VersionUP

0.7.1 Beta2

API.md

@@ -40,7 +40,7 @@ curl -X POST \
     "target_image": "data:image/png;base64,/9j/4QAYRXhpZgAASUkqAAgAAAAAAAAAAAAAAP/sABFEdWNreQABAAQAAABCAAD/7g...",
     "source_faces_index": [0],
     "face_index": [0],
-    "upscaler": "4x_Struzan_300000",
+    "upscaler": "4x_NMKD-Siax_200k",
     "scale": 2,
     "upscale_visibility": 1,
     "face_restorer": "CodeFormer",
@@ -50,13 +50,26 @@ curl -X POST \
     "gender_source": 0,
     "gender_target": 0,
     "save_to_file": 0,
-    "result_file_path": ""
+    "result_file_path": "",
+    "device": "CUDA",
+    "mask_face": 1,
+    "select_source": 1,
+    "face_model": "elena.safetensors",
+    "source_folder": "C:/faces",
+    "random_image": 1,
+    "upscale_force": 1
 	}'
 ```
 
 * 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"`.
+* `"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"`;
+* Set `"mask_face"` to `1` if you want ReActor to mask the face or to `0` if want ReActor to create a bbox around the face;
+* Set `"select_source"` to: 0 - Image, 1 - Face Model, 2 - Source Folder;
+* Set `"face_model"` to the face model file you want to choose if you set `"select_source": 1`;
+* Set `"source_folder"` to the path with source images (with faces you need as the results) if you set `"select_source": 2`;
+* Set `"random_image"` to `1` if want ReActor to choose a random image from the path of `"source_folder"`;
+* Set `"upscale_force"` to `1` if you want ReActor to upscale the image even if no face found.
 
 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).
 
@@ -69,3 +82,20 @@ As a result you recieve a "base64" image:
 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
+* http://127.0.0.1:7860/reactor/facemodels
+
+### FaceModel Buid API
+
+Send POST to http://127.0.0.1:7860/reactor/facemodels with body:
+
+```
+{
+    "source_images": ["data:image/png;base64,/9j/4QAYRXhpZgAASUkqAAgAAAAAAAAAAAAAAP/sABFEdWNreQABAAQAAABQAAD/7g...","data:image/png;base64,/9j/4QAYRXhpZgAASUkqAAgAAAAAAAAAAAAAAP/sABFEdWNreQABAAQAAABQAAD/7g...","data:image/png;base64,/9j/4QAYRXhpZgAASUkqAAgAAAAAAAAAAAAAAP/sABFEdWNreQABAAQAAABQAAD/7g..."],
+    "name": "my_super_model",
+    "compute_method": 0
+}
+```
+
+where:<br>
+"source_images" is a list of base64 encoded images,<br>
+"compute_method" is: 0 - Mean, 1- Median, 2 - Mode

README.md

@@ -2,7 +2,7 @@
 
   <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-brightgreen?style=for-the-badge&labelColor=darkgreen)
+  ![Version](https://img.shields.io/badge/version-0.7.1_beta2-green?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"/>
@@ -40,8 +40,65 @@
 
 ## What's new in the latest updates
 
-### 0.6.0 <sub><sup>ALPHA1
+### 0.7.1 <sub><sup>BETA1
 
+- Allow spaces for face indexes (e.g.: 0, 1, 2)
+- Sorting of face models list alphabetically
+- [FaceModels Build API](./API.md#facemodel-build-api)
+- Fixes and improvements
+
+<details>
+	<summary><a>Click to expand more</a></summary>
+
+### 0.7.0 <sub><sup>BETA2
+
+- X/Y/Z is improved! One more parameter is ready: you can now select several face models to create a variation of swaps to choose the best one!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-05.jpg?raw=true" alt="0.7.0-whatsnew-05" width="100%"/>
+
+To use "Face Model" axis - you should enable ReActor and choose any face model as the Source:<br>
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-07.jpg?raw=true" alt="0.7.0-whatsnew-07" width="50%"/><img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-06.jpg?raw=true" alt="0.7.0-whatsnew-06" width="50%"/>
+
+Full size demo image: [xyz_demo_2.png](https://raw.githubusercontent.com/Gourieff/Assets/main/sd-webui-reactor/xyz_demo_2.png)
+
+### 0.7.0 <sub><sup>BETA1
+
+- X/Y/Z Script support (up to 3 axes: CodeFormer Weight, Restorer Visibility, Face Mask Correction)
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-03.jpg?raw=true" alt="0.7.0-whatsnew-03" width="100%"/>
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-04.jpg?raw=true" alt="0.7.0-whatsnew-04" width="100%"/>
+
+Full size demo image: [xyz_demo.png](https://raw.githubusercontent.com/Gourieff/Assets/main/sd-webui-reactor/xyz_demo.png)
+
+__Don't forget to enable ReActor and set any source (to prevent "no source" error)__
+
+### 0.7.0 <sub><sup>ALPHA1
+
+- You can now blend faces to build blended face models ("Tools->Face Models->Blend") - due to popular demand
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-01.jpg?raw=true" alt="0.7.0-whatsnew-01" width="100%"/><img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-02.jpg?raw=true" alt="0.7.0-whatsnew-02" width="100%"/>
+
+- CUDA 12 Support in the Installer script for 1.17.0 ORT-GPU library
+- New tab "Detection" with "Threshold" and "Max Faces" parameters
+
+### 0.6.1 <sub><sup>BETA3
+
+- 'Force Upscale' option inside the 'Upscale' tab: ReActor will run the Upscaler even if there's no face is detected (FR https://github.com/Gourieff/sd-webui-reactor/issues/116)
+- ReActor shows filenames of source images in-process when the multiple images mode or the folder mode (random as well) is selected
+
+### 0.6.1 <sub><sup>BETA2
+
+- 'Save original' option works fine now when you select 'Multiple Images' or 'Source Folder'
+- Random Mode for 'Source Folder'
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/random_from_folder_demo_01.jpg?raw=true" alt="0.6.1-whatsnew-01" width="100%"/>
+
+### 0.6.0
+
+- New Logo
+- Adaptation to A1111 1.7.0 (appropriate GFPGAN loader)
+- New URL for the main model file
 - UI reworked
 - You can now load several source images (with reference faces) or set the path to the folder containing faces images
 
@@ -56,11 +113,13 @@
 
 <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%"/>
 
+</details>
+
 ## Installation
 
-[Automatic1111](#a1111) | [Vladmandic SD.Next](#sdnext) | [Google Colab SD WebUI](#colab)
+[A1111 WebUI / WebUI-Forge](#a1111) | [SD.Next](#sdnext) | [Google Colab SD WebUI](#colab)
 
-<a name="a1111">If you use [AUTOMATIC1111 web-ui](https://github.com/AUTOMATIC1111/stable-diffusion-webui/):
+<a name="a1111">If you use [AUTOMATIC1111 SD WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) or [SD WebUI Forge](https://github.com/lllyasviel/stable-diffusion-webui-forge):
 
 1. (For Windows Users):
   - Install **Visual Studio 2022** (Community version, for example - you need this step to build some of dependencies):
@@ -257,7 +316,7 @@ If this method doesn't help - there is some other extension that has a wrong ver
 ### **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 or (A1111 Portable) "run.bat"
+2. Download and put [prebuilt Insightface package](https://github.com/Gourieff/Assets/raw/main/Insightface/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 or (A1111 Portable) "run.bat"
 3. From stable-diffusion-webui (or SD.Next) root folder run CMD and `.\venv\Scripts\activate`<br>OR<br>(A1111 Portable) Run CMD
 4. Then update your PIP: `python -m pip install -U pip`<br>OR<br>(A1111 Portable)`system\python\python.exe -m pip install -U pip`
 5. Then install Insightface: `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`<br>OR<br>(A1111 Portable)`system\python\python.exe -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`
@@ -294,7 +353,7 @@ For the installation instruction follow the [ReActor Node repo](https://github.c
 
 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.
+The developers of this software are aware of its possible unethical application 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.**
 

README_RU.md

@@ -2,7 +2,7 @@
 
   <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-brightgreen?style=for-the-badge&labelColor=darkgreen)
+  ![Version](https://img.shields.io/badge/версия-0.7.1_beta2-green?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"/>
@@ -39,8 +39,61 @@
 
 ## Что нового в последних обновлениях
 
-### 0.6.0 <sub><sup>ALPHA1
+### 0.7.1 <sub><sup>BETA1
 
+- Использование пробелов в индексах лиц (пример: 0, 1, 2)
+- Список моделей лиц теперь отсортирован по алфавиту
+- [API для создания моделей лиц](./API.md#facemodel-build-api)
+- Правки и улучшения
+
+<details>
+	<summary><a>Нажмите, чтобы посмотреть больше</a></summary>
+
+### 0.7.0 <sub><sup>BETA2
+
+- X/Y/Z опция улучшена! Добавлен ещё один параметр: теперь вы можете выбрать несколько моделей лиц для создания вариации замененных лиц, чтобы выбрать наилучшие!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-05.jpg?raw=true" alt="0.7.0-whatsnew-05" width="100%"/>
+
+Чтобы использовать ось "Face Model" - активируйте РеАктор и выбирите любую модель лица в качестве источника:<br>
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-07.jpg?raw=true" alt="0.7.0-whatsnew-07" width="50%"/><img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-06.jpg?raw=true" alt="0.7.0-whatsnew-06" width="50%"/>
+
+Полноразмерное демо-изображение: [xyz_demo_2.png](https://raw.githubusercontent.com/Gourieff/Assets/main/sd-webui-reactor/xyz_demo_2.png)
+
+### 0.7.0 <sub><sup>BETA1
+
+- Поддержка X/Y/Z скрипта (до 3-х параметров: CodeFormer Weight, Restorer Visibility, Face Mask Correction)
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-03.jpg?raw=true" alt="0.7.0-whatsnew-03" width="100%"/>
+
+Полноразмерное демо-изображение: [xyz_demo.png](https://raw.githubusercontent.com/Gourieff/Assets/main/sd-webui-reactor/xyz_demo.png)
+
+### 0.7.0 <sub><sup>ALPHA1
+
+- По многочисленным просьбам появилась возможность строить смешанные модели лиц ("Tools->Face Models->Blend")
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-01.jpg?raw=true" alt="0.7.0-whatsnew-01" width="100%"/><img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-02.jpg?raw=true" alt="0.7.0-whatsnew-02" width="100%"/>
+
+- Поддержка CUDA 12 в скрипте установщика для библиотеки ORT-GPU версии 1.17.0
+- Новая вкладка "Detection" с параметрами "Threshold" и "Max Faces"
+
+### 0.6.1 <sub><sup>BETA3
+
+- Опция 'Force Upscale' внутри вкладки 'Upscale': апскейл выполнится, даже если не было обнаружено ни одного лица (FR https://github.com/Gourieff/sd-webui-reactor/issues/116)
+- Отображение имён файлов используемых изображений, когда выбрано несколько изображений или папка (а также режим случайного изображения)
+
+### 0.6.1 <sub><sup>BETA2
+
+- Опция 'Save original' теперь работает правильно, когда вы выбираете 'Multiple Images' или 'Source Folder'
+- Добавлен режим выбора случайного изображения для 'Source Folder'
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/random_from_folder_demo_01.jpg?raw=true" alt="0.6.1-whatsnew-01" width="100%"/>
+
+### 0.6.0
+
+- Новый логотип
+- Адаптация к версии A1111 1.7.0 (правильная загрузка GFPGAN)
+- Новая ссылка для файла основной модели
 - UI переработан
 - Появилась возможность загружать несколько исходных изображений с лицами или задавать путь к папке, содержащей такие изображения
 
@@ -55,13 +108,15 @@
 
 <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%"/>
 
+</details>
+
 <a name="installation">
 
 ## Установка
 
-[Automatic1111](#a1111) | [Vladmandic SD.Next](#sdnext) | [Google Colab SD WebUI](#colab)
+[A1111 WebUI / WebUI-Forge](#a1111) | [SD.Next](#sdnext) | [Google Colab SD WebUI](#colab)
 
-<a name="a1111">Если вы используете [AUTOMATIC1111 Web-UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui/):
+<a name="a1111">Если вы используете [AUTOMATIC1111 SD WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) или [SD WebUI Forge](https://github.com/lllyasviel/stable-diffusion-webui-forge):
 
 1. (Для пользователей Windows):
   - Установите **Visual Studio 2022** (Например, версию Community - этот шаг нужен для правильной компиляции библиотеки Insightface):
@@ -264,7 +319,7 @@ Inpainting также работает, но замена лица происх
 ### **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" или (A1111 Portable) "run.bat"
+2. Скачайте готовый [пакет Insightface](https://github.com/Gourieff/Assets/raw/main/Insightface/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" или (A1111 Portable) "run.bat"
 3. Из корневой директории откройте Консоль (CMD) и выполните `.\venv\Scripts\activate`<br>ИЛИ<br>(A1111 Portable) Откройте Консоль (CMD)
 4. Обновите PIP: `python -m pip install -U pip`<br>ИЛИ<br>(A1111 Portable)`system\python\python.exe -m pip install -U pip`
 5. Затем установите Insightface: `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`<br>ИЛИ<br>(A1111 Portable)`system\python\python.exe -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`

example/api_example.py

@@ -47,6 +47,11 @@ args=[
     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
+    None, #25 skip it for API
+    True, #26 Randomly select an image from the path
+    True, #27 Force Upscale even if no face found
+    0.6, #28 Face Detection Threshold
+    2, #29 Maximum number of faces to detect (0 is unlimited)
 ]
 
 # The args for ReActor can be found by 

example/api_external.curl

@@ -22,5 +22,8 @@ curl -X POST \
     "device": "CUDA",
     "mask_face": 1,
     "select_source": 1,
-    "face_model": "elena.safetensors"
+    "face_model": "elena.safetensors",
+    "source_folder": "C:/faces",
+    "random_image": 1,
+    "upscale_force": 1
     }'

example/api_external.json

@@ -18,5 +18,8 @@
     "device": "CUDA",
     "mask_face": 1,
     "select_source": 1,
-    "face_model": "elena.safetensors"
+    "face_model": "elena.safetensors",
+    "source_folder": "C:/faces",
+    "random_image": 1,
+    "upscale_force": 1
 }

install.py

@@ -12,7 +12,7 @@ except:
     try:
         from modules.paths import models_path
     except:
-        model_path = os.path.abspath("models")
+        models_path = os.path.abspath("models")
 
 
 BASE_PATH = os.path.dirname(os.path.realpath(__file__))
@@ -21,20 +21,6 @@ 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://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/inswapper_128.onnx"
 model_name = os.path.basename(model_url)
 model_path = os.path.join(models_dir, model_name)
@@ -97,11 +83,14 @@ with open(req_file) as file:
     install_count = 0
     ort = "onnxruntime-gpu"
     import torch
+    cuda_version = None
     try:
         if torch.cuda.is_available():
+            cuda_version = torch.version.cuda
+            print(f"CUDA {cuda_version}")
             if first_run or last_device is None:
                 last_device = "CUDA"
-        elif torch.backends.mps.is_available() or hasattr(torch,'dml'):
+        elif torch.backends.mps.is_available() or hasattr(torch,'dml') or hasattr(torch,'privateuseone'):
             ort = "onnxruntime"
             # to prevent errors when ORT-GPU is installed but we want ORT instead:
             if first_run:
@@ -114,7 +103,17 @@ with open(req_file) as file:
                 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):
+        if cuda_version is not None:
+            if float(cuda_version)>=12: # CU12.x
+                extra_index_url = "https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/"
+            else: # CU11.8
+                extra_index_url = "https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-11/pypi/simple"
+            if not is_installed(ort,"1.17.1",True):
+                install_count += 1
+                ort = "onnxruntime-gpu==1.17.1"
+                pip_uninstall("onnxruntime", "onnxruntime-gpu")
+                pip_install(ort,"--extra-index-url",extra_index_url)
+        elif not is_installed(ort,"1.18.1",False):
             install_count += 1
             pip_install(ort, "-U")
     except Exception as e:

reactor_ui/__init__.py

@@ -2,3 +2,4 @@ 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
+import reactor_ui.reactor_detection_ui as ui_detection

reactor_ui/reactor_detection_ui.py

@@ -0,0 +1,54 @@
+import gradio as gr
+from scripts.reactor_swapper import (
+    clear_faces,
+    clear_faces_list,
+    clear_faces_target,
+    clear_faces_all
+)
+
+# TAB DETECTION
+def show(show_br: bool = True):
+    with gr.Tab("Detection"):
+        with gr.Row():
+            det_thresh = gr.Slider(
+                minimum=0.1,
+                maximum=1.0,
+                value=0.5,
+                step=0.01,
+                label="Threshold",
+                info="The higher the value, the more sensitive the detection is to what is considered a face (0.5 by default)",
+                scale=2
+            )
+            det_maxnum = gr.Slider(
+                minimum=0,
+                maximum=20,
+                value=0,
+                step=1,
+                label="Max Faces",
+                info="Maximum number of faces to detect (0 is unlimited)",
+                scale=1
+            )
+        # gr.Markdown("<br>", visible=show_br)
+        gr.Markdown("Hashed images get processed with previously set detection parameters (the face is hashed with all available parameters to bypass the analyzer and speed up the process). Please clear the hash if you want to apply new detection settings.", visible=show_br)
+        with gr.Row():
+            imgs_hash_clear_single = gr.Button(
+                value="Clear Source Images Hash (Single)",
+                scale=1
+            )
+            imgs_hash_clear_multiple = gr.Button(
+                value="Clear Source Images Hash (Multiple)",
+                scale=1
+            )
+            imgs_hash_clear_target = gr.Button(
+                value="Clear Target Image Hash",
+                scale=1
+            )
+            imgs_hash_clear_all = gr.Button(
+                value="Clear All Hash"
+            )
+        progressbar_area = gr.Markdown("")
+        imgs_hash_clear_single.click(clear_faces,None,[progressbar_area])
+        imgs_hash_clear_multiple.click(clear_faces_list,None,[progressbar_area])
+        imgs_hash_clear_target.click(clear_faces_target,None,[progressbar_area])
+        imgs_hash_clear_all.click(clear_faces_all,None,[progressbar_area])
+    return det_thresh, det_maxnum

reactor_ui/reactor_main_ui.py

@@ -8,44 +8,77 @@ from scripts.reactor_swapper import (
 )
 from modules import shared
 
-SAVE_ORIGINAL: bool = False
+# SAVE_ORIGINAL: bool = False
 
 def update_fm_list(selected: str):
+    try: # GR3.x
         return gr.Dropdown.update(
             value=selected, choices=get_model_names(get_facemodels)
         )
+    except: # GR4.x
+        return gr.Dropdown(
+            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):
+    # def on_select_source(selected: bool, evt: gr.SelectData):
-        global SAVE_ORIGINAL
+    def on_select_source(evt: gr.SelectData):
+        # global SAVE_ORIGINAL
         if evt.index == 2:
-            if SAVE_ORIGINAL != selected:
+            # if SAVE_ORIGINAL != selected:
-                SAVE_ORIGINAL = selected
+            #     SAVE_ORIGINAL = selected
+            try: # GR3.x
                 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),
+                    # save_original: gr.Checkbox.update(value=False,visible=False),
                     imgs_hash_clear: gr.Button.update(visible=True)
                 }
+            except: # GR4.x
+                return {
+                    control_col_1: gr.Column(visible=False),
+                    control_col_2: gr.Column(visible=False),
+                    control_col_3: gr.Column(visible=True),
+                    # save_original: gr.Checkbox.update(value=False,visible=False),
+                    imgs_hash_clear: gr.Button(visible=True)
+                }
         if evt.index == 0:
+            try: # GR3.x
                 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),
+                    # save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
                     imgs_hash_clear: gr.Button.update(visible=False)
                 }
+            except: # GR4.x
+                return {
+                    control_col_1: gr.Column(visible=True),
+                    control_col_2: gr.Column(visible=False),
+                    control_col_3: gr.Column(visible=False),
+                    # save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
+                    imgs_hash_clear: gr.Button(visible=False)
+                }
         if evt.index == 1:
+            try: # GR3.x
                 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),
+                    # save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
                     imgs_hash_clear: gr.Button.update(visible=False)
                 }
+            except: # GR4.x
+                return {
+                    control_col_1: gr.Column(visible=False),
+                    control_col_2: gr.Column(visible=True),
+                    control_col_3: gr.Column(visible=False),
+                    # save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
+                    imgs_hash_clear: gr.Button(visible=False)
+                }
         
     progressbar_area = gr.Markdown("")
     with gr.Tab("Main"):
@@ -84,35 +117,48 @@ def show(is_img2img: bool, show_br: bool = True, **msgs):
                 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():
+                    selected_tab = gr.Textbox('tab_single', visible=False)
+                    with gr.Tabs() as tab_single:
+                        with gr.Tab('Single'):
                             img = gr.Image(
                                 type="pil",
                                 label="Single Source Image",
                             )
+                        with gr.Tab('Multiple') as tab_multiple:
                             imgs = gr.Files(
                                 label=f"Multiple Source Images{msgs['extra_multiple_source']}",
                                 file_types=["image"],
                             )
+                    tab_single.select(fn=lambda: 'tab_single', inputs=[], outputs=[selected_tab])
+                    tab_multiple.select(fn=lambda: 'tab_multiple', inputs=[], outputs=[selected_tab])
             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>")
+                with gr.Row():
                     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']}",
+                        scale=2,
+                    )
+                    random_image = gr.Checkbox(
+                        False,
+                        label="Random Image",
+                        info="Randomly select an image from the path",
+                        scale=1,
                     )
             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)"
+                    info="Save the original image(s) made before swapping"
                 )
             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)",
+                    info="Save the original image(s) made before swapping",
                     visible=show_br
                 )
             # imgs.upload(on_files_upload_uncheck_so,[save_original],[save_original],show_progress=False)
@@ -177,6 +223,7 @@ def show(is_img2img: bool, show_br: bool = True, **msgs):
                 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)
+    # 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)
+    select_source.select(on_select_source,None,[control_col_1,control_col_2,control_col_3,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
+    return img, imgs, selected_tab, 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, random_image

reactor_ui/reactor_tools_ui.py

@@ -1,14 +1,16 @@
 import gradio as gr
-from scripts.reactor_swapper import build_face_model
+from scripts.reactor_swapper import build_face_model, blend_faces
 
 # TAB TOOLS
 def show():
     with gr.Tab("Tools"):
         with gr.Tab("Face Models"):
+
+            with gr.Tab("Single"):
                 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",
+                    label="Load an Image to build -Face Model-",
                 )
                 with gr.Row(equal_height=True):
                     fm_name = gr.Textbox(
@@ -23,3 +25,37 @@ def show():
                     inputs=[img_fm, fm_name],
                     outputs=[save_fm],
                 )
+            
+            with gr.Tab("Blend"):
+                gr.Markdown("Load a set of images containing any person, name it and click 'Build and Save'")
+                with gr.Row():
+                    imgs_fm = gr.Files(
+                        label=f"Load Images to build -Blended Face Model-",
+                        file_types=["image"]
+                    )
+                    with gr.Column():
+                        compute_method = gr.Radio(
+                            ["Mean", "Median", "Mode"],
+                            value="Mean",
+                            label="Compute Method",
+                            type="index",
+                            info="Mean (recommended) - Average value (best result 👍); Median* - Mid-point value (may be funny 😅); Mode - Most common value (may be scary 😨); *Mean and Median will be similar if you load two images"
+                        )
+                        shape_check = gr.Checkbox(
+                            False,
+                            label="Check -Embedding Shape- on Similarity",
+                            info="(Experimental) Turn it ON if you want to skip the faces which are too much different from the first one in the list to prevent some probable 'shape mismatches'"
+                        )
+                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(
+                    blend_faces,
+                    inputs=[imgs_fm, fm_name, compute_method, shape_check],
+                    outputs=[save_fm],
+                )

reactor_ui/reactor_upscale_ui.py

@@ -9,10 +9,18 @@ def update_upscalers_list(selected: str):
 # TAB UPSCALE
 def show(show_br: bool = True):
     with gr.Tab("Upscale"):
+        with gr.Row():
             restore_first = gr.Checkbox(
                 True,
                 label="1. Restore Face -> 2. Upscale (-Uncheck- if you want vice versa)",
-            info="Postprocessing Order"
+                info="Postprocessing Order",
+                scale=2
+            )
+            upscale_force = gr.Checkbox(
+                False,
+                label="Force Upscale",
+                info="Upscale anyway - even if no face found",
+                scale=1
             )
         with gr.Row():
             upscaler_name = gr.Dropdown(
@@ -36,4 +44,4 @@ def show(show_br: bool = True):
             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
+    return restore_first, upscaler_name, upscaler_scale, upscaler_visibility, upscale_force

requirements.txt

@@ -1,3 +1,4 @@
+albumentations==1.4.3
 insightface==0.7.3
-onnx>=1.14.0
+onnx==1.16.1
 opencv-python>=4.7.0.72

scripts/console_log_patch.py

@@ -2,7 +2,7 @@ import os.path as osp
 import glob
 import logging
 import insightface
-from insightface.model_zoo.model_zoo import ModelRouter, PickableInferenceSession
+from insightface.model_zoo.model_zoo import ModelRouter, PickableInferenceSession, get_default_providers
 from insightface.model_zoo.retinaface import RetinaFace
 from insightface.model_zoo.landmark import Landmark
 from insightface.model_zoo.attribute import Attribute
@@ -97,15 +97,20 @@ def patched_inswapper_init(self, model_file=None, session=None):
     self.input_size = tuple(input_shape[2:4][::-1])
 
 
-def patch_insightface(get_model, faceanalysis_init, faceanalysis_prepare, inswapper_init):
+def patched_get_default_providers():
+    return ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider']
+
+
+def patch_insightface(get_default_providers, get_model, faceanalysis_init, faceanalysis_prepare, inswapper_init):
+    insightface.model_zoo.model_zoo.get_default_providers = get_default_providers
     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__]
+original_functions = [patched_get_default_providers, ModelRouter.get_model, FaceAnalysis.__init__, FaceAnalysis.prepare, INSwapper.__init__]
-patched_functions = [patched_get_model, patched_faceanalysis_init, patched_faceanalysis_prepare, patched_inswapper_init]
+patched_functions = [patched_get_default_providers, patched_get_model, patched_faceanalysis_init, patched_faceanalysis_prepare, patched_inswapper_init]
 
 
 def apply_logging_patch(console_logging_level):

scripts/reactor_api.py

@@ -1,12 +1,23 @@
 '''
 Thanks SpenserCai for the original version of the roop api script
 -----------------------------------
---- ReActor External API v1.0.1 ---
+--- ReActor External API v1.0.8a ---
 -----------------------------------
 '''
 import os, glob
 from datetime import datetime, date
 from fastapi import FastAPI, Body
+# from fastapi.exceptions import HTTPException
+# from io import BytesIO
+# from PIL import Image
+# import base64
+# import numpy as np
+# import cv2
+import asyncio
+from concurrent.futures import ThreadPoolExecutor
+# from concurrent.futures.process import ProcessPoolExecutor
+# from contextlib import asynccontextmanager
+# import multiprocessing
 
 # from modules.api.models import *
 from modules import scripts, shared
@@ -14,8 +25,32 @@ from modules.api import api
 
 import gradio as gr
 
-from scripts.reactor_swapper import EnhancementOptions, swap_face
+from scripts.reactor_swapper import EnhancementOptions, blend_faces, swap_face, DetectionOptions
 from scripts.reactor_logger import logger
+from scripts.reactor_helpers import get_facemodels
+
+
+# @asynccontextmanager
+# async def lifespan(app: FastAPI):
+#     app.state.executor = ProcessPoolExecutor(max_workers=4)
+#     yield
+#     app.state.executor.shutdown()
+
+# app = FastAPI(lifespan=lifespan)
+
+# def run_app(a: FastAPI):
+#     global app
+#     a = app
+#     return a
+
+# _executor_tp = ThreadPoolExecutor(max_workers=8)
+# def entry_point():
+#     _executor_pp = ProcessPoolExecutor(max_workers=8)
+# pool = multiprocessing.Pool(4)
+
+async def run_event(app, fn, *args):
+    loop = asyncio.get_event_loop()
+    return await loop.run_in_executor(app.state.executor, fn, *args)
 
 
 def default_file_path():
@@ -52,7 +87,21 @@ def get_full_model(model_name):
             return model
     return None
 
+# def decode_base64_to_image_rgba(encoding):
+#     if encoding.startswith("data:image/"):
+#         encoding = encoding.split(";")[1].split(",")[1]
+#     try:
+#         im_bytes = base64.b64decode(encoding)
+#         im_arr = np.frombuffer(im_bytes, dtype=np.uint8)  # im_arr is one-dim Numpy array
+#         img = cv2.imdecode(im_arr, flags=cv2.IMREAD_UNCHANGED)
+#         img = cv2.cvtColor(img, cv2.COLOR_BGRA2RGBA)
+#         image = Image.fromarray(img, mode="RGBA")
+#         return image
+#     except Exception as e:
+#         raise HTTPException(status_code=500, detail="Invalid encoded image") from e
+
 def reactor_api(_: gr.Blocks, app: FastAPI):
+    app.state.executor = ThreadPoolExecutor(max_workers=8)
     @app.post("/reactor/image")
     async def reactor_image(
         source_image: str = Body("",title="Source Face Image"),
@@ -75,30 +124,53 @@ def reactor_api(_: gr.Blocks, app: FastAPI):
         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")
+        source_folder: str = Body("",title="The path to the folder containing source faces images"),
+        random_image: int = Body(0,title="Randomly select an image from the path"),
+        upscale_force: int = Body(0,title="Force Upscale even if no face found"),
+        det_thresh: float = Body(0.5,title="Face Detection Threshold"),
+        det_maxnum: int = Body(0,title="Maximum number of faces to detect (0 is unlimited)"),
     ):
-        s_image = api.decode_base64_to_image(source_image)
+        s_image = api.decode_base64_to_image(source_image) if select_source == 0 else None
         t_image = api.decode_base64_to_image(target_image)
+
+        if t_image.mode == 'RGBA':
+            _, _, _, alpha = t_image.split()
+        else:
+            alpha = None
+        
         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)
+        random_image = False if random_image == 0 else True
+        upscale_force = False if upscale_force == 0 else True
+        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,upscale_force=upscale_force)
+        det_options = DetectionOptions(det_thresh=det_thresh, det_maxnum=det_maxnum)
         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)
+        
+        args = [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, random_image,det_options]
+        # result,_,_ = pool.map(swap_face, *args)
+        result,_,_ = await run_event(app,swap_face,*args)
+        # 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, random_image,det_options)
+
+        if alpha is not None:
+            result = result.convert("RGBA")
+            result.putalpha(alpha)
+
         if save_to_file == 1:
             if result_file_path == "":
                 result_file_path = default_file_path()
             try:
-                result[0].save(result_file_path, format='PNG')
+                file_format = os.path.split(result_file_path)[1].split(".")[1]
+                result.save(result_file_path, format=file_format)
                 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])}
+        return {"image": api.encode_pil_to_base64(result)}
 
     @app.get("/reactor/models")
     async def reactor_models():
@@ -110,9 +182,23 @@ def reactor_api(_: gr.Blocks, app: FastAPI):
         names = [upscaler.name for upscaler in shared.sd_upscalers]
         return {"upscalers": names}
     
+    @app.get("/reactor/facemodels")
+    async def reactor_facemodels():
+        facemodels = [os.path.split(model)[1].split(".")[0] for model in get_facemodels()]
+        return {"facemodels": facemodels}
+
+    @app.post("/reactor/facemodels")
+    async def reactor_facemodels_build(
+        source_images: list[str] = Body([""],title="Source Face Image List"),
+        name: str = Body("",title="Face Model Name"),
+        compute_method: int = Body(0,title="Compute Method (Mean, Median, Mode)"),
+    ):
+        images = [api.decode_base64_to_image(img) for img in source_images]
+        blend_faces(images, name, compute_method, False, is_api=True)
+        return {"facemodels": [os.path.split(model)[1].split(".")[0] for model in get_facemodels()]}
+
 try:
     import modules.script_callbacks as script_callbacks
-
     script_callbacks.on_app_started(reactor_api)
 except:
     pass

scripts/reactor_faceswap.py

@@ -6,7 +6,7 @@ from typing import List
 
 import modules.scripts as scripts
 from modules.upscaler import Upscaler, UpscalerData
-from modules import scripts, shared, images, scripts_postprocessing, ui_components
+from modules import scripts, shared, images, scripts_postprocessing
 from modules.processing import (
     Processed,
     StableDiffusionProcessing,
@@ -15,10 +15,17 @@ from modules.processing import (
 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 reactor_ui import (
+    ui_main,
+    ui_upscale,
+    ui_tools,
+    ui_settings,
+    ui_detection,
+)
 from scripts.reactor_logger import logger
 from scripts.reactor_swapper import (
     EnhancementOptions,
+    DetectionOptions,
     swap_face,
     check_process_halt,
     reset_messaged,
@@ -28,10 +35,24 @@ from scripts.console_log_patch import apply_logging_patch
 from scripts.reactor_helpers import (
     make_grid,
     set_Device,
-    get_SDNEXT
+    get_SDNEXT,
 )
 from scripts.reactor_globals import SWAPPER_MODELS_PATH #, DEVICE, DEVICE_LIST
 
+def IA_cap(cond: bool, label: str=""):
+    return None
+
+try:
+    from modules.ui_components import InputAccordion
+    NO_IA = False
+except:
+    NO_IA = True
+    InputAccordion = IA_cap
+
+
+def check_old_webui():
+    return NO_IA
+
 
 class FaceSwapScript(scripts.Script):
     def title(self):
@@ -41,19 +62,12 @@ class FaceSwapScript(scripts.Script):
         return scripts.AlwaysVisible
 
     def ui(self, is_img2img):
-        with ui_components.InputAccordion(False, label=f"{app_title}") as enable:
+        with (
-        # with gr.Accordion(f"{app_title}", open=False):
+            gr.Accordion(f"{app_title}", open=False) if check_old_webui() else InputAccordion(False, label=f"{app_title}") as enable
+        ):
 
-            # def on_files_upload_uncheck_so(selected: bool):
+            # SD.Next or A1111 1.52:
-            #     global SAVE_ORIGINAL
+            if get_SDNEXT() or check_old_webui():
-            #     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)
-
-            # SD.Next fix
-            if get_SDNEXT():
                 enable = gr.Checkbox(False, label="Enable")
             
             # enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
@@ -63,10 +77,13 @@ class FaceSwapScript(scripts.Script):
             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)
+            img, imgs, selected_tab, 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, random_image = ui_main.show(is_img2img=is_img2img, **msgs)
+            
+            # TAB DETECTION
+            det_thresh, det_maxnum = ui_detection.show()
             
             # TAB UPSCALE
-            restore_first, upscaler_name, upscaler_scale, upscaler_visibility = ui_upscale.show()
+            restore_first, upscaler_name, upscaler_scale, upscaler_visibility, upscale_force = ui_upscale.show()
 
             # TAB TOOLS
             ui_tools.show()
@@ -103,6 +120,11 @@ class FaceSwapScript(scripts.Script):
             face_model,
             source_folder,
             imgs,
+            random_image,
+            upscale_force,
+            det_thresh,
+            det_maxnum,
+            selected_tab,
         ]
 
 
@@ -130,6 +152,14 @@ class FaceSwapScript(scripts.Script):
             upscale_visibility=self.upscaler_visibility,
             restorer_visibility=self.face_restorer_visibility,
             codeformer_weight=self.codeformer_weight,
+            upscale_force=self.upscale_force
+        )
+    
+    @property
+    def detection_options(self) -> DetectionOptions:
+        return DetectionOptions(
+            det_thresh=self.det_thresh,
+            det_maxnum=self.det_maxnum
         )
 
     def process(
@@ -161,6 +191,11 @@ class FaceSwapScript(scripts.Script):
         face_model,
         source_folder,
         imgs,
+        random_image,
+        upscale_force,
+        det_thresh,
+        det_maxnum,
+        selected_tab,
     ):
         self.enable = enable
         if self.enable:
@@ -172,7 +207,10 @@ class FaceSwapScript(scripts.Script):
                 return
             
             global SWAPPER_MODELS_PATH
+            if selected_tab == "tab_single":
                 self.source = img
+            else:
+                self.source = None
             self.face_restorer_name = face_restorer_name
             self.upscaler_scale = upscaler_scale
             self.upscaler_visibility = upscaler_visibility
@@ -194,16 +232,23 @@ class FaceSwapScript(scripts.Script):
             self.select_source = select_source
             self.face_model = face_model
             self.source_folder = source_folder
+            if selected_tab == "tab_single":
+                self.source_imgs = None
+            else:
                 self.source_imgs = imgs
+            self.random_image = random_image
+            self.upscale_force = upscale_force
+            self.det_thresh=det_thresh
+            self.det_maxnum=det_maxnum
             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()
+                int(x) for x in source_faces_index.strip().replace(" ", "").strip(",").split(",") if x.isnumeric()
             ]
             self.faces_index = [
-                int(x) for x in faces_index.strip(",").split(",") if x.isnumeric()
+                int(x) for x in faces_index.strip().replace(" ", "").strip(",").split(",") if x.isnumeric()
             ]
             if len(self.source_faces_index) == 0:
                 self.source_faces_index = [0]
@@ -217,14 +262,32 @@ class FaceSwapScript(scripts.Script):
                 self.target_hash_check = False
             if self.mask_face is None:
                 self.mask_face = False
+            if self.random_image is None:
+                self.random_image = False
+            if self.upscale_force is None:
+                self.upscale_force = False
+            
+            if shared.state.job_count > 0:
+                # logger.debug(f"Job count: {shared.state.job_count}")
+                self.face_restorer_visibility = shared.opts.data['restorer_visibility'] if 'restorer_visibility' in shared.opts.data.keys() else face_restorer_visibility
+                self.codeformer_weight = shared.opts.data['codeformer_weight'] if 'codeformer_weight' in shared.opts.data.keys() else codeformer_weight
+                self.mask_face = shared.opts.data['mask_face'] if 'mask_face' in shared.opts.data.keys() else mask_face
+                self.face_model = shared.opts.data['face_model'] if 'face_model' in shared.opts.data.keys() else face_model
 
             logger.debug("*** Set Device")
             set_Device(self.device)
 
+            if (self.save_original is None or not self.save_original) and (self.select_source == 2 or self.source_imgs is not None):
+                p.do_not_save_samples = True
+            
             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.debug("*** Check process")
+
                     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)):
@@ -247,6 +310,8 @@ class FaceSwapScript(scripts.Script):
                             face_model = self.face_model,
                             source_folder = None,
                             source_imgs = None,
+                            random_image = False,
+                            detection_options=self.detection_options,
                         )
                         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")
@@ -264,7 +329,7 @@ class FaceSwapScript(scripts.Script):
     def postprocess(self, p: StableDiffusionProcessing, processed: Processed, *args):
         if self.enable:
 
-            logger.debug("*** Check postprocess")
+            logger.debug("*** Check postprocess - before IF")
 
             reset_messaged()
             if check_process_halt():
@@ -272,6 +337,8 @@ class FaceSwapScript(scripts.Script):
 
             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)):
 
+                logger.debug("*** Check postprocess - after IF")
+
                 postprocess_run: bool = True
 
                 orig_images : List[Image.Image] = processed.images[processed.index_of_first_image:]
@@ -311,17 +378,24 @@ class FaceSwapScript(scripts.Script):
                             face_model = self.face_model,
                             source_folder = self.source_folder,
                             source_imgs = self.source_imgs,
+                            random_image = self.random_image,
+                            detection_options=self.detection_options,
                         )
 
                         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)
+                                if self.save_original:
                                     result_images.extend(result)
+                                else:
+                                    result_images = 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")
 
@@ -353,6 +427,21 @@ class FaceSwapScript(scripts.Script):
                 processed.images = result_images
                 # processed.infotexts = result_info
             
+            elif self.select_source == 0 and self.source is not None and self.source_imgs is not None:
+
+                logger.debug("*** Check postprocess - after ELIF")
+
+                if self.result is not None:
+                    orig_infotexts : List[str] = processed.infotexts[processed.index_of_first_image:]
+                    processed.images = [self.result]
+                    try:
+                        img_path = save_image(self.result, p.outpath_samples, "", p.all_seeds[0], p.all_prompts[0], "png", info=orig_infotexts[0], p=p, suffix="")
+                    except:
+                        logger.error("Cannot save a result image - please, check SD WebUI Settings (Saving and Paths)")
+                else:
+                    logger.error("Cannot create a result image")
+
+    
     def postprocess_batch(self, p, *args, **kwargs):
         if self.enable and not self.save_original:
             logger.debug("*** Check postprocess_batch")
@@ -390,7 +479,10 @@ class FaceSwapScript(scripts.Script):
                 face_model = self.face_model,
                 source_folder = None,
                 source_imgs = None,
+                random_image = False,
+                detection_options=self.detection_options,
             )
+            self.result = result
             try:
                 pp = scripts_postprocessing.PostprocessedImage(result)
                 pp.info = {}
@@ -411,11 +503,14 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
     order = 20000
 
     def ui(self):
-        with ui_components.InputAccordion(False, label=f"{app_title}") as enable:
+        with (
+            gr.Accordion(f"{app_title}", open=False) if check_old_webui() else InputAccordion(False, label=f"{app_title}") as enable
+        ):
+        # with ui_components.InputAccordion(False, label=f"{app_title}") as enable:
         # with gr.Accordion(f"{app_title}", open=False):
             
-            # SD.Next fix
+            # SD.Next or A1111 1.52:
-            if get_SDNEXT():
+            if get_SDNEXT() or check_old_webui():
                 enable = gr.Checkbox(False, label="Enable")
 
             # enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
@@ -423,12 +518,15 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
 
             # TAB MAIN
             msgs: dict = {
-                "extra_multiple_source": " | Сomparison grid as a result",
+                "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=False, show_br=False, **msgs)
+            img, imgs, selected_tab, 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, random_image = ui_main.show(is_img2img=False, show_br=False, **msgs)
+            
+            # TAB DETECTION
+            det_thresh, det_maxnum = ui_detection.show()
             
             # TAB UPSCALE
-            restore_first, upscaler_name, upscaler_scale, upscaler_visibility = ui_upscale.show(show_br=False)
+            restore_first, upscaler_name, upscaler_scale, upscaler_visibility, upscale_force = ui_upscale.show(show_br=False)
                         
             # TAB TOOLS
             ui_tools.show()
@@ -460,6 +558,11 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
             'face_model': face_model,
             'source_folder': source_folder,
             'imgs': imgs,
+            'random_image': random_image,
+            'upscale_force': upscale_force,
+            'det_thresh': det_thresh,
+            'det_maxnum': det_maxnum,
+            'selected_tab': selected_tab,
         }
         return args
 
@@ -487,6 +590,14 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
             upscale_visibility=self.upscaler_visibility,
             restorer_visibility=self.face_restorer_visibility,
             codeformer_weight=self.codeformer_weight,
+            upscale_force=self.upscale_force,
+        )
+    
+    @property
+    def detection_options(self) -> DetectionOptions:
+        return DetectionOptions(
+            det_thresh=self.det_thresh,
+            det_maxnum=self.det_maxnum
         )
 
     def process(self, pp: scripts_postprocessing.PostprocessedImage, **args):
@@ -496,7 +607,10 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
                 return
 
             global SWAPPER_MODELS_PATH
+            if args['selected_tab'] == "tab_single":
                 self.source = args['img']
+            else:
+                self.source = None
             self.face_restorer_name = args['face_restorer_name']
             self.upscaler_scale = args['upscaler_scale']
             self.upscaler_visibility = args['upscaler_visibility']
@@ -513,7 +627,14 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
             self.select_source = args['select_source']
             self.face_model = args['face_model']
             self.source_folder = args['source_folder']
+            if args['selected_tab'] == "tab_single":
+                self.source_imgs = None
+            else:
                 self.source_imgs = args['imgs']
+            self.random_image = args['random_image']
+            self.upscale_force = args['upscale_force']
+            self.det_thresh = args['det_thresh']
+            self.det_maxnum = args['det_maxnum']
             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":
@@ -530,6 +651,10 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
                 self.faces_index = [0]
             if self.mask_face is None:
                 self.mask_face = False
+            if self.random_image is None:
+                self.random_image = False
+            if self.upscale_force is None:
+                self.upscale_force = False
 
             current_job_number = shared.state.job_no + 1
             job_count = shared.state.job_count
@@ -544,10 +669,22 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
 
                 logger.debug("We're here: process() 2")
 
+                if self.source is not None and self.select_source == 0:
+                    self.source_imgs = None
+
                 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
+
+                # Extract alpha channel
+                logger.debug(f"image = {image}")
+                if image.mode == 'RGBA':
+                    _, _, _, alpha = image.split()
+                else:
+                    alpha = None
+                logger.debug(f"alpha = {alpha}")
+
                 result, output, swapped = swap_face(
                     self.source,
                     image,
@@ -565,11 +702,17 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
                     face_model=self.face_model,
                     source_folder=self.source_folder,
                     source_imgs=self.source_imgs,
+                    random_image=self.random_image,
+                    detection_options=self.detection_options,
                 )
                 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:
+                            if hasattr(pp, 'extra_images'):
+                                image = result[0]
+                                pp.extra_images.extend(result[1:])
+                            else:
                                 grid = make_grid(result)
                                 result.insert(0, grid)
                                 image = grid
@@ -581,6 +724,13 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
                 else:
                     try:
                         pp.info["ReActor"] = True
+
+                        if alpha is not None:
+                            logger.debug(f"result = {result}")
+                            result = result.convert("RGBA")
+                            result.putalpha(alpha)
+                            logger.debug(f"result_alpha = {result}")
+
                         pp.image = result
                         logger.status("---Done!---")
                     except Exception:

scripts/reactor_helpers.py

@@ -1,4 +1,4 @@
-import os, glob
+import os, glob, random
 from collections import Counter
 from PIL import Image
 from math import isqrt, ceil
@@ -203,15 +203,36 @@ def get_facemodels():
 
 def get_model_names(get_models):
     models = get_models()
-    names = ["None"]
+    names = []
     for x in models:
         names.append(os.path.basename(x))
+    # Sort ignoring case during sort but retain in output
+    names.sort(key=str.lower)
+    names.insert(0, "None")
     return names
 
 def get_images_from_folder(path: str):
-    images_path = os.path.join(path, "*")
+    files_path = os.path.join(path, "*")
-    images = glob.glob(images_path)
+    files = glob.glob(files_path)
-    return [Image.open(x) for x in images if x.endswith(('jpg', 'png', 'jpeg', 'webp', 'bmp'))]
+    images = []
+    images_names = []
+    for x in files:
+        if x.endswith(('jpg', 'png', 'jpeg', 'webp', 'bmp')):
+            images.append(Image.open(x))
+            images_names.append(os.path.basename(x))
+    return images,images_names
+    # return [Image.open(x) for x in images if x.endswith(('jpg', 'png', 'jpeg', 'webp', 'bmp'))],[os.path.basename(x) for x in images if x.endswith(('jpg', 'png', 'jpeg', 'webp', 'bmp'))]
+
+def get_random_image_from_folder(path: str):
+    images,names = get_images_from_folder(path)
+    random_image_index = random.randint(0, len(images) - 1)
+    return [images[random_image_index]],[names[random_image_index]]
 
 def get_images_from_list(imgs: List):
-    return [Image.open(os.path.abspath(x.name)) for x in imgs]
+    images = []
+    images_names = []
+    for x in imgs:
+        images.append(Image.open(os.path.abspath(x.name)))
+        images_names.append(os.path.basename(x.name))
+    return images,images_names
+    # return [Image.open(os.path.abspath(x.name)) for x in imgs],[os.path.basename(x.name) for x in imgs]

scripts/reactor_swapper.py

@@ -6,6 +6,7 @@ from typing import List, Union
 import cv2
 import numpy as np
 from PIL import Image
+from scipy import stats
 
 import insightface
 from insightface.app.common import Face
@@ -17,6 +18,7 @@ from scripts.reactor_helpers import (
     save_face_model, 
     load_face_model, 
     get_images_from_folder,
+    get_random_image_from_folder,
     get_images_from_list,
     set_SDNEXT
 )
@@ -63,7 +65,12 @@ class EnhancementOptions:
     face_restorer: FaceRestoration = None
     restorer_visibility: float = 0.5
     codeformer_weight: float = 0.5
+    upscale_force: bool = False
 
+@dataclass
+class DetectionOptions:
+    det_thresh: float = 0.5
+    det_maxnum: int = 0
 
 MESSAGED_STOPPED = False
 MESSAGED_SKIPPED = False
@@ -104,12 +111,33 @@ TARGET_IMAGE_HASH = None
 SOURCE_FACES_LIST = []
 SOURCE_IMAGE_LIST_HASH = []
 
+def clear_faces():
+    global SOURCE_FACES, SOURCE_IMAGE_HASH
+    SOURCE_FACES = None
+    SOURCE_IMAGE_HASH = None
+    logger.status("Source Images Hash has been reset (for Single Source or Face Model)")
+
 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 clear_faces_target():
+    global TARGET_FACES, TARGET_IMAGE_HASH
+    TARGET_FACES = None
+    TARGET_IMAGE_HASH = None
+    logger.status("Target Images Hash has been reset")
+
+def clear_faces_all():
+    global SOURCE_FACES, SOURCE_IMAGE_HASH, SOURCE_FACES_LIST, SOURCE_IMAGE_LIST_HASH, TARGET_FACES, TARGET_IMAGE_HASH
+    SOURCE_FACES = None
+    SOURCE_IMAGE_HASH = None
+    TARGET_FACES = None
+    TARGET_IMAGE_HASH = None
+    SOURCE_FACES_LIST = []
+    SOURCE_IMAGE_LIST_HASH = []
+    logger.status("All Images Hash has been reset")
 
 def getAnalysisModel():
     global ANALYSIS_MODEL
@@ -138,13 +166,14 @@ def restore_face(image: Image, enhancement_options: EnhancementOptions):
     
     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":
+            logger.status("Restoring the face with %s (weight: %s)", enhancement_options.face_restorer.name(), enhancement_options.codeformer_weight)
             numpy_image = codeformer_model.codeformer.restore(
                 numpy_image, w=enhancement_options.codeformer_weight
             )
         else: # GFPGAN:
+            logger.status("Restoring the face with %s", enhancement_options.face_restorer.name())
             numpy_image = gfpgan_model.gfpgan_fix_faces(numpy_image)
             # numpy_image = enhancement_options.face_restorer.restore(numpy_image)
         restored_image = Image.fromarray(numpy_image)
@@ -268,13 +297,13 @@ 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)):
+def analyze_faces(img_data: np.ndarray, det_size=(640, 640), det_thresh=0.5, det_maxnum=0):
     logger.info("Applied Execution Provider: %s", PROVIDERS[0])
     face_analyser = copy.deepcopy(getAnalysisModel())
-    face_analyser.prepare(ctx_id=0, det_size=det_size)
+    face_analyser.prepare(ctx_id=0, det_thresh=det_thresh, det_size=det_size)
-    return face_analyser.get(img_data)
+    return face_analyser.get(img_data, max_num=det_maxnum)
 
-def get_face_single(img_data: np.ndarray, face, face_index=0, det_size=(640, 640), gender_source=0, gender_target=0):
+def get_face_single(img_data: np.ndarray, face, face_index=0, det_size=(640, 640), gender_source=0, gender_target=0, det_thresh=0.5, det_maxnum=0):
 
     buffalo_path = os.path.join(models_path, "insightface/models/buffalo_l.zip")
     if os.path.exists(buffalo_path):
@@ -297,20 +326,20 @@ def get_face_single(img_data: np.ndarray, face, face_index=0, det_size=(640, 640
     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)
+            return get_face_single(img_data, analyze_faces(img_data, det_size_half, det_thresh, det_maxnum), face_index, det_size_half, gender_source, gender_target, det_thresh, det_maxnum)
         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)
+            return get_face_single(img_data, analyze_faces(img_data, det_size_half, det_thresh, det_maxnum), face_index, det_size_half, gender_source, gender_target, det_thresh, det_maxnum)
         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)
+        return get_face_single(img_data, analyze_faces(img_data, det_size_half, det_thresh, det_maxnum), face_index, det_size_half, gender_source, gender_target, det_thresh, det_maxnum)
 
     try:
         return sorted(face, key=lambda x: x.bbox[0])[face_index], 0, face_age, face_gender
@@ -335,6 +364,8 @@ def swap_face(
     face_model: str = "None",
     source_folder: str = "",
     source_imgs: Union[List, None] = None,
+    random_image: bool = False,
+    detection_options: Union[DetectionOptions, None] = None,
 ):
     global SOURCE_FACES, SOURCE_IMAGE_HASH, TARGET_FACES, TARGET_IMAGE_HASH, PROVIDERS, SOURCE_FACES_LIST, SOURCE_IMAGE_LIST_HASH
 
@@ -376,7 +407,11 @@ def swap_face(
 
             result = []
 
-            source_images = get_images_from_folder(source_folder) if select_source == 2 else get_images_from_list(source_imgs)
+            if random_image and select_source == 2:
+                source_images,source_images_names = get_random_image_from_folder(source_folder)
+                logger.status(f"Processing with Random Image from the folder: {source_images_names[0]}")
+            else:
+                source_images,source_images_names = 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 = []
@@ -405,16 +440,16 @@ def swap_face(
                         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}...")
+                            logger.status(f"Analyzing Source Image {i}: {source_images_names[i]}...")
-                            source_faces = analyze_faces(source_image)
+                            source_faces = analyze_faces(source_image, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
                             SOURCE_FACES_LIST = [source_faces]
                         elif len(SOURCE_FACES_LIST) == i and not source_image_same:
-                            logger.status(f"Analyzing Source Image {i}...")
+                            logger.status(f"Analyzing Source Image {i}: {source_images_names[i]}...")
-                            source_faces = analyze_faces(source_image)
+                            source_faces = analyze_faces(source_image, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
                             SOURCE_FACES_LIST.append(source_faces)
                         elif len(SOURCE_FACES_LIST) != i and not source_image_same:
-                            logger.status(f"Analyzing Source Image {i}...")
+                            logger.status(f"Analyzing Source Image {i}: {source_images_names[i]}...")
-                            source_faces = analyze_faces(source_image)
+                            source_faces = analyze_faces(source_image, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
                             SOURCE_FACES_LIST[i] = source_faces
                         elif source_image_same:
                             logger.status("(Image %s) Using Hashed Source Face(s) Model...", i)
@@ -422,7 +457,7 @@ def swap_face(
 
                     else:
                         logger.status(f"Analyzing Source Image {i}...")
-                        source_faces = analyze_faces(source_image)
+                        source_faces = analyze_faces(source_image, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
 
                     if source_faces is not None:
                         source_faces_ff.append(source_faces)
@@ -446,7 +481,7 @@ def swap_face(
                     
                     if TARGET_FACES is None or not target_image_same:
                         logger.status("Analyzing Target Image...")
-                        target_faces = analyze_faces(target_img)
+                        target_faces = analyze_faces(target_img, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
                         TARGET_FACES = target_faces
                     elif target_image_same:
                         logger.status("Using Hashed Target Face(s) Model...")
@@ -454,12 +489,12 @@ def swap_face(
                 
                 else:
                     logger.status("Analyzing Target Image...")
-                    target_faces = analyze_faces(target_img)
+                    target_faces = analyze_faces(target_img, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
 
                 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)
+                    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, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
                     
                     if source_age != "None" or source_gender != "None":
                         logger.status("(Image %s) Detected: -%s- y.o. %s", i, source_age, source_gender)
@@ -469,7 +504,7 @@ def swap_face(
                     
                     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_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,detection_options)
 
                         result.append(result_image)
 
@@ -506,7 +541,7 @@ def swap_face(
 
                     if SOURCE_FACES is None or not source_image_same:
                         logger.status("Analyzing Source Image...")
-                        source_faces = analyze_faces(source_img)
+                        source_faces = analyze_faces(source_img, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
                         SOURCE_FACES = source_faces
                     elif source_image_same:
                         logger.status("Using Hashed Source Face(s) Model...")
@@ -514,16 +549,16 @@ def swap_face(
 
                 else:
                     logger.status("Analyzing Source Image...")
-                    source_faces = analyze_faces(source_img)
+                    source_faces = analyze_faces(source_img, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
             
             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...")
+                    logger.status(f"Using Loaded Source Face Model: {face_model}")
                 else:
-                    logger.error(f"Cannot load Face Model File: {face_model}.safetensors")
+                    logger.error(f"Cannot load Face Model File: {face_model}")
             
             else:
                 logger.error("Cannot detect any Source")
@@ -548,7 +583,7 @@ def swap_face(
                     
                     if TARGET_FACES is None or not target_image_same:
                         logger.status("Analyzing Target Image...")
-                        target_faces = analyze_faces(target_img)
+                        target_faces = analyze_faces(target_img, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
                         TARGET_FACES = target_faces
                     elif target_image_same:
                         logger.status("Using Hashed Target Face(s) Model...")
@@ -556,11 +591,11 @@ def swap_face(
                 
                 else:
                     logger.status("Analyzing Target Image...")
-                    target_faces = analyze_faces(target_img)
+                    target_faces = analyze_faces(target_img, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
 
                 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)
+                    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, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
                 else:
                     source_face = sorted(source_faces, key=lambda x: x.bbox[0])[source_faces_index[0]]
                     wrong_gender = 0
@@ -578,7 +613,7 @@ def swap_face(
                 
                 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)
+                    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,detection_options)
                 
                 else:
                     logger.status("No source face(s) in the provided Index")
@@ -592,7 +627,7 @@ def swap_face(
     
     return result_image, [], 0
 
-def build_face_model(image: Image.Image, name: str):
+def build_face_model(image: Image.Image, name: str, save_model: bool = True, det_size=(640, 640)):
     if image is None:
         error_msg = "Please load an Image"
         logger.error(error_msg)
@@ -603,20 +638,91 @@ def build_face_model(image: Image.Image, name: str):
         return error_msg
     apply_logging_patch(1)
     image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    if save_model:
         logger.status("Building Face Model...")
-    face_model = analyze_faces(image)
+    face_model = analyze_faces(image, det_size)
+
+    if len(face_model) == 0:
+        det_size_half = half_det_size(det_size)
+        face_model = analyze_faces(image, det_size_half)
+    
     if face_model is not None and len(face_model) > 0:
+        if save_model:
             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:
+            return face_model[0]
     else:
         no_face_msg = "No face found, please try another image"
         logger.error(no_face_msg)
         return no_face_msg
 
+def blend_faces(images_list: List, name: str, compute_method: int = 0, shape_check: bool = False, is_api: bool = False):
+    faces = []
+    embeddings = []
+    images: List[Image.Image] = []
+    if not is_api:
+        images, images_names = get_images_from_list(images_list)
+    else: 
+        images = images_list
+    for i,image in enumerate(images):
+        if not is_api:
+            logger.status(f"Building Face Model for {images_names[i]}...")
+        else:
+            logger.status(f"Building Face Model for Image {i+1}...")
+        face = build_face_model(image,str(i),save_model=False)
+        if isinstance(face, str):
+            # logger.error(f"No faces found in {images_names[i]}, skipping")
+            continue
+        if shape_check:
+            if i == 0:
+                embedding_shape = face.embedding.shape
+            elif face.embedding.shape != embedding_shape:
+                if not is_api:
+                    logger.error(f"Embedding Shape Mismatch for {images_names[i]}, skipping")
+                else:
+                    logger.error(f"Embedding Shape Mismatch for Image {i+1}, skipping")
+                continue
+        faces.append(face)
+        embeddings.append(face.embedding)
+    if len(faces) > 0:
+        # if shape_check:
+        #     embedding_shape = embeddings[0].shape
+        #     for embedding in embeddings:
+        #         if embedding.shape != embedding_shape:
+        #             logger.error("Embedding Shape Mismatch")
+        #             break
+        compute_method_name = "Mean" if compute_method == 0 else "Median" if compute_method == 1 else "Mode"
+        logger.status(f"Blending with Compute Method {compute_method_name}...")
+        blended_embedding = np.mean(embeddings, axis=0) if compute_method == 0 else np.median(embeddings, axis=0) if compute_method == 1 else stats.mode(embeddings, axis=0)[0].astype(np.float32)
+        blended_face = Face(
+            bbox=faces[0].bbox,
+            kps=faces[0].kps,
+            det_score=faces[0].det_score,
+            landmark_3d_68=faces[0].landmark_3d_68,
+            pose=faces[0].pose,
+            landmark_2d_106=faces[0].landmark_2d_106,
+            embedding=blended_embedding,
+            gender=faces[0].gender,
+            age=faces[0].age
+        )
+        if blended_face is not None:
+            face_model_path = os.path.join(FACE_MODELS_PATH, name + ".safetensors")
+            save_face_model(blended_face,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 = "Something went wrong, please try another set of images"
+            logger.error(no_face_msg)
+            return no_face_msg
+    return "No faces found"
+
 
 def operate(
         source_img,
@@ -638,6 +744,7 @@ def operate(
         mask_face,
         entire_mask_image,
         enhancement_options,
+        detection_options,
     ):
     result = target_img
     face_swapper = getFaceSwapModel(model)
@@ -649,7 +756,7 @@ def operate(
             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)
+            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, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
             if source_age != "None" or source_gender != "None":
                 logger.status("Detected: -%s- y.o. %s", source_age, source_gender)
 
@@ -660,7 +767,7 @@ def operate(
 
         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)
+            target_face, wrong_gender, target_age, target_gender = get_face_single(target_img, target_faces, face_index=face_num, gender_target=gender_target, det_thresh=detection_options.det_thresh, det_maxnum=detection_options.det_maxnum)
             if target_age != "None" or target_gender != "None":
                 logger.status("Detected: -%s- y.o. %s", target_age, target_gender)
 
@@ -707,7 +814,7 @@ def operate(
 
     result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
     
-    if enhancement_options is not None and swapped > 0:
+    if (enhancement_options is not None and swapped > 0) or enhancement_options.upscale_force:
         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:    

scripts/reactor_version.py

@@ -1,5 +1,5 @@
 app_title = "ReActor"
-version_flag = "v0.6.0"
+version_flag = "v0.7.1-b2"
 
 from scripts.reactor_logger import logger, get_Run, set_Run
 from scripts.reactor_globals import DEVICE

scripts/reactor_xyz.py

@@ -0,0 +1,94 @@
+'''
+Thanks @ledahu for contributing
+'''
+
+from modules import scripts
+from modules.shared import opts
+
+from scripts.reactor_helpers import (
+    get_model_names, 
+    get_facemodels
+)
+
+
+# xyz_grid = [x for x in scripts.scripts_data if x.script_class.__module__ == "xyz_grid.py"][0].module
+
+def find_module(module_names):
+    if isinstance(module_names, str):
+        module_names = [s.strip() for s in module_names.split(",")]
+    for data in scripts.scripts_data:
+        if data.script_class.__module__ in module_names and hasattr(data, "module"):
+            return data.module
+    return None
+
+def bool_(string):
+    string = str(string)
+    if string in ["None", ""]:
+        return None
+    elif string.lower() in ["true", "1"]:
+        return True
+    elif string.lower() in ["false", "0"]:
+        return False
+    else:
+        raise ValueError(f"Could not convert string to boolean: {string}")
+
+def choices_bool():
+    return ["False", "True"]
+
+def choices_face_models():
+    return get_model_names(get_facemodels)
+
+def float_applier(value_name:str, min_range:float = 0, max_range:float = 1):
+    """
+    Returns a function that applies the given value to the given value_name in opts.data.
+    """
+    def validate(value_name:str, value:str):
+        value = float(value)
+        # validate value
+        if not min_range == 0:
+            assert value >= min_range, f"Value {value} for {value_name} must be greater than or equal to {min_range}"
+        if not max_range == 1:
+            assert value <= max_range, f"Value {value} for {value_name} must be less than or equal to {max_range}"
+    def apply_float(p, x, xs):
+        validate(value_name, x)
+        opts.data[value_name] = float(x)
+    return apply_float
+
+def bool_applier(value_name:str):
+    def apply_bool(p, x, xs):
+        x_normed = bool_(x)
+        opts.data[value_name] = x_normed
+        # print(f'normed = {x_normed}')
+    return apply_bool
+
+def str_applier(value_name:str):
+    def apply_str(p, x, xs):
+        opts.data[value_name] = x
+    return apply_str
+
+
+def add_axis_options(xyz_grid):
+    extra_axis_options = [
+        xyz_grid.AxisOption("[ReActor] CodeFormer Weight", float, float_applier("codeformer_weight", 0, 1)),
+        xyz_grid.AxisOption("[ReActor] Restorer Visibility", float, float_applier("restorer_visibility", 0, 1)),
+        xyz_grid.AxisOption("[ReActor] Face Mask Correction", str, bool_applier("mask_face"), choices=choices_bool),
+        xyz_grid.AxisOption("[ReActor] Face Models", str, str_applier("face_model"), choices=choices_face_models),
+    ]
+    set_a = {opt.label for opt in xyz_grid.axis_options}
+    set_b = {opt.label for opt in extra_axis_options}
+    if set_a.intersection(set_b):
+        return
+
+    xyz_grid.axis_options.extend(extra_axis_options)
+
+def run():
+    xyz_grid = find_module("xyz_grid.py, xy_grid.py")
+    if xyz_grid:
+        add_axis_options(xyz_grid)
+
+# XYZ init:
+try:
+    import modules.script_callbacks as script_callbacks
+    script_callbacks.on_before_ui(run)
+except:
+    pass