic--manipulated-media-tools)
+
+### 0.5.2 <sub><sup>ALPHA2</sup></sub>
+
+- Небольшие исправления
+
+### 0.5.2 <sub><sup>ALPHA1</sup></sub>
+
+- Новый нод "Unload ReActor Models" - полезен для сложных воркфлоу, когда вам нужно освободить ОЗУ, занятую РеАктором
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-01.jpg?raw=true" alt="0.5.2-whatsnew-01" width="100%"/>
+
+- Поддержка ORT CoreML and ROCM EPs, достаточно установить ту версию onnxruntime, которая соответствует вашему GPU
+- Некоторые улучшения скрипта установки для поддержки последней версии ORT-GPU
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-02.jpg?raw=true" alt="0.5.2-whatsnew-02" width="50%"/>
+
+<details>
+	<summary><a>Предыдущие версии</a></summary>
+
+### 0.5.1
+
+- Поддержка м��делей восстановления лиц GPEN 1024/2048 (доступны в датасете на HF https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models/facerestore_models)
+- Нод ReActorFaceBoost - попытка улучшить качество заменённых лиц. Идея состоит в том, чтобы восстановить и увеличить заменённое лицо (в соответствии с параметром `face_size` модели реставрации) ДО того, как лицо будет вставлено в целевое изображения (через алгоритмы инсваппера), больше информации [здесь (PR#321)](https://github.com/Gourieff/comfyui-reactor-node/pull/321)
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.1-whatsnew-01.jpg?raw=true" alt="0.5.1-whatsnew-01" width="100%"/>
+
+[Полноразмерное демо-превью](https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.1-whatsnew-02.png)
+
+- Сортировка моделей лиц по алфавиту
+- Множество исправлений и улучшений
+
+### [0.5.0 <sub><sup>BETA4</sup></sub>](https://github.com/Gourieff/comfyui-reactor-node/releases/tag/v0.5.0)
+
+- Поддержка библиотеки Spandrel при работе с GFPGAN
+
+### 0.5.0 <sub><sup>BETA3</sup></sub>
+
+- Исправления: "RAM issue", "No detection" для MaskingHelper
+
+### 0.5.0 <sub><sup>BETA2</sup></sub>
+
+- Появилась возможность строить смешанные модели лиц из пачки уже имеющихся моделей - добавьте для этого нод "Make Face Model Batch" в свой воркфлоу и загрузите несколько моделей через ноды "Load Face Model"
+- Огромный буст производительности модуля анализа изображений! 10-кратный прирост скорости! Работа с видео теперь в удовольствие!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-05.png?raw=true" alt="0.5.0-whatsnew-05" width="100%"/>
+
+### 0.5.0 <sub><sup>BETA1</sup></sub>
+
+- Добавлен выход SWAPPED_FACE для нода Masking Helper
+- FIX: Удалён пустой A-канал на выходе IMAGE нода Masking Helper (вызывавший ошибки с некоторым нодами)
+
+### 0.5.0 <sub><sup>ALPHA1</sup></sub>
+
+- Нод ReActorBuildFaceModel получил выход "face_model" для отправки совмещенной модели лиц непосредственно в основной Нод:
+
+Basic workflow [💾](https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/workflows/ReActor--Build-Blended-Face-Model--v2.json)
+
+- Функции маски лица теперь доступна и в версии для Комфи, просто добавьте нод "ReActorMaskHelper" в воркфлоу и соедините узлы, как показано ниже:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-01.jpg?raw=true" alt="0.5.0-whatsnew-01" width="100%"/>
+
+Если модель "face_yolov8m.pt" у вас отсутствует - можете скачать её [отсюда](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/detection/bbox/face_yolov8m.pt) и положить в папку "ComfyUI\models\ultralytics\bbox"
+<br>
+То же самое и с ["sam_vit_b_01ec64.pth"](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/sams/sam_vit_b_01ec64.pth) - скачайте (если отсутствует) и положите в папку "ComfyUI\models\sams";
+
+Данный нод поможет вам получить куда более аккуратный результат при замене лиц:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-02.jpg?raw=true" alt="0.5.0-whatsnew-02" width="100%"/>
+
+- Нод ReActorImageDublicator - полезен тем, кто создает видео, помогает продублировать одиночное изображение в несколько копий, чтобы использовать их, к примеру, с VAE энкодером:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-03.jpg?raw=true" alt="0.5.0-whatsnew-03" width="100%"/>
+
+- ReActorFaceSwapOpt (упрощенная версия основного нода) + нод ReActorOptions для установки дополнительных опций, как (новые) "отдельный порядок лиц для input/source". Да! Теперь можно установить любой порядок "чтения" индекса лиц на изображении, в т.ч. ��т большего к меньшему (по умолчанию)!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.0-whatsnew-04.jpg?raw=true" alt="0.5.0-whatsnew-04" width="100%"/>
+
+- Небольшое улучшение скорости анализа целевых изображений (input)
+
+### [0.4.2](https://github.com/Gourieff/comfyui-reactor-node/releases/tag/v0.4.2)
+
+- Добавлена поддержка GPEN-BFR-512 и RestoreFormer_Plus_Plus моделей восстановления лиц
+
+Скачать можно здесь: https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models/facerestore_models
+<br>Добавьте модели в папку `ComfyUI\models\facerestore_models`
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.2-whatsnew-04.jpg?raw=true" alt="0.4.2-whatsnew-04" width="100%"/>
+
+- По многочисленным просьбам появилась возможность строить смешанные модели лиц и в ComfyUI тоже и использовать их с нодом "Load Face Model" Node или в SD WebUI;
+
+Экспериментируйте и создавайте новые лица или совмещайте разные лица нужного вам персонажа, чтобы добиться лучшей точности и схожести с оригиналом!
+
+Достаточно добавить нод "Make Image Batch" (ImpactPack) на вход нового нода РеАктора и загрузить в пачку необходимые вам изображения для построения смешанной модели:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.2-whatsnew-01.jpg?raw=true" alt="0.4.2-whatsnew-01" width="100%"/>
+
+Пример результата (на основе лиц 4-х актрис создано новое лицо):
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.2-whatsnew-02.jpg?raw=true" alt="0.4.2-whatsnew-02" width="75%"/>
+
+Базовый воркфлоу [💾](https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/workflows/ReActor--Build-Blended-Face-Model--v1.json)
+
+### [0.4.1](https://github.com/Gourieff/comfyui-reactor-node/releases/tag/v0.4.1)
+
+- Поддержка CUDA 12 - не забудьте запустить (Windows) `install.bat` или (Linux/MacOS) `install.py` для используемого Python окружения или попробуйте установить ORT-GPU для CU12 вручную (https://onnxruntime.ai/docs/install/#install-onnx-runtime-gpu-cuda-12x)
+- Исправление Issue https://github.com/Gourieff/comfyui-reactor-node/issues/173
+
+- Отдельный Нод для восстаноления лиц (FR https://github.com/Gourieff/comfyui-reactor-node/issues/191), располагается внутри меню ReActor (нод RestoreFace)
+- (Windows) Установка зависимостей теперь может быть выполнена в Python из PATH ОС
+- Разные исправления и улучшения
+
+- Face Restore Visibility и CodeFormer Weight (Fidelity) теперь доступны; не забудьте заново добавить Нод в ваших существующих воркфлоу
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.1-whatsnew-01.jpg?raw=true" alt="0.4.1-whatsnew-01" width="100%"/>
+
+### [0.4.0](https://github.com/Gourieff/comfyui-reactor-node/releases/tag/v0.4.0)
+
+- Вход "input_image" теперь идёт первым, это даёт возможность корректного байпаса, а также это правильно с точки зрения расположения входов (главный вход - первый);
+- Теперь можно сохранять модели лиц в качестве файлов "safetensors" (`ComfyUI\models\reactor\faces`) и загружать их в ReActor, реализуя разные сценарии использования, а также  храня супер легкие модели лиц, которые вы чаще всего используете:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.0-whatsnew-01.jpg?raw=true" alt="0.4.0-whatsnew-01" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.0-whatsnew-02.jpg?raw=true" alt="0.4.0-whatsnew-02" width="100%"/>
+
+- Возможность сохранять модели лиц напрямую из изображения:
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.4.0-whatsnew-03.jpg?raw=true" alt="0.4.0-whatsnew-03" width="50%"/>
+
+- Оба входа опциональны, присоедините один из них в соответствии с вашим воркфлоу; если присо��денены оба - вход `image` имеет приоритет.
+- Различные исправления, делающие это расширение лучше.
+
+Спасибо всем, кто находит ошибки, предлагает новые функции и поддерживает данный проект!
+
+</details>
+
+<a name="installation">
+
+## Установка
+
+<details>
+	<summary>SD WebUI: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/">AUTOMATIC1111</a> или <a href="https://github.com/vladmandic/automatic">SD.Next</a></summary>
+
+1. Закройте (остановите) SD-WebUI Сервер, если запущен
+2. (Для пользователей Windows):
+   - Установите [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) (Например, версию Community - этот шаг нужен для правильной компиляции библиотеки Insightface)
+   - ИЛИ только [VS C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/), выберите "Desktop Development with C++" в разделе "Workloads -> Desktop & Mobile"
+   - ИЛИ если же вы не хотите устанавливать что-либо из вышеуказанного - выполните [данные шаги (раздел. I)](#insightfacebuild)
+3. Перейдите в `extensions\sd-webui-comfyui\ComfyUI\custom_nodes`
+4. Откройте Консоль или Терминал и выполните `git clone https://github.com/Gourieff/ComfyUI-ReActor`
+5. Перейдите в корневую директорию SD WebUI, откройте Консоль или Терминал и выполните (для пользователей Windows)`.\venv\Scripts\activate` или (для пользователей Linux/MacOS)`venv/bin/activate`
+6. `python -m pip install -U pip`
+7. `cd extensions\sd-webui-comfyui\ComfyUI\custom_nodes\ComfyUI-ReActor`
+8. `python install.py`
+9.  Пожалуйста, дождитесь полного завершения установки
+10. (Начиная с версии 0.3.0) Скачайте дополнительные модели восстановления лиц (по ссылке ниже) и сохраните их в папку `extensions\sd-webui-comfyui\ComfyUI\models\facerestore_models`:<br>
+https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models/facerestore_models
+11. Запустите SD WebUI и проверьте консоль на сообщение, что ReActor Node работает:
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/uploads/console_status_running.jpg?raw=true" alt="console_status_running" width="759"/>
+
+12.   Перейдите во вкладку ComfyUI и найдите там ReActor Node внутри меню `ReActor` или через поиск:
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/uploads/webui-demo.png?raw=true" alt="webui-demo" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/uploads/search-demo.png?raw=true" alt="webui-demo" width="1043"/>
+
+</details>
+
+<details>
+	<summary>Портативная версия <a href="https://github.com/comfyanonymous/ComfyUI">ComfyUI</a> для Windows</summary>
+
+1. Сделайте следующее:
+   - Установите [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) (Например, версию Community - этот шаг нужен для правильной компиляции библиотеки Insightface)
+   - ИЛИ только [VS C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/), выберите "Desktop Development with C++" в разделе "Workloads -> Desktop & Mobile"
+   - ИЛИ если же вы не хотите устанавливать что-либо из вышеуказанного - выполните [данные шаги (раздел. I)](#insightfacebuild)
+2. Выберите из двух вариантов:
+   - (ComfyUI Manager) Откройте ComfyUI Manager, нажвите "Install Custom Nodes", введите "ReActor" в поле "Search" и далее нажмите "Install". После того, как ComfyUI завершит установку, перезагрузите сервер.
+   - (Вручную) Перейдите в `ComfyUI\custom_nodes`, откройте Консоль и выполните `git clone https://github.com/Gourieff/ComfyUI-ReActor`
+3. Перейдите `ComfyUI\custom_nodes\ComfyUI-ReActor` и запустите `install.bat`, дождитесь окончания установки
+4. Если модель "face_yolov8m.pt" у вас отсутствует - можете скачать её [отсюда](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/detection/bbox/face_yolov8m.pt) и положить в папку "ComfyUI\models\ultralytics\bbox"
+<br>
+То ��е самое и с "Sams" моделями, скачайте одну или обе [отсюда](https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models/sams) - и положите в папку "ComfyUI\models\sams"
+5. Запустите ComfyUI и найдите ReActor Node внутри меню `ReActor` или через поиск
+
+</details>
+
+<a name="usage">
+
+## Использование
+
+Вы можете найти ноды ReActor внутри меню `ReActor` или через поиск (достаточно ввести "ReActor" в поисковой строке)
+
+Список нодов:
+- ••• Main Nodes •••
+   - ReActorFaceSwap (Основной нод)
+   - ReActorFaceSwapOpt (Основной нод с доп. входом Options)
+   - ReActorOptions (Опции для ReActorFaceSwapOpt)
+   - ReActorFaceBoost (Нод Face Booster)
+   - ReActorMaskHelper (Masking Helper)
+- ••• Operations with Face Models •••
+  - ReActorSaveFaceModel (Save Face Model)
+  - ReActorLoadFaceModel (Load Face Model)
+  - ReActorBuildFaceModel (Build Blended Face Model)
+  - ReActorMakeFaceModelBatch (Make Face Model Batch)
+- ••• Additional Nodes •••
+  - ReActorRestoreFace (Face Restoration)
+  - ReActorImageDublicator (Dublicate one Image to Images List)
+  - ImageRGBA2RGB (Convert RGBA to RGB)
+
+Соедините все необходимые слоты (slots) и запустите очередь (query).
+
+### Входы основного Нода
+
+- `input_image` - это изображение, на котором надо поменять лицо или лица (целевое изображение, аналог "target image" в версии для SD WebUI);
+  - Поддерживаемые ноды: "Load Image", "Load Video" или любые другие ноды предоставляющие изображение в качестве выхода;
+- `source_image` - это изображение с лицом или лицами для замены (изображение-источник, аналог "source image" в версии для SD WebUI);
+  - Поддерживаемые ноды: "Load Image" или любые другие ноды с выходом Image(s);
+- `face_model` - это вход для выхода с нода "Load Face Model" или другого нода ReActor для загрузки модели лица (face model или face embedding), которое вы создали ранее через нод "Save Face Model";
+  - Поддерживаемые ноды: "Load Face Model", "Build Blended Face Model";
+
+### Выходы основного Нода
+
+- `IMAGE` - выход с готовым изображением (результатом);
+  - Поддерживаемые ноды: любые ноды с изображением на входе;
+- `FACE_MODEL` - выход, предоставляющий модель лица, построенную в ходе замены;
+  - Поддерживаемые ноды: "Save Face Model", "ReActor", "Make Face Model Batch";
+
+### Восстановление лиц
+
+Начиная с версии 0.3.0 ReActor Node имеет встроенное восстановление лиц.<br>Скачайте нужные вам модели (см. инструкцию по [Установке](#installation)) и выберите одну из них, чтобы улучшить качество финального лица.
+
+### Индексы Лиц (Face Indexes)
+
+По умолчанию ReActor определяет лица на изображении в порядке от "большого" к "малому".<br>Вы можете поменять эту опцию, используя нод ReActorFaceSwapOpt вместе с ReActorOptions.
+
+Если вам нужно заменить определенное лицо, вы можете указать индекс для исходного (source, с лицом) и входного (input, где будет замена лица) изображений.
+
+Индекс первого обнаруженного лица - 0.
+
+Вы можете задать индексы в том порядке, который вам нужен.<br>
+Например: 0,1,2 (для Source); 1,0,2 (для Input).<br>Это означает, что: второе лицо из Input (индекс = 1) будет заменено первым лицом из Source (индекс = 0) и так далее.
+
+### Определение Пола
+
+Вы можете обозначить, какой пол нужно определять на изображении.<br>
+ReActor заменит только то лицо, которое удовлетворяет заданному условию.
+
+### Модели Лиц
+Начиная с версии 0.4.0, вы можете сохранять модели лиц как файлы "safetensors" (хранятся в папке `ComfyUI\models\reactor\faces`) и загружать их в ReActor, реализуя разные сценарии использования, а также  храня супер легкие модели лиц, которые вы чаще всего используете.
+
+Чтобы новые модели появились в списке моделей нода "Load Face Model" - обновите страницу of с ComfyUI.<br>
+(Рекомендую использовать ComfyUI Manager - иначе ваше воркфлоу может быть потеряно после перезагрузки страницы, если вы не сохранили его).
+
+<a name="troubleshooting">
+
+## Устранение проблем
+
+<a name="insightfacebuild">
+
+### **I. (Для пользователей Windows) Если вы до сих пор не можете установить пакет Insightface по каким-то причинам или же просто не желаете устанавливать Visual Studio или VS C++ Build Tools - сделайте следующее:**
+
+1. (ComfyUI Portable) Находясь в корневой директории, проверьте версию Python:<br>запустите CMD и выполните `python_embeded\python.exe -V`<br>Вы должны увидеть версию или 3.10, или 3.11, или 3.12
+2. Скачайте готовый пакет Insightface [для версии 3.10](https://github.com/Gourieff/sd-webui-reactor/raw/main/example/insightface-0.7.3-cp310-cp310-win_amd64.whl) или [для 3.11](https://github.com/Gourieff/Assets/raw/main/Insightface/insightface-0.7.3-cp311-cp311-win_amd64.whl) (если на предыдущем шаге вы увидели 3.11) или [для 3.12](https://github.com/Gourieff/Assets/raw/main/Insightface/insightface-0.7.3-cp312-cp312-win_amd64.whl) (если на предыдущем шаге вы увидели 3.12) и сохраните его в корневую директорию stable-diffusion-webui (A1111 или SD.Next) - туда, где лежит файл "webui-user.bat" -ИЛИ- в корневую директорию ComfyUI, если вы используете ComfyUI Portable
+3. Из корневой директории запустите:
+   - (SD WebUI) CMD и `.\venv\Scripts\activate`
+   - (ComfyUI Portable) CMD
+4. Обновите PIP:
+   - (SD WebUI) `python -m pip install -U pip`
+   - (ComfyUI Portable) `python_embeded\python.exe -m pip install -U pip`
+5. Затем установите Insightface:
+   - (SD WebUI) `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl` (для 3.10) или `pip install insightface-0.7.3-cp311-cp311-win_amd64.whl` (для 3.11) или `pip install insightface-0.7.3-cp312-cp312-win_amd64.whl` (for 3.12)
+   - (ComfyUI Portable) `python_embeded\python.exe -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl` (для 3.10) или `python_embeded\python.exe -m pip install insightface-0.7.3-cp311-cp311-win_amd64.whl` (для 3.11) или `python_embeded\python.exe -m pip install insightface-0.7.3-cp312-cp312-win_amd64.whl` (for 3.12)
+6. Готово!
+
+### **II. "AttributeError: 'NoneType' object has no attribute 'get'"**
+
+Эта ошибка появляется, если что-то не так с файлом модели `inswapper_128.onnx`
+
+Скачайте вручную по ссылке [отсюда](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx)
+и сохраните в директорию `ComfyUI\models\insightface`, заменив имеющийся файл
+
+### **III. "reactor.execute() got an unexpected keyword argument 'reference_image'"**
+
+Это означает, что поменялось обозначение входных точек (input points) всвязи с последним обновлением<br>
+Удалите из вашего рабочего пространства имеющийся ReActor Node и добавьте его снова
+
+### **IV. ControlNet Aux Node IMPORT failed - при использовании совместно с нодом ReActor**
+
+1. Закройте или остановите ComfyUI сервер, если он запущен
+2. Перейдите в корневую папку ComfyUI, откройте консоль CMD и выполните следующее:
+   - `python_embeded\python.exe -m pip uninstall -y opencv-python opencv-contrib-python opencv-python-headless`
+   - `python_embeded\python.exe -m pip install opencv-python==4.7.0.72`
+3. Готово!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/uploads/reactor-w-controlnet.png?raw=true" alt="reactor+controlnet" />
+
+### **V. "ModuleNotFoundError: No module named 'basicsr'" или "subprocess-exited-with-error" при установке пакета future-0.18.3**
+
+- Скачайте https://github.com/Gourieff/Assets/raw/main/comfyui-reactor-node/future-0.18.3-py3-none-any.whl<br>
+- Скопируйте файл в корневую папку ComfyUI и выполните в консоли:
+
+      python_embeded\python.exe -m pip install future-0.18.3-py3-none-any.whl
+
+- Затем:
+
+      python_embeded\python.exe -m pip install basicsr
+
+### **VI. "fatal: fetch-pack: invalid index-pack output" при исполнении команды `git clone`"**
+
+Попробуйте клонировать репозиторий с параметром `--depth=1` (только последний коммит):
+
+     git clone --depth=1 https://github.com/Gourieff/ComfyUI-ReActor
+
+Затем вытяните оставшееся (если требуется):
+
+     git fetch --unshallow
+
+<a name="updating">
+
+## Обновление
+
+Положите .bat или .sh скрипт из [данного репозитория](https://github.com/Gourieff/sd-webui-extensions-updater) в папку `ComfyUI\custom_nodes` и запустите, когда желаете обновить ComfyUI и Ноды
+
+<a name="disclaimer">
+
+## Ответственность
+
+Это программное обеспечение призвано стать продуктивным вкладом в быстрорастущую медиаиндустрию на основе генеративных сетей и искусственного интеллекта. Данное ПО поможет художникам в решении таких задач, как анимация собственного персонажа или использование персонажа в качестве модели для одежды и т.д.
+
+Разработчики этого программного обеспечения осведомлены о возможных неэтичных применениях и обязуются принять против этого превентивные меры. Мы продолжим развивать этот проект в позитивном направлении, придерживаясь закона и этики.
+
+Подразумевается, что пользователи этого программного обеспечения будут использовать его ответственно, соблюдая локальное законодательство. Если используется лицо реального человека, пользователь обязан получить согласие заинтересованного лица и четко указать, что это дипфейк при размещении контента в Интернете. **Разработчики и Со-авторы данного программного обеспечения не несут ответственности за действия конечных пользователей.**
+
+Используя данное расширение, вы соглашаетесь не создавать материалы, которые:
+- нарушают какие-либо действующие законы тех или иных государств или международных организаций;
+- причиняют какой-либо вред человеку или лицам;
+- пропагандируют любую информацию (как общедоступную, так и личную) или изображения (как общедоступные, так и личные), которые могут быть направлены на причинение вреда;
+- используются для распространения дезинформации;
+- нацелены на уязвимые группы людей.
+
+Данное программное обеспечение использует предварительно обученные модели `buffalo_l` и `inswapper_128.onnx`, представленные разработчиками [InsightFace](https://github.com/deepinsight/insightface/). Эти модели распространяются при следующих условиях:
+
+[Перевод из текста лицензии insighface](https://github.com/deepinsight/insightface/tree/master/python-package): Предварительно обученные модели InsightFace доступны только для некоммерческих исследовательских целей. Сюда входят как модели с автоматической загрузкой, так и модели, загруженные вручную.
+
+Пользователи данного программного обеспечения должны строго соблюдать данные условия использования. Разработчики и Со-авторы данного программного продукта не несут ответственности за неправильное использование предварительн�� обученных моделей InsightFace.
+
+Обратите внимание: если вы собираетесь использовать это программное обеспечение в каких-либо коммерческих целях, вам необходимо будет обучить свои собственные модели или найти модели, которые можно использовать в коммерческих целях.
+
+### Хэш файлов моделей
+
+#### Безопасные для использования модели имеют следующий хэш:
+
+inswapper_128.onnx
+```
+MD5:a3a155b90354160350efd66fed6b3d80
+SHA256:e4a3f08c753cb72d04e10aa0f7dbe3deebbf39567d4ead6dce08e98aa49e16af
+```
+
+1k3d68.onnx
+
+```
+MD5:6fb94fcdb0055e3638bf9158e6a108f4
+SHA256:df5c06b8a0c12e422b2ed8947b8869faa4105387f199c477af038aa01f9a45cc
+```
+
+2d106det.onnx
+
+```
+MD5:a3613ef9eb3662b4ef88eb90db1fcf26
+SHA256:f001b856447c413801ef5c42091ed0cd516fcd21f2d6b79635b1e733a7109dbf
+```
+
+det_10g.onnx
+
+```
+MD5:4c10eef5c9e168357a16fdd580fa8371
+SHA256:5838f7fe053675b1c7a08b633df49e7af5495cee0493c7dcf6697200b85b5b91
+```
+
+genderage.onnx
+
+```
+MD5:81c77ba87ab38163b0dec6b26f8e2af2
+SHA256:4fde69b1c810857b88c64a335084f1c3fe8f01246c9a191b48c7bb756d6652fb
+```
+
+w600k_r50.onnx
+
+```
+MD5:80248d427976241cbd1343889ed132b3
+SHA256:4c06341c33c2ca1f86781dab0e829f88ad5b64be9fba56e56bc9ebdefc619e43
+```
+
+**Пожалуйста, сравните хэш, если вы скачиваете данные модели из непроверенных источников**
+
+<a name="credits">
+
+## Благодарности и авторы компонентов
+
+<details>
+	<summary><a>Нажмите, чтобы посмотреть</a></summary>
+
+<br>
+
+|файл|источник|лицензия|
+|----|--------|--------|
+|[buffalo_l.zip](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/buffalo_l.zip) | [DeepInsight](https://github.com/deepinsight/insightface) | ![license](https://img.shields.io/badge/license-non_commercial-red) |
+| [codeformer-v0.1.0.pth](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/facerestore_models/codeformer-v0.1.0.pth) | [sczhou](https://github.com/sczhou/CodeFormer) | ![license](https://img.shields.io/badge/license-non_commercial-red) |
+| [GFPGANv1.3.pth](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/facerestore_models/GFPGANv1.3.pth) | [TencentARC](https://github.com/TencentARC/GFPGAN) | ![license](https://img.shields.io/badge/license-Apache_2.0-green.svg) |
+| [GFPGANv1.4.pth](https://huggingface.co/datasets/Gourieff/ReActor/blob/main/models/facerestore_models/GFPGANv1.4.pth) | [TencentARC](https://github.com/TencentARC/GFPGAN) | ![license](https://img.shields.io/badge/license-Apache_2.0-green.svg) |
+| [inswapper_128.onnx](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx) | [DeepInsight](https://github.com/deepinsight/insightface) | ![license](https://img.shields.io/badge/license-non_commercial-red) |
+| [inswapper_128_fp16.onnx](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128_fp16.onnx) | [Hillobar](https://github.com/Hillobar/Rope) | ![license](https://img.shields.io/badge/license-non_commercial-red) |
+
+[BasicSR](https://github.com/XPixelGroup/BasicSR) - [@XPixelGroup](https://github.com/XPixelGroup) <br>
+[facexlib](https://github.com/xinntao/facexlib) - [@xinntao](https://github.com/xinntao) <br>
+
+[@s0md3v](https://github.com/s0md3v), [@henryruhs](https://github.com/henryruhs) - оригинальное приложение Roop <br>
+[@ssitu](https://github.com/ssitu) - первая версия расширения с поддержкой ComfyUI [ComfyUI_roop](https://github.com/ssitu/ComfyUI_roop)
+
+</details>
+
+<a name="note">
+
+### Обратите внимание!
+
+**Если у вас возникли какие-либо ошибки при очередном использовании Нода ReActor - не торопитесь открывать Issue, для начала попробуйте удалить текущий Нод из вашего рабочего пространства и добавить его снова**
+
+**ReActor Node периодически получает обновления, появляются новые функции, из-за чего имеющийся Нод может работать с ошибками или не работать вовсе**

custom_nodes/ComfyUI-ReActor/__init__.py

@@ -0,0 +1,39 @@
+import sys
+import os
+
+repo_dir = os.path.dirname(os.path.realpath(__file__))
+sys.path.insert(0, repo_dir)
+original_modules = sys.modules.copy()
+
+# Place aside existing modules if using a1111 web ui
+modules_used = [
+    "modules",
+    "modules.images",
+    "modules.processing",
+    "modules.scripts_postprocessing",
+    "modules.scripts",
+    "modules.shared",
+]
+original_webui_modules = {}
+for module in modules_used:
+    if module in sys.modules:
+        original_webui_modules[module] = sys.modules.pop(module)
+
+# Proceed with node setup
+from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+
+__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
+
+# Clean up imports
+# Remove repo directory from path
+sys.path.remove(repo_dir)
+# Remove any new modules
+modules_to_remove = []
+for module in sys.modules:
+    if module not in original_modules and not module.startswith("google.protobuf") and not module.startswith("onnx") and not module.startswith("cv2"):
+        modules_to_remove.append(module)
+for module in modules_to_remove:
+    del sys.modules[module]
+
+# Restore original modules
+sys.modules.update(original_webui_modules)

custom_nodes/ComfyUI-ReActor/install.bat

@@ -0,0 +1,37 @@
+@echo off
+setlocal enabledelayedexpansion
+
+:: Try to use embedded python first
+if exist ..\..\..\python_embeded\python.exe (
+    :: Use the embedded python
+    set PYTHON=..\..\..\python_embeded\python.exe
+) else (
+    :: Embedded python not found, check for python in the PATH
+    for /f "tokens=* USEBACKQ" %%F in (`python --version 2^>^&1`) do (
+        set PYTHON_VERSION=%%F
+    )
+    if errorlevel 1 (
+        echo I couldn't find an embedded version of Python, nor one in the Windows PATH. Please install manually.
+        pause
+        exit /b 1
+    ) else (
+        :: Use python from the PATH (if it's the right version and the user agrees)
+        echo I couldn't find an embedded version of Python, but I did find !PYTHON_VERSION! in your Windows PATH.
+        echo Would you like to proceed with the install using that version? (Y/N^)
+        set /p USE_PYTHON=
+        if /i "!USE_PYTHON!"=="Y" (
+            set PYTHON=python
+        ) else (
+            echo Okay. Please install manually.
+            pause
+            exit /b 1
+        )
+    )
+)
+
+:: Install the package
+echo Installing...
+%PYTHON% install.py
+echo Done^!
+
+@pause

custom_nodes/ComfyUI-ReActor/install.py

@@ -0,0 +1,104 @@
+import warnings
+warnings.filterwarnings("ignore", category=DeprecationWarning)
+
+import subprocess
+import os, sys
+try:
+    from pkg_resources import get_distribution as distributions
+except:
+    from importlib_metadata import distributions
+from tqdm import tqdm
+import urllib.request
+from packaging import version as pv
+try:
+    from folder_paths import models_dir
+except:
+    from pathlib import Path
+    models_dir = os.path.join(Path(__file__).parents[2], "models")
+
+sys.path.append(os.path.dirname(os.path.realpath(__file__)))
+
+req_file = os.path.join(os.path.dirname(os.path.realpath(__file__)), "requirements.txt")
+
+model_url = "https://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/inswapper_128.onnx"
+model_name = os.path.basename(model_url)
+models_dir_path = os.path.join(models_dir, "insightface")
+model_path = os.path.join(models_dir_path, model_name)
+
+def run_pip(*args):
+    subprocess.run([sys.executable, "-m", "pip", "install", "--no-warn-script-location", *args])
+
+def is_installed (
+        package: str, version: str = None, strict: bool = True
+):
+    has_package = None
+    try:
+        has_package = distributions(package)
+        if has_package is not None:
+            if version is not None:
+                installed_version = has_package.version
+                if (installed_version != version and strict == True) or (pv.parse(installed_version) < pv.parse(version) and strict == False):
+                    return False
+                else:
+                    return True
+            else:
+                return True
+        else:
+            return False
+    except Exception as e:
+        print(f"Status: {e}")
+        return False
+    
+def download(url, path, name):
+    request = urllib.request.urlopen(url)
+    total = int(request.headers.get('Content-Length', 0))
+    with tqdm(total=total, desc=f'[ReActor] Downloading {name} to {path}', unit='B', unit_scale=True, unit_divisor=1024) as progress:
+        urllib.request.urlretrieve(url, path, reporthook=lambda count, block_size, total_size: progress.update(block_size))
+
+if not os.path.exists(models_dir_path):
+    os.makedirs(models_dir_path)
+
+if not os.path.exists(model_path):
+    download(model_url, model_path, model_name)
+
+with open(req_file) as file:
+    try:
+        ort = "onnxruntime-gpu"
+        import torch
+        cuda_version = None
+        if torch.cuda.is_available():
+            cuda_version = torch.version.cuda
+            print(f"CUDA {cuda_version}")
+        elif torch.backends.mps.is_available() or hasattr(torch,'dml') or hasattr(torch,'privateuseone'):
+            ort = "onnxruntime"
+        if cuda_version is not None and float(cuda_version)>=12 and torch.torch_version.__version__ <= "2.2.0": # CU12.x and torch<=2.2.0
+            print(f"Torch: {torch.torch_version.__version__}")
+            if not is_installed(ort,"1.17.0",False):
+                run_pip(ort,"--extra-index-url", "https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/")
+        elif cuda_version is not None and float(cuda_version)>=12 and torch.torch_version.__version__ >= "2.4.0" : # CU12.x and latest torch
+            print(f"Torch: {torch.torch_version.__version__}")
+            if not is_installed(ort,"1.20.1",False): # latest ort-gpu
+                run_pip(ort,"-U")
+        elif not is_installed(ort,"1.16.1",False):
+            run_pip(ort, "-U")
+    except Exception as e:
+        print(e)
+        print(f"Warning: Failed to install {ort}, ReActor will not work.")
+        raise e
+    strict = True
+    for package in file:
+        package_version = None
+        try:
+            package = package.strip()
+            if "==" in package:
+                package_version = package.split('==')[1]
+            elif ">=" in package:
+                package_version = package.split('>=')[1]
+                strict = False
+            if not is_installed(package,package_version,strict):
+                run_pip(package)
+        except Exception as e:
+            print(e)
+            print(f"Warning: Failed to install {package}, ReActor will not work.")
+            raise e
+print("Ok")

custom_nodes/ComfyUI-ReActor/modules/processing.py

@@ -0,0 +1,13 @@
+class StableDiffusionProcessing:
+
+    def __init__(self, init_imgs):
+        self.init_images = init_imgs
+        self.width = init_imgs[0].width
+        self.height = init_imgs[0].height
+        self.extra_generation_params = {}
+
+
+class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
+
+    def __init__(self, init_img):
+        super().__init__(init_img)

custom_nodes/ComfyUI-ReActor/modules/scripts.py

@@ -0,0 +1,13 @@
+import os
+
+
+class Script:
+    pass
+
+
+def basedir():
+    return os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+
+
+class PostprocessImageArgs:
+    pass

custom_nodes/ComfyUI-ReActor/modules/shared.py

@@ -0,0 +1,19 @@
+class Options:
+    img2img_background_color = "#ffffff"  # Set to white for now
+
+
+class State:
+    interrupted = False
+
+    def begin(self):
+        pass
+
+    def end(self):
+        pass
+
+
+opts = Options()
+state = State()
+cmd_opts = None
+sd_upscalers = []
+face_restorers = []

custom_nodes/ComfyUI-ReActor/nodes.py

@@ -0,0 +1,1275 @@
+import os, glob, sys
+import logging
+
+import torch
+import torch.nn.functional as torchfn
+from torchvision.transforms.functional import normalize
+from torchvision.ops import masks_to_boxes
+
+import numpy as np
+import cv2
+import math
+from typing import List
+from PIL import Image
+from scipy import stats
+from insightface.app.common import Face
+from segment_anything import sam_model_registry
+
+from modules.processing import StableDiffusionProcessingImg2Img
+from modules.shared import state
+# from comfy_extras.chainner_models import model_loading
+import comfy.model_management as model_management
+import comfy.utils
+import folder_paths
+
+import scripts.reactor_version
+from r_chainner import model_loading
+from scripts.reactor_faceswap import (
+    FaceSwapScript,
+    get_models,
+    get_current_faces_model,
+    analyze_faces,
+    half_det_size,
+    providers
+)
+from scripts.reactor_swapper import (
+    unload_all_models,
+)
+from scripts.reactor_logger import logger
+from reactor_utils import (
+    batch_tensor_to_pil,
+    batched_pil_to_tensor,
+    tensor_to_pil,
+    img2tensor,
+    tensor2img,
+    save_face_model,
+    load_face_model,
+    download,
+    set_ort_session,
+    prepare_cropped_face,
+    normalize_cropped_face,
+    add_folder_path_and_extensions,
+    rgba2rgb_tensor
+)
+from reactor_patcher import apply_patch
+from r_facelib.utils.face_restoration_helper import FaceRestoreHelper
+from r_basicsr.utils.registry import ARCH_REGISTRY
+import scripts.r_archs.codeformer_arch
+import scripts.r_masking.subcore as subcore
+import scripts.r_masking.core as core
+import scripts.r_masking.segs as masking_segs
+
+import scripts.reactor_sfw as sfw
+
+
+models_dir = folder_paths.models_dir
+REACTOR_MODELS_PATH = os.path.join(models_dir, "reactor")
+FACE_MODELS_PATH = os.path.join(REACTOR_MODELS_PATH, "faces")
+NSFWDET_MODEL_PATH = os.path.join(models_dir, "nsfw_detector","vit-base-nsfw-detector")
+
+if not os.path.exists(REACTOR_MODELS_PATH):
+    os.makedirs(REACTOR_MODELS_PATH)
+    if not os.path.exists(FACE_MODELS_PATH):
+        os.makedirs(FACE_MODELS_PATH)
+
+if not os.path.exists(NSFWDET_MODEL_PATH):
+    os.makedirs(NSFWDET_MODEL_PATH)
+    nd_urls = [
+        "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/config.json",
+        "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/confusion_matrix.png",
+        "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/model.safetensors",
+        "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/preprocessor_config.json",
+    ]
+    for model_url in nd_urls:
+        model_name = os.path.basename(model_url)
+        model_path = os.path.join(NSFWDET_MODEL_PATH, model_name)
+        download(model_url, model_path, model_name)
+
+dir_facerestore_models = os.path.join(models_dir, "facerestore_models")
+os.makedirs(dir_facerestore_models, exist_ok=True)
+folder_paths.folder_names_and_paths["facerestore_models"] = ([dir_facerestore_models], folder_paths.supported_pt_extensions)
+
+BLENDED_FACE_MODEL = None
+FACE_SIZE: int = 512
+FACE_HELPER = None
+
+if "ultralytics" not in folder_paths.folder_names_and_paths:
+    add_folder_path_and_extensions("ultralytics_bbox", [os.path.join(models_dir, "ultralytics", "bbox")], folder_paths.supported_pt_extensions)
+    add_folder_path_and_extensions("ultralytics_segm", [os.path.join(models_dir, "ultralytics", "segm")], folder_paths.supported_pt_extensions)
+    add_folder_path_and_extensions("ultralytics", [os.path.join(models_dir, "ultralytics")], folder_paths.supported_pt_extensions)
+if "sams" not in folder_paths.folder_names_and_paths:
+    add_folder_path_and_extensions("sams", [os.path.join(models_dir, "sams")], folder_paths.supported_pt_extensions)
+
+def get_facemodels():
+    models_path = os.path.join(FACE_MODELS_PATH, "*")
+    models = glob.glob(models_path)
+    models = [x for x in models if x.endswith(".safetensors")]
+    return models
+
+def get_restorers():
+    models_path = os.path.join(models_dir, "facerestore_models/*")
+    models = glob.glob(models_path)
+    models = [x for x in models if (x.endswith(".pth") or x.endswith(".onnx"))]
+    if len(models) == 0:
+        fr_urls = [
+            "https://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/facerestore_models/GFPGANv1.3.pth",
+            "https://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/facerestore_models/GFPGANv1.4.pth",
+            "https://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/facerestore_models/codeformer-v0.1.0.pth",
+            "https://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/facerestore_models/GPEN-BFR-512.onnx",
+        ]
+        for model_url in fr_urls:
+            model_name = os.path.basename(model_url)
+            model_path = os.path.join(dir_facerestore_models, model_name)
+            download(model_url, model_path, model_name)
+        models = glob.glob(models_path)
+        models = [x for x in models if (x.endswith(".pth") or x.endswith(".onnx"))]
+    return models
+
+def get_model_names(get_models):
+    models = get_models()
+    names = []
+    for x in models:
+        names.append(os.path.basename(x))
+    names.sort(key=str.lower)
+    names.insert(0, "none")
+    return names
+
+def model_names():
+    models = get_models()
+    return {os.path.basename(x): x for x in models}
+
+
+class reactor:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "enabled": ("BOOLEAN", {"default": True, "label_off": "OFF", "label_on": "ON"}),
+                "input_image": ("IMAGE",),
+                "swap_model": (list(model_names().keys()),),
+                "facedetection": (["retinaface_resnet50", "retinaface_mobile0.25", "YOLOv5l", "YOLOv5n"],),
+                "face_restore_model": (get_model_names(get_restorers),),
+                "face_restore_visibility": ("FLOAT", {"default": 1, "min": 0.1, "max": 1, "step": 0.05}),
+                "codeformer_weight": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1, "step": 0.05}),
+                "detect_gender_input": (["no","female","male"], {"default": "no"}),
+                "detect_gender_source": (["no","female","male"], {"default": "no"}),
+                "input_faces_index": ("STRING", {"default": "0"}),
+                "source_faces_index": ("STRING", {"default": "0"}),
+                "console_log_level": ([0, 1, 2], {"default": 1}),
+            },
+            "optional": {
+                "source_image": ("IMAGE",),
+                "face_model": ("FACE_MODEL",),
+                "face_boost": ("FACE_BOOST",),
+            },
+            "hidden": {"faces_order": "FACES_ORDER"},
+        }
+
+    RETURN_TYPES = ("IMAGE","FACE_MODEL")
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    def __init__(self):
+        # self.face_helper = None
+        self.faces_order = ["large-small", "large-small"]
+        # self.face_size = FACE_SIZE
+        self.face_boost_enabled = False
+        self.restore = True
+        self.boost_model = None
+        self.interpolation = "Bicubic"
+        self.boost_model_visibility = 1
+        self.boost_cf_weight = 0.5
+
+    def restore_face(
+            self,
+            input_image,
+            face_restore_model,
+            face_restore_visibility,
+            codeformer_weight,
+            facedetection,
+        ):
+
+        result = input_image
+
+        if face_restore_model != "none" and not model_management.processing_interrupted():
+
+            global FACE_SIZE, FACE_HELPER
+
+            self.face_helper = FACE_HELPER
+            
+            faceSize = 512
+            if "1024" in face_restore_model.lower():
+                faceSize = 1024
+            elif "2048" in face_restore_model.lower():
+                faceSize = 2048
+
+            logger.status(f"Restoring with {face_restore_model} | Face Size is set to {faceSize}")
+
+            model_path = folder_paths.get_full_path("facerestore_models", face_restore_model)
+
+            device = model_management.get_torch_device()
+
+            if "codeformer" in face_restore_model.lower():
+
+                codeformer_net = ARCH_REGISTRY.get("CodeFormer")(
+                    dim_embd=512,
+                    codebook_size=1024,
+                    n_head=8,
+                    n_layers=9,
+                    connect_list=["32", "64", "128", "256"],
+                ).to(device)
+                checkpoint = torch.load(model_path)["params_ema"]
+                codeformer_net.load_state_dict(checkpoint)
+                facerestore_model = codeformer_net.eval()
+
+            elif ".onnx" in face_restore_model:
+
+                ort_session = set_ort_session(model_path, providers=providers)
+                ort_session_inputs = {}
+                facerestore_model = ort_session
+
+            else:
+
+                sd = comfy.utils.load_torch_file(model_path, safe_load=True)
+                facerestore_model = model_loading.load_state_dict(sd).eval()
+                facerestore_model.to(device)
+            
+            if faceSize != FACE_SIZE or self.face_helper is None:
+                self.face_helper = FaceRestoreHelper(1, face_size=faceSize, crop_ratio=(1, 1), det_model=facedetection, save_ext='png', use_parse=True, device=device)
+                FACE_SIZE = faceSize
+                FACE_HELPER = self.face_helper
+
+            image_np = 255. * result.numpy()
+
+            total_images = image_np.shape[0]
+
+            out_images = []
+
+            for i in range(total_images):
+
+                if total_images > 1:
+                    logger.status(f"Restoring {i+1}")
+
+                cur_image_np = image_np[i,:, :, ::-1]
+
+                original_resolution = cur_image_np.shape[0:2]
+
+                if facerestore_model is None or self.face_helper is None:
+                    return result
+
+                self.face_helper.clean_all()
+                self.face_helper.read_image(cur_image_np)
+                self.face_helper.get_face_landmarks_5(only_center_face=False, resize=640, eye_dist_threshold=5)
+                self.face_helper.align_warp_face()
+
+                restored_face = None
+
+                for idx, cropped_face in enumerate(self.face_helper.cropped_faces):
+
+                    # if ".pth" in face_restore_model:
+                    cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True)
+                    normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)
+                    cropped_face_t = cropped_face_t.unsqueeze(0).to(device)
+
+                    try:
+
+                        with torch.no_grad():
+
+                            if ".onnx" in face_restore_model: # ONNX models
+
+                                for ort_session_input in ort_session.get_inputs():
+                                    if ort_session_input.name == "input":
+                                        cropped_face_prep = prepare_cropped_face(cropped_face)
+                                        ort_session_inputs[ort_session_input.name] = cropped_face_prep
+                                    if ort_session_input.name == "weight":
+                                        weight = np.array([ 1 ], dtype = np.double)
+                                        ort_session_inputs[ort_session_input.name] = weight
+
+                                output = ort_session.run(None, ort_session_inputs)[0][0]
+                                restored_face = normalize_cropped_face(output)
+
+                            else: # PTH models
+
+                                output = facerestore_model(cropped_face_t, w=codeformer_weight)[0] if "codeformer" in face_restore_model.lower() else facerestore_model(cropped_face_t)[0]
+                                restored_face = tensor2img(output, rgb2bgr=True, min_max=(-1, 1))
+
+                        del output
+                        torch.cuda.empty_cache()
+
+                    except Exception as error:
+
+                        print(f"\tFailed inference: {error}", file=sys.stderr)
+                        restored_face = tensor2img(cropped_face_t, rgb2bgr=True, min_max=(-1, 1))
+
+                    if face_restore_visibility < 1:
+                        restored_face = cropped_face * (1 - face_restore_visibility) + restored_face * face_restore_visibility
+
+                    restored_face = restored_face.astype("uint8")
+                    self.face_helper.add_restored_face(restored_face)
+
+                self.face_helper.get_inverse_affine(None)
+
+                restored_img = self.face_helper.paste_faces_to_input_image()
+                restored_img = restored_img[:, :, ::-1]
+
+                if original_resolution != restored_img.shape[0:2]:
+                    restored_img = cv2.resize(restored_img, (0, 0), fx=original_resolution[1]/restored_img.shape[1], fy=original_resolution[0]/restored_img.shape[0], interpolation=cv2.INTER_AREA)
+
+                self.face_helper.clean_all()
+
+                # out_images[i] = restored_img
+                out_images.append(restored_img)
+
+                if state.interrupted or model_management.processing_interrupted():
+                    logger.status("Interrupted by User")
+                    return input_image
+
+            restored_img_np = np.array(out_images).astype(np.float32) / 255.0
+            restored_img_tensor = torch.from_numpy(restored_img_np)
+
+            result = restored_img_tensor
+
+        return result
+    
+    def execute(self, enabled, input_image, swap_model, detect_gender_source, detect_gender_input, source_faces_index, input_faces_index, console_log_level, face_restore_model,face_restore_visibility, codeformer_weight, facedetection, source_image=None, face_model=None, faces_order=None, face_boost=None):
+
+        if face_boost is not None:
+            self.face_boost_enabled = face_boost["enabled"]
+            self.boost_model = face_boost["boost_model"]
+            self.interpolation = face_boost["interpolation"]
+            self.boost_model_visibility = face_boost["visibility"]
+            self.boost_cf_weight = face_boost["codeformer_weight"]
+            self.restore = face_boost["restore_with_main_after"]
+        else:
+            self.face_boost_enabled = False
+
+        if faces_order is None:
+            faces_order = self.faces_order
+
+        apply_patch(console_log_level)
+
+        if not enabled:
+            return (input_image,face_model)
+        elif source_image is None and face_model is None:
+            logger.error("Please provide 'source_image' or `face_model`")
+            return (input_image,face_model)
+
+        if face_model == "none":
+            face_model = None
+        
+        script = FaceSwapScript()
+        pil_images = batch_tensor_to_pil(input_image)
+
+        # NSFW checker
+        logger.status("Checking for any unsafe content")
+        pil_images_sfw = []
+        tmp_img = "reactor_tmp.png"
+        for img in pil_images:
+            if state.interrupted or model_management.processing_interrupted():
+                logger.status("Interrupted by User")
+                break
+            img.save(tmp_img)
+            if not sfw.nsfw_image(tmp_img, NSFWDET_MODEL_PATH):
+                pil_images_sfw.append(img)
+        if os.path.exists(tmp_img):
+            os.remove(tmp_img)
+        pil_images = pil_images_sfw
+        # # #
+
+        if len(pil_images) > 0:
+
+            if source_image is not None:
+                source = tensor_to_pil(source_image)
+            else:
+                source = None
+            p = StableDiffusionProcessingImg2Img(pil_images)
+            script.process(
+                p=p,
+                img=source,
+                enable=True,
+                source_faces_index=source_faces_index,
+                faces_index=input_faces_index,
+                model=swap_model,
+                swap_in_source=True,
+                swap_in_generated=True,
+                gender_source=detect_gender_source,
+                gender_target=detect_gender_input,
+                face_model=face_model,
+                faces_order=faces_order,
+                # face boost:
+                face_boost_enabled=self.face_boost_enabled,
+                face_restore_model=self.boost_model,
+                face_restore_visibility=self.boost_model_visibility,
+                codeformer_weight=self.boost_cf_weight,
+                interpolation=self.interpolation,
+            )
+            result = batched_pil_to_tensor(p.init_images)
+
+            if face_model is None:
+                current_face_model = get_current_faces_model()
+                face_model_to_provide = current_face_model[0] if (current_face_model is not None and len(current_face_model) > 0) else face_model
+            else:
+                face_model_to_provide = face_model
+
+            if self.restore or not self.face_boost_enabled:
+                result = reactor.restore_face(self,result,face_restore_model,face_restore_visibility,codeformer_weight,facedetection)
+        
+        else:
+            image_black = Image.new("RGB", (512, 512))
+            result = batched_pil_to_tensor([image_black])
+            face_model_to_provide = None
+
+        return (result,face_model_to_provide)
+
+
+class ReActorPlusOpt:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "enabled": ("BOOLEAN", {"default": True, "label_off": "OFF", "label_on": "ON"}),
+                "input_image": ("IMAGE",),               
+                "swap_model": (list(model_names().keys()),),
+                "facedetection": (["retinaface_resnet50", "retinaface_mobile0.25", "YOLOv5l", "YOLOv5n"],),
+                "face_restore_model": (get_model_names(get_restorers),),
+                "face_restore_visibility": ("FLOAT", {"default": 1, "min": 0.1, "max": 1, "step": 0.05}),
+                "codeformer_weight": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1, "step": 0.05}),
+            },
+            "optional": {
+                "source_image": ("IMAGE",),
+                "face_model": ("FACE_MODEL",),
+                "options": ("OPTIONS",),
+                "face_boost": ("FACE_BOOST",),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE","FACE_MODEL")
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    def __init__(self):
+        # self.face_helper = None
+        self.faces_order = ["large-small", "large-small"]
+        self.detect_gender_input = "no"
+        self.detect_gender_source = "no"
+        self.input_faces_index = "0"
+        self.source_faces_index = "0"
+        self.console_log_level = 1
+        # self.face_size = 512
+        self.face_boost_enabled = False
+        self.restore = True
+        self.boost_model = None
+        self.interpolation = "Bicubic"
+        self.boost_model_visibility = 1
+        self.boost_cf_weight = 0.5
+    
+    def execute(self, enabled, input_image, swap_model, facedetection, face_restore_model, face_restore_visibility, codeformer_weight, source_image=None, face_model=None, options=None, face_boost=None):
+
+        if options is not None:
+            self.faces_order = [options["input_faces_order"], options["source_faces_order"]]
+            self.console_log_level = options["console_log_level"]
+            self.detect_gender_input = options["detect_gender_input"]
+            self.detect_gender_source = options["detect_gender_source"]
+            self.input_faces_index = options["input_faces_index"]
+            self.source_faces_index = options["source_faces_index"]
+        
+        if face_boost is not None:
+            self.face_boost_enabled = face_boost["enabled"]
+            self.restore = face_boost["restore_with_main_after"]
+        else:
+            self.face_boost_enabled = False
+        
+        result = reactor.execute(
+            self,enabled,input_image,swap_model,self.detect_gender_source,self.detect_gender_input,self.source_faces_index,self.input_faces_index,self.console_log_level,face_restore_model,face_restore_visibility,codeformer_weight,facedetection,source_image,face_model,self.faces_order, face_boost=face_boost
+        )
+
+        return result
+
+
+class LoadFaceModel:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "face_model": (get_model_names(get_facemodels),),
+            }
+        }
+    
+    RETURN_TYPES = ("FACE_MODEL",)
+    FUNCTION = "load_model"
+    CATEGORY = "🌌 ReActor"
+
+    def load_model(self, face_model):
+        self.face_model = face_model
+        self.face_models_path = FACE_MODELS_PATH
+        if self.face_model != "none":
+            face_model_path = os.path.join(self.face_models_path, self.face_model)
+            out = load_face_model(face_model_path)
+        else:
+            out = None
+        return (out, )
+
+
+class BuildFaceModel:
+    def __init__(self):
+        self.output_dir = FACE_MODELS_PATH
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "save_mode": ("BOOLEAN", {"default": True, "label_off": "OFF", "label_on": "ON"}),
+                "send_only": ("BOOLEAN", {"default": False, "label_off": "NO", "label_on": "YES"}),
+                "face_model_name": ("STRING", {"default": "default"}),
+                "compute_method": (["Mean", "Median", "Mode"], {"default": "Mean"}),
+            },
+            "optional": {
+                "images": ("IMAGE",),
+                "face_models": ("FACE_MODEL",),
+            }
+        }
+
+    RETURN_TYPES = ("FACE_MODEL",)
+    FUNCTION = "blend_faces"
+
+    OUTPUT_NODE = True
+
+    CATEGORY = "🌌 ReActor"
+
+    def build_face_model(self, image: Image.Image, det_size=(640, 640)):
+        logging.StreamHandler.terminator = "\n"
+        if image is None:
+            error_msg = "Please load an Image"
+            logger.error(error_msg)
+            return error_msg
+        image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+        face_model = analyze_faces(image, det_size)
+
+        if len(face_model) == 0:
+            print("")
+            det_size_half = half_det_size(det_size)
+            face_model = analyze_faces(image, det_size_half)
+            if face_model is not None and len(face_model) > 0:
+                print("...........................................................", end=" ")
+        
+        if face_model is not None and len(face_model) > 0:
+            return face_model[0]
+        else:
+            no_face_msg = "No face found, please try another image"
+            # logger.error(no_face_msg)
+            return no_face_msg
+    
+    def blend_faces(self, save_mode, send_only, face_model_name, compute_method, images=None, face_models=None):
+        global BLENDED_FACE_MODEL
+        blended_face: Face = BLENDED_FACE_MODEL
+
+        if send_only and blended_face is None:
+            send_only = False
+
+        if (images is not None or face_models is not None) and not send_only:
+
+            faces = []
+            embeddings = []
+
+            apply_patch(1)
+
+            if images is not None:
+                images_list: List[Image.Image] = batch_tensor_to_pil(images)
+
+                n = len(images_list)
+
+                for i,image in enumerate(images_list):
+                    logging.StreamHandler.terminator = " "
+                    logger.status(f"Building Face Model {i+1} of {n}...")
+                    face = self.build_face_model(image)
+                    if isinstance(face, str):
+                        logger.error(f"No faces found in image {i+1}, skipping")
+                        continue
+                    else:
+                        print(f"{int(((i+1)/n)*100)}%")
+                    faces.append(face)
+                    embeddings.append(face.embedding)
+            
+            elif face_models is not None:
+
+                n = len(face_models)
+
+                for i,face_model in enumerate(face_models):
+                    logging.StreamHandler.terminator = " "
+                    logger.status(f"Extracting Face Model {i+1} of {n}...")
+                    face = face_model
+                    if isinstance(face, str):
+                        logger.error(f"No faces found for face_model {i+1}, skipping")
+                        continue
+                    else:
+                        print(f"{int(((i+1)/n)*100)}%")
+                    faces.append(face)
+                    embeddings.append(face.embedding)
+
+            logging.StreamHandler.terminator = "\n"
+            if len(faces) > 0:
+                # compute_method_name = "Mean" if compute_method == 0 else "Median" if compute_method == 1 else "Mode"
+                logger.status(f"Blending with Compute Method '{compute_method}'...")
+                blended_embedding = np.mean(embeddings, axis=0) if compute_method == "Mean" else np.median(embeddings, axis=0) if compute_method == "Median" else stats.mode(embeddings, axis=0)[0].astype(np.float32)
+                blended_face = Face(
+                    bbox=faces[0].bbox,
+                    kps=faces[0].kps,
+                    det_score=faces[0].det_score,
+                    landmark_3d_68=faces[0].landmark_3d_68,
+                    pose=faces[0].pose,
+                    landmark_2d_106=faces[0].landmark_2d_106,
+                    embedding=blended_embedding,
+                    gender=faces[0].gender,
+                    age=faces[0].age
+                )
+                if blended_face is not None:
+                    BLENDED_FACE_MODEL = blended_face
+                    if save_mode:
+                        face_model_path = os.path.join(FACE_MODELS_PATH, face_model_name + ".safetensors")
+                        save_face_model(blended_face,face_model_path)
+                        # done_msg = f"Face model has been saved to '{face_model_path}'"
+                        # logger.status(done_msg)
+                    logger.status("--Done!--")
+                    # return (blended_face,)
+                else:
+                    no_face_msg = "Something went wrong, please try another set of images"
+                    logger.error(no_face_msg)
+                    # return (blended_face,)
+            # logger.status("--Done!--")
+        if images is None and face_models is None:
+            logger.error("Please provide `images` or `face_models`")
+        return (blended_face,)
+
+
+class SaveFaceModel:
+    def __init__(self):
+        self.output_dir = FACE_MODELS_PATH
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "save_mode": ("BOOLEAN", {"default": True, "label_off": "OFF", "label_on": "ON"}),
+                "face_model_name": ("STRING", {"default": "default"}),
+                "select_face_index": ("INT", {"default": 0, "min": 0}),
+            },
+            "optional": {
+                "image": ("IMAGE",),
+                "face_model": ("FACE_MODEL",),
+            }
+        }
+
+    RETURN_TYPES = ()
+    FUNCTION = "save_model"
+
+    OUTPUT_NODE = True
+
+    CATEGORY = "🌌 ReActor"
+
+    def save_model(self, save_mode, face_model_name, select_face_index, image=None, face_model=None, det_size=(640, 640)):
+        if save_mode and image is not None:
+            source = tensor_to_pil(image)
+            source = cv2.cvtColor(np.array(source), cv2.COLOR_RGB2BGR)
+            apply_patch(1)
+            logger.status("Building Face Model...")
+            face_model_raw = analyze_faces(source, det_size)
+            if len(face_model_raw) == 0:
+                det_size_half = half_det_size(det_size)
+                face_model_raw = analyze_faces(source, det_size_half)
+            try:
+                face_model = face_model_raw[select_face_index]
+            except:
+                logger.error("No face(s) found")
+                return face_model_name
+            logger.status("--Done!--")
+        if save_mode and (face_model != "none" or face_model is not None):
+            face_model_path = os.path.join(self.output_dir, face_model_name + ".safetensors")
+            save_face_model(face_model,face_model_path)
+        if image is None and face_model is None:
+            logger.error("Please provide `face_model` or `image`")
+        return face_model_name
+
+
+class RestoreFace:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),               
+                "facedetection": (["retinaface_resnet50", "retinaface_mobile0.25", "YOLOv5l", "YOLOv5n"],),
+                "model": (get_model_names(get_restorers),),
+                "visibility": ("FLOAT", {"default": 1, "min": 0.0, "max": 1, "step": 0.05}),
+                "codeformer_weight": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1, "step": 0.05}),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    # def __init__(self):
+    #     self.face_helper = None
+    #     self.face_size = 512
+
+    def execute(self, image, model, visibility, codeformer_weight, facedetection):
+        result = reactor.restore_face(self,image,model,visibility,codeformer_weight,facedetection)
+        return (result,)
+
+
+class MaskHelper:
+    def __init__(self):
+        # self.threshold = 0.5
+        # self.dilation = 10
+        # self.crop_factor = 3.0
+        # self.drop_size = 1
+        self.labels = "all"
+        self.detailer_hook = None
+        self.device_mode = "AUTO"
+        self.detection_hint = "center-1"
+        # self.sam_dilation = 0
+        # self.sam_threshold = 0.93
+        # self.bbox_expansion = 0
+        # self.mask_hint_threshold = 0.7
+        # self.mask_hint_use_negative = "False"
+        # self.force_resize_width = 0
+        # self.force_resize_height = 0
+        # self.resize_behavior = "source_size"
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        bboxs = ["bbox/"+x for x in folder_paths.get_filename_list("ultralytics_bbox")]
+        segms = ["segm/"+x for x in folder_paths.get_filename_list("ultralytics_segm")]
+        sam_models = [x for x in folder_paths.get_filename_list("sams") if 'hq' not in x]
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "swapped_image": ("IMAGE",),
+                "bbox_model_name": (bboxs + segms, ),
+                "bbox_threshold": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
+                "bbox_dilation": ("INT", {"default": 10, "min": -512, "max": 512, "step": 1}),
+                "bbox_crop_factor": ("FLOAT", {"default": 3.0, "min": 1.0, "max": 100, "step": 0.1}),
+                "bbox_drop_size": ("INT", {"min": 1, "max": 8192, "step": 1, "default": 10}),
+                "sam_model_name": (sam_models, ),
+                "sam_dilation": ("INT", {"default": 0, "min": -512, "max": 512, "step": 1}),
+                "sam_threshold": ("FLOAT", {"default": 0.93, "min": 0.0, "max": 1.0, "step": 0.01}),
+                "bbox_expansion": ("INT", {"default": 0, "min": 0, "max": 1000, "step": 1}),
+                "mask_hint_threshold": ("FLOAT", {"default": 0.7, "min": 0.0, "max": 1.0, "step": 0.01}),
+                "mask_hint_use_negative": (["False", "Small", "Outter"], ),
+                "morphology_operation": (["dilate", "erode", "open", "close"],),
+                "morphology_distance": ("INT", {"default": 0, "min": 0, "max": 128, "step": 1}),
+                "blur_radius": ("INT", {"default": 9, "min": 0, "max": 48, "step": 1}),
+                "sigma_factor": ("FLOAT", {"default": 1.0, "min": 0.01, "max": 3., "step": 0.01}),
+            },
+            "optional": {
+                "mask_optional": ("MASK",),
+            }
+        }
+    
+    RETURN_TYPES = ("IMAGE","MASK","IMAGE","IMAGE")
+    RETURN_NAMES = ("IMAGE","MASK","MASK_PREVIEW","SWAPPED_FACE")
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    def execute(self, image, swapped_image, bbox_model_name, bbox_threshold, bbox_dilation, bbox_crop_factor, bbox_drop_size, sam_model_name, sam_dilation, sam_threshold, bbox_expansion, mask_hint_threshold, mask_hint_use_negative, morphology_operation, morphology_distance, blur_radius, sigma_factor, mask_optional=None):
+
+        # images = [image[i:i + 1, ...] for i in range(image.shape[0])]
+
+        images = image
+
+        if mask_optional is None:
+
+            bbox_model_path = folder_paths.get_full_path("ultralytics", bbox_model_name)
+            bbox_model = subcore.load_yolo(bbox_model_path)
+            bbox_detector = subcore.UltraBBoxDetector(bbox_model)
+
+            segs = bbox_detector.detect(images, bbox_threshold, bbox_dilation, bbox_crop_factor, bbox_drop_size, self.detailer_hook)
+
+            if isinstance(self.labels, list):
+                self.labels = str(self.labels[0])
+
+            if self.labels is not None and self.labels != '':
+                self.labels = self.labels.split(',')
+                if len(self.labels) > 0:
+                    segs, _ = masking_segs.filter(segs, self.labels)
+            # segs, _ = masking_segs.filter(segs, "all")
+            
+            sam_modelname = folder_paths.get_full_path("sams", sam_model_name)
+
+            if 'vit_h' in sam_model_name:
+                model_kind = 'vit_h'
+            elif 'vit_l' in sam_model_name:
+                model_kind = 'vit_l'
+            else:
+                model_kind = 'vit_b'
+
+            sam = sam_model_registry[model_kind](checkpoint=sam_modelname)
+            size = os.path.getsize(sam_modelname)
+            sam.safe_to = core.SafeToGPU(size)
+
+            device = model_management.get_torch_device()
+
+            sam.safe_to.to_device(sam, device)
+
+            sam.is_auto_mode = self.device_mode == "AUTO"
+
+            combined_mask, _ = core.make_sam_mask_segmented(sam, segs, images, self.detection_hint, sam_dilation, sam_threshold, bbox_expansion, mask_hint_threshold, mask_hint_use_negative)
+        
+        else:
+            combined_mask = mask_optional
+
+        # *** MASK TO IMAGE ***:
+        
+        mask_image = combined_mask.reshape((-1, 1, combined_mask.shape[-2], combined_mask.shape[-1])).movedim(1, -1).expand(-1, -1, -1, 3)
+
+        # *** MASK MORPH ***:
+
+        mask_image = core.tensor2mask(mask_image)
+
+        if morphology_operation == "dilate":
+            mask_image = self.dilate(mask_image, morphology_distance)
+        elif morphology_operation == "erode":
+            mask_image = self.erode(mask_image, morphology_distance)
+        elif morphology_operation == "open":
+            mask_image = self.erode(mask_image, morphology_distance)
+            mask_image = self.dilate(mask_image, morphology_distance)
+        elif morphology_operation == "close":
+            mask_image = self.dilate(mask_image, morphology_distance)
+            mask_image = self.erode(mask_image, morphology_distance)
+        
+        # *** MASK BLUR ***:
+        
+        if len(mask_image.size()) == 3:
+            mask_image = mask_image.unsqueeze(3)
+        
+        mask_image = mask_image.permute(0, 3, 1, 2)
+        kernel_size = blur_radius * 2 + 1
+        sigma = sigma_factor * (0.6 * blur_radius - 0.3)
+        mask_image_final = self.gaussian_blur(mask_image, kernel_size, sigma).permute(0, 2, 3, 1)
+        if mask_image_final.size()[3] == 1:
+            mask_image_final = mask_image_final[:, :, :, 0]
+
+        # *** CUT BY MASK ***:
+        
+        if len(swapped_image.shape) < 4:
+            C = 1
+        else:
+            C = swapped_image.shape[3]
+
+        # We operate on RGBA to keep the code clean and then convert back after
+        swapped_image = core.tensor2rgba(swapped_image)
+        mask = core.tensor2mask(mask_image_final)
+
+        # Scale the mask to be a matching size if it isn't
+        B, H, W, _ = swapped_image.shape
+        mask = torch.nn.functional.interpolate(mask.unsqueeze(1), size=(H, W), mode='nearest')[:,0,:,:]
+        MB, _, _ = mask.shape
+
+        if MB < B:
+            assert(B % MB == 0)
+            mask = mask.repeat(B // MB, 1, 1)
+
+        # masks_to_boxes errors if the tensor is all zeros, so we'll add a single pixel and zero it out at the end
+        is_empty = ~torch.gt(torch.max(torch.reshape(mask,[MB, H * W]), dim=1).values, 0.)
+        mask[is_empty,0,0] = 1.
+        boxes = masks_to_boxes(mask)
+        mask[is_empty,0,0] = 0.
+
+        min_x = boxes[:,0]
+        min_y = boxes[:,1]
+        max_x = boxes[:,2]
+        max_y = boxes[:,3]
+
+        width = max_x - min_x + 1
+        height = max_y - min_y + 1
+
+        use_width = int(torch.max(width).item())
+        use_height = int(torch.max(height).item())
+
+        # if self.force_resize_width > 0:
+        #     use_width = self.force_resize_width
+
+        # if self.force_resize_height > 0:
+        #     use_height = self.force_resize_height
+
+        alpha_mask = torch.ones((B, H, W, 4))
+        alpha_mask[:,:,:,3] = mask
+
+        swapped_image = swapped_image * alpha_mask
+
+        cutted_image = torch.zeros((B, use_height, use_width, 4))
+        for i in range(0, B):
+            if not is_empty[i]:
+                ymin = int(min_y[i].item())
+                ymax = int(max_y[i].item())
+                xmin = int(min_x[i].item())
+                xmax = int(max_x[i].item())
+                single = (swapped_image[i, ymin:ymax+1, xmin:xmax+1,:]).unsqueeze(0)
+                resized = torch.nn.functional.interpolate(single.permute(0, 3, 1, 2), size=(use_height, use_width), mode='bicubic').permute(0, 2, 3, 1)
+                cutted_image[i] = resized[0]
+        
+        # Preserve our type unless we were previously RGB and added non-opaque alpha due to the mask size
+        if C == 1:
+            cutted_image = core.tensor2mask(cutted_image)
+        elif C == 3 and torch.min(cutted_image[:,:,:,3]) == 1:
+            cutted_image = core.tensor2rgb(cutted_image)
+
+        # *** PASTE BY MASK ***:
+
+        image_base = core.tensor2rgba(images)
+        image_to_paste = core.tensor2rgba(cutted_image)
+        mask = core.tensor2mask(mask_image_final)
+
+        # Scale the mask to be a matching size if it isn't
+        B, H, W, C = image_base.shape
+        MB = mask.shape[0]
+        PB = image_to_paste.shape[0]
+
+        if B < PB:
+            assert(PB % B == 0)
+            image_base = image_base.repeat(PB // B, 1, 1, 1)
+        B, H, W, C = image_base.shape
+        if MB < B:
+            assert(B % MB == 0)
+            mask = mask.repeat(B // MB, 1, 1)
+        elif B < MB:
+            assert(MB % B == 0)
+            image_base = image_base.repeat(MB // B, 1, 1, 1)
+        if PB < B:
+            assert(B % PB == 0)
+            image_to_paste = image_to_paste.repeat(B // PB, 1, 1, 1)
+
+        mask = torch.nn.functional.interpolate(mask.unsqueeze(1), size=(H, W), mode='nearest')[:,0,:,:]
+        MB, MH, MW = mask.shape
+
+        # masks_to_boxes errors if the tensor is all zeros, so we'll add a single pixel and zero it out at the end
+        is_empty = ~torch.gt(torch.max(torch.reshape(mask,[MB, MH * MW]), dim=1).values, 0.)
+        mask[is_empty,0,0] = 1.
+        boxes = masks_to_boxes(mask)
+        mask[is_empty,0,0] = 0.
+
+        min_x = boxes[:,0]
+        min_y = boxes[:,1]
+        max_x = boxes[:,2]
+        max_y = boxes[:,3]
+        mid_x = (min_x + max_x) / 2
+        mid_y = (min_y + max_y) / 2
+
+        target_width = max_x - min_x + 1
+        target_height = max_y - min_y + 1
+
+        result = image_base.detach().clone()
+        face_segment = mask_image_final
+        
+        for i in range(0, MB):
+            if is_empty[i]:
+                continue
+            else:
+                image_index = i
+                source_size = image_to_paste.size()
+                SB, SH, SW, _ = image_to_paste.shape
+
+                # Figure out the desired size
+                width = int(target_width[i].item())
+                height = int(target_height[i].item())
+                # if self.resize_behavior == "keep_ratio_fill":
+                #     target_ratio = width / height
+                #     actual_ratio = SW / SH
+                #     if actual_ratio > target_ratio:
+                #         width = int(height * actual_ratio)
+                #     elif actual_ratio < target_ratio:
+                #         height = int(width / actual_ratio)
+                # elif self.resize_behavior == "keep_ratio_fit":
+                #     target_ratio = width / height
+                #     actual_ratio = SW / SH
+                #     if actual_ratio > target_ratio:
+                #         height = int(width / actual_ratio)
+                #     elif actual_ratio < target_ratio:
+                #         width = int(height * actual_ratio)
+                # elif self.resize_behavior == "source_size" or self.resize_behavior == "source_size_unmasked":
+
+                width = SW
+                height = SH
+
+                # Resize the image we're pasting if needed
+                resized_image = image_to_paste[i].unsqueeze(0)
+                # if SH != height or SW != width:
+                #     resized_image = torch.nn.functional.interpolate(resized_image.permute(0, 3, 1, 2), size=(height,width), mode='bicubic').permute(0, 2, 3, 1)
+
+                pasting = torch.ones([H, W, C])
+                ymid = float(mid_y[i].item())
+                ymin = int(math.floor(ymid - height / 2)) + 1
+                ymax = int(math.floor(ymid + height / 2)) + 1
+                xmid = float(mid_x[i].item())
+                xmin = int(math.floor(xmid - width / 2)) + 1
+                xmax = int(math.floor(xmid + width / 2)) + 1
+
+                _, source_ymax, source_xmax, _ = resized_image.shape
+                source_ymin, source_xmin = 0, 0
+
+                if xmin < 0:
+                    source_xmin = abs(xmin)
+                    xmin = 0
+                if ymin < 0:
+                    source_ymin = abs(ymin)
+                    ymin = 0
+                if xmax > W:
+                    source_xmax -= (xmax - W)
+                    xmax = W
+                if ymax > H:
+                    source_ymax -= (ymax - H)
+                    ymax = H
+
+                pasting[ymin:ymax, xmin:xmax, :] = resized_image[0, source_ymin:source_ymax, source_xmin:source_xmax, :]
+                pasting[:, :, 3] = 1.
+
+                pasting_alpha = torch.zeros([H, W])
+                pasting_alpha[ymin:ymax, xmin:xmax] = resized_image[0, source_ymin:source_ymax, source_xmin:source_xmax, 3]
+
+                # if self.resize_behavior == "keep_ratio_fill" or self.resize_behavior == "source_size_unmasked":
+                #     # If we explicitly want to fill the area, we are ok with extending outside
+                #     paste_mask = pasting_alpha.unsqueeze(2).repeat(1, 1, 4)
+                # else:
+                #     paste_mask = torch.min(pasting_alpha, mask[i]).unsqueeze(2).repeat(1, 1, 4)
+                paste_mask = torch.min(pasting_alpha, mask[i]).unsqueeze(2).repeat(1, 1, 4)
+                result[image_index] = pasting * paste_mask + result[image_index] * (1. - paste_mask)
+
+                face_segment = result
+
+                face_segment[...,3] = mask[i]
+
+                result = rgba2rgb_tensor(result)
+        
+        return (result,combined_mask,mask_image_final,face_segment,)
+
+    def gaussian_blur(self, image, kernel_size, sigma):
+        kernel = torch.Tensor(kernel_size, kernel_size).to(device=image.device)
+        center = kernel_size // 2
+        variance = sigma**2
+        for i in range(kernel_size):
+            for j in range(kernel_size):
+                x = i - center
+                y = j - center
+                kernel[i, j] = math.exp(-(x**2 + y**2)/(2*variance))
+        kernel /= kernel.sum()
+
+        # Pad the input tensor
+        padding = (kernel_size - 1) // 2
+        input_pad = torch.nn.functional.pad(image, (padding, padding, padding, padding), mode='reflect')
+
+        # Reshape the padded input tensor for batched convolution
+        batch_size, num_channels, height, width = image.shape
+        input_reshaped = input_pad.reshape(batch_size*num_channels, 1, height+padding*2, width+padding*2)
+
+        # Perform batched convolution with the Gaussian kernel
+        output_reshaped = torch.nn.functional.conv2d(input_reshaped, kernel.unsqueeze(0).unsqueeze(0))
+
+        # Reshape the output tensor to its original shape
+        output_tensor = output_reshaped.reshape(batch_size, num_channels, height, width)
+
+        return output_tensor
+    
+    def erode(self, image, distance):
+        return 1. - self.dilate(1. - image, distance)
+
+    def dilate(self, image, distance):
+        kernel_size = 1 + distance * 2
+        # Add the channels dimension
+        image = image.unsqueeze(1)
+        out = torchfn.max_pool2d(image, kernel_size=kernel_size, stride=1, padding=kernel_size // 2).squeeze(1)
+        return out
+
+
+class ImageDublicator:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),               
+                "count": ("INT", {"default": 1, "min": 0}),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("IMAGES",)
+    OUTPUT_IS_LIST = (True,)
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    def execute(self, image, count):
+        images = [image for i in range(count)]        
+        return (images,)
+
+
+class ImageRGBA2RGB:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    def execute(self, image):
+        out = rgba2rgb_tensor(image)       
+        return (out,)
+
+
+class MakeFaceModelBatch:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "face_model1": ("FACE_MODEL",), 
+            },
+            "optional": {
+                "face_model2": ("FACE_MODEL",),
+                "face_model3": ("FACE_MODEL",),
+                "face_model4": ("FACE_MODEL",),
+                "face_model5": ("FACE_MODEL",),
+                "face_model6": ("FACE_MODEL",),
+                "face_model7": ("FACE_MODEL",),
+                "face_model8": ("FACE_MODEL",),
+                "face_model9": ("FACE_MODEL",),
+                "face_model10": ("FACE_MODEL",),
+            },
+        }
+
+    RETURN_TYPES = ("FACE_MODEL",)
+    RETURN_NAMES = ("FACE_MODELS",)
+    FUNCTION = "execute"
+
+    CATEGORY = "🌌 ReActor"
+
+    def execute(self, **kwargs):
+        if len(kwargs) > 0:
+            face_models = [value for value in kwargs.values()]
+            return (face_models,)
+        else:
+            logger.error("Please provide at least 1 `face_model`")
+            return (None,)
+
+
+class ReActorOptions:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_faces_order": (
+                    ["left-right","right-left","top-bottom","bottom-top","small-large","large-small"], {"default": "large-small"}
+                ),
+                "input_faces_index": ("STRING", {"default": "0"}),
+                "detect_gender_input": (["no","female","male"], {"default": "no"}),
+                "source_faces_order": (
+                    ["left-right","right-left","top-bottom","bottom-top","small-large","large-small"], {"default": "large-small"}
+                ),
+                "source_faces_index": ("STRING", {"default": "0"}),
+                "detect_gender_source": (["no","female","male"], {"default": "no"}),
+                "console_log_level": ([0, 1, 2], {"default": 1}),
+            }
+        }
+
+    RETURN_TYPES = ("OPTIONS",)
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    def execute(self,input_faces_order, input_faces_index, detect_gender_input, source_faces_order, source_faces_index, detect_gender_source, console_log_level):
+        options: dict = {
+            "input_faces_order": input_faces_order,
+            "input_faces_index": input_faces_index,
+            "detect_gender_input": detect_gender_input,
+            "source_faces_order": source_faces_order,
+            "source_faces_index": source_faces_index,
+            "detect_gender_source": detect_gender_source,
+            "console_log_level": console_log_level,
+        }
+        return (options, )
+
+
+class ReActorFaceBoost:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "enabled": ("BOOLEAN", {"default": True, "label_off": "OFF", "label_on": "ON"}),
+                "boost_model": (get_model_names(get_restorers),),
+                "interpolation": (["Nearest","Bilinear","Bicubic","Lanczos"], {"default": "Bicubic"}),
+                "visibility": ("FLOAT", {"default": 1, "min": 0.1, "max": 1, "step": 0.05}),
+                "codeformer_weight": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1, "step": 0.05}),
+                "restore_with_main_after": ("BOOLEAN", {"default": False}),
+            }
+        }
+
+    RETURN_TYPES = ("FACE_BOOST",)
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    def execute(self,enabled,boost_model,interpolation,visibility,codeformer_weight,restore_with_main_after):
+        face_boost: dict = {
+            "enabled": enabled,
+            "boost_model": boost_model,
+            "interpolation": interpolation,
+            "visibility": visibility,
+            "codeformer_weight": codeformer_weight,
+            "restore_with_main_after": restore_with_main_after,
+        }
+        return (face_boost, )
+    
+class ReActorUnload:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "trigger": ("IMAGE", ),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "execute"
+    CATEGORY = "🌌 ReActor"
+
+    def execute(self, trigger):
+        unload_all_models()
+        return (trigger,)
+
+
+NODE_CLASS_MAPPINGS = {
+    # --- MAIN NODES ---
+    "ReActorFaceSwap": reactor,
+    "ReActorFaceSwapOpt": ReActorPlusOpt,
+    "ReActorOptions": ReActorOptions,
+    "ReActorFaceBoost": ReActorFaceBoost,
+    "ReActorMaskHelper": MaskHelper,
+    # --- Operations with Face Models ---
+    "ReActorSaveFaceModel": SaveFaceModel,
+    "ReActorLoadFaceModel": LoadFaceModel,
+    "ReActorBuildFaceModel": BuildFaceModel,
+    "ReActorMakeFaceModelBatch": MakeFaceModelBatch,
+    # --- Additional Nodes ---
+    "ReActorRestoreFace": RestoreFace,
+    "ReActorImageDublicator": ImageDublicator,
+    "ImageRGBA2RGB": ImageRGBA2RGB,
+    "ReActorUnload": ReActorUnload,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    # --- MAIN NODES ---
+    "ReActorFaceSwap": "ReActor 🌌 Fast Face Swap",
+    "ReActorFaceSwapOpt": "ReActor 🌌 Fast Face Swap [OPTIONS]",
+    "ReActorOptions": "ReActor 🌌 Options",
+    "ReActorFaceBoost": "ReActor 🌌 Face Booster",
+    "ReActorMaskHelper": "ReActor 🌌 Masking Helper",
+    # --- Operations with Face Models ---
+    "ReActorSaveFaceModel": "Save Face Model 🌌 ReActor",
+    "ReActorLoadFaceModel": "Load Face Model 🌌 ReActor",
+    "ReActorBuildFaceModel": "Build Blended Face Model 🌌 ReActor",
+    "ReActorMakeFaceModelBatch": "Make Face Model Batch 🌌 ReActor",
+    # --- Additional Nodes ---
+    "ReActorRestoreFace": "Restore Face 🌌 ReActor",
+    "ReActorImageDublicator": "Image Dublicator (List) 🌌 ReActor",
+    "ImageRGBA2RGB": "Convert RGBA to RGB 🌌 ReActor",
+    "ReActorUnload": "Unload ReActor Models 🌌 ReActor",
+}

custom_nodes/ComfyUI-ReActor/pyproject.toml

@@ -0,0 +1,15 @@
+[project]
+name = "comfyui-reactor"
+description = "(SFW-Friendly) The Fast and Simple Face Swap Extension Node for ComfyUI, based on ReActor SD-WebUI Face Swap Extension"
+version = "0.5.2-b2"
+license = { file = "LICENSE" }
+dependencies = ["insightface==0.7.3", "onnx>=1.14.0", "opencv-python>=4.7.0.72", "numpy==1.26.3", "segment_anything", "albumentations>=1.4.16", "ultralytics"]
+
+[project.urls]
+Repository = "https://github.com/Gourieff/ComfyUI-ReActor"
+#  Used by Comfy Registry https://comfyregistry.org
+
+[tool.comfy]
+PublisherId = "gourieff"
+DisplayName = "ComfyUI-ReActor"
+Icon = ""

custom_nodes/ComfyUI-ReActor/r_basicsr/__init__.py

@@ -0,0 +1,12 @@
+# https://github.com/xinntao/BasicSR
+# flake8: noqa
+from .archs import *
+from .data import *
+from .losses import *
+from .metrics import *
+from .models import *
+from .ops import *
+from .test import *
+from .train import *
+from .utils import *
+from .version import __gitsha__, __version__

custom_nodes/ComfyUI-ReActor/r_basicsr/archs/__init__.py

@@ -0,0 +1,25 @@
+import importlib
+from copy import deepcopy
+from os import path as osp
+
+from r_basicsr.utils import get_root_logger, scandir
+from r_basicsr.utils.registry import ARCH_REGISTRY
+
+__all__ = ['build_network']
+
+# automatically scan and import arch modules for registry
+# scan all the files under the 'archs' folder and collect files ending with
+# '_arch.py'
+arch_folder = osp.dirname(osp.abspath(__file__))
+arch_filenames = [osp.splitext(osp.basename(v))[0] for v in scandir(arch_folder) if v.endswith('_arch.py')]
+# import all the arch modules
+_arch_modules = [importlib.import_module(f'r_basicsr.archs.{file_name}') for file_name in arch_filenames]
+
+
+def build_network(opt):
+    opt = deepcopy(opt)
+    network_type = opt.pop('type')
+    net = ARCH_REGISTRY.get(network_type)(**opt)
+    logger = get_root_logger()
+    logger.info(f'Network [{net.__class__.__name__}] is created.')
+    return net