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sd-webui-reactor-main/sd-webui-reactor-main/.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/sd-webui-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: |
+        1. Go to .... 
+        2. Press ....
+        3. ...
+    validations:
+      required: true
+  - type: textarea
+    id: sysinfo
+    attributes:
+      label: Sysinfo
+      description: Describe your platform. OS, browser, GPU, what SD WebUI you use, what version and what extensions are also enabled. If you use A1111 you can generate "System info file" (Settings -> Sysinfo) and put it here.
+    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.

sd-webui-reactor-main/sd-webui-reactor-main/.github/ISSUE_TEMPLATE/config.yml

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

sd-webui-reactor-main/sd-webui-reactor-main/.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/sd-webui-reactor/discussions) section (choose the "Idea" category)

sd-webui-reactor-main/sd-webui-reactor-main/.gitignore

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+__pycache__/
+*.py[cod]
+*$py.class
+*.pyc
+
+.vscode/
+
+example
+*.txt
+!requirements.txt

sd-webui-reactor-main/sd-webui-reactor-main/API.md

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+# <div align="center">ReActor Extension API</div>
+
+<div align="center">
+
+[Built-in SD WebUI API](#built-in-sd-webui-api) | [External ReActor API](#external-reactor-api)
+
+---
+</div>
+
+Gourieff's **ReActor** SD WebUI Extension allows to operate via API: both built-in and external (POST and GET requests).
+
+
+## Built-in SD WebUI API
+
+This API is actual if you use Automatic1111 stable-diffusion-webui.
+
+First of all - check the [SD Web API Wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/API) for how to use the API.
+
+* Call `requests.get(url=f'{address}/sdapi/v1/script-info')` to find the args that ReActor needs;
+* Define ReActor script args and add like this `"alwayson_scripts": {"reactor":{"args":args}}` in the payload;
+* Call the API. 
+
+You can find the [full usage example](./example/api_example.py) with all the available parameters and discriptions in the "example" folder.
+
+## External ReActor API
+
+ReActor extension supports for external calls via POST or GET requests while your SD WebUI server is working.
+
+> :warning: Source and Target images must be "base64".
+
+Example:
+
+```
+curl -X POST \
+	'http://127.0.0.1:7860/reactor/image' \
+    -H 'accept: application/json' \
+    -H 'Content-Type: application/json' \
+    -d '{
+    "source_image": "data:image/png;base64,/9j/4QAYRXhpZgAASUkqAAgAAAAAAAAAAAAAAP/sABFEdWNreQABAAQAAABQAAD/7g...",
+    "target_image": "data:image/png;base64,/9j/4QAYRXhpZgAASUkqAAgAAAAAAAAAAAAAAP/sABFEdWNreQABAAQAAABCAAD/7g...",
+    "source_faces_index": [0],
+    "face_index": [0],
+    "upscaler": "4x_Struzan_300000",
+    "scale": 2,
+    "upscale_visibility": 1,
+    "face_restorer": "CodeFormer",
+    "restorer_visibility": 1,
+    "restore_first": 1,
+    "model": "inswapper_128.onnx",
+    "gender_source": 0,
+    "gender_target": 0,
+    "save_to_file": 0,
+    "result_file_path": ""
+	}'
+```
+
+* Set `"upscaler"` to `"None"` and `"scale"` to `1` if you don't need to upscale;
+* Set `"save_to_file"` to `1` if you need to save result to a file;
+* `"result_file_path"` is set to the `"outputs/api"` folder by default (please, create the folder beforehand to avoid any errors) with a timestamped filename; (output_YYYY-MM-DD_hh-mm-ss), you can set any specific path, e.g. `"C:/stable-diffusion-webui/outputs/api/output.png"`.
+
+You can find full usage examples with all the available parameters in the "example" folder: [cURL](./example/api_external.curl), [JSON](./example/api_external.json).
+
+As a result you recieve a "base64" image:
+
+```
+{"image":"iVBORw0KGgoAAAANSUhEUgAABlAAAARQCAIAAAAdiYuqAAEAAElEQVR4nOz9+ZMlSXImBn6qau4vIjKzzr5wzwBCDrm/7f+/K7IHV3ZkhUIuyZHlkBhiMGig0Y0..."}
+```
+
+A list of available models can be seen by GET:
+* http://127.0.0.1:7860/reactor/models
+* http://127.0.0.1:7860/reactor/upscalers

sd-webui-reactor-main/sd-webui-reactor-main/LICENSE

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+                    GNU AFFERO GENERAL PUBLIC LICENSE
+                       Version 3, 19 November 2007
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sd-webui-reactor-main/sd-webui-reactor-main/README.md

@@ -0,0 +1,361 @@
+<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/version-0.6.0_alpha1-lightgreen?style=for-the-badge&labelColor=darkgreen)
+  
+  <a href="https://boosty.to/artgourieff" target="_blank">
+    <img src="https://lovemet.ru/www/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/sd-webui-reactor/main?cacheSeconds=0)](https://github.com/Gourieff/sd-webui-reactor/commits/main)
+  ![Last commit](https://img.shields.io/github/last-commit/Gourieff/sd-webui-reactor/main?cacheSeconds=0)
+  [![Opened issues](https://img.shields.io/github/issues/Gourieff/sd-webui-reactor?color=red)](https://github.com/Gourieff/sd-webui-reactor/issues?cacheSeconds=0)
+  [![Closed issues](https://img.shields.io/github/issues-closed/Gourieff/sd-webui-reactor?color=green&cacheSeconds=0)](https://github.com/Gourieff/sd-webui-reactor/issues?q=is%3Aissue+is%3Aclosed)
+  ![License](https://img.shields.io/github/license/Gourieff/sd-webui-reactor)
+
+  English | [Русский](/README_RU.md)
+
+# ReActor for Stable Diffusion
+
+### The Fast and Simple FaceSwap Extension with a lot of improvements and without NSFW filter (uncensored, use it on your own [responsibility](#disclaimer))
+
+---
+  <b>
+    <a href="#latestupdate">What's new</a> | <a href="#installation">Installation</a> | <a href="#features">Features</a> | <a href="#usage">Usage</a> | <a href="#api">API</a> | <a href="#troubleshooting">Troubleshooting</a> | <a href="#updating">Updating</a> | <a href="#comfyui">ComfyUI</a> | <a href="#disclaimer">Disclaimer</a>
+  </b>
+</div>
+
+---
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/demo_crop.jpg?raw=true" alt="example"/>
+
+<a name="latestupdate">
+
+## What's new in the latest updates
+
+### 0.6.0 <sub><sup>ALPHA1
+
+- UI reworked
+- You can now load several source images (with reference faces) or set the path to the folder containing faces images
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_01.png?raw=true" alt="0.6.0-whatsnew-01" width="100%"/>
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_02.png?raw=true" alt="0.6.0-whatsnew-02" width="100%"/>
+
+### 0.5.1
+
+- You can save face models as "safetensors" files (stored in `<sd-web-ui-folder>\models\reactor\faces`) and load them into ReActor, keeping super lightweight face models of the faces you use;
+- "Face Mask Correction" option - if you encounter some pixelation around face contours, this option will be useful;
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/face_model_demo_01.jpg?raw=true" alt="0.5.0-whatsnew-01" width="100%"/>
+
+## Installation
+
+[Automatic1111](#a1111) | [Vladmandic SD.Next](#sdnext) | [Google Colab SD WebUI](#colab)
+
+<a name="a1111">If you use [AUTOMATIC1111 web-ui](https://github.com/AUTOMATIC1111/stable-diffusion-webui/):
+
+1. (For Windows Users):
+  - Install **Visual Studio 2022** (Community version, for example - you need this step to build some of dependencies):
+  https://visualstudio.microsoft.com/downloads/
+  - OR only **VS C++ Build Tools** (if you don't need the whole Visual Studio) and select "Desktop Development with C++" under "Workloads -> Desktop & Mobile":
+  https://visualstudio.microsoft.com/visual-cpp-build-tools/
+  - OR if you don't want to install VS or VS C++ BT - follow [this steps (sec. VIII)](#insightfacebuild)
+2. In web-ui, go to the "Extensions" tab, load "Available" extensions and type "ReActor" in the search field or use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab - and click "Install"
+3. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
+4. Check the last message in your SD-WebUI Console:
+* If you see the message "--- PLEASE, RESTART the Server! ---" - so, do it, stop the Server (CTRL+C or CMD+C) and start it again - or just go to the "Installed" tab, click "Apply and restart UI" 
+* If you see the message "Done!", just reload the UI
+5. Enjoy!
+
+<a name="sdnext">If you use [SD.Next](https://github.com/vladmandic/automatic):
+
+1. Close (stop) your SD WebUI Server if it's running
+2. (For Windows Users) See the [1st step](#a1111) for Automatic1111 (if you followed [this steps (sec. VIII)](#insightfacebuild) instead - go to the Step 5)
+3. Go to (Windows)`automatic\venv\Scripts` or (MacOS/Linux)`automatic/venv/bin`, run Terminal or Console (cmd) for that folder and type `activate`
+4. Run `pip install insightface==0.7.3`
+5. Run SD.Next, go to the "Extensions" tab and use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab and click "Install"
+6. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
+7. Check the last message in your SD.Next Console:
+* If you see the message "--- PLEASE, RESTART the Server! ---" - stop the Server (CTRL+C or CMD+C) or just close your console
+8. Go to the `automatic\extensions\sd-webui-reactor` directory - if you see there `models\insightface` folder with the file `inswapper_128.onnx`, just move the file to the `automatic\models\insightface` folder
+9. Run your SD.Next WebUI and enjoy!
+
+<a name="colab">If you use [Cagliostro Colab UI](https://github.com/Linaqruf/sd-notebook-collection):
+
+1. In active WebUI, go to the "Extensions" tab, load "Available" extensions and type "ReActor" in the search field or use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab - and click "Install"
+2. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
+3. When you see the message "--- PLEASE, RESTART the Server! ---" (in your Colab Notebook Start UI section "Start Cagliostro Colab UI") - just go to the "Installed" tab and click "Apply and restart UI"
+4. Enjoy!
+
+## Features
+
+- Very fast and accurate **face replacement (face swap)** in images
+- **Multiple faces support**
+- **Gender detection**
+- Ability to **save original images** (made before swapping)
+- **Face restoration** of a swapped face
+- **Upscaling** of a resulting image
+- Saving ans loading **Safetensors Face Models**
+- **Facial Mask Correction** to avoid any  pixelation around face contours
+- Ability to set the **Postprocessing order**
+- **100% compatibility** with different **SD WebUIs**: Automatic1111, SD.Next, Cagliostro Colab UI
+- **Fast performance** even with CPU, ReActor for SD WebUI is absolutely not picky about how powerful your GPU is
+- **CUDA** acceleration support since version 0.5.0
+- **[API](/API.md) support**: both SD WebUI built-in and external (via POST/GET requests)
+- **ComfyUI [support](https://github.com/Gourieff/comfyui-reactor-node)**
+- **Mac M1/M2 [support](https://github.com/Gourieff/sd-webui-reactor/issues/42)**
+- Console **log level control**
+- **NSFW filter free** (this extension is aimed at highly developed intellectual people, not at perverts; our society must be oriented on its way towards the highest standards, not the lowest - this is the essence of development and evolution; so, my position is - that mature-minded people are clever enough to understand for themselves what is good and what is bad and take full responsibility for personal actions; for others - no "filters" will help until they do understand how Universe works)
+
+## Usage
+
+> Using this software you are agree with [disclaimer](#disclaimer)
+
+1. Under "ReActor" drop-down menu, import an image containing a face;
+2. Turn on the "Enable" checkbox;
+3. That's it, now the generated result will have the face you selected.
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/example.jpg?raw=true" alt="example" width="808"/>
+
+### Face Indexes
+
+ReActor detects faces in images in the following order:<br>
+left->right, top->bottom
+
+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.
+
+### The result face is blurry
+Use the "Restore Face" option. You can also try the "Upscaler" option or for more finer control, use an upscaler from the "Extras" tab.
+You can also set the postproduction order (from 0.1.0 version):
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/pp-order.png?raw=true" alt="example"/>
+
+*The old logic was the opposite (Upscale -> then Restore), resulting in worse face quality (and big texture differences) after upscaling.* 
+
+### There are multiple faces in result
+Select the face numbers you wish to swap using the "Comma separated face number(s)" option for swap-source and result images. You can use different index order.
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/multiple-faces.png?raw=true" alt="example"/>
+
+### ~~The result is totally black~~
+~~This means NSFW filter detected that your image is NSFW.~~
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/IamSFW.jpg?raw=true" alt="IamSFW" width="50%"/>
+
+### Img2Img
+
+You can choose to activate the swap on the source image or on the generated image, or on both using the checkboxes. Activating on source image allows you to start from a given base and apply the diffusion process to it.
+
+ReActor works with Inpainting - but only the masked part will be swapped.<br>Please use with the "Only masked" option for "Inpaint area" if you enabled "Upscaler". Otherwise use the upscale option via the Extras tab or via the Script loader (below the screen) with "SD upscale" or "Ultimate SD upscale".
+
+### Extras Tab
+
+From the version 0.5.0 you can use ReActor via the Extras Tab. It gives a superfast perfomance and ability to swap face2image avoiding SD pipeline that can cause smushing of original image's details
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/extras_tab.jpg?raw=true" alt="IamSFW"/>
+
+## API
+
+You can use ReActor with the built-in Webui API or via an external API.
+
+Please follow **[this](/API.md)** page for the detailed instruction.
+
+## Troubleshooting
+
+### **I. "You should at least have one model in models directory"**
+
+Please, check the path where "inswapper_128.onnx" model is stored. It must be inside the folder `stable-diffusion-webui\models\insightface`. Move the model there if it's stored in a different directory.
+
+### **II. Any problems with installing Insightface or other dependencies**
+
+(for Mac M1/M2 users) If you get errors when trying to install Insightface - please read https://github.com/Gourieff/sd-webui-reactor/issues/42
+
+(for Windows Users) If you have VS C++ Build Tools or MS VS 2022 installed but still have a problem, then try the next step:
+1. Close (stop) your SD WebUI Server and start it again
+   
+(for Any OS Users) If the problem still there, then do the following:
+1. Close (stop) your SD WebUI Server if it's running
+2. Go to (Windows)`venv\Lib\site-packages` folder or (MacOS/Linux)`venv/lib/python3.10/site-packages`
+3. If you see any folders with names start from `~` (e.g. "~rotobuf") - delete them
+4. Go to (Windows)`venv\Scripts` or (MacOS/Linux)`venv/bin`
+5. Run Terminal or Console (cmd) for that folder and type `activate`
+6. Update your pip at first: `pip install -U pip`
+7. Then one-by-one:
+   - `pip install insightface==0.7.3`
+   - `pip install onnx`
+   - `pip install "onnxruntime-gpu>=1.16.1"`
+   - `pip install opencv-python`
+   - `pip install tqdm`
+8. Type `deactivate`, you can close your Terminal or Console and start your SD WebUI, ReActor should start OK - if not, welcome to the Issues section.
+
+### **III. "TypeError: UpscaleOptions.init() got an unexpected keyword argument 'do_restore_first'"**
+
+First of all - you need to disable any other Roop-based extensions:
+- Go to 'Extensions -> Installed' tab and uncheck any Roop-based extensions except this one
+  <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/roop-off.png?raw=true" alt="uncompatible-with-other-roop"/>
+- Click 'Apply and restart UI'
+
+Alternative solutions: 
+- https://github.com/Gourieff/sd-webui-reactor/issues/3#issuecomment-1615919243
+- https://github.com/Gourieff/sd-webui-reactor/issues/39#issuecomment-1666559134 (can be actual, if you use Vladmandic SD.Next)
+
+### **IV. "AttributeError: 'FaceSwapScript' object has no attribute 'enable'"**
+
+Probably, you need to disable the "SD-CN-Animation" extension (or perhaps some another that causes the conflict)
+
+### **V. "INVALID_PROTOBUF : Load model from <...>\models\insightface\inswapper_128.onnx failed:Protobuf parsing failed" OR "AttributeError: 'NoneType' object has no attribute 'get'" OR "AttributeError: 'FaceSwapScript' object has no attribute 'save_original'"**
+
+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 `stable-diffusion-webui\models\insightface` replacing existing one
+
+### **VI. "ValueError: This ORT build has ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider'] enabled" OR "ValueError: This ORT build has ['AzureExecutionProvider', 'CPUExecutionProvider'] enabled"**
+
+1. Close (stop) your SD WebUI Server if it's running
+2. Go to the (Windows)`venv\Lib\site-packages` or (MacOS/Linux)`venv/lib/python3.10/site-packages` and see if there are any folders with names start from "~" (for example "~rotobuf"), delete them
+3. Go to the (Windows)`venv\Scripts` or (MacOS/Linux)`venv/bin` run Terminal or Console (cmd) there and type `activate`
+4. Then:
+- `python -m pip install -U pip`
+- `pip uninstall -y onnxruntime onnxruntime-gpu onnxruntime-silicon onnxruntime-extensions`
+- `pip install "onnxruntime-gpu>=1.16.1"`
+
+If it didn't help - it seems that you have another extension reinstalling `onnxruntime` when SD WebUI checks requirements. Please see your extensions list. Some extensions can causes reinstalling of `onnxruntime-gpu` to `onnxruntime<1.16.1` every time SD WebUI runs.<br>ORT 1.16.0 has a bug https://github.com/microsoft/onnxruntime/issues/17631 - don't install it!
+
+### **VII. "ImportError: cannot import name 'builder' from 'google.protobuf.internal'"**
+
+1. Close (stop) your SD WebUI Server if it's running
+2. Go to the (Windows)`venv\Lib\site-packages` or (MacOS/Linux)`venv/lib/python3.10/site-packages` and see if there are any folders with names start from "~" (for example "~rotobuf"), delete them
+3. Go to the "google" folder (inside the "site-packages") and delete any folders there with names start from "~"
+4. Go to the (Windows)`venv\Scripts` or (MacOS/Linux)`venv/bin` run Terminal or Console (cmd) there and type `activate`
+5. Then:
+- `python -m pip install -U pip`
+- `pip uninstall protobuf`
+- `pip install "protobuf>=3.20.3"`
+
+If this method doesn't help - there is some other extension that has a wrong version of protobuf dependence and SD WebUI installs it on a startup requirements check
+
+<a name="insightfacebuild">
+
+### **VIII. (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. Close (stop) your SD WebUI Server if it's running
+2. Download and put [prebuilt Insightface package](https://github.com/Gourieff/sd-webui-reactor/raw/main/example/insightface-0.7.3-cp310-cp310-win_amd64.whl) into the stable-diffusion-webui (or SD.Next) root folder (where you have "webui-user.bat" file)
+3. From stable-diffusion-webui (or SD.Next) root folder run CMD and `.\venv\Scripts\activate`
+4. Then update your PIP: `python -m pip install -U pip`
+5. Then install Insightface: `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`
+6. Enjoy!
+
+### **IX. 07-August-23 Update problem**
+
+If after `git pull` you see the message: `Merge made by the 'recursive' strategy` and then when you check `git status` you see `Your branch is ahead of 'origin/main' by`
+
+Please do the next:
+
+Inside the folder `extensions\sd-webui-reactor` run Terminal or Console (cmd) and then:
+- `git reset f48bdf1 --hard`
+- `git pull`
+
+OR
+
+Just delete the folder `sd-webui-reactor` inside the `extensions` directory and then run Terminal or Console (cmd) and type `git clone https://github.com/Gourieff/sd-webui-reactor`
+
+### **X. StabilityMatrix Issues**
+
+If you encounter any issues with installing this extension in the StabilityMatrix package manager - read here how to solve: https://github.com/Gourieff/sd-webui-reactor/issues/129#issuecomment-1768210875
+
+## Updating
+
+A good and quick way to check for Extensions updates: https://github.com/Gourieff/sd-webui-extensions-updater
+
+## ComfyUI
+
+You can use ReActor with ComfyUI.<br>
+For the installation instruction follow the [ReActor Node repo](https://github.com/Gourieff/comfyui-reactor-node)
+
+## 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 applicaitons 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;
+- propogates (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 licence](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 folowing 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**

sd-webui-reactor-main/sd-webui-reactor-main/README_RU.md

@@ -0,0 +1,370 @@
+<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-0.6.0_alpha1-lightgreen?style=for-the-badge&labelColor=darkgreen)
+  
+  <a href="https://boosty.to/artgourieff" target="_blank">
+    <img src="https://lovemet.ru/www/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/sd-webui-reactor/main?cacheSeconds=0)](https://github.com/Gourieff/sd-webui-reactor/commits/main)
+  ![Last commit](https://img.shields.io/github/last-commit/Gourieff/sd-webui-reactor/main?cacheSeconds=0)
+  [![Opened issues](https://img.shields.io/github/issues/Gourieff/sd-webui-reactor?color=red)](https://github.com/Gourieff/sd-webui-reactor/issues?cacheSeconds=0)
+  [![Closed issues](https://img.shields.io/github/issues-closed/Gourieff/sd-webui-reactor?color=green&cacheSeconds=0)](https://github.com/Gourieff/sd-webui-reactor/issues?q=is%3Aissue+is%3Aclosed)
+  ![License](https://img.shields.io/github/license/Gourieff/sd-webui-reactor)
+
+  [English](/README.md) | Русский
+
+# ReActor для Stable Diffusion
+### Расширение для быстрой и простой замены лиц на любых изображениях. Без фильтра цензуры, 18+, используйте под вашу собственную [ответственность](#disclaimer)
+
+---
+  <b>
+    <a href="#latestupdate">Что нового</a> | <a href="#installation">Установка</a> | <a href="#features">Возможности</a> | <a href="#usage">Использование</a> | <a href="#api">API</a> | <a href="#troubleshooting">Устранение проблем</a> | <a href="#updating">Обновление</a> | <a href="#comfyui">ComfyUI</a> | <a href="#disclaimer">Ответственность</a>
+  </b>
+</div>
+
+---
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/demo_crop.jpg?raw=true" alt="example"/>
+
+<a name="latestupdate">
+
+## Что нового в последних обновлениях
+
+### 0.6.0 <sub><sup>ALPHA1
+
+- UI переработан
+- Появилась возможность загружать несколько исходных изображений с лицами или задавать путь к папке, содержащей такие изображения
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_01.png?raw=true" alt="0.6.0-whatsnew-01" width="100%"/>
+
+### 0.5.1
+
+- Теперь можно сохранять модели лиц в качестве файлов "safetensors" (находятся в `<sd-web-ui-folder>\models\reactor\faces`) и загружать их с ReActor, храня супер легкие модели лиц, которые вы чаще всего используете;
+- Новые опция "Face Mask Correction" - если вы сталкиваетесь с пикселизацией вокруг контуров лица, эта опция будет полезной;
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/face_model_demo_01.jpg?raw=true" alt="0.5.0-whatsnew-01" width="100%"/>
+
+<a name="installation">
+
+## Установка
+
+[Automatic1111](#a1111) | [Vladmandic SD.Next](#sdnext) | [Google Colab SD WebUI](#colab)
+
+<a name="a1111">Если вы используете [AUTOMATIC1111 Web-UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui/):
+
+1. (Для пользователей Windows):
+  - Установите **Visual Studio 2022** (Например, версию Community - этот шаг нужен для правильной компиляции библиотеки Insightface):
+  https://visualstudio.microsoft.com/downloads/
+  - ИЛИ только **VS C++ Build Tools** (если вам не нужен весь пакет Visual Studio), выберите "Desktop Development with C++" в разделе "Workloads -> Desktop & Mobile":
+  https://visualstudio.microsoft.com/visual-cpp-build-tools/
+  - ИЛИ если же вы не хотите устанавливать что-либо из вышеуказанного - выполните [следующие шаги (пункт VIII)](#insightfacebuild)
+2. Внутри SD Web-UI перейдите во вкладку "Extensions", загрузите список доступных расширений (вкладка "Available") и введите "ReActor" в строке поиска или же вставьте ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" - и нажмите "Install"
+3. Пожалуйста, подождите несколько минут, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
+4. Проверьте последнее сообщение в консоли SD-WebUI:
+* Если вы видите "--- PLEASE, RESTART the Server! ---" - остановите Сервер (CTRL+C или CMD+C) и запустите его заново - ИЛИ же перейдите во вкладку "Installed", нажмите "Apply and restart UI" 
+* Если вы видите "Done!", просто перезагрузите UI, нажав на "Reload UI"
+5. Готово!
+
+<a name="sdnext">Если вы используете [SD.Next](https://github.com/vladmandic/automatic):
+
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. (Для пользователей Windows) Смотрите [Шаг 1](#a1111) для Automatic1111 (если же вы следовали [данным шагам (пункт VIII)](#insightfacebuild) вместо этого - переходите к Шагу 5)
+3. Перейдите в (Windows)`automatic\venv\Scripts` или (MacOS/Linux)`automatic/venv/bin`, запустите Терминал или Консоль (cmd) для данной папки и выполните `activate`
+4. Выполните `pip install insightface==0.7.3`
+5. Запустите SD.Next, перейдите во вкладку "Extensions", вставьте эту ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" и нажмите "Install"
+6. Пожалуйста, подождите несколько минут, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
+7. Проверьте последнее сообщение в консоли SD.Next:
+* Если вы видите "--- PLEASE, RESTART the Server! ---" - остановите Сервер (CTRL+C или CMD+C) или просто закройте консоль
+8. Перейдите в директорию `automatic\extensions\sd-webui-reactor` - если вы видите там папку `models\insightface` с файлом `inswapper_128.onnx` внутри, переместите его в папку `automatic\models\insightface`
+9. Готово, можете запустить SD.Next WebUI!
+
+<a name="colab">Если вы используете [Cagliostro Colab UI](https://github.com/Linaqruf/sd-notebook-collection):
+
+1. В активном WebUI перейдите во вкладку "Extensions", загрузите список доступных расширений (вкладка "Available") и введите "ReActor" в строке поиска или же вставьте ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" - и нажмите "Install"
+2. Пожалуйста, подождите некоторое время, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
+3. Когда вы увидите сообщение "--- PLEASE, RESTART the Server! ---" (в секции "Start UI" вашего ноутбука "Start Cagliostro Colab UI") - перейдите во вкладку "Installed" и нажмите "Apply and restart UI"
+4. Готово!
+
+<a name="features">
+
+## Возможности
+
+- Быстрая и точна **замена лиц (faceswap)** на изображении
+- **Поддержка нескольких лиц**
+- **Определение пола**
+- Функция **сохранения оригинального изображения** (сгенерированного до замены лица)
+- **Восстановление лица** после замены
+- **Увеличение размера** полученного изображения
+- Сохранение и загрузка **Моделей Лиц типа Safetensors**
+- **Коррекция Маски Лица** для предотвращения какой-либо пикселизации вокруг контуров лиц
+- Возможность задать **порядок постобработки**
+- **100% совместимость** с разными **SD WebUI**: Automatic1111, SD.Next, Cagliostro Colab UI
+- **Отличная производительность** даже с использованием ЦПУ, ReActor для SD WebUI абсолютно не требователен к мощности вашей видеокарты
+- **Поддержка CUDA**, начиная с версии 0.5.0
+- **Поддержка [API](/API.md)**: как встроенного в SD WebUI, так и внешнего (через POST/GET запросы)
+- **[Поддержка](https://github.com/Gourieff/comfyui-reactor-node) ComfyUI**
+- **[Поддержка](https://github.com/Gourieff/sd-webui-reactor/issues/42) ��омпьютеров Mac M1/M2**
+- **Регулировка уровня логов** консоли
+- **Без NSFW фильтров** (данное расширение адресовано высокоразвитым интеллектуальным людям, а не извращенцам; наше общество должно быть ориентировано на своём пути на высшие стандарты, а не на низшие - в этом состоит суть развития и эволюции человеческого общества; поэтому, моя позиция такова - что зрелые умом люди достаточно разумны, чтобы понимать, что есть хорошо, а что плохо и нести полную ответственность за собственные действия; для прочих - никакие "фильтры" не помогут, пока эти люди сами не поймут, как работает Вселенная)
+
+<a name="usage">
+
+## Использование
+
+> Используя данное программное обеспечение, вы соглашаетесь с [ответственностью](#disclaimer)
+
+1. В раскрывающимся меню "ReActor" импортируйте изображение, содержащее лицо;
+2. Установите флажок "Enable";
+3. Готово, теперь результат будет иметь то лицо, которое вы выбрали.
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/example.jpg?raw=true" alt="example" width="808"/>
+
+### Индексы Лиц (Face Indexes)
+
+ReActor определяет лица на изображении в следующей последовательности:<br>
+слева-направо, сверху-вниз.
+
+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.
+
+### Если лицо получилось нечётким
+Используйте опцию "Restore Face". Также можете попробовать опцию "Upscaler". Для более точного контроля параметров используйте Upscaler во вкладке "Extras".
+Также вы можете установить порядок постобработки (начиная с версии 0.1.0):
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/pp-order.png?raw=true" alt="example"/>
+
+*Прежняя логика была противоположенной (Upscale -> затем Restore), что приводило к более худшему качеству изображения лица (а также к значительной разнице текстур) после увеличения.* 
+
+### Результат имеет несколько лиц
+Выберите номера лиц, которые нужно поменять, используя поля "Comma separated face number(s)" для исходного изображения лица и для результата. Можно устанавливать любой, необходимый вам, порядок лиц.
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/multiple-faces.png?raw=true" alt="example"/>
+
+### ~~Результат получился чёрным~~
+~~Это значит, что сработал NSFW фильтр.~~
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/IamSFW.jpg?raw=true" alt="IamSFW" width="50%"/>
+
+### Img2Img
+
+Используйте эту вкладку, чтобы заменить лицо на уже готовом изображении (флажок "Swap in source image") или на сгенерированном на основе готового (флажок "Swap in generated image").
+
+Inpainting также работает, но замена лица происходит только в области маски.<br>Пожалуйста, используйте с опцией "Only masked" для "Inpaint area", если вы применяете "Upscaler". Иначе, используйте функцию увеличения (апскейла) через вкладку "Extras" или через опциональный загрузчик "Script" (внизу экрана), применив "SD upscale" или "Ultimate SD upscale".
+
+### Extras
+
+Начиная с версии 0.5.0, вы можете использовать ReActor через вкладку Extras, что даёт очень быструю производительность и возможность замены лиц в обход пайплайна SD, что иногда вызывает размытие или искажение деталей оригинального изображения
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/extras_tab.jpg?raw=true" alt="IamSFW"/>
+
+## API
+
+Вы можете использовать ReActor как со встроенным SD Webui API так и через внешнее API.
+
+Подробная инструкция **[здесь](/API.md)**.
+
+<a name="troubleshooting">
+
+## Устранение проблем
+
+### **I. "You should at least have one model in models directory"**
+
+Проверьте путь, где хранится модель "inswapper_128.onnx". Файл должен находиться в папке `stable-diffusion-webui\models\insightface`. Переместите модель туда, если она находится в какой-то иной директории.
+
+### **II. Какие-либо проблемы с установкой Insightface или прочих пакетов**
+
+(Для пользователей Mac M1/M2) Если вы получаете ошибки в ходе установки Insightface - читайте https://github.com/Gourieff/sd-webui-reactor/issues/42
+
+(Для пользователей Windows) Если VS C++ Build Tools или MS VS 2022 установлены но вы видите ошибки, связанные с отсутствием Insightface, попробуйте следующее:
+1. Закройте (остановите) SD WebUI Сервер и запустите его снова (возможно, не прошла инициализация пакета после его установки)
+   
+(Для пользователей любых ОС) Попробуйте следующее:
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. Перейдите в папку (Windows)`venv\Lib\site-packages` или (MacOS/Linux)`venv/lib/python3.10/site-packages`
+3. Если вы видите к-л папки с именами, начинающимися с `~` (например, "~rotobuf") - удалите их
+4. Перейдите в (Windows)`venv\Scripts` или (MacOS/Linux)`venv/bin`
+5. Откройте Терминал или Консоль (cmd) для этой папки и выполните `activate`
+6. Для начала обновите pip: `pip install -U pip`
+7. Далее:
+   - `pip install insightface==0.7.3`
+   - `pip install onnx`
+   - `pip install "onnxruntime-gpu>=1.16.1"`
+   - `pip install opencv-python`
+   - `pip install tqdm`
+8. Выполните `deactivate`, закройте Терминал или Консоль и запустите SD WebUI, ReActor должен запуститься без к-л проблем - если же нет, добро пожаловать в раздел "Issues".
+
+### **III. "TypeError: UpscaleOptions.init() got an unexpected keyword argument 'do_restore_first'"**
+
+Для начала отключите любые другие Roop-подобные расширения:
+- Перейдите в 'Extensions -> Installed' и снимите флажок с ненужных:
+  <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/roop-off.png?raw=true" alt="uncompatible-with-other-roop"/>
+- Нажмите 'Apply and restart UI'
+
+Альтернативные решения: 
+- https://github.com/Gourieff/sd-webui-reactor/issues/3#issuecomment-1615919243
+- https://github.com/Gourieff/sd-webui-reactor/issues/39#issuecomment-1666559134 (актуально для Vladmandic SD.Next)
+
+### **IV. "AttributeError: 'FaceSwapScript' object has no attribute 'enable'"**
+
+Отключите расширение "SD-CN-Animation" (или какое-либо другое, вызывающее конфликт)
+
+### **V. "INVALID_PROTOBUF : Load model from <...>\models\insightface\inswapper_128.onnx failed:Protobuf parsing failed" ИЛИ "AttributeError: 'NoneType' object has no attribute 'get'" ИЛИ "AttributeError: 'FaceSwapScript' object has no attribute 'save_original'"**
+
+Эта ошибка появляется, если что-то не так с файлом модели `inswapper_128.onnx`.
+
+Скачайте вручную по ссылке [here](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx)
+и сохраните в директорию `stable-diffusion-webui\models\insightface`, заменив имеющийся файл.
+
+### **VI. "ValueError: This ORT build has ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider'] enabled" ИЛИ "ValueError: This ORT build has ['AzureExecutionProvider', 'CPUExecutionProvider'] enabled"**
+
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. Перейдите в (Windows)`venv\Lib\site-packages` или (MacOS/Linux)`venv/lib/python3.10/site-packages` и посмотрите, если там папки с именам, начинающимися на "~" (например, "~rotobuf"), удалите их
+3. Перейдите в (Windows)`venv\Scripts` или (MacOS/Linux)`venv/bin`, откройте Терминал или Консоль (cmd) и выполните `activate`
+4. Затем:
+- `python -m pip install -U pip`
+- `pip uninstall -y onnxruntime onnxruntime-gpu onnxruntime-silicon onnxruntime-extensions`
+- `pip install "onnxruntime-gpu>=1.16.1"`
+
+Если это не помогло - значит какое-то другое расширение переустанавливает `onnxruntime` всякий раз, когда SD WebUI проверяет требования пакетов. Внимательно посмотрите список активных расширений. Некоторые расширения могут вызывать переустановку `onnxruntime-gpu` на версию `onnxruntime<1.16.1` при каждом запуске SD WebUI.<br>ORT 1.16.0 выкатили с ошибкой https://github.com/microsoft/onnxruntime/issues/17631 - не устанавливайте её!
+
+### **VII. "ImportError: cannot import name 'builder' from 'google.protobuf.internal'"**
+
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. Перейдите в (Windows)`venv\Lib\site-packages` или (MacOS/Linux)`venv/lib/python3.10/site-packages` и посмотрите, если там папки с именам, начинающимися на "~" (например, "~rotobuf"), удалите их
+3. Перейдите в папку "google" (внутри "site-packages") и удалите любые папки с именам, начинающимися на "~"
+4. Перейдите в (Windows)`venv\Scripts` или (MacOS/Linux)`venv/bin`, откройте Терминал или Консоль (cmd) и выполните `activate`
+5. Затем:
+- `python -m pip install -U pip`
+- `pip uninstall protobuf`
+- `pip install "protobuf>=3.20.3"`
+
+Если это не помгло - значит, есть к-л другое расширение, которое использует неподходящую версию пакета protobuf, и SD WebUI устанавливает эту версию при каждом запуске.
+
+<a name="insightfacebuild">
+
+### **VIII. (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. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. Скачайте готовый [пакет Insightface](https://github.com/Gourieff/sd-webui-reactor/raw/main/example/insightface-0.7.3-cp310-cp310-win_amd64.whl) и сохраните его в корневую директорию stable-diffusion-webui (или SD.Next) - туда, где лежит файл "webui-user.bat"
+3. Из корневой директории откройте Консоль (CMD) и выполните `.\venv\Scripts\activate`
+4. Обновите PIP: `python -m pip install -U pip`
+5. Затем установите Insightface: `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`
+6. Готово!
+
+### **IX. Ошибка обновления 07-Август-23**
+
+Если после очередного `git pull` вы получили сообщение: `Merge made by the 'recursive' strategy` и затем, когда проверяете статус репозитория через `git status`, вы видите `Your branch is ahead of 'origin/main' by`
+
+Выполните следующее:
+
+Внутри папки `extensions\sd-webui-reactor` запустите Терминал или Консоль (cmd) и затем:
+- `git reset f48bdf1 --hard`
+- `git pull`
+
+ИЛИ:
+
+Полностью удалите папку `sd-webui-reactor` внутри директории `extensions`, запустите Терминал или Консоль (cmd) и выполните `git clone https://github.com/Gourieff/sd-webui-reactor`
+
+### **X. Ошибки установки в StabilityMatrix**
+
+Если вы столкнулись с ошибками при установки данного расширения в пакетном менеджере StabilityMatrix - изучите информацию по ссылке: https://github.com/Gourieff/sd-webui-reactor/issues/129#issuecomment-1768210875
+
+<a name="updating">
+
+## Обновление
+
+Самый простой и удобный способ обновления SD WebUI и расширений: https://github.com/Gourieff/sd-webui-extensions-updater
+
+## ComfyUI
+
+Вы можете использовать ReActor с ComfyUI<br>
+Инструкция здесь: [ReActor Node](https://github.com/Gourieff/comfyui-reactor-node)
+
+<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 предварительно обученных моделей InsightFace.
+
+Обратите внимание: если вы собираетесь использовать это программное обеспечение в каких-либо коммерческих целях, вам необходимо будет обучить свои собстве��ные 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**

sd-webui-reactor-main/sd-webui-reactor-main/example/api_example.py

@@ -0,0 +1,103 @@
+import base64, io, requests, json
+from PIL import Image, PngImagePlugin
+from datetime import datetime, date
+
+address = 'http://127.0.0.1:7860'
+input_file = "extensions\sd-webui-reactor\example\IamSFW.jpg" # Input file path
+time = datetime.now()
+today = date.today()
+current_date = today.strftime('%Y-%m-%d')
+current_time = time.strftime('%H-%M-%S')
+output = 'outputs/api/output_'+current_date+'_'+current_time # Output file path + name index
+try:
+    im = Image.open(input_file)
+except Exception as e:
+    print(e)
+finally:
+    print(im)
+
+img_bytes = io.BytesIO()
+im.save(img_bytes, format='PNG') 
+img_base64 = base64.b64encode(img_bytes.getvalue()).decode('utf-8')
+
+# ReActor arguments:
+args=[
+    img_base64, #0
+    True, #1 Enable ReActor
+    '0', #2 Comma separated face number(s) from swap-source image
+    '0', #3 Comma separated face number(s) for target image (result)
+    'C:\stable-diffusion-webui\models\insightface\inswapper_128.onnx', #4 model path
+    'CodeFormer', #4 Restore Face: None; CodeFormer; GFPGAN
+    1, #5 Restore visibility value
+    True, #7 Restore face -> Upscale
+    '4x_NMKD-Superscale-SP_178000_G', #8 Upscaler (type 'None' if doesn't need), see full list here: http://127.0.0.1:7860/sdapi/v1/script-info -> reactor -> sec.8
+    2, #9 Upscaler scale value
+    1, #10 Upscaler visibility (if scale = 1)
+    False, #11 Swap in source image
+    True, #12 Swap in generated image
+    1, #13 Console Log Level (0 - min, 1 - med or 2 - max)
+    0, #14 Gender Detection (Source) (0 - No, 1 - Female Only, 2 - Male Only)
+    0, #15 Gender Detection (Target) (0 - No, 1 - Female Only, 2 - Male Only)
+    False, #16 Save the original image(s) made before swapping
+    0.8, #17 CodeFormer Weight (0 = maximum effect, 1 = minimum effect), 0.5 - by default
+    False, #18 Source Image Hash Check, True - by default
+    False, #19 Target Image Hash Check, False - by default
+    "CUDA", #20 CPU or CUDA (if you have it), CPU - by default
+    True, #21 Face Mask Correction
+    1, #22 Select Source, 0 - Image, 1 - Face Model, 2 - Source Folder
+    "elena.safetensors", #23 Filename of the face model (from "models/reactor/faces"), e.g. elena.safetensors, don't forger to set #22 to 1
+    "C:\PATH_TO_FACES_IMAGES", #24 The path to the folder containing source faces images, don't forger to set #22 to 2
+]
+
+# The args for ReActor can be found by 
+# requests.get(url=f'{address}/sdapi/v1/script-info')
+
+prompt = "(8k, best quality, masterpiece, highly detailed:1.1),realistic photo of fantastic happy woman,hairstyle of blonde and red short bob hair,modern clothing,cinematic lightning,film grain,dynamic pose,bokeh,dof"
+
+neg = "ng_deepnegative_v1_75t,(badhandv4:1.2),(worst quality:2),(low quality:2),(normal quality:2),lowres,(bad anatomy),(bad hands),((monochrome)),((grayscale)),(verybadimagenegative_v1.3:0.8),negative_hand-neg,badhandv4,nude,naked,(strabismus),cross-eye,heterochromia,((blurred))"
+
+payload = {
+    "prompt": prompt,
+    "negative_prompt": neg,
+    "seed": -1,
+    "sampler_name": "DPM++ 2M Karras",
+    "steps": 15,
+    "cfg_scale": 7,
+    "width": 512,
+    "height": 768,
+    "restore_faces": False,
+    "alwayson_scripts": {"reactor":{"args":args}}
+}
+
+try:
+    print('Working... Please wait...')
+    result = requests.post(url=f'{address}/sdapi/v1/txt2img', json=payload)
+except Exception as e:
+    print(e)
+finally:
+    print('Done! Saving file...')
+
+if result is not None:
+    r = result.json()
+    n = 0
+
+    for i in r['images']:
+        image = Image.open(io.BytesIO(base64.b64decode(i.split(",",1)[0])))
+
+        png_payload = {
+            "image": "data:image/png;base64," + i
+        }
+        response2 = requests.post(url=f'{address}/sdapi/v1/png-info', json=png_payload)
+
+        pnginfo = PngImagePlugin.PngInfo()
+        pnginfo.add_text("parameters", response2.json().get("info"))
+        output_file = output+'_'+str(n)+'_.png'
+        try:
+            image.save(output_file, pnginfo=pnginfo)
+        except Exception as e:
+            print(e)
+        finally:
+            print(f'{output_file} is saved\nAll is done!')
+        n += 1
+else:
+    print('Something went wrong...')

sd-webui-reactor-main/sd-webui-reactor-main/install.py

@@ -0,0 +1,147 @@
+import subprocess
+import os, sys
+from typing import Any
+import pkg_resources
+from tqdm import tqdm
+import urllib.request
+from packaging import version as pv
+
+try:
+    from modules.paths_internal import models_path
+except:
+    try:
+        from modules.paths import models_path
+    except:
+        model_path = os.path.abspath("models")
+
+
+BASE_PATH = os.path.dirname(os.path.realpath(__file__))
+
+req_file = os.path.join(BASE_PATH, "requirements.txt")
+
+models_dir = os.path.join(models_path, "insightface")
+
+# DEPRECATED:
+# models_dir_old = os.path.join(models_path, "roop")
+# if os.path.exists(models_dir_old):
+#     if not os.listdir(models_dir_old) and (not os.listdir(models_dir) or not os.path.exists(models_dir)):
+#         os.rename(models_dir_old, models_dir)
+#     else:
+#         import shutil
+#         for file in os.listdir(models_dir_old):
+#             shutil.move(os.path.join(models_dir_old, file), os.path.join(models_dir, file))
+#         try:
+#             os.rmdir(models_dir_old)
+#         except Exception as e:
+#             print(f"OSError: {e}")
+            
+model_url = "https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx"
+model_name = os.path.basename(model_url)
+model_path = os.path.join(models_dir, model_name)
+
+def pip_install(*args):
+    subprocess.run([sys.executable, "-m", "pip", "install", *args])
+
+def pip_uninstall(*args):
+    subprocess.run([sys.executable, "-m", "pip", "uninstall", "-y", *args])
+
+def is_installed (
+        package: str, version: str | None = None, strict: bool = True
+):
+    has_package = None
+    try:
+        has_package = pkg_resources.get_distribution(package)
+        if has_package 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 False
+    except Exception as e:
+        print(f"Error: {e}")
+        return False
+    
+def download(url, path):
+    request = urllib.request.urlopen(url)
+    total = int(request.headers.get('Content-Length', 0))
+    with tqdm(total=total, desc='Downloading...', 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):
+    os.makedirs(models_dir)
+
+if not os.path.exists(model_path):
+    download(model_url, model_path)
+
+print("ReActor preheating...", end=' ')
+
+last_device = None
+first_run = False
+available_devices = ["CPU", "CUDA"]
+
+try:
+    last_device_log = os.path.join(BASE_PATH, "last_device.txt")
+    with open(last_device_log) as f:
+        last_device = f.readline().strip()
+    if last_device not in available_devices:
+        last_device = None
+except:
+    last_device = "CPU"
+    first_run = True
+    with open(os.path.join(BASE_PATH, "last_device.txt"), "w") as txt:
+        txt.write(last_device)
+
+with open(req_file) as file:
+    install_count = 0
+    ort = "onnxruntime-gpu"
+    import torch
+    try:
+        if torch.cuda.is_available():
+            if first_run or last_device is None:
+                last_device = "CUDA"
+        elif torch.backends.mps.is_available() or hasattr(torch,'dml'):
+            ort = "onnxruntime"
+            # to prevent errors when ORT-GPU is installed but we want ORT instead:
+            if first_run:
+                pip_uninstall("onnxruntime", "onnxruntime-gpu")
+            # just in case:
+            if last_device == "CUDA" or last_device is None:
+                last_device = "CPU"
+        else:
+            if last_device == "CUDA" or last_device is None:
+                last_device = "CPU"
+        with open(os.path.join(BASE_PATH, "last_device.txt"), "w") as txt:
+            txt.write(last_device)
+        if not is_installed(ort,"1.16.1",False):
+            install_count += 1
+            pip_install(ort, "-U")
+    except Exception as e:
+        print(e)
+        print(f"\nERROR: Failed to install {ort} - ReActor won't start")
+        raise e
+    print(f"Device: {last_device}")
+    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):
+                install_count += 1
+                pip_install(package)
+        except Exception as e:
+            print(e)
+            print(f"\nERROR: Failed to install {package} - ReActor won't start")
+            raise e
+    if install_count > 0:
+        print(f"""
+        +---------------------------------+
+        --- PLEASE, RESTART the Server! ---
+        +---------------------------------+
+        """)

sd-webui-reactor-main/sd-webui-reactor-main/reactor_modules/reactor_mask.py

@@ -0,0 +1,176 @@
+import cv2
+import numpy as np
+from PIL import Image, ImageDraw
+
+from torchvision.transforms.functional import to_pil_image
+
+from scripts.reactor_logger import logger
+from scripts.reactor_inferencers.bisenet_mask_generator import BiSeNetMaskGenerator
+from scripts.reactor_entities.face import FaceArea
+from scripts.reactor_entities.rect import Rect
+
+
+colors = [
+    (255, 0, 0),
+    (0, 255, 0),
+    (0, 0, 255),
+    (255, 255, 0),
+    (255, 0, 255),
+    (0, 255, 255),
+    (255, 255, 255),
+    (128, 0, 0),
+    (0, 128, 0),
+    (128, 128, 0),
+    (0, 0, 128),
+    (0, 128, 128),
+]
+
+def color_generator(colors):
+    while True:
+        for color in colors:
+            yield color
+
+
+def process_face_image(
+        face: FaceArea,
+        **kwargs,
+    ) -> Image:
+        image = np.array(face.image)
+        overlay = image.copy()
+        color_iter = color_generator(colors)
+        cv2.rectangle(overlay, (0, 0), (image.shape[1], image.shape[0]), next(color_iter), -1)
+        l, t, r, b = face.face_area_on_image
+        cv2.rectangle(overlay, (l, t), (r, b), (0, 0, 0), 10)
+        if face.landmarks_on_image is not None:
+            for landmark in face.landmarks_on_image:
+                cv2.circle(overlay, (int(landmark.x), int(landmark.y)), 6, (0, 0, 0), 10)
+        alpha = 0.3
+        output = cv2.addWeighted(image, 1 - alpha, overlay, alpha, 0)
+        
+        return Image.fromarray(output)
+
+
+def apply_face_mask(swapped_image:np.ndarray,target_image:np.ndarray,target_face,entire_mask_image:np.array)->np.ndarray:
+    logger.status("Correcting Face Mask")
+    mask_generator =  BiSeNetMaskGenerator()
+    face = FaceArea(target_image,Rect.from_ndarray(np.array(target_face.bbox)),1.6,512,"")
+    face_image = np.array(face.image)
+    process_face_image(face)
+    face_area_on_image = face.face_area_on_image
+    mask = mask_generator.generate_mask(
+        face_image,
+        face_area_on_image=face_area_on_image,
+        affected_areas=["Face"],
+        mask_size=0,
+        use_minimal_area=True
+    )
+    mask = cv2.blur(mask, (12, 12))
+    # """entire_mask_image = np.zeros_like(target_image)"""
+    larger_mask = cv2.resize(mask, dsize=(face.width, face.height))
+    entire_mask_image[
+        face.top : face.bottom,
+        face.left : face.right,
+    ] = larger_mask
+   
+    result = Image.composite(Image.fromarray(swapped_image),Image.fromarray(target_image), Image.fromarray(entire_mask_image).convert("L"))
+    return np.array(result)
+
+
+def rotate_array(image: np.ndarray, angle: float) -> np.ndarray:
+    if angle == 0:
+        return image
+
+    h, w = image.shape[:2]
+    center = (w // 2, h // 2)
+
+    M = cv2.getRotationMatrix2D(center, angle, 1.0)
+    return cv2.warpAffine(image, M, (w, h))
+
+
+def rotate_image(image: Image, angle: float) -> Image:
+    if angle == 0:
+        return image
+    return Image.fromarray(rotate_array(np.array(image), angle))
+
+
+def correct_face_tilt(angle: float) -> bool:
+    angle = abs(angle)
+    if angle > 180:
+        angle = 360 - angle
+    return angle > 40
+
+
+def _dilate(arr: np.ndarray, value: int) -> np.ndarray:
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (value, value))
+    return cv2.dilate(arr, kernel, iterations=1)
+
+
+def _erode(arr: np.ndarray, value: int) -> np.ndarray:
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (value, value))
+    return cv2.erode(arr, kernel, iterations=1)
+
+
+def dilate_erode(img: Image.Image, value: int) -> Image.Image:
+    """
+    The dilate_erode function takes an image and a value.
+    If the value is positive, it dilates the image by that amount.
+    If the value is negative, it erodes the image by that amount.
+
+    Parameters
+    ----------
+        img: PIL.Image.Image
+            the image to be processed
+        value: int
+            kernel size of dilation or erosion
+
+    Returns
+    -------
+        PIL.Image.Image
+            The image that has been dilated or eroded
+    """
+    if value == 0:
+        return img
+
+    arr = np.array(img)
+    arr = _dilate(arr, value) if value > 0 else _erode(arr, -value)
+
+    return Image.fromarray(arr)
+
+def mask_to_pil(masks, shape: tuple[int, int]) -> list[Image.Image]:
+    """
+    Parameters
+    ----------
+    masks: torch.Tensor, dtype=torch.float32, shape=(N, H, W).
+        The device can be CUDA, but `to_pil_image` takes care of that.
+
+    shape: tuple[int, int]
+        (width, height) of the original image
+    """
+    n = masks.shape[0]
+    return [to_pil_image(masks[i], mode="L").resize(shape) for i in range(n)]
+
+def create_mask_from_bbox(
+    bboxes: list[list[float]], shape: tuple[int, int]
+) -> list[Image.Image]:
+    """
+    Parameters
+    ----------
+        bboxes: list[list[float]]
+            list of [x1, y1, x2, y2]
+            bounding boxes
+        shape: tuple[int, int]
+            shape of the image (width, height)
+
+    Returns
+    -------
+        masks: list[Image.Image]
+        A list of masks
+
+    """
+    masks = []
+    for bbox in bboxes:
+        mask = Image.new("L", shape, 0)
+        mask_draw = ImageDraw.Draw(mask)
+        mask_draw.rectangle(bbox, fill=255)
+        masks.append(mask)
+    return masks

sd-webui-reactor-main/sd-webui-reactor-main/reactor_ui/__init__.py

@@ -0,0 +1,4 @@
+import reactor_ui.reactor_upscale_ui as ui_upscale
+import reactor_ui.reactor_tools_ui as ui_tools
+import reactor_ui.reactor_settings_ui as ui_settings
+import reactor_ui.reactor_main_ui as ui_main

sd-webui-reactor-main/sd-webui-reactor-main/reactor_ui/reactor_main_ui.py

@@ -0,0 +1,182 @@
+import gradio as gr
+from scripts.reactor_helpers import (
+    get_model_names, 
+    get_facemodels
+)
+from scripts.reactor_swapper import (
+    clear_faces_list,
+)
+from modules import shared
+
+SAVE_ORIGINAL: bool = False
+
+def update_fm_list(selected: str):
+    return gr.Dropdown.update(
+        value=selected, choices=get_model_names(get_facemodels)
+    )
+
+# TAB MAIN
+def show(is_img2img: bool, show_br: bool = True, **msgs):
+
+    def on_select_source(selected: bool, evt: gr.SelectData):
+        global SAVE_ORIGINAL
+        if evt.index == 2:
+            if SAVE_ORIGINAL != selected:
+                SAVE_ORIGINAL = selected
+            return {
+                control_col_1: gr.Column.update(visible=False),
+                control_col_2: gr.Column.update(visible=False),
+                control_col_3: gr.Column.update(visible=True),
+                save_original: gr.Checkbox.update(value=False,visible=False),
+                imgs_hash_clear: gr.Button.update(visible=True)
+            }
+        if evt.index == 0:
+            return {
+                control_col_1: gr.Column.update(visible=True),
+                control_col_2: gr.Column.update(visible=False),
+                control_col_3: gr.Column.update(visible=False),
+                save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
+                imgs_hash_clear: gr.Button.update(visible=False)
+            }
+        if evt.index == 1:
+            return {
+                control_col_1: gr.Column.update(visible=False),
+                control_col_2: gr.Column.update(visible=True),
+                control_col_3: gr.Column.update(visible=False),
+                save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
+                imgs_hash_clear: gr.Button.update(visible=False)
+            }
+        
+    progressbar_area = gr.Markdown("")
+    with gr.Tab("Main"):
+        with gr.Column():
+            with gr.Row():
+                select_source = gr.Radio(
+                    ["Image(s)","Face Model","Folder"],
+                    value="Image(s)",
+                    label="Select Source",
+                    type="index",
+                    scale=1,
+                )
+                with gr.Column(visible=False) as control_col_2:
+                    with gr.Row():
+                        face_models = get_model_names(get_facemodels)
+                        face_model = gr.Dropdown(
+                            choices=face_models,
+                            label="Choose Face Model",
+                            value="None",
+                            scale=1,
+                        )
+                        fm_update = gr.Button(
+                            value="🔄",
+                            variant="tool",
+                        )
+                        fm_update.click(
+                            update_fm_list, 
+                            inputs=[face_model],
+                            outputs=[face_model],
+                        )
+                imgs_hash_clear = gr.Button(
+                    value="Clear Source Images Hash",
+                    scale=1,
+                    visible=False,
+                )
+                imgs_hash_clear.click(clear_faces_list,None,[progressbar_area])
+            gr.Markdown("<br>", visible=show_br)
+            with gr.Column(visible=True) as control_col_1:
+                gr.Markdown("<center>🔽🔽🔽 Single Image has priority when both Areas in use 🔽🔽🔽</center>")
+                with gr.Row():
+                    img = gr.Image(
+                        type="pil",
+                        label="Single Source Image",
+                    )
+                    imgs = gr.Files(
+                        label=f"Multiple Source Images{msgs['extra_multiple_source']}",
+                        file_types=["image"],
+                    )
+            with gr.Column(visible=False) as control_col_3:
+                gr.Markdown("<span style='display:block;text-align:right;padding-right:3px;margin: -15px 0;font-size:1.1em'><sup>Clear Hash if you see the previous face was swapped instead of the new one</sup></span>")
+                source_folder = gr.Textbox(
+                    value="",
+                    placeholder="Paste here the path to the folder containing source faces images",
+                    label=f"Source Folder{msgs['extra_multiple_source']}",
+                )
+            setattr(face_model, "do_not_save_to_config", True)
+            if is_img2img:
+                save_original = gr.Checkbox(
+                    False,
+                    label="Save Original (Swap in generated only)", 
+                    info="Save the original image(s) made before swapping (it always saves Original when you use Multiple Images or Folder)"
+                )
+            else:
+                save_original = gr.Checkbox(
+                    False,
+                    label="Save Original", 
+                    info="Save the original image(s) made before swapping (it always saves Original when you use Multiple Images or Folder)",
+                    visible=show_br
+                )
+            # imgs.upload(on_files_upload_uncheck_so,[save_original],[save_original],show_progress=False)
+            # imgs.clear(on_files_clear,None,[save_original],show_progress=False)
+            imgs.clear(clear_faces_list,None,None,show_progress=False)
+            mask_face = gr.Checkbox(
+                False,
+                label="Face Mask Correction", 
+                info="Apply this option if you see some pixelation around face contours"
+            )
+            gr.Markdown("<br>", visible=show_br)
+            gr.Markdown("Source Image (above):")
+            with gr.Row():
+                source_faces_index = gr.Textbox(
+                    value="0",
+                    placeholder="Which face(s) to use as Source (comma separated)",
+                    label="Comma separated face number(s); Example: 0,2,1",
+                )
+                gender_source = gr.Radio(
+                    ["No", "Female Only", "Male Only"],
+                    value="No",
+                    label="Gender Detection (Source)",
+                    type="index",
+                )
+            gr.Markdown("<br>", visible=show_br)
+            gr.Markdown("Target Image (result):")
+            with gr.Row():
+                faces_index = gr.Textbox(
+                    value="0",
+                    placeholder="Which face(s) to Swap into Target (comma separated)",
+                    label="Comma separated face number(s); Example: 1,0,2",
+                )
+                gender_target = gr.Radio(
+                    ["No", "Female Only", "Male Only"],
+                    value="No",
+                    label="Gender Detection (Target)",
+                    type="index",
+                )
+            gr.Markdown("<br>", visible=show_br)
+            with gr.Row():
+                face_restorer_name = gr.Radio(
+                    label="Restore Face",
+                    choices=["None"] + [x.name() for x in shared.face_restorers],
+                    value=shared.face_restorers[0].name(),
+                    type="value",
+                )
+                with gr.Column():
+                    face_restorer_visibility = gr.Slider(
+                        0, 1, 1, step=0.1, label="Restore Face Visibility"
+                    )
+                    codeformer_weight = gr.Slider(
+                        0, 1, 0.5, step=0.1, label="CodeFormer Weight", info="0 = maximum effect, 1 = minimum effect"
+                    )
+            gr.Markdown("<br>", visible=show_br)
+            swap_in_source = gr.Checkbox(
+                False,
+                label="Swap in source image",
+                visible=is_img2img,
+            )
+            swap_in_generated = gr.Checkbox(
+                True,
+                label="Swap in generated image",
+                visible=is_img2img,
+            )
+    select_source.select(on_select_source,[save_original],[control_col_1,control_col_2,control_col_3,save_original,imgs_hash_clear],show_progress=False)
+
+    return img, imgs, select_source, face_model, source_folder, save_original, mask_face, source_faces_index, gender_source, faces_index, gender_target, face_restorer_name, face_restorer_visibility, codeformer_weight, swap_in_source, swap_in_generated

sd-webui-reactor-main/sd-webui-reactor-main/reactor_ui/reactor_settings_ui.py

@@ -0,0 +1,77 @@
+import gradio as gr
+from scripts.reactor_logger import logger
+from scripts.reactor_helpers import get_models, set_Device
+from scripts.reactor_globals import DEVICE, DEVICE_LIST
+try:
+    import torch.cuda as cuda
+    EP_is_visible = True if cuda.is_available() else False
+except:
+    EP_is_visible = False
+
+def update_models_list(selected: str):
+    return gr.Dropdown.update(
+        value=selected, choices=get_models()
+    )
+
+def show(hash_check_block: bool = True):
+    # TAB SETTINGS
+    with gr.Tab("Settings"):
+        models = get_models()
+        with gr.Row(visible=EP_is_visible):
+            device = gr.Radio(
+                label="Execution Provider",
+                choices=DEVICE_LIST,
+                value=DEVICE,
+                type="value",
+                info="If you already run 'Generate' - RESTART is required to apply. Click 'Save', (A1111) Extensions Tab -> 'Apply and restart UI' or (SD.Next) close the Server and start it again",
+                scale=2,
+            )
+            save_device_btn = gr.Button("Save", scale=0)
+        save = gr.Markdown("", visible=EP_is_visible)
+        setattr(device, "do_not_save_to_config", True)
+        save_device_btn.click(
+            set_Device,
+            inputs=[device],
+            outputs=[save],
+        )
+        with gr.Row():
+            if len(models) == 0:
+                logger.warning(
+                    "You should at least have one model in models directory, please read the doc here: https://github.com/Gourieff/sd-webui-reactor/"
+                )
+                model = gr.Dropdown(
+                    choices=models,
+                    label="Model not found, please download one and refresh the list"
+                )
+            else:
+                model = gr.Dropdown(
+                    choices=models, label="Model", value=models[0]
+                )
+            models_update = gr.Button(
+                value="🔄",
+                variant="tool",
+            )
+            models_update.click(
+                update_models_list, 
+                inputs=[model],
+                outputs=[model],
+            )
+            console_logging_level = gr.Radio(
+                ["No log", "Minimum", "Default"],
+                value="Minimum",
+                label="Console Log Level",
+                type="index"
+            )
+        gr.Markdown("<br>", visible=hash_check_block)
+        with gr.Row(visible=hash_check_block):
+            source_hash_check = gr.Checkbox(
+                True,
+                label="Source Image Hash Check",
+                info="Recommended to keep it ON. Processing is faster when Source Image is the same."
+            )
+            target_hash_check = gr.Checkbox(
+                False,
+                label="Target Image Hash Check",
+                info="Affects if you use Extras tab or img2img with only 'Swap in source image' on."
+            )
+    return model, device, console_logging_level, source_hash_check, target_hash_check

sd-webui-reactor-main/sd-webui-reactor-main/reactor_ui/reactor_tools_ui.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from scripts.reactor_swapper import build_face_model
+
+# TAB TOOLS
+def show():
+    with gr.Tab("Tools"):
+        with gr.Tab("Face Models"):
+            gr.Markdown("Load an image containing one person, name it and click 'Build and Save'")
+            img_fm = gr.Image(
+                type="pil",
+                label="Load Image to build Face Model",
+            )
+            with gr.Row(equal_height=True):
+                fm_name = gr.Textbox(
+                    value="",
+                    placeholder="Please type any name (e.g. Elena)",
+                    label="Face Model Name",
+                )
+                save_fm_btn = gr.Button("Build and Save")
+            save_fm = gr.Markdown("You can find saved models in 'models/reactor/faces'")
+            save_fm_btn.click(
+                build_face_model,
+                inputs=[img_fm, fm_name],
+                outputs=[save_fm],
+            )

sd-webui-reactor-main/sd-webui-reactor-main/reactor_ui/reactor_upscale_ui.py

@@ -0,0 +1,39 @@
+import gradio as gr
+from modules import shared
+
+def update_upscalers_list(selected: str):
+    return gr.Dropdown.update(
+        value=selected, choices=[upscaler.name for upscaler in shared.sd_upscalers]
+    )
+
+# TAB UPSCALE
+def show(show_br: bool = True):
+    with gr.Tab("Upscale"):
+        restore_first = gr.Checkbox(
+            True,
+            label="1. Restore Face -> 2. Upscale (-Uncheck- if you want vice versa)",
+            info="Postprocessing Order"
+        )
+        with gr.Row():
+            upscaler_name = gr.Dropdown(
+                choices=[upscaler.name for upscaler in shared.sd_upscalers],
+                label="Upscaler",
+                value="None",
+                info="Won't scale if you choose -Swap in Source- via img2img, only 1x-postprocessing will affect (texturing, denoising, restyling etc.)"
+            )
+            upscalers_update = gr.Button(
+                value="🔄",
+                variant="tool",
+            )
+        upscalers_update.click(
+            update_upscalers_list, 
+            inputs=[upscaler_name],
+            outputs=[upscaler_name],
+        )
+        gr.Markdown("<br>", visible=show_br)
+        with gr.Row():
+            upscaler_scale = gr.Slider(1, 8, 1, step=0.1, label="Scale by")
+            upscaler_visibility = gr.Slider(
+                0, 1, 1, step=0.1, label="Upscaler Visibility (if scale = 1)"
+            )
+    return restore_first, upscaler_name, upscaler_scale, upscaler_visibility

sd-webui-reactor-main/sd-webui-reactor-main/requirements.txt

@@ -0,0 +1,3 @@
+insightface==0.7.3
+onnx>=1.14.0
+opencv-python>=4.7.0.72

sd-webui-reactor-main/sd-webui-reactor-main/scripts/console_log_patch.py

@@ -0,0 +1,120 @@
+import os.path as osp
+import glob
+import logging
+import insightface
+from insightface.model_zoo.model_zoo import ModelRouter, PickableInferenceSession
+from insightface.model_zoo.retinaface import RetinaFace
+from insightface.model_zoo.landmark import Landmark
+from insightface.model_zoo.attribute import Attribute
+from insightface.model_zoo.inswapper import INSwapper
+from insightface.model_zoo.arcface_onnx import ArcFaceONNX
+from insightface.app import FaceAnalysis
+from insightface.utils import DEFAULT_MP_NAME, ensure_available
+from insightface.model_zoo import model_zoo
+import onnxruntime
+import onnx
+from onnx import numpy_helper
+from scripts.reactor_logger import logger
+
+
+def patched_get_model(self, **kwargs):
+    session = PickableInferenceSession(self.onnx_file, **kwargs)
+    inputs = session.get_inputs()
+    input_cfg = inputs[0]
+    input_shape = input_cfg.shape
+    outputs = session.get_outputs()
+
+    if len(outputs) >= 5:
+        return RetinaFace(model_file=self.onnx_file, session=session)
+    elif input_shape[2] == 192 and input_shape[3] == 192:
+        return Landmark(model_file=self.onnx_file, session=session)
+    elif input_shape[2] == 96 and input_shape[3] == 96:
+        return Attribute(model_file=self.onnx_file, session=session)
+    elif len(inputs) == 2 and input_shape[2] == 128 and input_shape[3] == 128:
+        return INSwapper(model_file=self.onnx_file, session=session)
+    elif input_shape[2] == input_shape[3] and input_shape[2] >= 112 and input_shape[2] % 16 == 0:
+        return ArcFaceONNX(model_file=self.onnx_file, session=session)
+    else:
+        return None
+
+
+def patched_faceanalysis_init(self, name=DEFAULT_MP_NAME, root='~/.insightface', allowed_modules=None, **kwargs):
+    onnxruntime.set_default_logger_severity(3)
+    self.models = {}
+    self.model_dir = ensure_available('models', name, root=root)
+    onnx_files = glob.glob(osp.join(self.model_dir, '*.onnx'))
+    onnx_files = sorted(onnx_files)
+    for onnx_file in onnx_files:
+        model = model_zoo.get_model(onnx_file, **kwargs)
+        if model is None:
+            print('model not recognized:', onnx_file)
+        elif allowed_modules is not None and model.taskname not in allowed_modules:
+            print('model ignore:', onnx_file, model.taskname)
+            del model
+        elif model.taskname not in self.models and (allowed_modules is None or model.taskname in allowed_modules):
+            self.models[model.taskname] = model
+        else:
+            print('duplicated model task type, ignore:', onnx_file, model.taskname)
+            del model
+    assert 'detection' in self.models
+    self.det_model = self.models['detection']
+
+
+def patched_faceanalysis_prepare(self, ctx_id, det_thresh=0.5, det_size=(640, 640)):
+    self.det_thresh = det_thresh
+    assert det_size is not None
+    self.det_size = det_size
+    for taskname, model in self.models.items():
+        if taskname == 'detection':
+            model.prepare(ctx_id, input_size=det_size, det_thresh=det_thresh)
+        else:
+            model.prepare(ctx_id)
+
+
+def patched_inswapper_init(self, model_file=None, session=None):
+    self.model_file = model_file
+    self.session = session
+    model = onnx.load(self.model_file)
+    graph = model.graph
+    self.emap = numpy_helper.to_array(graph.initializer[-1])
+    self.input_mean = 0.0
+    self.input_std = 255.0
+    if self.session is None:
+        self.session = onnxruntime.InferenceSession(self.model_file, None)
+    inputs = self.session.get_inputs()
+    self.input_names = []
+    for inp in inputs:
+        self.input_names.append(inp.name)
+    outputs = self.session.get_outputs()
+    output_names = []
+    for out in outputs:
+        output_names.append(out.name)
+    self.output_names = output_names
+    assert len(self.output_names) == 1
+    input_cfg = inputs[0]
+    input_shape = input_cfg.shape
+    self.input_shape = input_shape
+    self.input_size = tuple(input_shape[2:4][::-1])
+
+
+def patch_insightface(get_model, faceanalysis_init, faceanalysis_prepare, inswapper_init):
+    insightface.model_zoo.model_zoo.ModelRouter.get_model = get_model
+    insightface.app.FaceAnalysis.__init__ = faceanalysis_init
+    insightface.app.FaceAnalysis.prepare = faceanalysis_prepare
+    insightface.model_zoo.inswapper.INSwapper.__init__ = inswapper_init
+
+
+original_functions = [ModelRouter.get_model, FaceAnalysis.__init__, FaceAnalysis.prepare, INSwapper.__init__]
+patched_functions = [patched_get_model, patched_faceanalysis_init, patched_faceanalysis_prepare, patched_inswapper_init]
+
+
+def apply_logging_patch(console_logging_level):
+    if console_logging_level == 0:
+        patch_insightface(*patched_functions)
+        logger.setLevel(logging.WARNING)
+    elif console_logging_level == 1:
+        patch_insightface(*patched_functions)
+        logger.setLevel(logging.STATUS)
+    elif console_logging_level == 2:
+        patch_insightface(*original_functions)
+        logger.setLevel(logging.INFO)

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_api.py

@@ -0,0 +1,118 @@
+'''
+Thanks SpenserCai for the original version of the roop api script
+-----------------------------------
+--- ReActor External API v1.0.1 ---
+-----------------------------------
+'''
+import os, glob
+from datetime import datetime, date
+from fastapi import FastAPI, Body
+
+# from modules.api.models import *
+from modules import scripts, shared
+from modules.api import api
+
+import gradio as gr
+
+from scripts.reactor_swapper import EnhancementOptions, swap_face
+from scripts.reactor_logger import logger
+
+
+def default_file_path():
+    time = datetime.now()
+    today = date.today()
+    current_date = today.strftime('%Y-%m-%d')
+    current_time = time.strftime('%H-%M-%S')
+    output_file = 'output_'+current_date+'_'+current_time+'.png'
+    return os.path.join(os.path.abspath("outputs/api"), output_file)
+
+def get_face_restorer(name):
+    for restorer in shared.face_restorers:
+        if restorer.name() == name:
+            return restorer
+    return None
+
+def get_upscaler(name):
+    for upscaler in shared.sd_upscalers:
+        if upscaler.name == name:
+            return upscaler
+    return None
+
+def get_models():
+    models_path = os.path.join(scripts.basedir(), "models/insightface/*")
+    models = glob.glob(models_path)
+    models = [x for x in models if x.endswith(".onnx") or x.endswith(".pth")]
+    return models
+
+def get_full_model(model_name):
+    models = get_models()
+    for model in models:
+        model_path = os.path.split(model)
+        if model_path[1] == model_name:
+            return model
+    return None
+
+def reactor_api(_: gr.Blocks, app: FastAPI):
+    @app.post("/reactor/image")
+    async def reactor_image(
+        source_image: str = Body("",title="Source Face Image"),
+        target_image: str = Body("",title="Target Image"),
+        source_faces_index: list[int] = Body([0],title="Comma separated face number(s) from swap-source image"),
+        face_index: list[int] = Body([0],title="Comma separated face number(s) for target image (result)"),
+        upscaler: str = Body("None",title="Upscaler"),
+        scale: int = Body(1,title="Scale by"),
+        upscale_visibility: float = Body(1,title="Upscaler visibility (if scale = 1)"),
+        face_restorer: str = Body("None",title="Restore Face: 0 - None; 1 - CodeFormer; 2 - GFPGA"),
+        restorer_visibility: float = Body(1,title="Restore visibility value"),
+        codeformer_weight: float = Body(0.5,title="CodeFormer Weight"),
+        restore_first: int = Body(1,title="Restore face -> Then upscale, 1 - True, 0 - False"),
+        model: str = Body("inswapper_128.onnx",title="Model"),
+        gender_source: int = Body(0,title="Gender Detection (Source) (0 - No, 1 - Female Only, 2 - Male Only)"),
+        gender_target: int = Body(0,title="Gender Detection (Target) (0 - No, 1 - Female Only, 2 - Male Only)"),
+        save_to_file: int = Body(0,title="Save Result to file, 0 - No, 1 - Yes"),
+        result_file_path: str = Body("",title="(if 'save_to_file = 1') Result file path"),
+        device: str = Body("CPU",title="CPU or CUDA (if you have it)"),
+        mask_face: int = Body(0,title="Face Mask Correction, 1 - True, 0 - False"),
+        select_source: int = Body(0,title="Select Source, 0 - Image, 1 - Face Model, 2 - Source Folder"),
+        face_model: str = Body("None",title="Filename of the face model (from 'models/reactor/faces'), e.g. elena.safetensors"),
+        source_folder: str = Body("",title="The path to the folder containing source faces images")
+    ):
+        s_image = api.decode_base64_to_image(source_image)
+        t_image = api.decode_base64_to_image(target_image)
+        sf_index = source_faces_index
+        f_index = face_index
+        gender_s = gender_source
+        gender_t = gender_target
+        restore_first_bool = True if restore_first == 1 else False
+        mask_face = True if mask_face == 1 else False
+        up_options = EnhancementOptions(do_restore_first=restore_first_bool, scale=scale, upscaler=get_upscaler(upscaler), upscale_visibility=upscale_visibility,face_restorer=get_face_restorer(face_restorer),restorer_visibility=restorer_visibility,codeformer_weight=codeformer_weight)
+        use_model = get_full_model(model)
+        if use_model is None:
+            Exception("Model not found")
+        result = swap_face(s_image, t_image, use_model, sf_index, f_index, up_options, gender_s, gender_t, True, True, device, mask_face, select_source, face_model, source_folder, None)
+        if save_to_file == 1:
+            if result_file_path == "":
+                result_file_path = default_file_path()
+            try:
+                result[0].save(result_file_path, format='PNG')
+                logger.status("Result has been saved to: %s", result_file_path)
+            except Exception as e:
+                logger.error("Error while saving result: %s",e)
+        return {"image": api.encode_pil_to_base64(result[0])}
+
+    @app.get("/reactor/models")
+    async def reactor_models():
+        model_names = [os.path.split(model)[1] for model in get_models()]
+        return {"models": model_names}
+    
+    @app.get("/reactor/upscalers")
+    async def reactor_upscalers():
+        names = [upscaler.name for upscaler in shared.sd_upscalers]
+        return {"upscalers": names}
+
+try:
+    import modules.script_callbacks as script_callbacks
+
+    script_callbacks.on_app_started(reactor_api)
+except:
+    pass

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_entities/face.py

@@ -0,0 +1,147 @@
+import traceback
+
+import cv2
+import numpy as np
+from modules import images
+from PIL import Image
+
+
+from scripts.reactor_entities.rect import Point, Rect
+
+
+class FaceArea:
+    def __init__(self, entire_image: np.ndarray, face_area: Rect, face_margin: float, face_size: int, upscaler: str):
+        self.face_area = face_area
+        self.center = face_area.center
+        left, top, right, bottom = face_area.to_square()
+
+        self.left, self.top, self.right, self.bottom = self.__ensure_margin(
+            left, top, right, bottom, entire_image, face_margin
+        )
+
+        self.width = self.right - self.left
+        self.height = self.bottom - self.top
+
+        self.image = self.__crop_face_image(entire_image, face_size, upscaler)
+        self.face_size = face_size
+        self.scale_factor = face_size / self.width
+        self.face_area_on_image = self.__get_face_area_on_image()
+        self.landmarks_on_image = self.__get_landmarks_on_image()
+
+    def __get_face_area_on_image(self):
+        left = int((self.face_area.left - self.left) * self.scale_factor)
+        top = int((self.face_area.top - self.top) * self.scale_factor)
+        right = int((self.face_area.right - self.left) * self.scale_factor)
+        bottom = int((self.face_area.bottom - self.top) * self.scale_factor)
+        return self.__clip_values(left, top, right, bottom)
+
+    def __get_landmarks_on_image(self):
+        landmarks = []
+        if self.face_area.landmarks is not None:
+            for landmark in self.face_area.landmarks:
+                landmarks.append(
+                    Point(
+                        int((landmark.x - self.left) * self.scale_factor),
+                        int((landmark.y - self.top) * self.scale_factor),
+                    )
+                )
+        return landmarks
+
+    def __crop_face_image(self, entire_image: np.ndarray, face_size: int, upscaler: str):
+        cropped = entire_image[self.top : self.bottom, self.left : self.right, :]
+        if upscaler:
+            return images.resize_image(0, Image.fromarray(cropped), face_size, face_size, upscaler)
+        else:
+            return Image.fromarray(cv2.resize(cropped, dsize=(face_size, face_size)))
+
+    def __ensure_margin(self, left: int, top: int, right: int, bottom: int, entire_image: np.ndarray, margin: float):
+        entire_height, entire_width = entire_image.shape[:2]
+
+        side_length = right - left
+        margin = min(min(entire_height, entire_width) / side_length, margin)
+        diff = int((side_length * margin - side_length) / 2)
+
+        top = top - diff
+        bottom = bottom + diff
+        left = left - diff
+        right = right + diff
+
+        if top < 0:
+            bottom = bottom - top
+            top = 0
+        if left < 0:
+            right = right - left
+            left = 0
+
+        if bottom > entire_height:
+            top = top - (bottom - entire_height)
+            bottom = entire_height
+        if right > entire_width:
+            left = left - (right - entire_width)
+            right = entire_width
+
+        return left, top, right, bottom
+
+    def get_angle(self) -> float:
+        landmarks = getattr(self.face_area, "landmarks", None)
+        if landmarks is None:
+            return 0
+
+        eye1 = getattr(landmarks, "eye1", None)
+        eye2 = getattr(landmarks, "eye2", None)
+        if eye2 is None or eye1 is None:
+            return 0
+
+        try:
+            dx = eye2.x - eye1.x
+            dy = eye2.y - eye1.y
+            if dx == 0:
+                dx = 1
+            angle = np.arctan(dy / dx) * 180 / np.pi
+
+            if dx < 0:
+                angle = (angle + 180) % 360
+            return angle
+        except Exception:
+            print(traceback.format_exc())
+            return 0
+
+    def rotate_face_area_on_image(self, angle: float):
+        center = [
+            (self.face_area_on_image[0] + self.face_area_on_image[2]) / 2,
+            (self.face_area_on_image[1] + self.face_area_on_image[3]) / 2,
+        ]
+
+        points = [
+            [self.face_area_on_image[0], self.face_area_on_image[1]],
+            [self.face_area_on_image[2], self.face_area_on_image[3]],
+        ]
+
+        angle = np.radians(angle)
+        rot_matrix = np.array([[np.cos(angle), -np.sin(angle)], [np.sin(angle), np.cos(angle)]])
+
+        points = np.array(points) - center
+        points = np.dot(points, rot_matrix.T)
+        points += center
+        left, top, right, bottom = (int(points[0][0]), int(points[0][1]), int(points[1][0]), int(points[1][1]))
+
+        left, right = (right, left) if left > right else (left, right)
+        top, bottom = (bottom, top) if top > bottom else (top, bottom)
+
+        width, height = right - left, bottom - top
+        if width < height:
+            left, right = left - (height - width) // 2, right + (height - width) // 2
+        elif height < width:
+            top, bottom = top - (width - height) // 2, bottom + (width - height) // 2
+        return self.__clip_values(left, top, right, bottom)
+
+    def __clip_values(self, *args):
+        result = []
+        for val in args:
+            if val < 0:
+                result.append(0)
+            elif val > self.face_size:
+                result.append(self.face_size)
+            else:
+                result.append(val)
+        return tuple(result)

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_entities/rect.py

@@ -0,0 +1,78 @@
+from typing import Dict, NamedTuple, Tuple
+
+import numpy as np
+
+
+class Point(NamedTuple):
+    x: int
+    y: int
+
+
+class Landmarks(NamedTuple):
+    eye1: Point
+    eye2: Point
+    nose: Point
+    mouth1: Point
+    mouth2: Point
+
+
+class Rect:
+    def __init__(
+        self,
+        left: int,
+        top: int,
+        right: int,
+        bottom: int,
+        tag: str = "face",
+        landmarks: Landmarks = None,
+        attributes: Dict[str, str] = {},
+    ) -> None:
+        self.tag = tag
+        self.left = left
+        self.top = top
+        self.right = right
+        self.bottom = bottom
+        self.center = int((right + left) / 2)
+        self.middle = int((top + bottom) / 2)
+        self.width = right - left
+        self.height = bottom - top
+        self.size = self.width * self.height
+        self.landmarks = landmarks
+        self.attributes = attributes
+
+    @classmethod
+    def from_ndarray(
+        cls,
+        face_box: np.ndarray,
+        tag: str = "face",
+        landmarks: Landmarks = None,
+        attributes: Dict[str, str] = {},
+    ) -> "Rect":
+        left, top, right, bottom, *_ = list(map(int, face_box))
+        return cls(left, top, right, bottom, tag, landmarks, attributes)
+
+    def to_tuple(self) -> Tuple[int, int, int, int]:
+        return self.left, self.top, self.right, self.bottom
+
+    def to_square(self):
+        left, top, right, bottom = self.to_tuple()
+
+        width = right - left
+        height = bottom - top
+
+        if width % 2 == 1:
+            right = right + 1
+            width = width + 1
+        if height % 2 == 1:
+            bottom = bottom + 1
+            height = height + 1
+
+        diff = int(abs(width - height) / 2)
+        if width > height:
+            top = top - diff
+            bottom = bottom + diff
+        else:
+            left = left - diff
+            right = right + diff
+
+        return left, top, right, bottom

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_faceswap.py

@@ -0,0 +1,577 @@
+import os, glob
+import gradio as gr
+from PIL import Image
+
+from typing import List
+
+import modules.scripts as scripts
+from modules.upscaler import Upscaler, UpscalerData
+from modules import scripts, shared, images, scripts_postprocessing
+from modules.processing import (
+    Processed,
+    StableDiffusionProcessing,
+    StableDiffusionProcessingImg2Img,
+)
+from modules.face_restoration import FaceRestoration
+from modules.images import save_image
+
+from reactor_ui import ui_main, ui_upscale, ui_tools, ui_settings
+from scripts.reactor_logger import logger
+from scripts.reactor_swapper import (
+    EnhancementOptions, 
+    swap_face, 
+    check_process_halt, 
+    reset_messaged,
+)
+from scripts.reactor_version import version_flag, app_title
+from scripts.console_log_patch import apply_logging_patch
+from scripts.reactor_helpers import (
+    make_grid, 
+    set_Device, 
+)
+from scripts.reactor_globals import SWAPPER_MODELS_PATH #, DEVICE, DEVICE_LIST
+
+
+class FaceSwapScript(scripts.Script):
+    def title(self):
+        return f"{app_title}"
+
+    def show(self, is_img2img):
+        return scripts.AlwaysVisible
+
+    def ui(self, is_img2img):
+        with gr.Accordion(f"{app_title}", open=False):
+
+            # def on_files_upload_uncheck_so(selected: bool):
+            #     global SAVE_ORIGINAL
+            #     SAVE_ORIGINAL = selected
+            #     return gr.Checkbox.update(value=False,visible=False)
+            # def on_files_clear():
+            #     clear_faces_list()
+            #     return gr.Checkbox.update(value=SAVE_ORIGINAL,visible=True)
+            
+            enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
+            gr.Markdown("<br>")
+
+            # TAB MAIN
+            msgs: dict = {
+                "extra_multiple_source": "",
+            }
+            img, imgs, select_source, face_model, source_folder, save_original, mask_face, source_faces_index, gender_source, faces_index, gender_target, face_restorer_name, face_restorer_visibility, codeformer_weight, swap_in_source, swap_in_generated = ui_main.show(is_img2img=is_img2img, **msgs)
+            
+            # TAB UPSCALE
+            restore_first, upscaler_name, upscaler_scale, upscaler_visibility = ui_upscale.show()
+
+            # TAB TOOLS
+            ui_tools.show()
+            
+            # TAB SETTINGS
+            model, device, console_logging_level, source_hash_check, target_hash_check = ui_settings.show()
+            
+            gr.Markdown("<span style='display:block;text-align:right;padding:3px;font-size:0.666em;margin-bottom:-12px;'>by <a style='font-weight:normal' href='https://github.com/Gourieff' target='_blank'>Eugene Gourieff</a></span>")
+
+        return [
+            img,
+            enable,
+            source_faces_index,
+            faces_index,
+            model,
+            face_restorer_name,
+            face_restorer_visibility,
+            restore_first,
+            upscaler_name,
+            upscaler_scale,
+            upscaler_visibility,
+            swap_in_source,
+            swap_in_generated,
+            console_logging_level,
+            gender_source,
+            gender_target,
+            save_original,
+            codeformer_weight,
+            source_hash_check,
+            target_hash_check,
+            device,
+            mask_face,
+            select_source,
+            face_model,
+            source_folder,
+            imgs,
+        ]
+
+
+    @property
+    def upscaler(self) -> UpscalerData:
+        for upscaler in shared.sd_upscalers:
+            if upscaler.name == self.upscaler_name:
+                return upscaler
+        return None
+
+    @property
+    def face_restorer(self) -> FaceRestoration:
+        for face_restorer in shared.face_restorers:
+            if face_restorer.name() == self.face_restorer_name:
+                return face_restorer
+        return None
+
+    @property
+    def enhancement_options(self) -> EnhancementOptions:
+        return EnhancementOptions(
+            do_restore_first = self.restore_first,
+            scale=self.upscaler_scale,
+            upscaler=self.upscaler,
+            face_restorer=self.face_restorer,
+            upscale_visibility=self.upscaler_visibility,
+            restorer_visibility=self.face_restorer_visibility,
+            codeformer_weight=self.codeformer_weight,
+        )
+
+    def process(
+        self,
+        p: StableDiffusionProcessing,
+        img,
+        enable,
+        source_faces_index,
+        faces_index,
+        model,
+        face_restorer_name,
+        face_restorer_visibility,
+        restore_first,
+        upscaler_name,
+        upscaler_scale,
+        upscaler_visibility,
+        swap_in_source,
+        swap_in_generated,
+        console_logging_level,
+        gender_source,
+        gender_target,
+        save_original,
+        codeformer_weight,
+        source_hash_check,
+        target_hash_check,
+        device,
+        mask_face,
+        select_source,
+        face_model,
+        source_folder,
+        imgs,
+    ):
+        self.enable = enable
+        if self.enable:
+
+            logger.debug("*** Start process")
+
+            reset_messaged()
+            if check_process_halt():
+                return
+            
+            global SWAPPER_MODELS_PATH
+            self.source = img
+            self.face_restorer_name = face_restorer_name
+            self.upscaler_scale = upscaler_scale
+            self.upscaler_visibility = upscaler_visibility
+            self.face_restorer_visibility = face_restorer_visibility
+            self.restore_first = restore_first
+            self.upscaler_name = upscaler_name  
+            self.swap_in_source = swap_in_source
+            self.swap_in_generated = swap_in_generated
+            self.model = os.path.join(SWAPPER_MODELS_PATH,model)
+            self.console_logging_level = console_logging_level
+            self.gender_source = gender_source
+            self.gender_target = gender_target
+            self.save_original = save_original
+            self.codeformer_weight = codeformer_weight
+            self.source_hash_check = source_hash_check
+            self.target_hash_check = target_hash_check
+            self.device = device
+            self.mask_face = mask_face
+            self.select_source = select_source
+            self.face_model = face_model
+            self.source_folder = source_folder
+            self.source_imgs = imgs
+            if self.gender_source is None or self.gender_source == "No":
+                self.gender_source = 0
+            if self.gender_target is None or self.gender_target == "No":
+                self.gender_target = 0
+            self.source_faces_index = [
+                int(x) for x in source_faces_index.strip(",").split(",") if x.isnumeric()
+            ]
+            self.faces_index = [
+                int(x) for x in faces_index.strip(",").split(",") if x.isnumeric()
+            ]
+            if len(self.source_faces_index) == 0:
+                self.source_faces_index = [0]
+            if len(self.faces_index) == 0:
+                self.faces_index = [0]
+            if self.save_original is None:
+                self.save_original = False
+            if self.source_hash_check is None:
+                self.source_hash_check = True
+            if self.target_hash_check is None:
+                self.target_hash_check = False
+            if self.mask_face is None:
+                self.mask_face = False
+
+            logger.debug("*** Set Device")
+            set_Device(self.device)
+            
+            if ((self.source is not None or self.source_imgs is not None) and self.select_source == 0) or ((self.face_model is not None and self.face_model != "None") and self.select_source == 1) or ((self.source_folder is not None and self.source_folder != "") and self.select_source == 2):
+                logger.debug("*** Log patch")
+                apply_logging_patch(console_logging_level)
+                if isinstance(p, StableDiffusionProcessingImg2Img) and self.swap_in_source:
+                    logger.status("Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
+
+                    for i in range(len(p.init_images)):
+                        if len(p.init_images) > 1:
+                            logger.status("Swap in %s", i)
+                        result, output, swapped = swap_face(
+                            self.source,
+                            p.init_images[i],
+                            source_faces_index=self.source_faces_index,
+                            faces_index=self.faces_index,
+                            model=self.model,
+                            enhancement_options=self.enhancement_options,
+                            gender_source=self.gender_source,
+                            gender_target=self.gender_target,
+                            source_hash_check=self.source_hash_check,
+                            target_hash_check=self.target_hash_check,
+                            device=self.device,
+                            mask_face=self.mask_face,
+                            select_source=self.select_source,
+                            face_model = self.face_model,
+                            source_folder = None,
+                            source_imgs = None,
+                        )
+                        p.init_images[i] = result
+                        # result_path = get_image_path(p.init_images[i], p.outpath_samples, "", p.all_seeds[i], p.all_prompts[i], "txt", p=p, suffix="-swapped")
+                        # if len(output) != 0:
+                        #     with open(result_path, 'w', encoding="utf8") as f:
+                        #         f.writelines(output)
+
+                        if shared.state.interrupted or shared.state.skipped:
+                            return
+            
+            else:
+                logger.error("Please provide a source face")
+                return
+
+    def postprocess(self, p: StableDiffusionProcessing, processed: Processed, *args):
+        if self.enable:
+
+            logger.debug("*** Check postprocess")
+
+            reset_messaged()
+            if check_process_halt():
+                return
+
+            if self.save_original or ((self.select_source == 2 and self.source_folder is not None and self.source_folder != "") or (self.select_source == 0 and self.source_imgs is not None and self.source is None)):
+
+                postprocess_run: bool = True
+
+                orig_images : List[Image.Image] = processed.images[processed.index_of_first_image:]
+                orig_infotexts : List[str] = processed.infotexts[processed.index_of_first_image:]
+
+                result_images: List = processed.images
+                # result_info: List = processed.infotexts
+
+                if self.swap_in_generated:
+
+                    logger.status("Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
+
+                    if self.source is not None:
+                        # self.source_folder = None
+                        self.source_imgs = None
+
+                    for i,(img,info) in enumerate(zip(orig_images, orig_infotexts)):
+                        if check_process_halt():
+                            postprocess_run = False
+                            break
+                        if len(orig_images) > 1:
+                            logger.status("Swap in %s", i)
+                        result, output, swapped = swap_face(
+                            self.source,
+                            img,
+                            source_faces_index=self.source_faces_index,
+                            faces_index=self.faces_index,
+                            model=self.model,
+                            enhancement_options=self.enhancement_options,
+                            gender_source=self.gender_source,
+                            gender_target=self.gender_target,
+                            source_hash_check=self.source_hash_check,
+                            target_hash_check=self.target_hash_check,
+                            device=self.device,
+                            mask_face=self.mask_face,
+                            select_source=self.select_source,
+                            face_model = self.face_model,
+                            source_folder = self.source_folder,
+                            source_imgs = self.source_imgs,
+                        )
+
+                        if self.select_source == 2 or (self.select_source == 0 and self.source_imgs is not None and self.source is None):
+                            if len(result) > 0 and swapped > 0:
+                                result_images.extend(result)
+                                suffix = "-swapped"
+                                for i,x in enumerate(result):
+                                    try:
+                                        img_path = save_image(result[i], p.outpath_samples, "", p.all_seeds[0], p.all_prompts[0], "png",info=info, p=p, suffix=suffix)
+                                    except:
+                                        logger.error("Cannot save a result image - please, check SD WebUI Settings (Saving and Paths)")
+                            elif len(result) == 0:
+                                logger.error("Cannot create a result image")
+
+                        else:
+                            if result is not None and swapped > 0:
+                                result_images.append(result)
+                                suffix = "-swapped"
+                                try:
+                                    img_path = save_image(result, p.outpath_samples, "", p.all_seeds[0], p.all_prompts[0], "png",info=info, p=p, suffix=suffix)
+                                except:
+                                    logger.error("Cannot save a result image - please, check SD WebUI Settings (Saving and Paths)")
+                            elif result is None:
+                                logger.error("Cannot create a result image")
+                        
+                        # if len(output) != 0:
+                        #     split_fullfn = os.path.splitext(img_path[0])
+                        #     fullfn = split_fullfn[0] + ".txt"
+                        #     with open(fullfn, 'w', encoding="utf8") as f:
+                        #         f.writelines(output)
+                
+                if shared.opts.return_grid and len(result_images) > 2 and postprocess_run:
+                    grid = make_grid(result_images)
+                    result_images.insert(0, grid)
+                    try:
+                        save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], shared.opts.grid_format, info=info, short_filename=not shared.opts.grid_extended_filename, p=p, grid=True)
+                    except:
+                        logger.error("Cannot save a grid - please, check SD WebUI Settings (Saving and Paths)")
+                
+                processed.images = result_images
+                # processed.infotexts = result_info
+    
+    def postprocess_batch(self, p, *args, **kwargs):
+        if self.enable and not self.save_original:
+            logger.debug("*** Check postprocess_batch")
+            images = kwargs["images"]
+
+    def postprocess_image(self, p, script_pp: scripts.PostprocessImageArgs, *args):
+        if self.enable and self.swap_in_generated and not self.save_original and ((self.select_source == 0 and self.source is not None) or self.select_source == 1):
+
+            logger.debug("*** Check postprocess_image")
+
+            current_job_number = shared.state.job_no + 1
+            job_count = shared.state.job_count
+            if current_job_number == job_count:
+                reset_messaged()
+            if check_process_halt():
+                return
+            
+            # if (self.source is not None and self.select_source == 0) or ((self.face_model is not None and self.face_model != "None") and self.select_source == 1):
+            logger.status("Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
+            image: Image.Image = script_pp.image
+            result, output, swapped = swap_face(
+                self.source,
+                image,
+                source_faces_index=self.source_faces_index,
+                faces_index=self.faces_index,
+                model=self.model,
+                enhancement_options=self.enhancement_options,
+                gender_source=self.gender_source,
+                gender_target=self.gender_target,
+                source_hash_check=self.source_hash_check,
+                target_hash_check=self.target_hash_check,
+                device=self.device,
+                mask_face=self.mask_face,
+                select_source=self.select_source,
+                face_model = self.face_model,
+                source_folder = None,
+                source_imgs = None,
+            )
+            try:
+                pp = scripts_postprocessing.PostprocessedImage(result)
+                pp.info = {}
+                p.extra_generation_params.update(pp.info)
+                script_pp.image = pp.image
+
+                # if len(output) != 0:
+                #     result_path = get_image_path(script_pp.image, p.outpath_samples, "", p.all_seeds[0], p.all_prompts[0], "txt", p=p, suffix="-swapped")
+                #     if len(output) != 0:
+                #         with open(result_path, 'w', encoding="utf8") as f:
+                #             f.writelines(output)
+            except:
+                logger.error("Cannot create a result image")
+
+
+class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
+    name = 'ReActor'
+    order = 20000
+
+    def ui(self):
+        with gr.Accordion(f"{app_title}", open=False):
+
+            enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
+
+            # TAB MAIN
+            msgs: dict = {
+                "extra_multiple_source": " | Сomparison grid as a result",
+            }
+            img, imgs, select_source, face_model, source_folder, save_original, mask_face, source_faces_index, gender_source, faces_index, gender_target, face_restorer_name, face_restorer_visibility, codeformer_weight, swap_in_source, swap_in_generated = ui_main.show(is_img2img=False, show_br=False, **msgs)
+            
+            # TAB UPSCALE
+            restore_first, upscaler_name, upscaler_scale, upscaler_visibility = ui_upscale.show(show_br=False)
+                        
+            # TAB TOOLS
+            ui_tools.show()
+                        
+            # TAB SETTINGS
+            model, device, console_logging_level, source_hash_check, target_hash_check = ui_settings.show(hash_check_block=False)
+                        
+            gr.Markdown("<span style='display:block;text-align:right;padding-right:3px;font-size:0.666em;margin: -9px 0'>by <a style='font-weight:normal' href='https://github.com/Gourieff' target='_blank'>Eugene Gourieff</a></span>")
+
+        args = {
+            'img': img,
+            'enable': enable,
+            'source_faces_index': source_faces_index,
+            'faces_index': faces_index,
+            'model': model,
+            'face_restorer_name': face_restorer_name,
+            'face_restorer_visibility': face_restorer_visibility,
+            'restore_first': restore_first,
+            'upscaler_name': upscaler_name,
+            'upscaler_scale': upscaler_scale,
+            'upscaler_visibility': upscaler_visibility,
+            'console_logging_level': console_logging_level,
+            'gender_source': gender_source,
+            'gender_target': gender_target,
+            'codeformer_weight': codeformer_weight,
+            'device': device,
+            'mask_face': mask_face,
+            'select_source': select_source,
+            'face_model': face_model,
+            'source_folder': source_folder,
+            'imgs': imgs,
+        }
+        return args
+
+    @property
+    def upscaler(self) -> UpscalerData:
+        for upscaler in shared.sd_upscalers:
+            if upscaler.name == self.upscaler_name:
+                return upscaler
+        return None
+
+    @property
+    def face_restorer(self) -> FaceRestoration:
+        for face_restorer in shared.face_restorers:
+            if face_restorer.name() == self.face_restorer_name:
+                return face_restorer
+        return None
+
+    @property
+    def enhancement_options(self) -> EnhancementOptions:
+        return EnhancementOptions(
+            do_restore_first=self.restore_first,
+            scale=self.upscaler_scale,
+            upscaler=self.upscaler,
+            face_restorer=self.face_restorer,
+            upscale_visibility=self.upscaler_visibility,
+            restorer_visibility=self.face_restorer_visibility,
+            codeformer_weight=self.codeformer_weight,
+        )
+
+    def process(self, pp: scripts_postprocessing.PostprocessedImage, **args):
+        if args['enable']:
+            reset_messaged()
+            if check_process_halt():
+                return
+
+            global SWAPPER_MODELS_PATH
+            self.source = args['img']
+            self.face_restorer_name = args['face_restorer_name']
+            self.upscaler_scale = args['upscaler_scale']
+            self.upscaler_visibility = args['upscaler_visibility']
+            self.face_restorer_visibility = args['face_restorer_visibility']
+            self.restore_first = args['restore_first']
+            self.upscaler_name = args['upscaler_name']
+            self.model = os.path.join(SWAPPER_MODELS_PATH, args['model'])
+            self.console_logging_level = args['console_logging_level']
+            self.gender_source = args['gender_source']
+            self.gender_target = args['gender_target']
+            self.codeformer_weight = args['codeformer_weight']
+            self.device = args['device']
+            self.mask_face = args['mask_face']
+            self.select_source = args['select_source']
+            self.face_model = args['face_model']
+            self.source_folder = args['source_folder']
+            self.source_imgs = args['imgs']
+            if self.gender_source is None or self.gender_source == "No":
+                self.gender_source = 0
+            if self.gender_target is None or self.gender_target == "No":
+                self.gender_target = 0
+            self.source_faces_index = [
+                int(x) for x in args['source_faces_index'].strip(",").split(",") if x.isnumeric()
+            ]
+            self.faces_index = [
+                int(x) for x in args['faces_index'].strip(",").split(",") if x.isnumeric()
+            ]
+            if len(self.source_faces_index) == 0:
+                self.source_faces_index = [0]
+            if len(self.faces_index) == 0:
+                self.faces_index = [0]
+            if self.mask_face is None:
+                self.mask_face = False
+
+            current_job_number = shared.state.job_no + 1
+            job_count = shared.state.job_count
+            if current_job_number == job_count:
+                reset_messaged()
+
+            set_Device(self.device)
+
+            logger.debug("We're here: process() 1")
+            
+            if (self.source is not None and self.select_source == 0) or ((self.face_model is not None and self.face_model != "None") and self.select_source == 1) or ((self.source_folder is not None and self.source_folder != "") and self.select_source == 2) or ((self.source_imgs is not None and self.source is None) and self.select_source == 0):
+
+                logger.debug("We're here: process() 2")
+
+                apply_logging_patch(self.console_logging_level)
+                logger.status("Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
+                # if self.select_source != 2:
+                image: Image.Image = pp.image
+                result, output, swapped = swap_face(
+                    self.source,
+                    image,
+                    source_faces_index=self.source_faces_index,
+                    faces_index=self.faces_index,
+                    model=self.model,
+                    enhancement_options=self.enhancement_options,
+                    gender_source=self.gender_source,
+                    gender_target=self.gender_target,
+                    source_hash_check=True,
+                    target_hash_check=True,
+                    device=self.device,
+                    mask_face=self.mask_face,
+                    select_source=self.select_source,
+                    face_model=self.face_model,
+                    source_folder=self.source_folder,
+                    source_imgs=self.source_imgs,
+                )
+                if self.select_source == 2 or (self.select_source == 0 and self.source_imgs is not None and self.source is None):
+                    if len(result) > 0 and swapped > 0:
+                        image = result[0]
+                        if len(result) > 1:
+                            grid = make_grid(result)
+                            result.insert(0, grid)
+                            image = grid
+                        pp.info["ReActor"] = True
+                        pp.image = image
+                        logger.status("---Done!---")
+                    else:
+                        logger.error("Cannot create a result image")
+                else:
+                    try:
+                        pp.info["ReActor"] = True
+                        pp.image = result
+                        logger.status("---Done!---")
+                    except Exception:
+                        logger.error("Cannot create a result image")
+            else:
+                logger.error("Please provide a source face")

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_globals.py

@@ -0,0 +1,40 @@
+import os
+from pathlib import Path
+
+try:
+    from modules.paths_internal import models_path
+except:
+    try:
+        from modules.paths import models_path
+    except:
+        models_path = os.path.abspath("models")
+
+IS_RUN: bool = False
+BASE_PATH = os.path.join(Path(__file__).parents[1])
+DEVICE_LIST: list = ["CPU", "CUDA"]
+
+MODELS_PATH = models_path
+SWAPPER_MODELS_PATH = os.path.join(MODELS_PATH, "insightface")
+REACTOR_MODELS_PATH = os.path.join(MODELS_PATH, "reactor")
+FACE_MODELS_PATH = os.path.join(REACTOR_MODELS_PATH, "faces")
+
+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)
+
+def updateDevice():
+    try:
+        LAST_DEVICE_PATH = os.path.join(BASE_PATH, "last_device.txt")
+        with open(LAST_DEVICE_PATH) as f:
+            device = f.readline().strip()
+        if device not in DEVICE_LIST:
+            print(f"Error: Device {device} is not in DEVICE_LIST")
+            device = DEVICE_LIST[0]
+            print(f"Execution Provider has been set to {device}")
+    except Exception as e:
+        device = DEVICE_LIST[0]
+        print(f"Error: {e}\nExecution Provider has been set to {device}")
+    return device
+
+DEVICE = updateDevice()

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_helpers.py

@@ -0,0 +1,209 @@
+import os, glob
+from collections import Counter
+from PIL import Image
+from math import isqrt, ceil
+from typing import List
+import logging
+import hashlib
+import torch
+from safetensors.torch import save_file, safe_open
+from insightface.app.common import Face
+
+from modules.images import FilenameGenerator, get_next_sequence_number
+from modules import shared, script_callbacks
+from scripts.reactor_globals import DEVICE, BASE_PATH, FACE_MODELS_PATH
+
+try:
+    from modules.paths_internal import models_path
+except:
+    try:
+        from modules.paths import models_path
+    except:
+        model_path = os.path.abspath("models")
+
+MODELS_PATH = None
+
+def set_Device(value):
+    global DEVICE
+    DEVICE = value
+    with open(os.path.join(BASE_PATH, "last_device.txt"), "w") as txt:
+        txt.write(DEVICE)
+
+def get_Device():
+    global DEVICE
+    return DEVICE
+
+def make_grid(image_list: List):
+    
+    # Count the occurrences of each image size in the image_list
+    size_counter = Counter(image.size for image in image_list)
+    
+    # Get the most common image size (size with the highest count)
+    common_size = size_counter.most_common(1)[0][0]
+    
+    # Filter the image_list to include only images with the common size
+    image_list = [image for image in image_list if image.size == common_size]
+    
+    # Get the dimensions (width and height) of the common size
+    size = common_size
+    
+    # If there are more than one image in the image_list
+    if len(image_list) > 1:
+        num_images = len(image_list)
+        
+        # Calculate the number of rows and columns for the grid
+        rows = isqrt(num_images)
+        cols = ceil(num_images / rows)
+
+        # Calculate the size of the square image
+        square_size = (cols * size[0], rows * size[1])
+
+        # Create a new RGB image with the square size
+        square_image = Image.new("RGB", square_size)
+
+        # Paste each image onto the square image at the appropriate position
+        for i, image in enumerate(image_list):
+            row = i // cols
+            col = i % cols
+
+            square_image.paste(image, (col * size[0], row * size[1]))
+
+        # Return the resulting square image
+        return square_image
+    
+    # Return None if there are no images or only one image in the image_list
+    return None
+
+def get_image_path(image, path, basename, seed=None, prompt=None, extension='png', p=None, suffix=""):
+    
+    namegen = FilenameGenerator(p, seed, prompt, image)
+
+    save_to_dirs = shared.opts.save_to_dirs
+
+    if save_to_dirs:
+        dirname = namegen.apply(shared.opts.directories_filename_pattern or "[prompt_words]").lstrip(' ').rstrip('\\ /')
+        path = os.path.join(path, dirname)
+
+    os.makedirs(path, exist_ok=True)
+
+    if seed is None:
+        file_decoration = ""
+    elif shared.opts.save_to_dirs:
+        file_decoration = shared.opts.samples_filename_pattern or "[seed]"
+    else:
+        file_decoration = shared.opts.samples_filename_pattern or "[seed]-[prompt_spaces]"
+
+    file_decoration = namegen.apply(file_decoration) + suffix
+
+    add_number = shared.opts.save_images_add_number or file_decoration == ''
+
+    if file_decoration != "" and add_number:
+        file_decoration = f"-{file_decoration}"
+
+    if add_number:
+        basecount = get_next_sequence_number(path, basename)
+        fullfn = None
+        for i in range(500):
+            fn = f"{basecount + i:05}" if basename == '' else f"{basename}-{basecount + i:04}"
+            fullfn = os.path.join(path, f"{fn}{file_decoration}.{extension}")
+            if not os.path.exists(fullfn):
+                break
+    else:
+        fullfn = os.path.join(path, f"{file_decoration}.{extension}")
+
+    pnginfo = {}
+
+    params = script_callbacks.ImageSaveParams(image, p, fullfn, pnginfo)
+    # script_callbacks.before_image_saved_callback(params)
+
+    fullfn = params.filename
+
+    fullfn_without_extension, extension = os.path.splitext(params.filename)
+    if hasattr(os, 'statvfs'):
+        max_name_len = os.statvfs(path).f_namemax
+        fullfn_without_extension = fullfn_without_extension[:max_name_len - max(4, len(extension))]
+        params.filename = fullfn_without_extension + extension
+        fullfn = params.filename
+
+    return fullfn
+
+def addLoggingLevel(levelName, levelNum, methodName=None):
+    if not methodName:
+        methodName = levelName.lower()
+
+    def logForLevel(self, message, *args, **kwargs):
+        if self.isEnabledFor(levelNum):
+            self._log(levelNum, message, args, **kwargs)
+
+    def logToRoot(message, *args, **kwargs):
+        logging.log(levelNum, message, *args, **kwargs)
+
+    logging.addLevelName(levelNum, levelName)
+    setattr(logging, levelName, levelNum)
+    setattr(logging.getLoggerClass(), methodName, logForLevel)
+    setattr(logging, methodName, logToRoot)
+
+def get_image_md5hash(image: Image.Image):
+    md5hash = hashlib.md5(image.tobytes())
+    return md5hash.hexdigest()
+
+def save_face_model(face: Face, filename: str) -> None:
+    try:
+        tensors = {
+            "bbox": torch.tensor(face["bbox"]),
+            "kps": torch.tensor(face["kps"]),
+            "det_score": torch.tensor(face["det_score"]),
+            "landmark_3d_68": torch.tensor(face["landmark_3d_68"]),
+            "pose": torch.tensor(face["pose"]),
+            "landmark_2d_106": torch.tensor(face["landmark_2d_106"]),
+            "embedding": torch.tensor(face["embedding"]),
+            "gender": torch.tensor(face["gender"]),
+            "age": torch.tensor(face["age"]),
+        }
+        save_file(tensors, filename)
+        # print(f"Face model has been saved to '{filename}'")
+    except Exception as e:
+        print(f"Error: {e}")
+
+def get_models():
+    global MODELS_PATH
+    models_path_init = os.path.join(models_path, "insightface/*")
+    models = glob.glob(models_path_init)
+    models = [x for x in models if x.endswith(".onnx") or x.endswith(".pth")]
+    models_names = []
+    for model in models:
+        model_path = os.path.split(model)
+        if MODELS_PATH is None:
+            MODELS_PATH = model_path[0]
+        model_name = model_path[1]
+        models_names.append(model_name)
+    return models_names
+
+def load_face_model(filename: str):
+    face = {}
+    model_path = os.path.join(FACE_MODELS_PATH, filename)
+    with safe_open(model_path, framework="pt") as f:
+        for k in f.keys():
+            face[k] = f.get_tensor(k).numpy()
+    return Face(face)
+
+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_model_names(get_models):
+    models = get_models()
+    names = ["None"]
+    for x in models:
+        names.append(os.path.basename(x))
+    return names
+
+def get_images_from_folder(path: str):
+    images_path = os.path.join(path, "*")
+    images = glob.glob(images_path)
+    return [Image.open(x) for x in images if x.endswith(('jpg', 'png', 'jpeg', 'webp', 'bmp'))]
+
+def get_images_from_list(imgs: List):
+    return [Image.open(os.path.abspath(x.name)) for x in imgs]

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_inferencers/bisenet_mask_generator.py

@@ -0,0 +1,86 @@
+from typing import List, Tuple
+
+import cv2
+import modules.shared as shared
+import numpy as np
+import torch
+from facexlib.parsing import init_parsing_model
+from facexlib.utils.misc import img2tensor
+from torchvision.transforms.functional import normalize
+from scripts.reactor_inferencers.mask_generator import MaskGenerator
+
+class BiSeNetMaskGenerator(MaskGenerator):
+    def __init__(self) -> None:
+        self.mask_model = init_parsing_model(device=shared.device)
+
+    def name(self):
+        return "BiSeNet"
+
+    def generate_mask(
+        self,
+        face_image: np.ndarray,
+        face_area_on_image: Tuple[int, int, int, int],
+        affected_areas: List[str],
+        mask_size: int,
+        use_minimal_area: bool,
+        fallback_ratio: float = 0.25,
+        **kwargs,
+    ) -> np.ndarray:
+        # original_face_image = face_image
+        face_image = face_image.copy()
+        face_image = face_image[:, :, ::-1]
+
+        if use_minimal_area:
+            face_image = MaskGenerator.mask_non_face_areas(face_image, face_area_on_image)
+
+        h, w, _ = face_image.shape
+
+        if w != 512 or h != 512:
+            rw = (int(w * (512 / w)) // 8) * 8
+            rh = (int(h * (512 / h)) // 8) * 8
+            face_image = cv2.resize(face_image, dsize=(rw, rh))
+
+        face_tensor = img2tensor(face_image.astype("float32") / 255.0, float32=True)
+        normalize(face_tensor, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)
+        face_tensor = torch.unsqueeze(face_tensor, 0).to(shared.device)
+
+        with torch.no_grad():
+            face = self.mask_model(face_tensor)[0]
+        face = face.squeeze(0).cpu().numpy().argmax(0)
+        face = face.copy().astype(np.uint8)
+
+        mask = self.__to_mask(face, affected_areas)
+        
+        if mask_size > 0:
+            mask = cv2.dilate(mask, np.ones((5, 5), np.uint8), iterations=mask_size)
+        
+        if w != 512 or h != 512:
+            mask = cv2.resize(mask, dsize=(w, h))
+        
+        # """if MaskGenerator.calculate_mask_coverage(mask) < fallback_ratio:
+        #     logger.info("Use fallback mask generator")
+        #     mask = self.fallback_mask_generator.generate_mask(
+        #         original_face_image, face_area_on_image, use_minimal_area=True
+        #     )"""
+       
+        return mask
+
+    def __to_mask(self, face: np.ndarray, affected_areas: List[str]) -> np.ndarray:
+        keep_face = "Face" in affected_areas
+        keep_neck = "Neck" in affected_areas
+        keep_hair = "Hair" in affected_areas
+        keep_hat = "Hat" in affected_areas
+
+        mask = np.zeros((face.shape[0], face.shape[1], 3), dtype=np.uint8)
+        num_of_class = np.max(face)
+        for i in range(1, num_of_class + 1):
+            index = np.where(face == i)
+            if i < 14 and keep_face:
+                mask[index[0], index[1], :] = [255, 255, 255]
+            elif i == 14 and keep_neck:
+                mask[index[0], index[1], :] = [255, 255, 255]
+            elif i == 17 and keep_hair:
+                mask[index[0], index[1], :] = [255, 255, 255]
+            elif i == 18 and keep_hat:
+                mask[index[0], index[1], :] = [255, 255, 255]
+        return mask

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_inferencers/mask_generator.py

@@ -0,0 +1,36 @@
+from abc import ABC, abstractmethod
+from typing import Tuple
+
+import cv2
+import numpy as np
+
+class MaskGenerator(ABC):
+    @abstractmethod
+    def name(self) -> str:
+        pass
+
+    @abstractmethod
+    def generate_mask(
+        self,
+        face_image: np.ndarray,
+        face_area_on_image: Tuple[int, int, int, int],
+        **kwargs,
+    ) -> np.ndarray:
+        pass
+
+    @staticmethod
+    def mask_non_face_areas(image: np.ndarray, face_area_on_image: Tuple[int, int, int, int]) -> np.ndarray:
+        left, top, right, bottom = face_area_on_image
+        image = image.copy()
+        image[:top, :] = 0
+        image[bottom:, :] = 0
+        image[:, :left] = 0
+        image[:, right:] = 0
+        return image
+
+    @staticmethod
+    def calculate_mask_coverage(mask: np.ndarray):
+        gray_mask = cv2.cvtColor(mask, cv2.COLOR_RGB2GRAY)
+        non_black_pixels = np.count_nonzero(gray_mask)
+        total_pixels = gray_mask.size
+        return non_black_pixels / total_pixels

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_logger.py

@@ -0,0 +1,55 @@
+import logging
+import copy
+import sys
+
+from modules import shared
+from scripts.reactor_globals import IS_RUN
+from scripts.reactor_helpers import addLoggingLevel
+
+
+class ColoredFormatter(logging.Formatter):
+    COLORS = {
+        "DEBUG": "\033[0;36m",  # CYAN
+        "STATUS": "\033[38;5;173m",  # Calm ORANGE
+        "INFO": "\033[0;32m",  # GREEN
+        "WARNING": "\033[0;33m",  # YELLOW
+        "ERROR": "\033[0;31m",  # RED
+        "CRITICAL": "\033[0;37;41m",  # WHITE ON RED
+        "RESET": "\033[0m",  # RESET COLOR
+    }
+
+    def format(self, record):
+        colored_record = copy.copy(record)
+        levelname = colored_record.levelname
+        seq = self.COLORS.get(levelname, self.COLORS["RESET"])
+        colored_record.levelname = f"{seq}{levelname}{self.COLORS['RESET']}"
+        return super().format(colored_record)
+
+
+# Create a new logger
+logger = logging.getLogger("ReActor")
+logger.propagate = False
+
+# Add Custom Level
+addLoggingLevel("STATUS", logging.INFO + 5)
+
+# Add handler if we don't have one.
+if not logger.handlers:
+    handler = logging.StreamHandler(sys.stdout)
+    handler.setFormatter(
+        ColoredFormatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s","%H:%M:%S")
+    )
+    logger.addHandler(handler)
+
+# Configure logger
+loglevel_string = getattr(shared.cmd_opts, "reactor_loglevel", "INFO")
+loglevel = getattr(logging, loglevel_string.upper(), "info")
+logger.setLevel(loglevel)
+
+def set_Run(value):
+    global IS_RUN
+    IS_RUN = value
+
+def get_Run():
+    global IS_RUN
+    return IS_RUN

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_swapper.py

@@ -0,0 +1,715 @@
+import copy
+import os
+from dataclasses import dataclass
+from typing import List, Union
+
+import cv2
+import numpy as np
+from PIL import Image
+
+import insightface
+from insightface.app.common import Face
+
+from scripts.reactor_globals import FACE_MODELS_PATH
+from scripts.reactor_helpers import (
+    get_image_md5hash, 
+    get_Device, 
+    save_face_model, 
+    load_face_model, 
+    get_images_from_folder,
+    get_images_from_list
+)
+from scripts.console_log_patch import apply_logging_patch
+
+from modules.face_restoration import FaceRestoration
+try: # A1111
+    from modules import codeformer_model
+except: # SD.Next
+    from modules.postprocess import codeformer_model
+from modules.upscaler import UpscalerData
+from modules.shared import state
+from scripts.reactor_logger import logger
+from reactor_modules.reactor_mask import apply_face_mask
+
+try:
+    from modules.paths_internal import models_path
+except:
+    try:
+        from modules.paths import models_path
+    except:
+        models_path = os.path.abspath("models")
+
+import warnings
+
+np.warnings = warnings
+np.warnings.filterwarnings('ignore')
+
+
+DEVICE = get_Device()
+if DEVICE == "CUDA":
+    PROVIDERS = ["CUDAExecutionProvider"]
+else:
+    PROVIDERS = ["CPUExecutionProvider"]
+
+
+@dataclass
+class EnhancementOptions:
+    do_restore_first: bool = True
+    scale: int = 1
+    upscaler: UpscalerData = None
+    upscale_visibility: float = 0.5
+    face_restorer: FaceRestoration = None
+    restorer_visibility: float = 0.5
+    codeformer_weight: float = 0.5
+
+
+MESSAGED_STOPPED = False
+MESSAGED_SKIPPED = False
+
+def reset_messaged():
+    global MESSAGED_STOPPED, MESSAGED_SKIPPED
+    if not state.interrupted:
+        MESSAGED_STOPPED = False
+    if not state.skipped:
+        MESSAGED_SKIPPED = False
+
+def check_process_halt(msgforced: bool = False):
+    global MESSAGED_STOPPED, MESSAGED_SKIPPED
+    if state.interrupted:
+        if not MESSAGED_STOPPED or msgforced:
+            logger.status("Stopped by User")
+            MESSAGED_STOPPED = True
+        return True
+    if state.skipped:
+        if not MESSAGED_SKIPPED or msgforced:
+            logger.status("Skipped by User")
+            MESSAGED_SKIPPED = True
+        return True
+    return False
+
+
+FS_MODEL = None
+ANALYSIS_MODEL = None
+MASK_MODEL = None
+
+CURRENT_FS_MODEL_PATH = None
+CURRENT_MASK_MODEL_PATH = None
+
+SOURCE_FACES = None
+SOURCE_IMAGE_HASH = None
+TARGET_FACES = None
+TARGET_IMAGE_HASH = None
+SOURCE_FACES_LIST = []
+SOURCE_IMAGE_LIST_HASH = []
+
+def clear_faces_list():
+    global SOURCE_FACES_LIST, SOURCE_IMAGE_LIST_HASH
+    SOURCE_FACES_LIST = []
+    SOURCE_IMAGE_LIST_HASH = []
+    logger.status("Source Images Hash has been reset (for Multiple or Folder Source)")
+
+
+def getAnalysisModel():
+    global ANALYSIS_MODEL
+    if ANALYSIS_MODEL is None:
+        ANALYSIS_MODEL = insightface.app.FaceAnalysis(
+            name="buffalo_l", providers=PROVIDERS, root=os.path.join(models_path, "insightface") # note: allowed_modules=['detection', 'genderage']
+        )
+    return ANALYSIS_MODEL
+
+
+def getFaceSwapModel(model_path: str):
+    global FS_MODEL
+    global CURRENT_FS_MODEL_PATH
+    if CURRENT_FS_MODEL_PATH is None or CURRENT_FS_MODEL_PATH != model_path:
+        CURRENT_FS_MODEL_PATH = model_path
+        FS_MODEL = insightface.model_zoo.get_model(model_path, providers=PROVIDERS)
+
+    return FS_MODEL
+
+
+def restore_face(image: Image, enhancement_options: EnhancementOptions):
+    result_image = image
+
+    if check_process_halt(msgforced=True):
+        return result_image
+    
+    if enhancement_options.face_restorer is not None:
+        original_image = result_image.copy()
+        logger.status("Restoring the face with %s", enhancement_options.face_restorer.name())
+        numpy_image = np.array(result_image)
+        if enhancement_options.face_restorer.name() == "CodeFormer":
+            numpy_image = codeformer_model.codeformer.restore(
+                numpy_image, w=enhancement_options.codeformer_weight
+            )
+        else:
+            numpy_image = enhancement_options.face_restorer.restore(numpy_image)
+        restored_image = Image.fromarray(numpy_image)
+        result_image = Image.blend(
+            original_image, restored_image, enhancement_options.restorer_visibility
+        )
+    
+    return result_image
+
+def upscale_image(image: Image, enhancement_options: EnhancementOptions):
+    result_image = image
+
+    if check_process_halt(msgforced=True):
+        return result_image
+    
+    if enhancement_options.upscaler is not None and enhancement_options.upscaler.name != "None":
+        original_image = result_image.copy()
+        logger.status(
+            "Upscaling with %s scale = %s",
+            enhancement_options.upscaler.name,
+            enhancement_options.scale,
+        )
+        result_image = enhancement_options.upscaler.scaler.upscale(
+            original_image, enhancement_options.scale, enhancement_options.upscaler.data_path
+        )
+        if enhancement_options.scale == 1:
+            result_image = Image.blend(
+                original_image, result_image, enhancement_options.upscale_visibility
+            )
+    
+    return result_image
+
+def enhance_image(image: Image, enhancement_options: EnhancementOptions):
+    result_image = image
+    
+    if check_process_halt(msgforced=True):
+        return result_image
+    
+    if enhancement_options.do_restore_first:
+        
+        result_image = restore_face(result_image, enhancement_options)
+        result_image = upscale_image(result_image, enhancement_options)
+
+    else:
+
+        result_image = upscale_image(result_image, enhancement_options)
+        result_image = restore_face(result_image, enhancement_options)
+
+    return result_image
+
+def enhance_image_and_mask(image: Image.Image, enhancement_options: EnhancementOptions,target_img_orig:Image.Image,entire_mask_image:Image.Image)->Image.Image:
+    result_image = image
+    
+    if check_process_halt(msgforced=True):
+        return result_image
+    
+    if enhancement_options.do_restore_first:
+        
+        result_image = restore_face(result_image, enhancement_options)
+        result_image = Image.composite(result_image,target_img_orig,entire_mask_image)
+        result_image = upscale_image(result_image, enhancement_options)
+
+    else:
+
+        result_image = upscale_image(result_image, enhancement_options)
+        entire_mask_image = Image.fromarray(cv2.resize(np.array(entire_mask_image),result_image.size, interpolation=cv2.INTER_AREA)).convert("L")
+        result_image = Image.composite(result_image,target_img_orig,entire_mask_image)
+        result_image = restore_face(result_image, enhancement_options)
+
+    return result_image
+
+    
+def get_gender(face, face_index):
+    gender = [
+        x.sex
+        for x in face
+    ]
+    gender.reverse()
+    try:
+        face_gender = gender[face_index]
+    except:
+        logger.error("Gender Detection: No face with index = %s was found", face_index)
+        return "None"
+    return face_gender
+
+def get_face_gender(
+        face,
+        face_index,
+        gender_condition,
+        operated: str,
+        gender_detected,
+):
+    face_gender = gender_detected
+    if face_gender == "None":
+        return None, 0
+    logger.status("%s Face %s: Detected Gender -%s-", operated, face_index, face_gender)
+    if (gender_condition == 1 and face_gender == "F") or (gender_condition == 2 and face_gender == "M"):
+        logger.status("OK - Detected Gender matches Condition")
+        try:
+            return sorted(face, key=lambda x: x.bbox[0])[face_index], 0
+        except IndexError:
+            return None, 0
+    else:
+        logger.status("WRONG - Detected Gender doesn't match Condition")
+        return sorted(face, key=lambda x: x.bbox[0])[face_index], 1
+
+def get_face_age(face, face_index):
+    age = [
+        x.age
+        for x in face
+    ]
+    age.reverse()
+    try:
+        face_age = age[face_index]
+    except:
+        logger.error("Age Detection: No face with index = %s was found", face_index)
+        return "None"
+    return face_age
+
+def half_det_size(det_size):
+    logger.status("Trying to halve 'det_size' parameter")
+    return (det_size[0] // 2, det_size[1] // 2)
+
+def analyze_faces(img_data: np.ndarray, det_size=(640, 640)):
+    logger.info("Applied Execution Provider: %s", PROVIDERS[0])
+    face_analyser = copy.deepcopy(getAnalysisModel())
+    face_analyser.prepare(ctx_id=0, det_size=det_size)
+    return face_analyser.get(img_data)
+
+def get_face_single(img_data: np.ndarray, face, face_index=0, det_size=(640, 640), gender_source=0, gender_target=0):
+
+    buffalo_path = os.path.join(models_path, "insightface/models/buffalo_l.zip")
+    if os.path.exists(buffalo_path):
+        os.remove(buffalo_path)
+
+    face_age = "None"
+    try:
+        face_age = get_face_age(face, face_index)
+    except:
+        logger.error("Cannot detect any Age for Face index = %s", face_index)
+    
+    face_gender = "None"
+    try:
+        face_gender = get_gender(face, face_index)
+        gender_detected = face_gender
+        face_gender = "Female" if face_gender == "F" else ("Male" if face_gender == "M" else "None")
+    except:
+        logger.error("Cannot detect any Gender for Face index = %s", face_index)
+    
+    if gender_source != 0:
+        if len(face) == 0 and det_size[0] > 320 and det_size[1] > 320:
+            det_size_half = half_det_size(det_size)
+            return get_face_single(img_data, analyze_faces(img_data, det_size_half), face_index, det_size_half, gender_source, gender_target)
+        faces, wrong_gender = get_face_gender(face,face_index,gender_source,"Source",gender_detected)
+        return faces, wrong_gender, face_age, face_gender
+
+    if gender_target != 0:
+        if len(face) == 0 and det_size[0] > 320 and det_size[1] > 320:
+            det_size_half = half_det_size(det_size)
+            return get_face_single(img_data, analyze_faces(img_data, det_size_half), face_index, det_size_half, gender_source, gender_target)
+        faces, wrong_gender = get_face_gender(face,face_index,gender_target,"Target",gender_detected)
+        return faces, wrong_gender, face_age, face_gender
+    
+    if len(face) == 0 and det_size[0] > 320 and det_size[1] > 320:
+        det_size_half = half_det_size(det_size)
+        return get_face_single(img_data, analyze_faces(img_data, det_size_half), face_index, det_size_half, gender_source, gender_target)
+
+    try:
+        return sorted(face, key=lambda x: x.bbox[0])[face_index], 0, face_age, face_gender
+    except IndexError:
+        return None, 0, face_age, face_gender
+
+
+def swap_face(
+    source_img: Image.Image,
+    target_img: Image.Image,
+    model: Union[str, None] = None,
+    source_faces_index: List[int] = [0],
+    faces_index: List[int] = [0],
+    enhancement_options: Union[EnhancementOptions, None] = None,
+    gender_source: int = 0,
+    gender_target: int = 0,
+    source_hash_check: bool = True,
+    target_hash_check: bool = False,
+    device: str = "CPU",
+    mask_face: bool = False,
+    select_source: int = 0,
+    face_model: str = "None",
+    source_folder: str = "",
+    source_imgs: Union[List, None] = None,
+):
+    global SOURCE_FACES, SOURCE_IMAGE_HASH, TARGET_FACES, TARGET_IMAGE_HASH, PROVIDERS, SOURCE_FACES_LIST, SOURCE_IMAGE_LIST_HASH
+
+    result_image = target_img
+
+    PROVIDERS = ["CUDAExecutionProvider"] if device == "CUDA" else ["CPUExecutionProvider"]
+    
+    if check_process_halt():
+        return result_image, [], 0
+    
+    if model is not None:
+
+        if isinstance(source_img, str):  # source_img is a base64 string
+            import base64, io
+            if 'base64,' in source_img:  # check if the base64 string has a data URL scheme
+                # split the base64 string to get the actual base64 encoded image data
+                base64_data = source_img.split('base64,')[-1]
+                # decode base64 string to bytes
+                img_bytes = base64.b64decode(base64_data)
+            else:
+                # if no data URL scheme, just decode
+                img_bytes = base64.b64decode(source_img)
+            
+            source_img = Image.open(io.BytesIO(img_bytes))
+
+        target_img = cv2.cvtColor(np.array(target_img), cv2.COLOR_RGB2BGR)
+
+        target_img_orig = cv2.cvtColor(np.array(target_img), cv2.COLOR_RGB2BGR)
+        entire_mask_image = np.zeros_like(np.array(target_img))
+
+        output: List = []
+        output_info: str = ""
+        swapped = 0
+
+        # *****************
+        # SWAP from FOLDER or MULTIPLE images:
+        
+        if (select_source == 0 and source_imgs is not None) or (select_source == 2 and (source_folder is not None and source_folder != "")):
+
+            result = []
+
+            source_images = get_images_from_folder(source_folder) if select_source == 2 else get_images_from_list(source_imgs)
+
+            if len(source_images) > 0:
+                source_img_ff = []
+                source_faces_ff = []
+                for i, source_image in enumerate(source_images):
+
+                    source_image = cv2.cvtColor(np.array(source_image), cv2.COLOR_RGB2BGR)
+                    source_img_ff.append(source_image)
+
+                    if source_hash_check:
+
+                        source_image_md5hash = get_image_md5hash(source_image)
+
+                        if len(SOURCE_IMAGE_LIST_HASH) == 0:
+                            SOURCE_IMAGE_LIST_HASH = [source_image_md5hash]
+                            source_image_same = False
+                        elif len(SOURCE_IMAGE_LIST_HASH) == i:
+                            SOURCE_IMAGE_LIST_HASH.append(source_image_md5hash)
+                            source_image_same = False
+                        else:
+                            source_image_same = True if SOURCE_IMAGE_LIST_HASH[i] == source_image_md5hash else False
+                            if not source_image_same:
+                                SOURCE_IMAGE_LIST_HASH[i] = source_image_md5hash
+
+                        logger.info("(Image %s) Source Image MD5 Hash = %s", i, SOURCE_IMAGE_LIST_HASH[i])
+                        logger.info("(Image %s) Source Image the Same? %s", i, source_image_same)
+
+                        if len(SOURCE_FACES_LIST) == 0:
+                            logger.status(f"Analyzing Source Image {i}...")
+                            source_faces = analyze_faces(source_image)
+                            SOURCE_FACES_LIST = [source_faces]
+                        elif len(SOURCE_FACES_LIST) == i and not source_image_same:
+                            logger.status(f"Analyzing Source Image {i}...")
+                            source_faces = analyze_faces(source_image)
+                            SOURCE_FACES_LIST.append(source_faces)
+                        elif len(SOURCE_FACES_LIST) != i and not source_image_same:
+                            logger.status(f"Analyzing Source Image {i}...")
+                            source_faces = analyze_faces(source_image)
+                            SOURCE_FACES_LIST[i] = source_faces
+                        elif source_image_same:
+                            logger.status("(Image %s) Using Hashed Source Face(s) Model...", i)
+                            source_faces = SOURCE_FACES_LIST[i]
+
+                    else:
+                        logger.status(f"Analyzing Source Image {i}...")
+                        source_faces = analyze_faces(source_image)
+
+                    if source_faces is not None:
+                        source_faces_ff.append(source_faces)
+            
+            if len(source_faces_ff) > 0:
+
+                if target_hash_check:
+                
+                    target_image_md5hash = get_image_md5hash(target_img)
+
+                    if TARGET_IMAGE_HASH is None:
+                        TARGET_IMAGE_HASH = target_image_md5hash
+                        target_image_same = False
+                    else:
+                        target_image_same = True if TARGET_IMAGE_HASH == target_image_md5hash else False
+                        if not target_image_same:
+                            TARGET_IMAGE_HASH = target_image_md5hash
+
+                    logger.info("Target Image MD5 Hash = %s", TARGET_IMAGE_HASH)
+                    logger.info("Target Image the Same? %s", target_image_same)
+                    
+                    if TARGET_FACES is None or not target_image_same:
+                        logger.status("Analyzing Target Image...")
+                        target_faces = analyze_faces(target_img)
+                        TARGET_FACES = target_faces
+                    elif target_image_same:
+                        logger.status("Using Hashed Target Face(s) Model...")
+                        target_faces = TARGET_FACES
+                
+                else:
+                    logger.status("Analyzing Target Image...")
+                    target_faces = analyze_faces(target_img)
+
+                for i,source_faces in enumerate(source_faces_ff):
+
+                    logger.status("(Image %s) Detecting Source Face, Index = %s", i, source_faces_index[0])
+                    source_face, wrong_gender, source_age, source_gender = get_face_single(source_img_ff[i], source_faces, face_index=source_faces_index[0], gender_source=gender_source)
+                    
+                    if source_age != "None" or source_gender != "None":
+                        logger.status("(Image %s) Detected: -%s- y.o. %s", i, source_age, source_gender)
+
+                    if len(source_faces_index) != 0 and len(source_faces_index) != 1 and len(source_faces_index) != len(faces_index):
+                        logger.status("Source Faces must have no entries (default=0), one entry, or same number of entries as target faces.")
+                    
+                    elif source_face is not None:
+
+                        result_image, output, swapped = operate(source_img_ff[i],target_img,target_img_orig,model,source_faces_index,faces_index,source_faces,target_faces,gender_source,gender_target,source_face,wrong_gender,source_age,source_gender,output,swapped,mask_face,entire_mask_image,enhancement_options)
+
+                        result.append(result_image)
+
+                    result = [result_image] if len(result) == 0 else result
+            
+            return result, output, swapped
+        
+        # END
+        # *****************
+        
+        # ***********************
+        # SWAP from IMG or MODEL:
+
+        else:
+        
+            if select_source == 0 and source_img is not None:
+                
+                source_img = cv2.cvtColor(np.array(source_img), cv2.COLOR_RGB2BGR)
+
+                if source_hash_check:
+
+                    source_image_md5hash = get_image_md5hash(source_img)
+
+                    if SOURCE_IMAGE_HASH is None:
+                        SOURCE_IMAGE_HASH = source_image_md5hash
+                        source_image_same = False
+                    else:
+                        source_image_same = True if SOURCE_IMAGE_HASH == source_image_md5hash else False
+                        if not source_image_same:
+                            SOURCE_IMAGE_HASH = source_image_md5hash
+
+                    logger.info("Source Image MD5 Hash = %s", SOURCE_IMAGE_HASH)
+                    logger.info("Source Image the Same? %s", source_image_same)
+
+                    if SOURCE_FACES is None or not source_image_same:
+                        logger.status("Analyzing Source Image...")
+                        source_faces = analyze_faces(source_img)
+                        SOURCE_FACES = source_faces
+                    elif source_image_same:
+                        logger.status("Using Hashed Source Face(s) Model...")
+                        source_faces = SOURCE_FACES
+
+                else:
+                    logger.status("Analyzing Source Image...")
+                    source_faces = analyze_faces(source_img)
+            
+            elif select_source == 1 and (face_model is not None and face_model != "None"):
+                source_face_model = [load_face_model(face_model)]
+                if source_face_model is not None:
+                    source_faces_index = [0]
+                    source_faces = source_face_model                  
+                    logger.status("Using Loaded Source Face Model...")
+                else:
+                    logger.error(f"Cannot load Face Model File: {face_model}.safetensors")
+            
+            else:
+                logger.error("Cannot detect any Source")
+                return result_image, [], 0
+
+            if source_faces is not None:
+
+                if target_hash_check:
+                
+                    target_image_md5hash = get_image_md5hash(target_img)
+
+                    if TARGET_IMAGE_HASH is None:
+                        TARGET_IMAGE_HASH = target_image_md5hash
+                        target_image_same = False
+                    else:
+                        target_image_same = True if TARGET_IMAGE_HASH == target_image_md5hash else False
+                        if not target_image_same:
+                            TARGET_IMAGE_HASH = target_image_md5hash
+
+                    logger.info("Target Image MD5 Hash = %s", TARGET_IMAGE_HASH)
+                    logger.info("Target Image the Same? %s", target_image_same)
+                    
+                    if TARGET_FACES is None or not target_image_same:
+                        logger.status("Analyzing Target Image...")
+                        target_faces = analyze_faces(target_img)
+                        TARGET_FACES = target_faces
+                    elif target_image_same:
+                        logger.status("Using Hashed Target Face(s) Model...")
+                        target_faces = TARGET_FACES
+                
+                else:
+                    logger.status("Analyzing Target Image...")
+                    target_faces = analyze_faces(target_img)
+
+                logger.status("Detecting Source Face, Index = %s", source_faces_index[0])
+                if select_source == 0 and source_img is not None:
+                    source_face, wrong_gender, source_age, source_gender = get_face_single(source_img, source_faces, face_index=source_faces_index[0], gender_source=gender_source)
+                else:
+                    source_face = sorted(source_faces, key=lambda x: x.bbox[0])[source_faces_index[0]]
+                    wrong_gender = 0
+                    source_age = source_face["age"]
+                    source_gender = "Female" if source_face["gender"] == 0 else "Male"
+                
+                if source_age != "None" or source_gender != "None":
+                    logger.status("Detected: -%s- y.o. %s", source_age, source_gender)
+
+                output_info = f"SourceFaceIndex={source_faces_index[0]};Age={source_age};Gender={source_gender}\n"
+                output.append(output_info)
+                
+                if len(source_faces_index) != 0 and len(source_faces_index) != 1 and len(source_faces_index) != len(faces_index):
+                    logger.status("Source Faces must have no entries (default=0), one entry, or same number of entries as target faces.")
+                
+                elif source_face is not None:
+
+                    result_image, output, swapped = operate(source_img,target_img,target_img_orig,model,source_faces_index,faces_index,source_faces,target_faces,gender_source,gender_target,source_face,wrong_gender,source_age,source_gender,output,swapped,mask_face,entire_mask_image,enhancement_options)
+                
+                else:
+                    logger.status("No source face(s) in the provided Index")
+            else:
+                logger.status("No source face(s) found")
+    
+            return result_image, output, swapped
+        
+        # END
+        # **********************
+    
+    return result_image, [], 0
+
+def build_face_model(image: Image.Image, name: str):
+    if image is None:
+        error_msg = "Please load an Image"
+        logger.error(error_msg)
+        return error_msg
+    if name is None:
+        error_msg = "Please filled out the 'Face Model Name' field"
+        logger.error(error_msg)
+        return error_msg
+    apply_logging_patch(1)
+    image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    logger.status("Building Face Model...")
+    face_model = analyze_faces(image)
+    if face_model is not None and len(face_model) > 0:
+        face_model_path = os.path.join(FACE_MODELS_PATH, name + ".safetensors")
+        save_face_model(face_model[0],face_model_path)
+        logger.status("--Done!--")
+        done_msg = f"Face model has been saved to '{face_model_path}'"
+        logger.status(done_msg)
+        return done_msg
+    else:
+        no_face_msg = "No face found, please try another image"
+        logger.error(no_face_msg)
+        return no_face_msg
+
+
+def operate(
+        source_img,
+        target_img,
+        target_img_orig,
+        model,
+        source_faces_index,
+        faces_index,
+        source_faces,
+        target_faces,
+        gender_source,
+        gender_target,
+        source_face,
+        wrong_gender,
+        source_age,
+        source_gender,
+        output,
+        swapped,
+        mask_face,
+        entire_mask_image,
+        enhancement_options,
+    ):
+    result = target_img
+    face_swapper = getFaceSwapModel(model)
+
+    source_face_idx = 0
+
+    for face_num in faces_index:
+        if check_process_halt():
+            return result_image, [], 0
+        if len(source_faces_index) > 1 and source_face_idx > 0:
+            logger.status("Detecting Source Face, Index = %s", source_faces_index[source_face_idx])
+            source_face, wrong_gender, source_age, source_gender = get_face_single(source_img, source_faces, face_index=source_faces_index[source_face_idx], gender_source=gender_source)
+            if source_age != "None" or source_gender != "None":
+                logger.status("Detected: -%s- y.o. %s", source_age, source_gender)
+
+            output_info = f"SourceFaceIndex={source_faces_index[source_face_idx]};Age={source_age};Gender={source_gender}\n"
+            output.append(output_info)
+
+        source_face_idx += 1
+
+        if source_face is not None and wrong_gender == 0:
+            logger.status("Detecting Target Face, Index = %s", face_num)
+            target_face, wrong_gender, target_age, target_gender = get_face_single(target_img, target_faces, face_index=face_num, gender_target=gender_target)
+            if target_age != "None" or target_gender != "None":
+                logger.status("Detected: -%s- y.o. %s", target_age, target_gender)
+
+            output_info = f"TargetFaceIndex={face_num};Age={target_age};Gender={target_gender}\n"
+            output.append(output_info)
+            
+            if target_face is not None and wrong_gender == 0:
+                logger.status("Swapping Source into Target")
+                swapped_image = face_swapper.get(result, target_face, source_face)
+                                        
+                if mask_face:
+                    result = apply_face_mask(swapped_image=swapped_image,target_image=result,target_face=target_face,entire_mask_image=entire_mask_image)
+                else:
+                    result = swapped_image
+                swapped += 1
+            
+            elif wrong_gender == 1:
+                wrong_gender = 0
+                
+                if source_face_idx == len(source_faces_index):
+                    result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
+                    
+                    if enhancement_options is not None and len(source_faces_index) > 1:
+                        result_image = enhance_image(result_image, enhancement_options)
+                    
+                    return result_image, output, swapped
+            
+            else:
+                logger.status(f"No target face found for {face_num}")
+        
+        elif wrong_gender == 1:
+            wrong_gender = 0
+            
+            if source_face_idx == len(source_faces_index):
+                result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
+                
+                if enhancement_options is not None and len(source_faces_index) > 1:
+                    result_image = enhance_image(result_image, enhancement_options)
+                
+                return result_image, output, swapped
+        
+        else:
+            logger.status(f"No source face found for face number {source_face_idx}.")
+
+    result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
+    
+    if enhancement_options is not None and swapped > 0:
+        if mask_face and entire_mask_image is not None:
+            result_image = enhance_image_and_mask(result_image, enhancement_options,Image.fromarray(target_img_orig),Image.fromarray(entire_mask_image).convert("L"))    
+        else:    
+            result_image = enhance_image(result_image, enhancement_options)
+    elif mask_face and entire_mask_image is not None and swapped > 0:
+        result_image = Image.composite(result_image,Image.fromarray(target_img_orig),Image.fromarray(entire_mask_image).convert("L"))
+    
+    return result_image, output, swapped

sd-webui-reactor-main/sd-webui-reactor-main/scripts/reactor_version.py

@@ -0,0 +1,10 @@
+app_title = "ReActor"
+version_flag = "v0.6.0-a1"
+
+from scripts.reactor_logger import logger, get_Run, set_Run
+
+is_run = get_Run()
+
+if not is_run:
+    logger.status(f"Running {version_flag}")
+    set_Run(True)