Creating a fallback and switching of models

Models switch depending on the execution provider
Update requirements.txt
2025-08-02 02:56:20 +08:00 · 2025-07-09 17:19:26 +08:00 · 2025-07-02 18:37:10 +08:00 · 2025-07-02 18:29:32 +08:00 · 2025-07-02 04:08:26 +08:00 · 2025-06-29 15:03:35 +08:00
26 changed files with 1103 additions and 1186 deletions
@@ -1 +0,0 @@
-3.10.0
@@ -30,18 +30,13 @@ By using this software, you agree to these terms and commit to using it in a man

 Users are expected to use this software responsibly and legally. If using a real person's face, obtain their consent and clearly label any output as a deepfake when sharing online. We are not responsible for end-user actions.

+## Exclusive v2.1 Quick Start - Pre-built (Windows/Mac Silicon)

-## Quick Start - Pre-built (Windows / Nvidia)
+  <a href="https://deeplivecam.net/index.php/quickstart"> <img src="media/Download.png" width="285" height="77" />

-  <a href="https://hacksider.gumroad.com/l/vccdmm"> <img src="https://github.com/user-attachments/assets/7d993b32-e3e8-4cd3-bbfb-a549152ebdd5" width="285" height="77" />
-
-##### This is the fastest build you can get if you have a discrete NVIDIA GPU.
-
-## Quick Start - Pre-built (Mac / Silicon)
-    
-  <a href="https://krshh.gumroad.com/l/Deep-Live-Cam-Mac"> <img src="https://github.com/user-attachments/assets/d5d913b5-a7de-4609-96b9-979a5749a703" width="285" height="77" />
+##### This is the fastest build you can get if you have a discrete NVIDIA or AMD GPU or Mac Silicon, And you'll receive special priority support.
 
-###### These Pre-builts are perfect for non-technical users or those who don’t have time to, or can't manually install all the requirements. Just a heads-up: this is an open-source project, so you can also install it manually.
+###### These Pre-builts are perfect for non-technical users or those who don't have time to, or can't manually install all the requirements. Just a heads-up: this is an open-source project, so you can also install it manually. 

 ## TLDR; Live Deepfake in just 3 Clicks
 ![easysteps](https://github.com/user-attachments/assets/af825228-852c-411b-b787-ffd9aac72fc6)
@@ -49,7 +44,7 @@ Users are expected to use this software responsibly and legally. If using a real
 2. Select which camera to use
 3. Press live!

-## Features & Uses - Everything is real-time
+## Features & Uses - Everything is in real-time

 ### Mouth Mask

@@ -85,7 +80,7 @@ Users are expected to use this software responsibly and legally. If using a real

 ### Memes

-**Create Your most viral meme yet**
+**Create Your Most Viral Meme Yet**

 <p align="center">
  <img src="media/meme.gif" alt="show" width="450"> 
@@ -93,10 +88,17 @@ Users are expected to use this software responsibly and legally. If using a real
  <sub>Created using Many Faces feature in Deep-Live-Cam</sub>
 </p>

+### Omegle
+
+**Surprise people on Omegle**
+
+<p align="center">
+  <video src="https://github.com/user-attachments/assets/2e9b9b82-fa04-4b70-9f56-b1f68e7672d0" width="450" controls></video>
+</p>

 ## Installation (Manual)

-**Please be aware that the installation requires technical skills and is not for beginners. Consider downloading the prebuilt version.**
+**Please be aware that the installation requires technical skills and is not for beginners. Consider downloading the quickstart version.**

 <details>
 <summary>Click to see the process</summary>
@@ -107,7 +109,7 @@ This is more likely to work on your computer but will be slower as it utilizes t

 **1. Set up Your Platform**

-   Python (3.10 recommended)
+-   Python (3.11 recommended)
 -   pip
 -   git
 -   [ffmpeg](https://www.youtube.com/watch?v=OlNWCpFdVMA) - ```iex (irm ffmpeg.tc.ht)```
@@ -116,7 +118,8 @@ This is more likely to work on your computer but will be slower as it utilizes t
 **2. Clone the Repository**

 ```bash
-https://github.com/hacksider/Deep-Live-Cam.git
+git clone https://github.com/hacksider/Deep-Live-Cam.git
+cd Deep-Live-Cam
 ```

 **3. Download the Models**
@@ -130,14 +133,52 @@ Place these files in the "**models**" folder.

 We highly recommend using a `venv` to avoid issues.

+
+For Windows:
 ```bash
+python -m venv venv
+venv\Scripts\activate
+pip install -r requirements.txt
+```
+For Linux:
+```bash
+# Ensure you use the installed Python 3.10
+python3 -m venv venv
+source venv/bin/activate
 pip install -r requirements.txt
 ```

-**For macOS:** Install or upgrade the `python-tk` package:
+**For macOS:**
+
+Apple Silicon (M1/M2/M3) requires specific setup:

 ```bash
+# Install Python 3.11 (specific version is important)
+brew install python@3.11
+
+# Install tkinter package (required for the GUI)
 brew install python-tk@3.10
+
+# Create and activate virtual environment with Python 3.11
+python3.11 -m venv venv
+source venv/bin/activate
+
+# Install dependencies
+pip install -r requirements.txt
+```
+
+** In case something goes wrong and you need to reinstall the virtual environment **
+
+```bash
+# Deactivate the virtual environment
+rm -rf venv
+
+# Reinstall the virtual environment
+python -m venv venv
+source venv/bin/activate
+
+# install the dependencies again
+pip install -r requirements.txt
 ```

 **Run:** If you don't have a GPU, you can run Deep-Live-Cam using `python run.py`. Note that initial execution will download models (~300MB).
@@ -146,12 +187,16 @@ brew install python-tk@3.10

 **CUDA Execution Provider (Nvidia)**

-1. Install [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive) or [CUDA Toolkit 12.1.1](https://developer.nvidia.com/cuda-12-1-1-download-archive)
-2. Install dependencies:
+1. Install [CUDA Toolkit 12.8.0](https://developer.nvidia.com/cuda-12-8-0-download-archive)
+2. Install [cuDNN v8.9.7 for CUDA 12.x](https://developer.nvidia.com/rdp/cudnn-archive) (required for onnxruntime-gpu):
+   - Download cuDNN v8.9.7 for CUDA 12.x
+   - Make sure the cuDNN bin directory is in your system PATH
+3. Install dependencies:

 ```bash
+pip install -U torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128
 pip uninstall onnxruntime onnxruntime-gpu
-pip install onnxruntime-gpu==1.16.3
+pip install onnxruntime-gpu==1.21.0
 ```

 3. Usage:
@@ -162,26 +207,46 @@ python run.py --execution-provider cuda

 **CoreML Execution Provider (Apple Silicon)**

-1. Install dependencies:
+Apple Silicon (M1/M2/M3) specific installation:
+
+1. Make sure you've completed the macOS setup above using Python 3.10.
+2. Install dependencies:

 ```bash
 pip uninstall onnxruntime onnxruntime-silicon
 pip install onnxruntime-silicon==1.13.1
 ```

-2. Usage:
+3. Usage (important: specify Python 3.10):

 ```bash
-python run.py --execution-provider coreml
+python3.10 run.py --execution-provider coreml
 ```

+**Important Notes for macOS:**
+- You **must** use Python 3.10, not newer versions like 3.11 or 3.13
+- Always run with `python3.10` command not just `python` if you have multiple Python versions installed
+- If you get error about `_tkinter` missing, reinstall the tkinter package: `brew reinstall python-tk@3.10`
+- If you get model loading errors, check that your models are in the correct folder
+- If you encounter conflicts with other Python versions, consider uninstalling them:
+  ```bash
+  # List all installed Python versions
+  brew list | grep python
+  
+  # Uninstall conflicting versions if needed
+  brew uninstall --ignore-dependencies python@3.11 python@3.13
+  
+  # Keep only Python 3.11
+  brew cleanup
+  ```
+
 **CoreML Execution Provider (Apple Legacy)**

 1. Install dependencies:

 ```bash
 pip uninstall onnxruntime onnxruntime-coreml
-pip install onnxruntime-coreml==1.13.1
+pip install onnxruntime-coreml==1.21.0
 ```

 2. Usage:
@@ -196,7 +261,7 @@ python run.py --execution-provider coreml

 ```bash
 pip uninstall onnxruntime onnxruntime-directml
-pip install onnxruntime-directml==1.15.1
+pip install onnxruntime-directml==1.21.0
 ```

 2. Usage:
@@ -211,7 +276,7 @@ python run.py --execution-provider directml

 ```bash
 pip uninstall onnxruntime onnxruntime-openvino
-pip install onnxruntime-openvino==1.15.0
+pip install onnxruntime-openvino==1.21.0
 ```

 2. Usage:
@@ -219,7 +284,6 @@ pip install onnxruntime-openvino==1.15.0
 ```bash
 python run.py --execution-provider openvino
 ```
-
 </details>

 ## Usage
@@ -283,6 +347,8 @@ Looking for a CLI mode? Using the -s/--source argument will make the run program
 - [*"This real-time webcam deepfake tool raises alarms about the future of identity theft"*](https://www.diyphotography.net/this-real-time-webcam-deepfake-tool-raises-alarms-about-the-future-of-identity-theft/) - DIYPhotography
 - [*"That's Crazy, Oh God. That's Fucking Freaky Dude... That's So Wild Dude"*](https://www.youtube.com/watch?time_continue=1074&v=py4Tc-Y8BcY) - SomeOrdinaryGamers
 - [*"Alright look look look, now look chat, we can do any face we want to look like chat"*](https://www.youtube.com/live/mFsCe7AIxq8?feature=shared&t=2686) - IShowSpeed
+ - [*"They do a pretty good job matching poses, expression and even the lighting"*](https://www.youtube.com/watch?v=wnCghLjqv3s&t=551s) - TechLinked (LTT)
+

 ## Credits

@@ -313,5 +379,3 @@ Looking for a CLI mode? Using the -s/--source argument will make the run program
   <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=hacksider/deep-live-cam&type=Date" />
 </picture>
 </a>
-
-
@@ -0,0 +1,46 @@
+{
+    "Source x Target Mapper": "Quelle x Ziel Zuordnung",
+    "select a source image": "Wähle ein Quellbild",
+    "Preview": "Vorschau",
+    "select a target image or video": "Wähle ein Zielbild oder Video",
+    "save image output file": "Bildausgabedatei speichern",
+    "save video output file": "Videoausgabedatei speichern",
+    "select a target image": "Wähle ein Zielbild",
+    "source": "Quelle",
+    "Select a target": "Wähle ein Ziel",
+    "Select a face": "Wähle ein Gesicht",
+    "Keep audio": "Audio beibehalten",
+    "Face Enhancer": "Gesichtsverbesserung",
+    "Many faces": "Mehrere Gesichter",
+    "Show FPS": "FPS anzeigen",
+    "Keep fps": "FPS beibehalten",
+    "Keep frames": "Frames beibehalten",
+    "Fix Blueish Cam": "Bläuliche Kamera korrigieren",
+    "Mouth Mask": "Mundmaske",
+    "Show Mouth Mask Box": "Mundmaskenrahmen anzeigen",
+    "Start": "Starten",
+    "Live": "Live",
+    "Destroy": "Beenden",
+    "Map faces": "Gesichter zuordnen",
+    "Processing...": "Verarbeitung läuft...",
+    "Processing succeed!": "Verarbeitung erfolgreich!",
+    "Processing ignored!": "Verarbeitung ignoriert!",
+    "Failed to start camera": "Kamera konnte nicht gestartet werden",
+    "Please complete pop-up or close it.": "Bitte das Pop-up komplettieren oder schließen.",
+    "Getting unique faces": "Einzigartige Gesichter erfassen",
+    "Please select a source image first": "Bitte zuerst ein Quellbild auswählen",
+    "No faces found in target": "Keine Gesichter im Zielbild gefunden",
+    "Add": "Hinzufügen",
+    "Clear": "Löschen",
+    "Submit": "Absenden",
+    "Select source image": "Quellbild auswählen",
+    "Select target image": "Zielbild auswählen",
+    "Please provide mapping!": "Bitte eine Zuordnung angeben!",
+    "At least 1 source with target is required!": "Mindestens eine Quelle mit einem Ziel ist erforderlich!",
+    "At least 1 source with target is required!": "Mindestens eine Quelle mit einem Ziel ist erforderlich!",
+    "Face could not be detected in last upload!": "Im letzten Upload konnte kein Gesicht erkannt werden!",
+    "Select Camera:": "Kamera auswählen:",
+    "All mappings cleared!": "Alle Zuordnungen gelöscht!",
+    "Mappings successfully submitted!": "Zuordnungen erfolgreich übermittelt!",
+    "Source x Target Mapper is already open.": "Quell-zu-Ziel-Zuordnung ist bereits geöffnet."
+}
@@ -0,0 +1,46 @@
+{
+    "Source x Target Mapper": "Mapeador de fuente x destino",
+    "select a source image": "Seleccionar imagen fuente",
+    "Preview": "Vista previa",
+    "select a target image or video": "elegir un video o una imagen fuente",
+    "save image output file": "guardar imagen final",
+    "save video output file": "guardar video final",
+    "select a target image": "elegir una imagen objetiva",
+    "source": "fuente",
+    "Select a target": "Elegir un destino",
+    "Select a face": "Elegir una cara",
+    "Keep audio": "Mantener audio original",
+    "Face Enhancer": "Potenciador de caras",
+    "Many faces": "Varias caras",
+    "Show FPS": "Mostrar fps",
+    "Keep fps": "Mantener fps",
+    "Keep frames": "Mantener frames",
+    "Fix Blueish Cam": "Corregir tono azul de video",
+    "Mouth Mask": "Máscara de boca",
+    "Show Mouth Mask Box": "Mostrar área de la máscara de boca",
+    "Start": "Iniciar",
+    "Live": "En vivo",
+    "Destroy": "Borrar",
+    "Map faces": "Mapear caras",
+    "Processing...": "Procesando...",
+    "Processing succeed!": "¡Proceso terminado con éxito!",
+    "Processing ignored!": "¡Procesamiento omitido!",
+    "Failed to start camera": "No se pudo iniciar la cámara",
+    "Please complete pop-up or close it.": "Complete o cierre el pop-up",
+    "Getting unique faces": "Buscando caras únicas",
+    "Please select a source image first": "Primero, seleccione una imagen fuente",
+    "No faces found in target": "No se encontró una cara en el destino",
+    "Add": "Agregar",
+    "Clear": "Limpiar",
+    "Submit": "Enviar",
+    "Select source image": "Seleccionar imagen fuente",
+    "Select target image": "Seleccionar imagen destino",
+    "Please provide mapping!": "Por favor, proporcione un mapeo",
+    "At least 1 source with target is required!": "Se requiere al menos una fuente con un destino.",
+    "At least 1 source with target is required!": "Se requiere al menos una fuente con un destino.",
+    "Face could not be detected in last upload!": "¡No se pudo encontrar una cara en el último video o imagen!",
+    "Select Camera:": "Elegir cámara:",
+    "All mappings cleared!": "¡Todos los mapeos fueron borrados!",
+    "Mappings successfully submitted!": "Mapeos enviados con éxito!",
+    "Source x Target Mapper is already open.": "El mapeador de fuente x destino ya está abierto."
+}
@@ -0,0 +1,46 @@
+{
+    "Source x Target Mapper": "Source x Target Kartoitin",
+    "select an source image": "Valitse lähde kuva",
+    "Preview": "Esikatsele",
+    "select an target image or video": "Valitse kohde kuva tai video",
+    "save image output file": "tallenna kuva",
+    "save video output file": "tallenna video",
+    "select an target image": "Valitse kohde kuva",
+    "source": "lähde",
+    "Select a target": "Valitse kohde",
+    "Select a face": "Valitse kasvot",
+    "Keep audio": "Säilytä ääni",
+    "Face Enhancer": "Kasvojen Parantaja",
+    "Many faces": "Useampia kasvoja",
+    "Show FPS": "Näytä FPS",
+    "Keep fps": "Säilytä FPS",
+    "Keep frames": "Säilytä ruudut",
+    "Fix Blueish Cam": "Korjaa Sinertävä Kamera",
+    "Mouth Mask": "Suu Maski",
+    "Show Mouth Mask Box": "Näytä Suu Maski Laatiko",
+    "Start": "Aloita",
+    "Live": "Live",
+    "Destroy": "Tuhoa",
+    "Map faces": "Kartoita kasvot",
+    "Processing...": "Prosessoi...",
+    "Processing succeed!": "Prosessointi onnistui!",
+    "Processing ignored!": "Prosessointi lopetettu!",
+    "Failed to start camera": "Kameran käynnistäminen epäonnistui",
+    "Please complete pop-up or close it.": "Viimeistele tai sulje ponnahdusikkuna",
+    "Getting unique faces": "Hankitaan uniikkeja kasvoja",
+    "Please select a source image first": "Valitse ensin lähde kuva",
+    "No faces found in target": "Kasvoja ei löydetty kohteessa",
+    "Add": "Lisää",
+    "Clear": "Tyhjennä",
+    "Submit": "Lähetä",
+    "Select source image": "Valitse lähde kuva",
+    "Select target image": "Valitse kohde kuva",
+    "Please provide mapping!": "Tarjoa kartoitus!",
+    "Atleast 1 source with target is required!": "Vähintään 1 lähde kohteen kanssa on vaadittu!",
+    "At least 1 source with target is required!": "Vähintään 1 lähde kohteen kanssa on vaadittu!",
+    "Face could not be detected in last upload!": "Kasvoja ei voitu tunnistaa edellisessä latauksessa!",
+    "Select Camera:": "Valitse Kamera:",
+    "All mappings cleared!": "Kaikki kartoitukset tyhjennetty!",
+    "Mappings successfully submitted!": "Kartoitukset lähetety onnistuneesti!",
+    "Source x Target Mapper is already open.": "Lähde x Kohde Kartoittaja on jo auki."
+}
@@ -0,0 +1,45 @@
+{
+    "Source x Target Mapper": "ប្រភប x បន្ថែម Mapper",
+    "select a source image": "ជ្រើសរើសប្រភពរូបភាព",
+    "Preview": "បង្ហាញ",
+    "select a target image or video": "ជ្រើសរើសគោលដៅរូបភាពឬវីដេអូ",
+    "save image output file": "រក្សាទុកលទ្ធផលឯកសាររូបភាព",
+    "save video output file": "រក្សាទុកលទ្ធផលឯកសារវីដេអូ",
+    "select a target image": "ជ្រើសរើសគោលដៅរូបភាព",
+    "source": "ប្រភព",
+    "Select a target": "ជ្រើសរើសគោលដៅ",
+    "Select a face": "ជ្រើសរើសមុខ",
+    "Keep audio": "រម្លងសម្លេង",
+    "Face Enhancer": "ឧបករណ៍ពង្រឹងមុខ",
+    "Many faces": "ទម្រង់មុខច្រើន",
+    "Show FPS": "បង្ហាញ FPS",
+    "Keep fps": "រម្លង fps",
+    "Keep frames": "រម្លងទម្រង់",
+    "Fix Blueish Cam": "ជួសជុល Cam Blueish",
+    "Mouth Mask": "របាំងមាត់",
+    "Show Mouth Mask Box": "បង្ហាញប្រអប់របាំងមាត់",
+    "Start": "ចាប់ផ្ដើម",
+    "Live": "ផ្សាយផ្ទាល់",
+    "Destroy": "លុប",
+    "Map faces": "ផែនទីមុខ",
+    "Processing...": "កំពុងដំណើរការ...",
+    "Processing succeed!": "ការដំណើរការទទួលបានជោគជ័យ!",
+    "Processing ignored!": "ការដំណើរការមិនទទួលបានជោគជ័យ!",
+    "Failed to start camera": "បរាជ័យដើម្បីចាប់ផ្ដើមបើកកាមេរ៉ា",
+    "Please complete pop-up or close it.": "សូមបញ្ចប់ផ្ទាំងផុស ឬបិទវា.",
+    "Getting unique faces": "ការចាប់ផ្ដើមទម្រង់មុខប្លែក",
+    "Please select a source image first": "សូមជ្រើសរើសប្រភពរូបភាពដំបូង",
+    "No faces found in target": "រកអត់ឃើញមុខនៅក្នុងគោលដៅ",
+    "Add": "បន្ថែម",
+    "Clear": "សម្អាត",
+    "Submit": "បញ្ចូន",
+    "Select source image": "ជ្រើសរើសប្រភពរូបភាព",
+    "Select target image": "ជ្រើសរើសគោលដៅរូបភាព",
+    "Please provide mapping!": "សូមផ្ដល់នៅផែនទី",
+    "At least 1 source with target is required!": "ត្រូវការប្រភពយ៉ាងហោចណាស់ ១ ដែលមានគោលដៅ!",
+    "Face could not be detected in last upload!": "មុខមិនអាចភ្ជាប់នៅក្នុងការបង្ហេាះចុងក្រោយ!",
+    "Select Camera:": "ជ្រើសរើសកាមេរ៉ា",
+    "All mappings cleared!": "ផែនទីទាំងអស់ត្រូវបានសម្អាត!",
+    "Mappings successfully submitted!": "ផែនទីត្រូវបានបញ្ជូនជោគជ័យ!",
+    "Source x Target Mapper is already open.": "ប្រភព x Target Mapper បានបើករួចហើយ។"
+}
@@ -0,0 +1,45 @@
+{
+    "Source x Target Mapper": "소스 x 타겟 매퍼",
+    "select a source image": "소스 이미지 선택",
+    "Preview": "미리보기",
+    "select a target image or video": "타겟 이미지 또는 영상 선택",
+    "save image output file": "이미지 출력 파일 저장",
+    "save video output file": "영상 출력 파일 저장",
+    "select a target image": "타겟 이미지 선택",
+    "source": "소스",
+    "Select a target": "타겟 선택",
+    "Select a face": "얼굴 선택",
+    "Keep audio": "오디오 유지",
+    "Face Enhancer": "얼굴 향상",
+    "Many faces": "여러 얼굴",
+    "Show FPS": "FPS 표시",
+    "Keep fps": "FPS 유지",
+    "Keep frames": "프레임 유지",
+    "Fix Blueish Cam": "푸른빛 카메라 보정",
+    "Mouth Mask": "입 마스크",
+    "Show Mouth Mask Box": "입 마스크 박스 표시",
+    "Start": "시작",
+    "Live": "라이브",
+    "Destroy": "종료",
+    "Map faces": "얼굴 매핑",
+    "Processing...": "처리 중...",
+    "Processing succeed!": "처리 성공!",
+    "Processing ignored!": "처리 무시됨!",
+    "Failed to start camera": "카메라 시작 실패",
+    "Please complete pop-up or close it.": "팝업을 완료하거나 닫아주세요.",
+    "Getting unique faces": "고유 얼굴 가져오는 중",
+    "Please select a source image first": "먼저 소스 이미지를 선택해주세요",
+    "No faces found in target": "타겟에서 얼굴을 찾을 수 없음",
+    "Add": "추가",
+    "Clear": "지우기",
+    "Submit": "제출",
+    "Select source image": "소스 이미지 선택",
+    "Select target image": "타겟 이미지 선택",
+    "Please provide mapping!": "매핑을 입력해주세요!",
+    "At least 1 source with target is required!": "최소 하나의 소스와 타겟이 필요합니다!",
+    "Face could not be detected in last upload!": "최근 업로드에서 얼굴을 감지할 수 없습니다!",
+    "Select Camera:": "카메라 선택:",
+    "All mappings cleared!": "모든 매핑이 삭제되었습니다!",
+    "Mappings successfully submitted!": "매핑이 성공적으로 제출되었습니다!",
+    "Source x Target Mapper is already open.": "소스 x 타겟 매퍼가 이미 열려 있습니다."
+}
@@ -0,0 +1,46 @@
+{
+    "Source x Target Mapper": "Mapeador de Origem x Destino",
+    "select an source image": "Escolha uma imagem de origem",
+    "Preview": "Prévia",
+    "select an target image or video": "Escolha uma imagem ou vídeo de destino",
+    "save image output file": "Salvar imagem final",
+    "save video output file": "Salvar vídeo final",
+    "select an target image": "Escolha uma imagem de destino",
+    "source": "Origem",
+    "Select a target": "Escolha o destino",
+    "Select a face": "Escolha um rosto",
+    "Keep audio": "Manter o áudio original",
+    "Face Enhancer": "Melhorar rosto",
+    "Many faces": "Vários rostos",
+    "Show FPS": "Mostrar FPS",
+    "Keep fps": "Manter FPS",
+    "Keep frames": "Manter frames",
+    "Fix Blueish Cam": "Corrigir tom azulado da câmera",
+    "Mouth Mask": "Máscara da boca",
+    "Show Mouth Mask Box": "Mostrar área da máscara da boca",
+    "Start": "Começar",
+    "Live": "Ao vivo",
+    "Destroy": "Destruir",
+    "Map faces": "Mapear rostos",
+    "Processing...": "Processando...",
+    "Processing succeed!": "Tudo certo!",
+    "Processing ignored!": "Processamento ignorado!",
+    "Failed to start camera": "Não foi possível iniciar a câmera",
+    "Please complete pop-up or close it.": "Finalize ou feche o pop-up",
+    "Getting unique faces": "Buscando rostos diferentes",
+    "Please select a source image first": "Selecione primeiro uma imagem de origem",
+    "No faces found in target": "Nenhum rosto encontrado na imagem de destino",
+    "Add": "Adicionar",
+    "Clear": "Limpar",
+    "Submit": "Enviar",
+    "Select source image": "Escolha a imagem de origem",
+    "Select target image": "Escolha a imagem de destino",
+    "Please provide mapping!": "Você precisa realizar o mapeamento!",
+    "Atleast 1 source with target is required!": "É necessária pelo menos uma origem com um destino!",
+    "At least 1 source with target is required!": "É necessária pelo menos uma origem com um destino!",
+    "Face could not be detected in last upload!": "Não conseguimos detectar o rosto na última imagem!",
+    "Select Camera:": "Escolher câmera:",
+    "All mappings cleared!": "Todos os mapeamentos foram removidos!",
+    "Mappings successfully submitted!": "Mapeamentos enviados com sucesso!",
+    "Source x Target Mapper is already open.": "O Mapeador de Origem x Destino já está aberto."
+}
@@ -0,0 +1,45 @@
+{
+    "Source x Target Mapper": "Сопоставитель Источник x Цель",
+    "select a source image": "выберите исходное изображение",
+    "Preview": "Предпросмотр",
+    "select a target image or video": "выберите целевое изображение или видео",
+    "save image output file": "сохранить выходной файл изображения",
+    "save video output file": "сохранить выходной файл видео",
+    "select a target image": "выберите целевое изображение",
+    "source": "источник",
+    "Select a target": "Выберите целевое изображение",
+    "Select a face": "Выберите лицо",
+    "Keep audio": "Сохранить аудио",
+    "Face Enhancer": "Улучшение лица",
+    "Many faces": "Несколько лиц",
+    "Show FPS": "Показать FPS",
+    "Keep fps": "Сохранить FPS",
+    "Keep frames": "Сохранить кадры",
+    "Fix Blueish Cam": "Исправить синеву камеры",
+    "Mouth Mask": "Маска рта",
+    "Show Mouth Mask Box": "Показать рамку маски рта",
+    "Start": "Старт",
+    "Live": "В реальном времени",
+    "Destroy": "Остановить",
+    "Map faces": "Сопоставить лица",
+    "Processing...": "Обработка...",
+    "Processing succeed!": "Обработка успешна!",
+    "Processing ignored!": "Обработка проигнорирована!",
+    "Failed to start camera": "Не удалось запустить камеру",
+    "Please complete pop-up or close it.": "Пожалуйста, заполните всплывающее окно или закройте его.",
+    "Getting unique faces": "Получение уникальных лиц",
+    "Please select a source image first": "Сначала выберите исходное изображение, пожалуйста",
+    "No faces found in target": "В целевом изображении не найдено лиц",
+    "Add": "Добавить",
+    "Clear": "Очистить",
+    "Submit": "Отправить",
+    "Select source image": "Выбрать исходное изображение",
+    "Select target image": "Выбрать целевое изображение",
+    "Please provide mapping!": "Пожалуйста, укажите сопоставление!",
+    "At least 1 source with target is required!": "Требуется хотя бы 1 источник с целью!",
+    "Face could not be detected in last upload!": "Лицо не обнаружено в последнем загруженном изображении!",
+    "Select Camera:": "Выберите камеру:",
+    "All mappings cleared!": "Все сопоставления очищены!",
+    "Mappings successfully submitted!": "Сопоставления успешно отправлены!",
+    "Source x Target Mapper is already open.": "Сопоставитель Источник-Цель уже открыт."
+}
@@ -0,0 +1,45 @@
+{
+    "Source x Target Mapper": "ตัวจับคู่ต้นทาง x ปลายทาง",
+    "select a source image": "เลือกรูปภาพต้นฉบับ",
+    "Preview": "ตัวอย่าง",
+    "select a target image or video": "เลือกรูปภาพหรือวิดีโอเป้าหมาย",
+    "save image output file": "บันทึกไฟล์รูปภาพ",
+    "save video output file": "บันทึกไฟล์วิดีโอ",
+    "select a target image": "เลือกรูปภาพเป้าหมาย",
+    "source": "ต้นฉบับ",
+    "Select a target": "เลือกเป้าหมาย",
+    "Select a face": "เลือกใบหน้า",
+    "Keep audio": "เก็บเสียง",
+    "Face Enhancer": "ปรับปรุงใบหน้า",
+    "Many faces": "หลายใบหน้า",
+    "Show FPS": "แสดง FPS",
+    "Keep fps": "คงค่า FPS",
+    "Keep frames": "คงค่าเฟรม",
+    "Fix Blueish Cam": "แก้ไขภาพอมฟ้าจากกล้อง",
+    "Mouth Mask": "มาสก์ปาก",
+    "Show Mouth Mask Box": "แสดงกรอบมาสก์ปาก",
+    "Start": "เริ่ม",
+    "Live": "สด",
+    "Destroy": "หยุด",
+    "Map faces": "จับคู่ใบหน้า",
+    "Processing...": "กำลังประมวลผล...",
+    "Processing succeed!": "ประมวลผลสำเร็จแล้ว!",
+    "Processing ignored!": "การประมวลผลถูกละเว้น",
+    "Failed to start camera": "ไม่สามารถเริ่มกล้องได้",
+    "Please complete pop-up or close it.": "โปรดดำเนินการในป๊อปอัปให้เสร็จสิ้น หรือปิด",
+    "Getting unique faces": "กำลังค้นหาใบหน้าที่ไม่ซ้ำกัน",
+    "Please select a source image first": "โปรดเลือกภาพต้นฉบับก่อน",
+    "No faces found in target": "ไม่พบใบหน้าในภาพเป้าหมาย",
+    "Add": "เพิ่ม",
+    "Clear": "ล้าง",
+    "Submit": "ส่ง",
+    "Select source image": "เลือกภาพต้นฉบับ",
+    "Select target image": "เลือกภาพเป้าหมาย",
+    "Please provide mapping!": "โปรดระบุการจับคู่!",
+    "At least 1 source with target is required!": "ต้องมีการจับคู่ต้นฉบับกับเป้าหมายอย่างน้อย 1 คู่!",
+    "Face could not be detected in last upload!": "ไม่สามารถตรวจพบใบหน้าในไฟล์อัปโหลดล่าสุด!",
+    "Select Camera:": "เลือกกล้อง:",
+    "All mappings cleared!": "ล้างการจับคู่ทั้งหมดแล้ว!",
+    "Mappings successfully submitted!": "ส่งการจับคู่สำเร็จแล้ว!",
+    "Source x Target Mapper is already open.": "ตัวจับคู่ต้นทาง x ปลายทาง เปิดอยู่แล้ว"
+}
@@ -1,11 +1,11 @@
 {
    "Source x Target Mapper": "Source x Target Mapper",
-    "select an source image": "选择一个源图像",
+    "select a source image": "选择一个源图像",
    "Preview": "预览",
-    "select an target image or video": "选择一个目标图像或视频",
+    "select a target image or video": "选择一个目标图像或视频",
    "save image output file": "保存图像输出文件",
    "save video output file": "保存视频输出文件",
-    "select an target image": "选择一个目标图像",
+    "select a target image": "选择一个目标图像",
    "source": "源",
    "Select a target": "选择一个目标",
    "Select a face": "选择一张脸",
@@ -36,11 +36,11 @@
    "Select source image": "请选取源图像",
    "Select target image": "请选取目标图像",
    "Please provide mapping!": "请提供映射",
-    "Atleast 1 source with target is required!": "至少需要一个来源图像与目标图像相关！",
+    "At least 1 source with target is required!": "至少需要一个来源图像与目标图像相关！",
    "At least 1 source with target is required!": "至少需要一个来源图像与目标图像相关！",
    "Face could not be detected in last upload!": "最近上传的图像中没有检测到人脸!",
    "Select Camera:": "选择摄像头",
    "All mappings cleared!": "所有映射均已清除!",
    "Mappings successfully submitted!": "成功提交映射！",
    "Source x Target Mapper is already open.": "源 x 目标映射器已打开。"
-}
+}
@@ -0,0 +1,18 @@
+import os 
+import cv2
+import numpy as np
+
+# Utility function to support unicode characters in file paths for reading
+def imread_unicode(path, flags=cv2.IMREAD_COLOR):
+    return cv2.imdecode(np.fromfile(path, dtype=np.uint8), flags)
+
+# Utility function to support unicode characters in file paths for writing
+def imwrite_unicode(path, img, params=None):
+    root, ext = os.path.splitext(path)
+    if not ext:
+        ext = ".png"
+        result, encoded_img = cv2.imencode(ext, img, params if params else [])
+        result, encoded_img = cv2.imencode(f".{ext}", img, params if params is not None else [])
+        encoded_img.tofile(path)
+        return True
+    return False
@@ -20,7 +20,6 @@ import modules.metadata
 import modules.ui as ui
 from modules.processors.frame.core import get_frame_processors_modules
 from modules.utilities import has_image_extension, is_image, is_video, detect_fps, create_video, extract_frames, get_temp_frame_paths, restore_audio, create_temp, move_temp, clean_temp, normalize_output_path
-from modules.fake_face_handler import cleanup_fake_face

 if 'ROCMExecutionProvider' in modules.globals.execution_providers:
    del torch
@@ -36,7 +35,9 @@ def parse_args() -> None:
    program.add_argument('-t', '--target', help='select an target image or video', dest='target_path')
    program.add_argument('-o', '--output', help='select output file or directory', dest='output_path')
    program.add_argument('--frame-processor', help='pipeline of frame processors', dest='frame_processor', default=['face_swapper'], choices=['face_swapper', 'face_enhancer'], nargs='+')
+    program.add_argument('--keep-fps', help='keep original fps', dest='keep_fps', action='store_true', default=False)
    program.add_argument('--keep-audio', help='keep original audio', dest='keep_audio', action='store_true', default=True)
+    program.add_argument('--keep-frames', help='keep temporary frames', dest='keep_frames', action='store_true', default=False)
    program.add_argument('--many-faces', help='process every face', dest='many_faces', action='store_true', default=False)
    program.add_argument('--nsfw-filter', help='filter the NSFW image or video', dest='nsfw_filter', action='store_true', default=False)
    program.add_argument('--map-faces', help='map source target faces', dest='map_faces', action='store_true', default=False)
@@ -64,9 +65,9 @@ def parse_args() -> None:
    modules.globals.output_path = normalize_output_path(modules.globals.source_path, modules.globals.target_path, args.output_path)
    modules.globals.frame_processors = args.frame_processor
    modules.globals.headless = args.source_path or args.target_path or args.output_path
-    modules.globals.keep_fps = True
-    modules.globals.keep_frames = True
+    modules.globals.keep_fps = args.keep_fps
    modules.globals.keep_audio = args.keep_audio
+    modules.globals.keep_frames = args.keep_frames
    modules.globals.many_faces = args.many_faces
    modules.globals.mouth_mask = args.mouth_mask
    modules.globals.nsfw_filter = args.nsfw_filter
@@ -240,7 +241,6 @@ def start() -> None:
 def destroy(to_quit=True) -> None:
    if modules.globals.target_path:
        clean_temp(modules.globals.target_path)
-    cleanup_fake_face()
    if to_quit: quit()


@@ -39,13 +39,13 @@ def get_many_faces(frame: Frame) -> Any:
        return None

 def has_valid_map() -> bool:
-    for map in modules.globals.souce_target_map:
+    for map in modules.globals.source_target_map:
        if "source" in map and "target" in map:
            return True
    return False

 def default_source_face() -> Any:
-    for map in modules.globals.souce_target_map:
+    for map in modules.globals.source_target_map:
        if "source" in map:
            return map['source']['face']
    return None
@@ -53,7 +53,7 @@ def default_source_face() -> Any:
 def simplify_maps() -> Any:
    centroids = []
    faces = []
-    for map in modules.globals.souce_target_map:
+    for map in modules.globals.source_target_map:
        if "source" in map and "target" in map:
            centroids.append(map['target']['face'].normed_embedding)
            faces.append(map['source']['face'])
@@ -64,10 +64,10 @@ def simplify_maps() -> Any:
 def add_blank_map() -> Any:
    try:
        max_id = -1
-        if len(modules.globals.souce_target_map) > 0:
-            max_id = max(modules.globals.souce_target_map, key=lambda x: x['id'])['id']
+        if len(modules.globals.source_target_map) > 0:
+            max_id = max(modules.globals.source_target_map, key=lambda x: x['id'])['id']

-        modules.globals.souce_target_map.append({
+        modules.globals.source_target_map.append({
                'id' : max_id + 1
                })
    except ValueError:
@@ -75,14 +75,14 @@ def add_blank_map() -> Any:
    
 def get_unique_faces_from_target_image() -> Any:
    try:
-        modules.globals.souce_target_map = []
+        modules.globals.source_target_map = []
        target_frame = cv2.imread(modules.globals.target_path)
        many_faces = get_many_faces(target_frame)
        i = 0

        for face in many_faces:
            x_min, y_min, x_max, y_max = face['bbox']
-            modules.globals.souce_target_map.append({
+            modules.globals.source_target_map.append({
                'id' : i, 
                'target' : {
                            'cv2' : target_frame[int(y_min):int(y_max), int(x_min):int(x_max)],
@@ -96,7 +96,7 @@ def get_unique_faces_from_target_image() -> Any:
    
 def get_unique_faces_from_target_video() -> Any:
    try:
-        modules.globals.souce_target_map = []
+        modules.globals.source_target_map = []
        frame_face_embeddings = []
        face_embeddings = []
    
@@ -127,7 +127,7 @@ def get_unique_faces_from_target_video() -> Any:
                face['target_centroid'] = closest_centroid_index

        for i in range(len(centroids)):
-            modules.globals.souce_target_map.append({
+            modules.globals.source_target_map.append({
                'id' : i
            })

@@ -135,7 +135,7 @@ def get_unique_faces_from_target_video() -> Any:
            for frame in tqdm(frame_face_embeddings, desc=f"Mapping frame embeddings to centroids-{i}"):
                temp.append({'frame': frame['frame'], 'faces': [face for face in frame['faces'] if face['target_centroid'] == i], 'location': frame['location']})

-            modules.globals.souce_target_map[i]['target_faces_in_frame'] = temp
+            modules.globals.source_target_map[i]['target_faces_in_frame'] = temp

        # dump_faces(centroids, frame_face_embeddings)
        default_target_face()
@@ -144,7 +144,7 @@ def get_unique_faces_from_target_video() -> Any:
    

 def default_target_face():
-    for map in modules.globals.souce_target_map:
+    for map in modules.globals.source_target_map:
        best_face = None
        best_frame = None
        for frame in map['target_faces_in_frame']:
@@ -1,120 +0,0 @@
-import os
-import requests
-import tempfile
-from pathlib import Path
-import cv2
-import numpy as np
-import modules.globals
-
-def add_padding_to_face(image, padding_ratio=0.3):
-    """Add padding around the face image
-    
-    Args:
-        image: The input face image
-        padding_ratio: Amount of padding to add as a ratio of image dimensions
-        
-    Returns:
-        Padded image with background padding added
-    """
-    if image is None:
-        return None
-        
-    height, width = image.shape[:2]
-    pad_x = int(width * padding_ratio)
-    pad_y = int(height * padding_ratio)
-    
-    # Create larger image with padding
-    padded_height = height + 2 * pad_y
-    padded_width = width + 2 * pad_x
-    padded_image = np.zeros((padded_height, padded_width, 3), dtype=np.uint8)
-    
-    # Fill padded area with blurred and darkened edge pixels
-    edge_color = cv2.blur(image, (15, 15))
-    edge_color = (edge_color * 0.6).astype(np.uint8)  # Darken the padding
-    
-    # Fill the padded image with original face
-    padded_image[pad_y:pad_y+height, pad_x:pad_x+width] = image
-    
-    # Fill padding areas with edge color
-    # Top padding - repeat first row
-    top_edge = edge_color[0, :, :]
-    for i in range(pad_y):
-        padded_image[i, pad_x:pad_x+width] = top_edge
-        
-    # Bottom padding - repeat last row
-    bottom_edge = edge_color[-1, :, :]
-    for i in range(pad_y):
-        padded_image[pad_y+height+i, pad_x:pad_x+width] = bottom_edge
-        
-    # Left padding - repeat first column
-    left_edge = edge_color[:, 0, :]
-    for i in range(pad_x):
-        padded_image[pad_y:pad_y+height, i] = left_edge
-        
-    # Right padding - repeat last column
-    right_edge = edge_color[:, -1, :]
-    for i in range(pad_x):
-        padded_image[pad_y:pad_y+height, pad_x+width+i] = right_edge
-        
-    # Fill corners with nearest edge colors
-    # Top-left corner
-    padded_image[:pad_y, :pad_x] = edge_color[0, 0, :]
-    # Top-right corner
-    padded_image[:pad_y, pad_x+width:] = edge_color[0, -1, :]
-    # Bottom-left corner
-    padded_image[pad_y+height:, :pad_x] = edge_color[-1, 0, :]
-    # Bottom-right corner
-    padded_image[pad_y+height:, pad_x+width:] = edge_color[-1, -1, :]
-    
-    return padded_image
-
-def get_fake_face() -> str:
-    """Fetch a face from thispersondoesnotexist.com and save it temporarily"""
-    try:
-        # Create temp directory if it doesn't exist
-        temp_dir = Path(tempfile.gettempdir()) / "deep-live-cam"
-        temp_dir.mkdir(parents=True, exist_ok=True)
-        
-        # Generate temp file path
-        temp_file = temp_dir / "fake_face.jpg"
-        
-        # Basic headers to mimic a browser request
-        headers = {
-            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
-        }
-        
-        # Fetch the image
-        response = requests.get('https://thispersondoesnotexist.com', headers=headers)
-        
-        if response.status_code == 200:
-            # Read image from response
-            image_array = np.asarray(bytearray(response.content), dtype=np.uint8)
-            image = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
-            
-            # Add padding around the face
-            padded_image = add_padding_to_face(image)
-            
-            # Save the padded image
-            cv2.imwrite(str(temp_file), padded_image)
-            return str(temp_file)
-        else:
-            print(f"Failed to fetch fake face: {response.status_code}")
-            return None
-    except Exception as e:
-        print(f"Error fetching fake face: {str(e)}")
-        return None
-
-def cleanup_fake_face():
-    """Clean up the temporary fake face image"""
-    try:
-        if modules.globals.fake_face_path and os.path.exists(modules.globals.fake_face_path):
-            os.remove(modules.globals.fake_face_path)
-            modules.globals.fake_face_path = None
-    except Exception as e:
-        print(f"Error cleaning up fake face: {str(e)}")
-
-def refresh_fake_face():
-    """Refresh the fake face image"""
-    cleanup_fake_face()
-    modules.globals.fake_face_path = get_fake_face()
-    return modules.globals.fake_face_path is not None 
@@ -9,7 +9,7 @@ file_types = [
    ("Video", ("*.mp4", "*.mkv")),
 ]

-souce_target_map = []
+source_target_map = []
 simple_map = {}

 source_path = None
@@ -21,7 +21,7 @@ keep_audio = True
 keep_frames = False
 many_faces = False
 map_faces = False
-color_correction = False
+color_correction = False  # New global variable for color correction toggle
 nsfw_filter = False
 video_encoder = None
 video_quality = None
@@ -41,12 +41,3 @@ show_mouth_mask_box = False
 mask_feather_ratio = 8
 mask_down_size = 0.50
 mask_size = 1
-mouth_mask_size = 1.0
-eyes_mask = False
-show_eyes_mask_box = False
-eyebrows_mask = False
-show_eyebrows_mask_box = False
-eyes_mask_size = 1.0
-eyebrows_mask_size = 1.0
-use_fake_face = False
-fake_face_path = None
@@ -1,3 +1,3 @@
 name = 'Deep-Live-Cam'
-version = '1.8'
+version = '1.8.1'
 edition = 'GitHub Edition'
@@ -42,18 +42,29 @@ def get_frame_processors_modules(frame_processors: List[str]) -> List[ModuleType

 def set_frame_processors_modules_from_ui(frame_processors: List[str]) -> None:
    global FRAME_PROCESSORS_MODULES
+    current_processor_names = [proc.__name__.split('.')[-1] for proc in FRAME_PROCESSORS_MODULES]
+
    for frame_processor, state in modules.globals.fp_ui.items():
-        if state == True and frame_processor not in frame_processors:
-            frame_processor_module = load_frame_processor_module(frame_processor)
-            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
-            modules.globals.frame_processors.append(frame_processor)
-        if state == False:
+        if state == True and frame_processor not in current_processor_names:
            try:
                frame_processor_module = load_frame_processor_module(frame_processor)
-                FRAME_PROCESSORS_MODULES.remove(frame_processor_module)
-                modules.globals.frame_processors.remove(frame_processor)
-            except:
-                pass
+                FRAME_PROCESSORS_MODULES.append(frame_processor_module)
+                if frame_processor not in modules.globals.frame_processors:
+                     modules.globals.frame_processors.append(frame_processor)
+            except SystemExit:
+                 print(f"Warning: Failed to load frame processor {frame_processor} requested by UI state.")
+            except Exception as e:
+                 print(f"Warning: Error loading frame processor {frame_processor} requested by UI state: {e}")
+
+        elif state == False and frame_processor in current_processor_names:
+            try:
+                module_to_remove = next((mod for mod in FRAME_PROCESSORS_MODULES if mod.__name__.endswith(f'.{frame_processor}')), None)
+                if module_to_remove:
+                    FRAME_PROCESSORS_MODULES.remove(module_to_remove)
+                if frame_processor in modules.globals.frame_processors:
+                    modules.globals.frame_processors.remove(frame_processor)
+            except Exception as e:
+                 print(f"Warning: Error removing frame processor {frame_processor}: {e}")

 def multi_process_frame(source_path: str, temp_frame_paths: List[str], process_frames: Callable[[str, List[str], Any], None], progress: Any = None) -> None:
    with ThreadPoolExecutor(max_workers=modules.globals.execution_threads) as executor:
@@ -48,6 +48,17 @@ def pre_start() -> bool:
    return True


+TENSORRT_AVAILABLE = False
+try:
+    import torch_tensorrt
+    TENSORRT_AVAILABLE = True
+except ImportError as im:
+    print(f"TensorRT is not available: {im}")
+    pass
+except Exception as e:
+    print(f"TensorRT is not available: {e}")
+    pass
+
 def get_face_enhancer() -> Any:
    global FACE_ENHANCER

@@ -55,16 +66,26 @@ def get_face_enhancer() -> Any:
        if FACE_ENHANCER is None:
            model_path = os.path.join(models_dir, "GFPGANv1.4.pth")
            
-            match platform.system():
-                case "Darwin":  # Mac OS
-                    if torch.backends.mps.is_available():
-                        mps_device = torch.device("mps")
-                        FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1, device=mps_device)  # type: ignore[attr-defined]
-                    else:
-                        FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1)  # type: ignore[attr-defined]
-                case _:  # Other OS
-                    FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1)  # type: ignore[attr-defined]
+            selected_device = None
+            device_priority = []

+            if TENSORRT_AVAILABLE and torch.cuda.is_available():
+                selected_device = torch.device("cuda")
+                device_priority.append("TensorRT+CUDA")
+            elif torch.cuda.is_available():
+                selected_device = torch.device("cuda")
+                device_priority.append("CUDA")
+            elif torch.backends.mps.is_available() and platform.system() == "Darwin":
+                selected_device = torch.device("mps")
+                device_priority.append("MPS")
+            elif not torch.cuda.is_available():
+                selected_device = torch.device("cpu")
+                device_priority.append("CPU")
+            
+            FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1, device=selected_device)
+
+            # for debug:
+            print(f"Selected device: {selected_device} and device priority: {device_priority}")
    return FACE_ENHANCER


@@ -1,634 +0,0 @@
-import cv2
-import numpy as np
-from modules.typing import Face, Frame
-import modules.globals
-
-def apply_color_transfer(source, target):
-    """
-    Apply color transfer from target to source image
-    """
-    source = cv2.cvtColor(source, cv2.COLOR_BGR2LAB).astype("float32")
-    target = cv2.cvtColor(target, cv2.COLOR_BGR2LAB).astype("float32")
-
-    source_mean, source_std = cv2.meanStdDev(source)
-    target_mean, target_std = cv2.meanStdDev(target)
-
-    # Reshape mean and std to be broadcastable
-    source_mean = source_mean.reshape(1, 1, 3)
-    source_std = source_std.reshape(1, 1, 3)
-    target_mean = target_mean.reshape(1, 1, 3)
-    target_std = target_std.reshape(1, 1, 3)
-
-    # Perform the color transfer
-    source = (source - source_mean) * (target_std / source_std) + target_mean
-
-    return cv2.cvtColor(np.clip(source, 0, 255).astype("uint8"), cv2.COLOR_LAB2BGR)
-
-def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
-    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
-    landmarks = face.landmark_2d_106
-    if landmarks is not None:
-        # Convert landmarks to int32
-        landmarks = landmarks.astype(np.int32)
-
-        # Extract facial features
-        right_side_face = landmarks[0:16]
-        left_side_face = landmarks[17:32]
-        right_eye = landmarks[33:42]
-        right_eye_brow = landmarks[43:51]
-        left_eye = landmarks[87:96]
-        left_eye_brow = landmarks[97:105]
-
-        # Calculate forehead extension
-        right_eyebrow_top = np.min(right_eye_brow[:, 1])
-        left_eyebrow_top = np.min(left_eye_brow[:, 1])
-        eyebrow_top = min(right_eyebrow_top, left_eyebrow_top)
-
-        face_top = np.min([right_side_face[0, 1], left_side_face[-1, 1]])
-        forehead_height = face_top - eyebrow_top
-        extended_forehead_height = int(forehead_height * 5.0)  # Extend by 50%
-
-        # Create forehead points
-        forehead_left = right_side_face[0].copy()
-        forehead_right = left_side_face[-1].copy()
-        forehead_left[1] -= extended_forehead_height
-        forehead_right[1] -= extended_forehead_height
-
-        # Combine all points to create the face outline
-        face_outline = np.vstack(
-            [
-                [forehead_left],
-                right_side_face,
-                left_side_face[::-1],  # Reverse left side to create a continuous outline
-                [forehead_right],
-            ]
-        )
-
-        # Calculate padding
-        padding = int(
-            np.linalg.norm(right_side_face[0] - left_side_face[-1]) * 0.05
-        )  # 5% of face width
-
-        # Create a slightly larger convex hull for padding
-        hull = cv2.convexHull(face_outline)
-        hull_padded = []
-        for point in hull:
-            x, y = point[0]
-            center = np.mean(face_outline, axis=0)
-            direction = np.array([x, y]) - center
-            direction = direction / np.linalg.norm(direction)
-            padded_point = np.array([x, y]) + direction * padding
-            hull_padded.append(padded_point)
-
-        hull_padded = np.array(hull_padded, dtype=np.int32)
-
-        # Fill the padded convex hull
-        cv2.fillConvexPoly(mask, hull_padded, 255)
-
-        # Smooth the mask edges
-        mask = cv2.GaussianBlur(mask, (5, 5), 3)
-
-    return mask
-
-def create_lower_mouth_mask(
-    face: Face, frame: Frame
-) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
-    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
-    mouth_cutout = None
-    landmarks = face.landmark_2d_106
-    if landmarks is not None:
-        #                  0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20
-        lower_lip_order = [
-            65,
-            66,
-            62,
-            70,
-            69,
-            18,
-            19,
-            20,
-            21,
-            22,
-            23,
-            24,
-            0,
-            8,
-            7,
-            6,
-            5,
-            4,
-            3,
-            2,
-            65,
-        ]
-        lower_lip_landmarks = landmarks[lower_lip_order].astype(
-            np.float32
-        )  # Use float for precise calculations
-
-        # Calculate the center of the landmarks
-        center = np.mean(lower_lip_landmarks, axis=0)
-
-        # Expand the landmarks outward using the mouth_mask_size
-        expansion_factor = (
-            1 + modules.globals.mask_down_size * modules.globals.mouth_mask_size
-        )  # Adjust expansion based on slider
-        expanded_landmarks = (lower_lip_landmarks - center) * expansion_factor + center
-
-        # Extend the top lip part
-        toplip_indices = [
-            20,
-            0,
-            1,
-            2,
-            3,
-            4,
-            5,
-        ]  # Indices for landmarks 2, 65, 66, 62, 70, 69, 18
-        toplip_extension = (
-            modules.globals.mask_size * modules.globals.mouth_mask_size * 0.5
-        )  # Adjust extension based on slider
-        for idx in toplip_indices:
-            direction = expanded_landmarks[idx] - center
-            direction = direction / np.linalg.norm(direction)
-            expanded_landmarks[idx] += direction * toplip_extension
-
-        # Extend the bottom part (chin area)
-        chin_indices = [
-            11,
-            12,
-            13,
-            14,
-            15,
-            16,
-        ]  # Indices for landmarks 21, 22, 23, 24, 0, 8
-        chin_extension = 2 * 0.2  # Adjust this factor to control the extension
-        for idx in chin_indices:
-            expanded_landmarks[idx][1] += (
-                expanded_landmarks[idx][1] - center[1]
-            ) * chin_extension
-
-        # Convert back to integer coordinates
-        expanded_landmarks = expanded_landmarks.astype(np.int32)
-
-        # Calculate bounding box for the expanded lower mouth
-        min_x, min_y = np.min(expanded_landmarks, axis=0)
-        max_x, max_y = np.max(expanded_landmarks, axis=0)
-
-        # Add some padding to the bounding box
-        padding = int((max_x - min_x) * 0.1)  # 10% padding
-        min_x = max(0, min_x - padding)
-        min_y = max(0, min_y - padding)
-        max_x = min(frame.shape[1], max_x + padding)
-        max_y = min(frame.shape[0], max_y + padding)
-
-        # Ensure the bounding box dimensions are valid
-        if max_x <= min_x or max_y <= min_y:
-            if (max_x - min_x) <= 1:
-                max_x = min_x + 1
-            if (max_y - min_y) <= 1:
-                max_y = min_y + 1
-
-        # Create the mask
-        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
-        cv2.fillPoly(mask_roi, [expanded_landmarks - [min_x, min_y]], 255)
-
-        # Apply Gaussian blur to soften the mask edges
-        mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
-
-        # Place the mask ROI in the full-sized mask
-        mask[min_y:max_y, min_x:max_x] = mask_roi
-
-        # Extract the masked area from the frame
-        mouth_cutout = frame[min_y:max_y, min_x:max_x].copy()
-
-        # Return the expanded lower lip polygon in original frame coordinates
-        lower_lip_polygon = expanded_landmarks
-
-    return mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon
-
-def create_eyes_mask(face: Face, frame: Frame) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
-    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
-    eyes_cutout = None
-    landmarks = face.landmark_2d_106
-    if landmarks is not None:
-        # Left eye landmarks (87-96) and right eye landmarks (33-42)
-        left_eye = landmarks[87:96]
-        right_eye = landmarks[33:42]
-        
-        # Calculate centers and dimensions for each eye
-        left_eye_center = np.mean(left_eye, axis=0).astype(np.int32)
-        right_eye_center = np.mean(right_eye, axis=0).astype(np.int32)
-        
-        # Calculate eye dimensions with size adjustment
-        def get_eye_dimensions(eye_points):
-            x_coords = eye_points[:, 0]
-            y_coords = eye_points[:, 1]
-            width = int((np.max(x_coords) - np.min(x_coords)) * (1 + modules.globals.mask_down_size * modules.globals.eyes_mask_size))
-            height = int((np.max(y_coords) - np.min(y_coords)) * (1 + modules.globals.mask_down_size * modules.globals.eyes_mask_size))
-            return width, height
-        
-        left_width, left_height = get_eye_dimensions(left_eye)
-        right_width, right_height = get_eye_dimensions(right_eye)
-        
-        # Add extra padding
-        padding = int(max(left_width, right_width) * 0.2)
-        
-        # Calculate bounding box for both eyes
-        min_x = min(left_eye_center[0] - left_width//2, right_eye_center[0] - right_width//2) - padding
-        max_x = max(left_eye_center[0] + left_width//2, right_eye_center[0] + right_width//2) + padding
-        min_y = min(left_eye_center[1] - left_height//2, right_eye_center[1] - right_height//2) - padding
-        max_y = max(left_eye_center[1] + left_height//2, right_eye_center[1] + right_height//2) + padding
-        
-        # Ensure coordinates are within frame bounds
-        min_x = max(0, min_x)
-        min_y = max(0, min_y)
-        max_x = min(frame.shape[1], max_x)
-        max_y = min(frame.shape[0], max_y)
-        
-        # Create mask for the eyes region
-        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
-        
-        # Draw ellipses for both eyes
-        left_center = (left_eye_center[0] - min_x, left_eye_center[1] - min_y)
-        right_center = (right_eye_center[0] - min_x, right_eye_center[1] - min_y)
-        
-        # Calculate axes lengths (half of width and height)
-        left_axes = (left_width//2, left_height//2)
-        right_axes = (right_width//2, right_height//2)
-        
-        # Draw filled ellipses
-        cv2.ellipse(mask_roi, left_center, left_axes, 0, 0, 360, 255, -1)
-        cv2.ellipse(mask_roi, right_center, right_axes, 0, 0, 360, 255, -1)
-        
-        # Apply Gaussian blur to soften mask edges
-        mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
-        
-        # Place the mask ROI in the full-sized mask
-        mask[min_y:max_y, min_x:max_x] = mask_roi
-        
-        # Extract the masked area from the frame
-        eyes_cutout = frame[min_y:max_y, min_x:max_x].copy()
-        
-        # Create polygon points for visualization
-        def create_ellipse_points(center, axes):
-            t = np.linspace(0, 2*np.pi, 32)
-            x = center[0] + axes[0] * np.cos(t)
-            y = center[1] + axes[1] * np.sin(t)
-            return np.column_stack((x, y)).astype(np.int32)
-        
-        # Generate points for both ellipses
-        left_points = create_ellipse_points((left_eye_center[0], left_eye_center[1]), (left_width//2, left_height//2))
-        right_points = create_ellipse_points((right_eye_center[0], right_eye_center[1]), (right_width//2, right_height//2))
-        
-        # Combine points for both eyes
-        eyes_polygon = np.vstack([left_points, right_points])
-        
-    return mask, eyes_cutout, (min_x, min_y, max_x, max_y), eyes_polygon
-
-def create_curved_eyebrow(points):
-    if len(points) >= 5:
-        # Sort points by x-coordinate
-        sorted_idx = np.argsort(points[:, 0])
-        sorted_points = points[sorted_idx]
-        
-        # Calculate dimensions
-        x_min, y_min = np.min(sorted_points, axis=0)
-        x_max, y_max = np.max(sorted_points, axis=0)
-        width = x_max - x_min
-        height = y_max - y_min
-        
-        # Create more points for smoother curve
-        num_points = 50
-        x = np.linspace(x_min, x_max, num_points)
-        
-        # Fit quadratic curve through points for more natural arch
-        coeffs = np.polyfit(sorted_points[:, 0], sorted_points[:, 1], 2)
-        y = np.polyval(coeffs, x)
-        
-        # Increased offsets to create more separation
-        top_offset = height * 0.5  # Increased from 0.3 to shift up more
-        bottom_offset = height * 0.2  # Increased from 0.1 to shift down more
-        
-        # Create smooth curves
-        top_curve = y - top_offset
-        bottom_curve = y + bottom_offset
-        
-        # Create curved endpoints with more pronounced taper
-        end_points = 5
-        start_x = np.linspace(x[0] - width * 0.15, x[0], end_points)  # Increased taper
-        end_x = np.linspace(x[-1], x[-1] + width * 0.15, end_points)  # Increased taper
-        
-        # Create tapered ends
-        start_curve = np.column_stack((
-            start_x,
-            np.linspace(bottom_curve[0], top_curve[0], end_points)
-        ))
-        end_curve = np.column_stack((
-            end_x,
-            np.linspace(bottom_curve[-1], top_curve[-1], end_points)
-        ))
-        
-        # Combine all points to form a smooth contour
-        contour_points = np.vstack([
-            start_curve,
-            np.column_stack((x, top_curve)),
-            end_curve,
-            np.column_stack((x[::-1], bottom_curve[::-1]))
-        ])
-        
-        # Add slight padding for better coverage
-        center = np.mean(contour_points, axis=0)
-        vectors = contour_points - center
-        padded_points = center + vectors * 1.2  # Increased padding slightly
-        
-        return padded_points
-    return points
-
-def create_eyebrows_mask(face: Face, frame: Frame) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
-    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
-    eyebrows_cutout = None
-    landmarks = face.landmark_2d_106
-    if landmarks is not None:
-        # Left eyebrow landmarks (97-105) and right eyebrow landmarks (43-51)
-        left_eyebrow = landmarks[97:105].astype(np.float32)
-        right_eyebrow = landmarks[43:51].astype(np.float32)
-        
-        # Calculate centers and dimensions for each eyebrow
-        left_center = np.mean(left_eyebrow, axis=0)
-        right_center = np.mean(right_eyebrow, axis=0)
-        
-        # Calculate bounding box with padding adjusted by size
-        all_points = np.vstack([left_eyebrow, right_eyebrow])
-        padding_factor = modules.globals.eyebrows_mask_size
-        min_x = np.min(all_points[:, 0]) - 25 * padding_factor
-        max_x = np.max(all_points[:, 0]) + 25 * padding_factor
-        min_y = np.min(all_points[:, 1]) - 20 * padding_factor
-        max_y = np.max(all_points[:, 1]) + 15 * padding_factor
-        
-        # Ensure coordinates are within frame bounds
-        min_x = max(0, int(min_x))
-        min_y = max(0, int(min_y))
-        max_x = min(frame.shape[1], int(max_x))
-        max_y = min(frame.shape[0], int(max_y))
-        
-        # Create mask for the eyebrows region
-        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
-        
-        try:
-            # Convert points to local coordinates
-            left_local = left_eyebrow - [min_x, min_y]
-            right_local = right_eyebrow - [min_x, min_y]
-            
-            def create_curved_eyebrow(points):
-                if len(points) >= 5:
-                    # Sort points by x-coordinate
-                    sorted_idx = np.argsort(points[:, 0])
-                    sorted_points = points[sorted_idx]
-                    
-                    # Calculate dimensions
-                    x_min, y_min = np.min(sorted_points, axis=0)
-                    x_max, y_max = np.max(sorted_points, axis=0)
-                    width = x_max - x_min
-                    height = y_max - y_min
-                    
-                    # Create more points for smoother curve
-                    num_points = 50
-                    x = np.linspace(x_min, x_max, num_points)
-                    
-                    # Fit quadratic curve through points for more natural arch
-                    coeffs = np.polyfit(sorted_points[:, 0], sorted_points[:, 1], 2)
-                    y = np.polyval(coeffs, x)
-                    
-                    # Increased offsets to create more separation
-                    top_offset = height * 0.5  # Increased from 0.3 to shift up more
-                    bottom_offset = height * 0.2  # Increased from 0.1 to shift down more
-                    
-                    # Create smooth curves
-                    top_curve = y - top_offset
-                    bottom_curve = y + bottom_offset
-                    
-                    # Create curved endpoints with more pronounced taper
-                    end_points = 5
-                    start_x = np.linspace(x[0] - width * 0.15, x[0], end_points)  # Increased taper
-                    end_x = np.linspace(x[-1], x[-1] + width * 0.15, end_points)  # Increased taper
-                    
-                    # Create tapered ends
-                    start_curve = np.column_stack((
-                        start_x,
-                        np.linspace(bottom_curve[0], top_curve[0], end_points)
-                    ))
-                    end_curve = np.column_stack((
-                        end_x,
-                        np.linspace(bottom_curve[-1], top_curve[-1], end_points)
-                    ))
-                    
-                    # Combine all points to form a smooth contour
-                    contour_points = np.vstack([
-                        start_curve,
-                        np.column_stack((x, top_curve)),
-                        end_curve,
-                        np.column_stack((x[::-1], bottom_curve[::-1]))
-                    ])
-                    
-                    # Add slight padding for better coverage
-                    center = np.mean(contour_points, axis=0)
-                    vectors = contour_points - center
-                    padded_points = center + vectors * 1.2  # Increased padding slightly
-                    
-                    return padded_points
-                return points
-            
-            # Generate and draw eyebrow shapes
-            left_shape = create_curved_eyebrow(left_local)
-            right_shape = create_curved_eyebrow(right_local)
-            
-            # Apply multi-stage blurring for natural feathering
-            # First, strong Gaussian blur for initial softening
-            mask_roi = cv2.GaussianBlur(mask_roi, (21, 21), 7)
-            
-            # Second, medium blur for transition areas
-            mask_roi = cv2.GaussianBlur(mask_roi, (11, 11), 3)
-            
-            # Finally, light blur for fine details
-            mask_roi = cv2.GaussianBlur(mask_roi, (5, 5), 1)
-            
-            # Normalize mask values
-            mask_roi = cv2.normalize(mask_roi, None, 0, 255, cv2.NORM_MINMAX)
-            
-            # Place the mask ROI in the full-sized mask
-            mask[min_y:max_y, min_x:max_x] = mask_roi
-            
-            # Extract the masked area from the frame
-            eyebrows_cutout = frame[min_y:max_y, min_x:max_x].copy()
-            
-            # Combine points for visualization
-            eyebrows_polygon = np.vstack([
-                left_shape + [min_x, min_y],
-                right_shape + [min_x, min_y]
-            ]).astype(np.int32)
-            
-        except Exception as e:
-            # Fallback to simple polygons if curve fitting fails
-            left_local = left_eyebrow - [min_x, min_y]
-            right_local = right_eyebrow - [min_x, min_y]
-            cv2.fillPoly(mask_roi, [left_local.astype(np.int32)], 255)
-            cv2.fillPoly(mask_roi, [right_local.astype(np.int32)], 255)
-            mask_roi = cv2.GaussianBlur(mask_roi, (21, 21), 7)
-            mask[min_y:max_y, min_x:max_x] = mask_roi
-            eyebrows_cutout = frame[min_y:max_y, min_x:max_x].copy()
-            eyebrows_polygon = np.vstack([left_eyebrow, right_eyebrow]).astype(np.int32)
-        
-    return mask, eyebrows_cutout, (min_x, min_y, max_x, max_y), eyebrows_polygon
-
-def apply_mask_area(
-    frame: np.ndarray,
-    cutout: np.ndarray,
-    box: tuple,
-    face_mask: np.ndarray,
-    polygon: np.ndarray,
-) -> np.ndarray:
-    min_x, min_y, max_x, max_y = box
-    box_width = max_x - min_x
-    box_height = max_y - min_y
-
-    if (
-        cutout is None
-        or box_width is None
-        or box_height is None
-        or face_mask is None
-        or polygon is None
-    ):
-        return frame
-
-    try:
-        resized_cutout = cv2.resize(cutout, (box_width, box_height))
-        roi = frame[min_y:max_y, min_x:max_x]
-
-        if roi.shape != resized_cutout.shape:
-            resized_cutout = cv2.resize(
-                resized_cutout, (roi.shape[1], roi.shape[0])
-            )
-
-        color_corrected_area = apply_color_transfer(resized_cutout, roi)
-
-        # Create mask for the area
-        polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
-        
-        # Split points for left and right parts if needed
-        if len(polygon) > 50:  # Arbitrary threshold to detect if we have multiple parts
-            mid_point = len(polygon) // 2
-            left_points = polygon[:mid_point] - [min_x, min_y]
-            right_points = polygon[mid_point:] - [min_x, min_y]
-            cv2.fillPoly(polygon_mask, [left_points], 255)
-            cv2.fillPoly(polygon_mask, [right_points], 255)
-        else:
-            adjusted_polygon = polygon - [min_x, min_y]
-            cv2.fillPoly(polygon_mask, [adjusted_polygon], 255)
-
-        # Apply strong initial feathering
-        polygon_mask = cv2.GaussianBlur(polygon_mask, (21, 21), 7)
-
-        # Apply additional feathering
-        feather_amount = min(
-            30,
-            box_width // modules.globals.mask_feather_ratio,
-            box_height // modules.globals.mask_feather_ratio,
-        )
-        feathered_mask = cv2.GaussianBlur(
-            polygon_mask.astype(float), (0, 0), feather_amount
-        )
-        feathered_mask = feathered_mask / feathered_mask.max()
-
-        # Apply additional smoothing to the mask edges
-        feathered_mask = cv2.GaussianBlur(feathered_mask, (5, 5), 1)
-
-        face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
-        combined_mask = feathered_mask * (face_mask_roi / 255.0)
-
-        combined_mask = combined_mask[:, :, np.newaxis]
-        blended = (
-            color_corrected_area * combined_mask + roi * (1 - combined_mask)
-        ).astype(np.uint8)
-
-        # Apply face mask to blended result
-        face_mask_3channel = (
-            np.repeat(face_mask_roi[:, :, np.newaxis], 3, axis=2) / 255.0
-        )
-        final_blend = blended * face_mask_3channel + roi * (1 - face_mask_3channel)
-
-        frame[min_y:max_y, min_x:max_x] = final_blend.astype(np.uint8)
-    except Exception as e:
-        pass
-
-    return frame
-
-def draw_mask_visualization(
-    frame: Frame,
-    mask_data: tuple,
-    label: str,
-    draw_method: str = "polygon"
-) -> Frame:
-    mask, cutout, (min_x, min_y, max_x, max_y), polygon = mask_data
-
-    vis_frame = frame.copy()
-
-    # Ensure coordinates are within frame bounds
-    height, width = vis_frame.shape[:2]
-    min_x, min_y = max(0, min_x), max(0, min_y)
-    max_x, max_y = min(width, max_x), min(height, max_y)
-
-    if draw_method == "ellipse" and len(polygon) > 50:  # For eyes
-        # Split points for left and right parts
-        mid_point = len(polygon) // 2
-        left_points = polygon[:mid_point]
-        right_points = polygon[mid_point:]
-        
-        try:
-            # Fit ellipses to points - need at least 5 points
-            if len(left_points) >= 5 and len(right_points) >= 5:
-                # Convert points to the correct format for ellipse fitting
-                left_points = left_points.astype(np.float32)
-                right_points = right_points.astype(np.float32)
-                
-                # Fit ellipses
-                left_ellipse = cv2.fitEllipse(left_points)
-                right_ellipse = cv2.fitEllipse(right_points)
-                
-                # Draw the ellipses
-                cv2.ellipse(vis_frame, left_ellipse, (0, 255, 0), 2)
-                cv2.ellipse(vis_frame, right_ellipse, (0, 255, 0), 2)
-        except Exception as e:
-            # If ellipse fitting fails, draw simple rectangles as fallback
-            left_rect = cv2.boundingRect(left_points)
-            right_rect = cv2.boundingRect(right_points)
-            cv2.rectangle(vis_frame, 
-                        (left_rect[0], left_rect[1]), 
-                        (left_rect[0] + left_rect[2], left_rect[1] + left_rect[3]), 
-                        (0, 255, 0), 2)
-            cv2.rectangle(vis_frame,
-                        (right_rect[0], right_rect[1]),
-                        (right_rect[0] + right_rect[2], right_rect[1] + right_rect[3]),
-                        (0, 255, 0), 2)
-    else:  # For mouth and eyebrows
-        # Draw the polygon
-        if len(polygon) > 50:  # If we have multiple parts
-            mid_point = len(polygon) // 2
-            left_points = polygon[:mid_point]
-            right_points = polygon[mid_point:]
-            cv2.polylines(vis_frame, [left_points], True, (0, 255, 0), 2, cv2.LINE_AA)
-            cv2.polylines(vis_frame, [right_points], True, (0, 255, 0), 2, cv2.LINE_AA)
-        else:
-            cv2.polylines(vis_frame, [polygon], True, (0, 255, 0), 2, cv2.LINE_AA)
-
-    # Add label
-    cv2.putText(
-        vis_frame,
-        label,
-        (min_x, min_y - 10),
-        cv2.FONT_HERSHEY_SIMPLEX,
-        0.5,
-        (255, 255, 255),
-        1,
-    )
-
-    return vis_frame 
@@ -4,6 +4,7 @@ import insightface
 import threading
 import numpy as np
 import modules.globals
+import logging
 import modules.processors.frame.core
 from modules.core import update_status
 from modules.face_analyser import get_one_face, get_many_faces, default_source_face
@@ -14,14 +15,6 @@ from modules.utilities import (
    is_video,
 )
 from modules.cluster_analysis import find_closest_centroid
-from modules.processors.frame.face_masking import (
-    create_face_mask,
-    create_lower_mouth_mask,
-    create_eyes_mask,
-    create_eyebrows_mask,
-    apply_mask_area,
-    draw_mask_visualization
-)
 import os

 FACE_SWAPPER = None
@@ -35,12 +28,14 @@ models_dir = os.path.join(


 def pre_check() -> bool:
-    download_directory_path = abs_dir
+    download_directory_path = models_dir
+    model_url = "https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128.onnx"
+    if "CUDAExecutionProvider" in modules.globals.execution_providers:
+        model_url = "https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128_fp16.onnx"
+
    conditional_download(
        download_directory_path,
-        [
-            "https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx"
-        ],
+        [model_url],
    )
    return True

@@ -67,7 +62,10 @@ def get_face_swapper() -> Any:

    with THREAD_LOCK:
        if FACE_SWAPPER is None:
-            model_path = os.path.join(models_dir, "inswapper_128_fp16.onnx")
+            model_name = "inswapper_128.onnx"
+            if "CUDAExecutionProvider" in modules.globals.execution_providers:
+                model_name = "inswapper_128_fp16.onnx"
+            model_path = os.path.join(models_dir, model_name)
            FACE_SWAPPER = insightface.model_zoo.get_model(
                model_path, providers=modules.globals.execution_providers
            )
@@ -82,62 +80,24 @@ def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
        temp_frame, target_face, source_face, paste_back=True
    )

-    # Create face mask for both mouth and eyes masking
-    face_mask = create_face_mask(target_face, temp_frame)
-
    if modules.globals.mouth_mask:
-        # Create and apply mouth mask
-        mouth_mask_data = create_lower_mouth_mask(target_face, temp_frame)
-        swapped_frame = apply_mask_area(
-            swapped_frame, 
-            mouth_mask_data[1],  # mouth_cutout
-            mouth_mask_data[2],  # mouth_box
-            face_mask, 
-            mouth_mask_data[3]   # mouth_polygon
+        # Create a mask for the target face
+        face_mask = create_face_mask(target_face, temp_frame)
+
+        # Create the mouth mask
+        mouth_mask, mouth_cutout, mouth_box, lower_lip_polygon = (
+            create_lower_mouth_mask(target_face, temp_frame)
+        )
+
+        # Apply the mouth area
+        swapped_frame = apply_mouth_area(
+            swapped_frame, mouth_cutout, mouth_box, face_mask, lower_lip_polygon
        )

        if modules.globals.show_mouth_mask_box:
-            swapped_frame = draw_mask_visualization(
-                swapped_frame, 
-                mouth_mask_data,
-                "Lower Mouth Mask"
-            )
-
-    if modules.globals.eyes_mask:
-        # Create and apply eyes mask
-        eyes_mask_data = create_eyes_mask(target_face, temp_frame)
-        swapped_frame = apply_mask_area(
-            swapped_frame, 
-            eyes_mask_data[1],  # eyes_cutout
-            eyes_mask_data[2],  # eyes_box
-            face_mask, 
-            eyes_mask_data[3]   # eyes_polygon
-        )
-
-        if modules.globals.show_eyes_mask_box:
-            swapped_frame = draw_mask_visualization(
-                swapped_frame, 
-                eyes_mask_data,
-                "Eyes Mask",
-                draw_method="ellipse"
-            )
-
-    if modules.globals.eyebrows_mask:
-        # Create and apply eyebrows mask
-        eyebrows_mask_data = create_eyebrows_mask(target_face, temp_frame)
-        swapped_frame = apply_mask_area(
-            swapped_frame, 
-            eyebrows_mask_data[1],  # eyebrows_cutout
-            eyebrows_mask_data[2],  # eyebrows_box
-            face_mask, 
-            eyebrows_mask_data[3]   # eyebrows_polygon
-        )
-
-        if modules.globals.show_eyebrows_mask_box:
-            swapped_frame = draw_mask_visualization(
-                swapped_frame, 
-                eyebrows_mask_data,
-                "Eyebrows Mask"
+            mouth_mask_data = (mouth_mask, mouth_cutout, mouth_box, lower_lip_polygon)
+            swapped_frame = draw_mouth_mask_visualization(
+                swapped_frame, target_face, mouth_mask_data
            )

    return swapped_frame
@@ -151,24 +111,30 @@ def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
        many_faces = get_many_faces(temp_frame)
        if many_faces:
            for target_face in many_faces:
-                temp_frame = swap_face(source_face, target_face, temp_frame)
+                if source_face and target_face:
+                    temp_frame = swap_face(source_face, target_face, temp_frame)
+                else:
+                    print("Face detection failed for target/source.")
    else:
        target_face = get_one_face(temp_frame)
-        if target_face:
+        if target_face and source_face:
            temp_frame = swap_face(source_face, target_face, temp_frame)
+        else:
+            logging.error("Face detection failed for target or source.")
    return temp_frame


+
 def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
    if is_image(modules.globals.target_path):
        if modules.globals.many_faces:
            source_face = default_source_face()
-            for map in modules.globals.souce_target_map:
+            for map in modules.globals.source_target_map:
                target_face = map["target"]["face"]
                temp_frame = swap_face(source_face, target_face, temp_frame)

        elif not modules.globals.many_faces:
-            for map in modules.globals.souce_target_map:
+            for map in modules.globals.source_target_map:
                if "source" in map:
                    source_face = map["source"]["face"]
                    target_face = map["target"]["face"]
@@ -177,7 +143,7 @@ def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
    elif is_video(modules.globals.target_path):
        if modules.globals.many_faces:
            source_face = default_source_face()
-            for map in modules.globals.souce_target_map:
+            for map in modules.globals.source_target_map:
                target_frame = [
                    f
                    for f in map["target_faces_in_frame"]
@@ -189,7 +155,7 @@ def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
                        temp_frame = swap_face(source_face, target_face, temp_frame)

        elif not modules.globals.many_faces:
-            for map in modules.globals.souce_target_map:
+            for map in modules.globals.source_target_map:
                if "source" in map:
                    target_frame = [
                        f
@@ -301,3 +267,361 @@ def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
    modules.processors.frame.core.process_video(
        source_path, temp_frame_paths, process_frames
    )
+
+
+def create_lower_mouth_mask(
+    face: Face, frame: Frame
+) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
+    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
+    mouth_cutout = None
+    landmarks = face.landmark_2d_106
+    if landmarks is not None:
+        #                  0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20
+        lower_lip_order = [
+            65,
+            66,
+            62,
+            70,
+            69,
+            18,
+            19,
+            20,
+            21,
+            22,
+            23,
+            24,
+            0,
+            8,
+            7,
+            6,
+            5,
+            4,
+            3,
+            2,
+            65,
+        ]
+        lower_lip_landmarks = landmarks[lower_lip_order].astype(
+            np.float32
+        )  # Use float for precise calculations
+
+        # Calculate the center of the landmarks
+        center = np.mean(lower_lip_landmarks, axis=0)
+
+        # Expand the landmarks outward
+        expansion_factor = (
+            1 + modules.globals.mask_down_size
+        )  # Adjust this for more or less expansion
+        expanded_landmarks = (lower_lip_landmarks - center) * expansion_factor + center
+
+        # Extend the top lip part
+        toplip_indices = [
+            20,
+            0,
+            1,
+            2,
+            3,
+            4,
+            5,
+        ]  # Indices for landmarks 2, 65, 66, 62, 70, 69, 18
+        toplip_extension = (
+            modules.globals.mask_size * 0.5
+        )  # Adjust this factor to control the extension
+        for idx in toplip_indices:
+            direction = expanded_landmarks[idx] - center
+            direction = direction / np.linalg.norm(direction)
+            expanded_landmarks[idx] += direction * toplip_extension
+
+        # Extend the bottom part (chin area)
+        chin_indices = [
+            11,
+            12,
+            13,
+            14,
+            15,
+            16,
+        ]  # Indices for landmarks 21, 22, 23, 24, 0, 8
+        chin_extension = 2 * 0.2  # Adjust this factor to control the extension
+        for idx in chin_indices:
+            expanded_landmarks[idx][1] += (
+                expanded_landmarks[idx][1] - center[1]
+            ) * chin_extension
+
+        # Convert back to integer coordinates
+        expanded_landmarks = expanded_landmarks.astype(np.int32)
+
+        # Calculate bounding box for the expanded lower mouth
+        min_x, min_y = np.min(expanded_landmarks, axis=0)
+        max_x, max_y = np.max(expanded_landmarks, axis=0)
+
+        # Add some padding to the bounding box
+        padding = int((max_x - min_x) * 0.1)  # 10% padding
+        min_x = max(0, min_x - padding)
+        min_y = max(0, min_y - padding)
+        max_x = min(frame.shape[1], max_x + padding)
+        max_y = min(frame.shape[0], max_y + padding)
+
+        # Ensure the bounding box dimensions are valid
+        if max_x <= min_x or max_y <= min_y:
+            if (max_x - min_x) <= 1:
+                max_x = min_x + 1
+            if (max_y - min_y) <= 1:
+                max_y = min_y + 1
+
+        # Create the mask
+        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
+        cv2.fillPoly(mask_roi, [expanded_landmarks - [min_x, min_y]], 255)
+
+        # Apply Gaussian blur to soften the mask edges
+        mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
+
+        # Place the mask ROI in the full-sized mask
+        mask[min_y:max_y, min_x:max_x] = mask_roi
+
+        # Extract the masked area from the frame
+        mouth_cutout = frame[min_y:max_y, min_x:max_x].copy()
+
+        # Return the expanded lower lip polygon in original frame coordinates
+        lower_lip_polygon = expanded_landmarks
+
+    return mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon
+
+
+def draw_mouth_mask_visualization(
+    frame: Frame, face: Face, mouth_mask_data: tuple
+) -> Frame:
+    landmarks = face.landmark_2d_106
+    if landmarks is not None and mouth_mask_data is not None:
+        mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon = (
+            mouth_mask_data
+        )
+
+        vis_frame = frame.copy()
+
+        # Ensure coordinates are within frame bounds
+        height, width = vis_frame.shape[:2]
+        min_x, min_y = max(0, min_x), max(0, min_y)
+        max_x, max_y = min(width, max_x), min(height, max_y)
+
+        # Adjust mask to match the region size
+        mask_region = mask[0 : max_y - min_y, 0 : max_x - min_x]
+
+        # Remove the color mask overlay
+        # color_mask = cv2.applyColorMap((mask_region * 255).astype(np.uint8), cv2.COLORMAP_JET)
+
+        # Ensure shapes match before blending
+        vis_region = vis_frame[min_y:max_y, min_x:max_x]
+        # Remove blending with color_mask
+        # if vis_region.shape[:2] == color_mask.shape[:2]:
+        #     blended = cv2.addWeighted(vis_region, 0.7, color_mask, 0.3, 0)
+        #     vis_frame[min_y:max_y, min_x:max_x] = blended
+
+        # Draw the lower lip polygon
+        cv2.polylines(vis_frame, [lower_lip_polygon], True, (0, 255, 0), 2)
+
+        # Remove the red box
+        # cv2.rectangle(vis_frame, (min_x, min_y), (max_x, max_y), (0, 0, 255), 2)
+
+        # Visualize the feathered mask
+        feather_amount = max(
+            1,
+            min(
+                30,
+                (max_x - min_x) // modules.globals.mask_feather_ratio,
+                (max_y - min_y) // modules.globals.mask_feather_ratio,
+            ),
+        )
+        # Ensure kernel size is odd
+        kernel_size = 2 * feather_amount + 1
+        feathered_mask = cv2.GaussianBlur(
+            mask_region.astype(float), (kernel_size, kernel_size), 0
+        )
+        feathered_mask = (feathered_mask / feathered_mask.max() * 255).astype(np.uint8)
+        # Remove the feathered mask color overlay
+        # color_feathered_mask = cv2.applyColorMap(feathered_mask, cv2.COLORMAP_VIRIDIS)
+
+        # Ensure shapes match before blending feathered mask
+        # if vis_region.shape == color_feathered_mask.shape:
+        #     blended_feathered = cv2.addWeighted(vis_region, 0.7, color_feathered_mask, 0.3, 0)
+        #     vis_frame[min_y:max_y, min_x:max_x] = blended_feathered
+
+        # Add labels
+        cv2.putText(
+            vis_frame,
+            "Lower Mouth Mask",
+            (min_x, min_y - 10),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.5,
+            (255, 255, 255),
+            1,
+        )
+        cv2.putText(
+            vis_frame,
+            "Feathered Mask",
+            (min_x, max_y + 20),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.5,
+            (255, 255, 255),
+            1,
+        )
+
+        return vis_frame
+    return frame
+
+
+def apply_mouth_area(
+    frame: np.ndarray,
+    mouth_cutout: np.ndarray,
+    mouth_box: tuple,
+    face_mask: np.ndarray,
+    mouth_polygon: np.ndarray,
+) -> np.ndarray:
+    min_x, min_y, max_x, max_y = mouth_box
+    box_width = max_x - min_x
+    box_height = max_y - min_y
+
+    if (
+        mouth_cutout is None
+        or box_width is None
+        or box_height is None
+        or face_mask is None
+        or mouth_polygon is None
+    ):
+        return frame
+
+    try:
+        resized_mouth_cutout = cv2.resize(mouth_cutout, (box_width, box_height))
+        roi = frame[min_y:max_y, min_x:max_x]
+
+        if roi.shape != resized_mouth_cutout.shape:
+            resized_mouth_cutout = cv2.resize(
+                resized_mouth_cutout, (roi.shape[1], roi.shape[0])
+            )
+
+        color_corrected_mouth = apply_color_transfer(resized_mouth_cutout, roi)
+
+        # Use the provided mouth polygon to create the mask
+        polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
+        adjusted_polygon = mouth_polygon - [min_x, min_y]
+        cv2.fillPoly(polygon_mask, [adjusted_polygon], 255)
+
+        # Apply feathering to the polygon mask
+        feather_amount = min(
+            30,
+            box_width // modules.globals.mask_feather_ratio,
+            box_height // modules.globals.mask_feather_ratio,
+        )
+        feathered_mask = cv2.GaussianBlur(
+            polygon_mask.astype(float), (0, 0), feather_amount
+        )
+        feathered_mask = feathered_mask / feathered_mask.max()
+
+        face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
+        combined_mask = feathered_mask * (face_mask_roi / 255.0)
+
+        combined_mask = combined_mask[:, :, np.newaxis]
+        blended = (
+            color_corrected_mouth * combined_mask + roi * (1 - combined_mask)
+        ).astype(np.uint8)
+
+        # Apply face mask to blended result
+        face_mask_3channel = (
+            np.repeat(face_mask_roi[:, :, np.newaxis], 3, axis=2) / 255.0
+        )
+        final_blend = blended * face_mask_3channel + roi * (1 - face_mask_3channel)
+
+        frame[min_y:max_y, min_x:max_x] = final_blend.astype(np.uint8)
+    except Exception as e:
+        pass
+
+    return frame
+
+
+def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
+    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
+    landmarks = face.landmark_2d_106
+    if landmarks is not None:
+        # Convert landmarks to int32
+        landmarks = landmarks.astype(np.int32)
+
+        # Extract facial features
+        right_side_face = landmarks[0:16]
+        left_side_face = landmarks[17:32]
+        right_eye = landmarks[33:42]
+        right_eye_brow = landmarks[43:51]
+        left_eye = landmarks[87:96]
+        left_eye_brow = landmarks[97:105]
+
+        # Calculate forehead extension
+        right_eyebrow_top = np.min(right_eye_brow[:, 1])
+        left_eyebrow_top = np.min(left_eye_brow[:, 1])
+        eyebrow_top = min(right_eyebrow_top, left_eyebrow_top)
+
+        face_top = np.min([right_side_face[0, 1], left_side_face[-1, 1]])
+        forehead_height = face_top - eyebrow_top
+        extended_forehead_height = int(forehead_height * 5.0)  # Extend by 50%
+
+        # Create forehead points
+        forehead_left = right_side_face[0].copy()
+        forehead_right = left_side_face[-1].copy()
+        forehead_left[1] -= extended_forehead_height
+        forehead_right[1] -= extended_forehead_height
+
+        # Combine all points to create the face outline
+        face_outline = np.vstack(
+            [
+                [forehead_left],
+                right_side_face,
+                left_side_face[
+                    ::-1
+                ],  # Reverse left side to create a continuous outline
+                [forehead_right],
+            ]
+        )
+
+        # Calculate padding
+        padding = int(
+            np.linalg.norm(right_side_face[0] - left_side_face[-1]) * 0.05
+        )  # 5% of face width
+
+        # Create a slightly larger convex hull for padding
+        hull = cv2.convexHull(face_outline)
+        hull_padded = []
+        for point in hull:
+            x, y = point[0]
+            center = np.mean(face_outline, axis=0)
+            direction = np.array([x, y]) - center
+            direction = direction / np.linalg.norm(direction)
+            padded_point = np.array([x, y]) + direction * padding
+            hull_padded.append(padded_point)
+
+        hull_padded = np.array(hull_padded, dtype=np.int32)
+
+        # Fill the padded convex hull
+        cv2.fillConvexPoly(mask, hull_padded, 255)
+
+        # Smooth the mask edges
+        mask = cv2.GaussianBlur(mask, (5, 5), 3)
+
+    return mask
+
+
+def apply_color_transfer(source, target):
+    """
+    Apply color transfer from target to source image
+    """
+    source = cv2.cvtColor(source, cv2.COLOR_BGR2LAB).astype("float32")
+    target = cv2.cvtColor(target, cv2.COLOR_BGR2LAB).astype("float32")
+
+    source_mean, source_std = cv2.meanStdDev(source)
+    target_mean, target_std = cv2.meanStdDev(target)
+
+    # Reshape mean and std to be broadcastable
+    source_mean = source_mean.reshape(1, 1, 3)
+    source_std = source_std.reshape(1, 1, 3)
+    target_mean = target_mean.reshape(1, 1, 3)
+    target_std = target_std.reshape(1, 1, 3)
+
+    # Perform the color transfer
+    source = (source - source_mean) * (target_std / source_std) + target_mean
+
+    return cv2.cvtColor(np.clip(source, 0, 255).astype("uint8"), cv2.COLOR_LAB2BGR)
@@ -3,7 +3,7 @@ import webbrowser
 import customtkinter as ctk
 from typing import Callable, Tuple
 import cv2
-from cv2_enumerate_cameras import enumerate_cameras
+from cv2_enumerate_cameras import enumerate_cameras  # Add this import
 from PIL import Image, ImageOps
 import time
 import json
@@ -28,7 +28,6 @@ from modules.utilities import (
 from modules.video_capture import VideoCapturer
 from modules.gettext import LanguageManager
 import platform
-from modules.fake_face_handler import cleanup_fake_face, refresh_fake_face

 if platform.system() == "Windows":
    from pygrabber.dshow_graph import FilterGraph
@@ -36,7 +35,7 @@ if platform.system() == "Windows":
 ROOT = None
 POPUP = None
 POPUP_LIVE = None
-ROOT_HEIGHT = 730
+ROOT_HEIGHT = 700
 ROOT_WIDTH = 600

 PREVIEW = None
@@ -79,12 +78,9 @@ target_label_dict_live = {}

 img_ft, vid_ft = modules.globals.file_types

-fake_face_switch = None
-fake_face_value = None
-

 def init(start: Callable[[], None], destroy: Callable[[], None], lang: str) -> ctk.CTk:
-    global ROOT, PREVIEW, _, fake_face_switch, fake_face_value
+    global ROOT, PREVIEW, _

    lang_manager = LanguageManager(lang)
    _ = lang_manager._
@@ -95,56 +91,51 @@ def init(start: Callable[[], None], destroy: Callable[[], None], lang: str) -> c


 def save_switch_states():
-    try:
-        states = {
-            "keep_fps": modules.globals.keep_fps,
-            "keep_audio": modules.globals.keep_audio,
-            "keep_frames": modules.globals.keep_frames,
-            "many_faces": modules.globals.many_faces,
-            "map_faces": modules.globals.map_faces,
-            "color_correction": modules.globals.color_correction,
-            "nsfw_filter": modules.globals.nsfw_filter,
-            "live_mirror": modules.globals.live_mirror,
-            "live_resizable": modules.globals.live_resizable,
-            "fp_ui": modules.globals.fp_ui,
-            "show_fps": modules.globals.show_fps,
-            "mouth_mask": modules.globals.mouth_mask,
-            "show_mouth_mask_box": modules.globals.show_mouth_mask_box,
-            "use_fake_face": modules.globals.use_fake_face
-        }
-        with open(get_config_path(), 'w') as f:
-            json.dump(states, f)
-    except Exception as e:
-        print(f"Error saving switch states: {str(e)}")
+    switch_states = {
+        "keep_fps": modules.globals.keep_fps,
+        "keep_audio": modules.globals.keep_audio,
+        "keep_frames": modules.globals.keep_frames,
+        "many_faces": modules.globals.many_faces,
+        "map_faces": modules.globals.map_faces,
+        "color_correction": modules.globals.color_correction,
+        "nsfw_filter": modules.globals.nsfw_filter,
+        "live_mirror": modules.globals.live_mirror,
+        "live_resizable": modules.globals.live_resizable,
+        "fp_ui": modules.globals.fp_ui,
+        "show_fps": modules.globals.show_fps,
+        "mouth_mask": modules.globals.mouth_mask,
+        "show_mouth_mask_box": modules.globals.show_mouth_mask_box,
+    }
+    with open("switch_states.json", "w") as f:
+        json.dump(switch_states, f)


 def load_switch_states():
    try:
-        if os.path.exists(get_config_path()):
-            with open(get_config_path(), 'r') as f:
-                states = json.load(f)
-                modules.globals.keep_fps = states.get("keep_fps", True)
-                modules.globals.keep_audio = states.get("keep_audio", True)
-                modules.globals.keep_frames = states.get("keep_frames", False)
-                modules.globals.many_faces = states.get("many_faces", False)
-                modules.globals.map_faces = states.get("map_faces", False)
-                modules.globals.color_correction = states.get("color_correction", False)
-                modules.globals.nsfw_filter = states.get("nsfw_filter", False)
-                modules.globals.live_mirror = states.get("live_mirror", False)
-                modules.globals.live_resizable = states.get("live_resizable", False)
-                modules.globals.fp_ui = states.get("fp_ui", {"face_enhancer": False})
-                modules.globals.show_fps = states.get("show_fps", False)
-                modules.globals.mouth_mask = states.get("mouth_mask", False)
-                modules.globals.show_mouth_mask_box = states.get(
-                    "show_mouth_mask_box", False
-                )
-                modules.globals.use_fake_face = False
-    except Exception as e:
-        print(f"Error loading switch states: {str(e)}")
+        with open("switch_states.json", "r") as f:
+            switch_states = json.load(f)
+        modules.globals.keep_fps = switch_states.get("keep_fps", True)
+        modules.globals.keep_audio = switch_states.get("keep_audio", True)
+        modules.globals.keep_frames = switch_states.get("keep_frames", False)
+        modules.globals.many_faces = switch_states.get("many_faces", False)
+        modules.globals.map_faces = switch_states.get("map_faces", False)
+        modules.globals.color_correction = switch_states.get("color_correction", False)
+        modules.globals.nsfw_filter = switch_states.get("nsfw_filter", False)
+        modules.globals.live_mirror = switch_states.get("live_mirror", False)
+        modules.globals.live_resizable = switch_states.get("live_resizable", False)
+        modules.globals.fp_ui = switch_states.get("fp_ui", {"face_enhancer": False})
+        modules.globals.show_fps = switch_states.get("show_fps", False)
+        modules.globals.mouth_mask = switch_states.get("mouth_mask", False)
+        modules.globals.show_mouth_mask_box = switch_states.get(
+            "show_mouth_mask_box", False
+        )
+    except FileNotFoundError:
+        # If the file doesn't exist, use default values
+        pass


 def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
-    global source_label, target_label, status_label, show_fps_switch, fake_face_switch, fake_face_value
+    global source_label, target_label, status_label, show_fps_switch

    load_switch_states()

@@ -159,28 +150,22 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
    )
    root.configure()
    root.protocol("WM_DELETE_WINDOW", lambda: destroy())
-    
-    # Add icon to the main window
-    icon_path = resolve_relative_path("deeplivecam.ico")
-    if os.path.exists(icon_path):
-        root.iconbitmap(icon_path)

-    # Image Selection Area (Top)
    source_label = ctk.CTkLabel(root, text=None)
-    source_label.place(relx=0.1, rely=0.05, relwidth=0.3, relheight=0.25)
+    source_label.place(relx=0.1, rely=0.1, relwidth=0.3, relheight=0.25)

    target_label = ctk.CTkLabel(root, text=None)
-    target_label.place(relx=0.6, rely=0.05, relwidth=0.3, relheight=0.25)
+    target_label.place(relx=0.6, rely=0.1, relwidth=0.3, relheight=0.25)

    select_face_button = ctk.CTkButton(
        root, text=_("Select a face"), cursor="hand2", command=lambda: select_source_path()
    )
-    select_face_button.place(relx=0.1, rely=0.35, relwidth=0.3, relheight=0.1)
+    select_face_button.place(relx=0.1, rely=0.4, relwidth=0.3, relheight=0.1)

    swap_faces_button = ctk.CTkButton(
        root, text="↔", cursor="hand2", command=lambda: swap_faces_paths()
    )
-    swap_faces_button.place(relx=0.45, rely=0.35, relwidth=0.1, relheight=0.1)
+    swap_faces_button.place(relx=0.45, rely=0.4, relwidth=0.1, relheight=0.1)

    select_target_button = ctk.CTkButton(
        root,
@@ -188,30 +173,60 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
        cursor="hand2",
        command=lambda: select_target_path(),
    )
-    select_target_button.place(relx=0.6, rely=0.35, relwidth=0.3, relheight=0.1)
+    select_target_button.place(relx=0.6, rely=0.4, relwidth=0.3, relheight=0.1)

-    # AI Generated Face controls
-    fake_face_value = ctk.BooleanVar(value=modules.globals.use_fake_face)
-    fake_face_switch = ctk.CTkSwitch(
+    keep_fps_value = ctk.BooleanVar(value=modules.globals.keep_fps)
+    keep_fps_checkbox = ctk.CTkSwitch(
        root,
-        text=_("Privacy Mode"),
-        variable=fake_face_value,
+        text=_("Keep fps"),
+        variable=keep_fps_value,
        cursor="hand2",
-        command=lambda: toggle_fake_face(fake_face_value)
+        command=lambda: (
+            setattr(modules.globals, "keep_fps", keep_fps_value.get()),
+            save_switch_states(),
+        ),
    )
-    fake_face_switch.place(relx=0.1, rely=0.50)
+    keep_fps_checkbox.place(relx=0.1, rely=0.6)

-    # Add refresh button next to the switch
-    refresh_face_button = ctk.CTkButton(
+    keep_frames_value = ctk.BooleanVar(value=modules.globals.keep_frames)
+    keep_frames_switch = ctk.CTkSwitch(
        root,
-        text="↻",
-        width=30,
+        text=_("Keep frames"),
+        variable=keep_frames_value,
        cursor="hand2",
-        command=lambda: refresh_fake_face_clicked()
+        command=lambda: (
+            setattr(modules.globals, "keep_frames", keep_frames_value.get()),
+            save_switch_states(),
+        ),
    )
-    refresh_face_button.place(relx=0.35, rely=0.50)
+    keep_frames_switch.place(relx=0.1, rely=0.65)
+
+    enhancer_value = ctk.BooleanVar(value=modules.globals.fp_ui["face_enhancer"])
+    enhancer_switch = ctk.CTkSwitch(
+        root,
+        text=_("Face Enhancer"),
+        variable=enhancer_value,
+        cursor="hand2",
+        command=lambda: (
+            update_tumbler("face_enhancer", enhancer_value.get()),
+            save_switch_states(),
+        ),
+    )
+    enhancer_switch.place(relx=0.1, rely=0.7)
+
+    keep_audio_value = ctk.BooleanVar(value=modules.globals.keep_audio)
+    keep_audio_switch = ctk.CTkSwitch(
+        root,
+        text=_("Keep audio"),
+        variable=keep_audio_value,
+        cursor="hand2",
+        command=lambda: (
+            setattr(modules.globals, "keep_audio", keep_audio_value.get()),
+            save_switch_states(),
+        ),
+    )
+    keep_audio_switch.place(relx=0.6, rely=0.6)

-    # Face Processing Options (Middle Left)
    many_faces_value = ctk.BooleanVar(value=modules.globals.many_faces)
    many_faces_switch = ctk.CTkSwitch(
        root,
@@ -223,7 +238,24 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    many_faces_switch.place(relx=0.1, rely=0.55)
+    many_faces_switch.place(relx=0.6, rely=0.65)
+
+    color_correction_value = ctk.BooleanVar(value=modules.globals.color_correction)
+    color_correction_switch = ctk.CTkSwitch(
+        root,
+        text=_("Fix Blueish Cam"),
+        variable=color_correction_value,
+        cursor="hand2",
+        command=lambda: (
+            setattr(modules.globals, "color_correction", color_correction_value.get()),
+            save_switch_states(),
+        ),
+    )
+    color_correction_switch.place(relx=0.6, rely=0.70)
+
+    #    nsfw_value = ctk.BooleanVar(value=modules.globals.nsfw_filter)
+    #    nsfw_switch = ctk.CTkSwitch(root, text='NSFW filter', variable=nsfw_value, cursor='hand2', command=lambda: setattr(modules.globals, 'nsfw_filter', nsfw_value.get()))
+    #    nsfw_switch.place(relx=0.6, rely=0.7)

    map_faces = ctk.BooleanVar(value=modules.globals.map_faces)
    map_faces_switch = ctk.CTkSwitch(
@@ -237,35 +269,8 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            close_mapper_window() if not map_faces.get() else None
        ),
    )
-    map_faces_switch.place(relx=0.1, rely=0.60)
+    map_faces_switch.place(relx=0.1, rely=0.75)

-    enhancer_value = ctk.BooleanVar(value=modules.globals.fp_ui["face_enhancer"])
-    enhancer_switch = ctk.CTkSwitch(
-        root,
-        text=_("Face Enhancer"),
-        variable=enhancer_value,
-        cursor="hand2",
-        command=lambda: (
-            update_tumbler("face_enhancer", enhancer_value.get()),
-            save_switch_states(),
-        ),
-    )
-    enhancer_switch.place(relx=0.1, rely=0.65)
-
-    keep_audio_value = ctk.BooleanVar(value=modules.globals.keep_audio)
-    keep_audio_switch = ctk.CTkSwitch(
-        root,
-        text=_("Keep audio"),
-        variable=keep_audio_value,
-        cursor="hand2",
-        command=lambda: (
-            setattr(modules.globals, "keep_audio", keep_audio_value.get()),
-            save_switch_states(),
-        ),
-    )
-    keep_audio_switch.place(relx=0.1, rely=0.70)
-
-    # Add show FPS switch right after keep_audio_switch
    show_fps_value = ctk.BooleanVar(value=modules.globals.show_fps)
    show_fps_switch = ctk.CTkSwitch(
        root,
@@ -277,9 +282,8 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    show_fps_switch.place(relx=0.1, rely=0.75)
+    show_fps_switch.place(relx=0.6, rely=0.75)

-    # Mask Switches (Middle Right - Top Section)
    mouth_mask_var = ctk.BooleanVar(value=modules.globals.mouth_mask)
    mouth_mask_switch = ctk.CTkSwitch(
        root,
@@ -288,117 +292,38 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
        cursor="hand2",
        command=lambda: setattr(modules.globals, "mouth_mask", mouth_mask_var.get()),
    )
-    mouth_mask_switch.place(relx=0.6, rely=0.50)
+    mouth_mask_switch.place(relx=0.1, rely=0.55)

-    # Add mouth mask size slider
-    mouth_mask_size_slider = ctk.CTkSlider(
-        root,
-        from_=0.5,
-        to=2.0,
-        number_of_steps=30,
-        command=lambda value: setattr(modules.globals, "mouth_mask_size", value)
-    )
-    mouth_mask_size_slider.set(modules.globals.mouth_mask_size)
-    mouth_mask_size_slider.place(relx=0.8, rely=0.50, relwidth=0.1)
-
-    eyes_mask_var = ctk.BooleanVar(value=modules.globals.eyes_mask)
-    eyes_mask_switch = ctk.CTkSwitch(
-        root,
-        text=_("Eyes Mask"),
-        variable=eyes_mask_var,
-        cursor="hand2",
-        command=lambda: setattr(modules.globals, "eyes_mask", eyes_mask_var.get()),
-    )
-    eyes_mask_switch.place(relx=0.6, rely=0.55)
-
-    # Add eyes mask size slider
-    eyes_mask_size_slider = ctk.CTkSlider(
-        root,
-        from_=0.5,
-        to=2.0,
-        number_of_steps=30,
-        command=lambda value: setattr(modules.globals, "eyes_mask_size", value)
-    )
-    eyes_mask_size_slider.set(modules.globals.eyes_mask_size)
-    eyes_mask_size_slider.place(relx=0.8, rely=0.55, relwidth=0.1)
-
-    eyebrows_mask_var = ctk.BooleanVar(value=modules.globals.eyebrows_mask)
-    eyebrows_mask_switch = ctk.CTkSwitch(
-        root,
-        text=_("Eyebrows Mask"),
-        variable=eyebrows_mask_var,
-        cursor="hand2",
-        command=lambda: setattr(modules.globals, "eyebrows_mask", eyebrows_mask_var.get()),
-    )
-    eyebrows_mask_switch.place(relx=0.6, rely=0.60)
-
-    # Add eyebrows mask size slider
-    eyebrows_mask_size_slider = ctk.CTkSlider(
-        root,
-        from_=0.5,
-        to=2.0,
-        number_of_steps=30,
-        command=lambda value: setattr(modules.globals, "eyebrows_mask_size", value)
-    )
-    eyebrows_mask_size_slider.set(modules.globals.eyebrows_mask_size)
-    eyebrows_mask_size_slider.place(relx=0.8, rely=0.60, relwidth=0.1)
-
-    # Box Visualization Switches (Middle Right - Bottom Section)
    show_mouth_mask_box_var = ctk.BooleanVar(value=modules.globals.show_mouth_mask_box)
    show_mouth_mask_box_switch = ctk.CTkSwitch(
        root,
-        text=_("Show Mouth Box"),
+        text=_("Show Mouth Mask Box"),
        variable=show_mouth_mask_box_var,
        cursor="hand2",
        command=lambda: setattr(
            modules.globals, "show_mouth_mask_box", show_mouth_mask_box_var.get()
        ),
    )
-    show_mouth_mask_box_switch.place(relx=0.6, rely=0.65)
+    show_mouth_mask_box_switch.place(relx=0.6, rely=0.55)

-    show_eyes_mask_box_var = ctk.BooleanVar(value=modules.globals.show_eyes_mask_box)
-    show_eyes_mask_box_switch = ctk.CTkSwitch(
-        root,
-        text=_("Show Eyes Box"),
-        variable=show_eyes_mask_box_var,
-        cursor="hand2",
-        command=lambda: setattr(
-            modules.globals, "show_eyes_mask_box", show_eyes_mask_box_var.get()
-        ),
-    )
-    show_eyes_mask_box_switch.place(relx=0.6, rely=0.70)
-
-    show_eyebrows_mask_box_var = ctk.BooleanVar(value=modules.globals.show_eyebrows_mask_box)
-    show_eyebrows_mask_box_switch = ctk.CTkSwitch(
-        root,
-        text=_("Show Eyebrows Box"),
-        variable=show_eyebrows_mask_box_var,
-        cursor="hand2",
-        command=lambda: setattr(
-            modules.globals, "show_eyebrows_mask_box", show_eyebrows_mask_box_var.get()
-        ),
-    )
-    show_eyebrows_mask_box_switch.place(relx=0.6, rely=0.75)
-
-    # Main Control Buttons (Bottom)
    start_button = ctk.CTkButton(
        root, text=_("Start"), cursor="hand2", command=lambda: analyze_target(start, root)
    )
    start_button.place(relx=0.15, rely=0.80, relwidth=0.2, relheight=0.05)

-    preview_button = ctk.CTkButton(
-        root, text=_("Preview"), cursor="hand2", command=lambda: toggle_preview()
-    )
-    preview_button.place(relx=0.4, rely=0.80, relwidth=0.2, relheight=0.05)
-
    stop_button = ctk.CTkButton(
        root, text=_("Destroy"), cursor="hand2", command=lambda: destroy()
    )
-    stop_button.place(relx=0.65, rely=0.80, relwidth=0.2, relheight=0.05)
+    stop_button.place(relx=0.4, rely=0.80, relwidth=0.2, relheight=0.05)

-    # Camera Section (Bottom)
+    preview_button = ctk.CTkButton(
+        root, text=_("Preview"), cursor="hand2", command=lambda: toggle_preview()
+    )
+    preview_button.place(relx=0.65, rely=0.80, relwidth=0.2, relheight=0.05)
+
+    # --- Camera Selection ---
    camera_label = ctk.CTkLabel(root, text=_("Select Camera:"))
-    camera_label.place(relx=0.1, rely=0.87, relwidth=0.2, relheight=0.05)
+    camera_label.place(relx=0.1, rely=0.86, relwidth=0.2, relheight=0.05)

    available_cameras = get_available_cameras()
    camera_indices, camera_names = available_cameras
@@ -417,7 +342,7 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            root, variable=camera_variable, values=camera_names
        )

-    camera_optionmenu.place(relx=0.35, rely=0.87, relwidth=0.25, relheight=0.05)
+    camera_optionmenu.place(relx=0.35, rely=0.86, relwidth=0.25, relheight=0.05)

    live_button = ctk.CTkButton(
        root,
@@ -437,16 +362,16 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            else "disabled"
        ),
    )
-    live_button.place(relx=0.65, rely=0.87, relwidth=0.2, relheight=0.05)
+    live_button.place(relx=0.65, rely=0.86, relwidth=0.2, relheight=0.05)
+    # --- End Camera Selection ---

-    # Status and Links (Bottom)
    status_label = ctk.CTkLabel(root, text=None, justify="center")
-    status_label.place(relx=0.1, rely=0.92, relwidth=0.8)
+    status_label.place(relx=0.1, rely=0.9, relwidth=0.8)

    donate_label = ctk.CTkLabel(
        root, text="Deep Live Cam", justify="center", cursor="hand2"
    )
-    donate_label.place(relx=0.1, rely=0.94, relwidth=0.8)
+    donate_label.place(relx=0.1, rely=0.95, relwidth=0.8)
    donate_label.configure(
        text_color=ctk.ThemeManager.theme.get("URL").get("text_color")
    )
@@ -472,7 +397,7 @@ def analyze_target(start: Callable[[], None], root: ctk.CTk):
        return

    if modules.globals.map_faces:
-        modules.globals.souce_target_map = []
+        modules.globals.source_target_map = []

        if is_image(modules.globals.target_path):
            update_status("Getting unique faces")
@@ -481,8 +406,8 @@ def analyze_target(start: Callable[[], None], root: ctk.CTk):
            update_status("Getting unique faces")
            get_unique_faces_from_target_video()

-        if len(modules.globals.souce_target_map) > 0:
-            create_source_target_popup(start, root, modules.globals.souce_target_map)
+        if len(modules.globals.source_target_map) > 0:
+            create_source_target_popup(start, root, modules.globals.source_target_map)
        else:
            update_status("No faces found in target")
    else:
@@ -504,7 +429,7 @@ def create_source_target_popup(
            POPUP.destroy()
            select_output_path(start)
        else:
-            update_pop_status("Atleast 1 source with target is required!")
+            update_pop_status("At least 1 source with target is required!")

    scrollable_frame = ctk.CTkScrollableFrame(
        POPUP, width=POPUP_SCROLL_WIDTH, height=POPUP_SCROLL_HEIGHT
@@ -564,7 +489,7 @@ def update_popup_source(
    global source_label_dict

    source_path = ctk.filedialog.askopenfilename(
-        title=_("select an source image"),
+        title=_("select a source image"),
        initialdir=RECENT_DIRECTORY_SOURCE,
        filetypes=[img_ft],
    )
@@ -619,11 +544,6 @@ def create_preview(parent: ctk.CTkToplevel) -> ctk.CTkToplevel:
    preview.configure()
    preview.protocol("WM_DELETE_WINDOW", lambda: toggle_preview())
    preview.resizable(width=True, height=True)
-    
-    # Add icon to the preview window
-    icon_path = resolve_relative_path("deeplivecam.ico")
-    if os.path.exists(icon_path):
-        preview.iconbitmap(icon_path)

    preview_label = ctk.CTkLabel(preview, text=None)
    preview_label.pack(fill="both", expand=True)
@@ -660,19 +580,15 @@ def update_tumbler(var: str, value: bool) -> None:


 def select_source_path() -> None:
-    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft, fake_face_switch, fake_face_value
+    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft

    PREVIEW.withdraw()
    source_path = ctk.filedialog.askopenfilename(
-        title=_("select an source image"),
+        title=_("select a source image"),
        initialdir=RECENT_DIRECTORY_SOURCE,
        filetypes=[img_ft],
    )
    if is_image(source_path):
-        modules.globals.use_fake_face = False
-        fake_face_value.set(False)
-        cleanup_fake_face()
-        
        modules.globals.source_path = source_path
        RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
        image = render_image_preview(modules.globals.source_path, (200, 200))
@@ -711,7 +627,7 @@ def select_target_path() -> None:

    PREVIEW.withdraw()
    target_path = ctk.filedialog.askopenfilename(
-        title=_("select an target image or video"),
+        title=_("select a target image or video"),
        initialdir=RECENT_DIRECTORY_TARGET,
        filetypes=[img_ft, vid_ft],
    )
@@ -780,17 +696,21 @@ def check_and_ignore_nsfw(target, destroy: Callable = None) -> bool:


 def fit_image_to_size(image, width: int, height: int):
-    if width is None and height is None:
+    if width is None or height is None or width <= 0 or height <= 0:
        return image
    h, w, _ = image.shape
    ratio_h = 0.0
    ratio_w = 0.0
-    if width > height:
-        ratio_h = height / h
-    else:
-        ratio_w = width / w
-    ratio = max(ratio_w, ratio_h)
-    new_size = (int(ratio * w), int(ratio * h))
+    ratio_w = width / w
+    ratio_h = height / h
+    # Use the smaller ratio to ensure the image fits within the given dimensions
+    ratio = min(ratio_w, ratio_h)
+    
+    # Compute new dimensions, ensuring they're at least 1 pixel
+    new_width = max(1, int(ratio * w))
+    new_height = max(1, int(ratio * h))
+    new_size = (new_width, new_height)
+
    return cv2.resize(image, dsize=new_size)


@@ -845,7 +765,8 @@ def update_preview(frame_number: int = 0) -> None:
                modules.globals.frame_processors
        ):
            temp_frame = frame_processor.process_frame(
-                get_one_face(cv2.imread(modules.globals.source_path)), temp_frame)
+                get_one_face(cv2.imread(modules.globals.source_path)), temp_frame
+            )
        image = Image.fromarray(cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB))
        image = ImageOps.contain(
            image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS
@@ -870,9 +791,9 @@ def webcam_preview(root: ctk.CTk, camera_index: int):
            return
        create_webcam_preview(camera_index)
    else:
-        modules.globals.souce_target_map = []
+        modules.globals.source_target_map = []
        create_source_target_popup_for_webcam(
-            root, modules.globals.souce_target_map, camera_index
+            root, modules.globals.source_target_map, camera_index
        )


@@ -1187,7 +1108,7 @@ def update_webcam_source(
    global source_label_dict_live

    source_path = ctk.filedialog.askopenfilename(
-        title=_("select an source image"),
+        title=_("select a source image"),
        initialdir=RECENT_DIRECTORY_SOURCE,
        filetypes=[img_ft],
    )
@@ -1239,7 +1160,7 @@ def update_webcam_target(
    global target_label_dict_live

    target_path = ctk.filedialog.askopenfilename(
-        title=_("select an target image"),
+        title=_("select a target image"),
        initialdir=RECENT_DIRECTORY_SOURCE,
        filetypes=[img_ft],
    )
@@ -1283,42 +1204,3 @@ def update_webcam_target(
        else:
            update_pop_live_status("Face could not be detected in last upload!")
        return map
-
-def toggle_fake_face(switch_var: ctk.BooleanVar) -> None:
-    modules.globals.use_fake_face = switch_var.get()
-    if modules.globals.use_fake_face:
-        if not modules.globals.fake_face_path:
-            if refresh_fake_face():
-                modules.globals.source_path = modules.globals.fake_face_path
-                # Update the source image preview
-                image = render_image_preview(modules.globals.source_path, (200, 200))
-                source_label.configure(image=image)
-    else:
-        cleanup_fake_face()
-        # Clear the source image preview
-        source_label.configure(image=None)
-        modules.globals.source_path = None
-
-def refresh_fake_face_clicked() -> None:
-    """Handle refresh button click to update fake face during live preview"""
-    if not modules.globals.use_fake_face:
-        # If privacy mode is off, turn it on first
-        modules.globals.use_fake_face = True
-        fake_face_value.set(True)
-        
-    if refresh_fake_face():
-        modules.globals.source_path = modules.globals.fake_face_path
-        # Update the source image preview
-        image = render_image_preview(modules.globals.source_path, (200, 200))
-        source_label.configure(image=image)
-        
-        # Force reload of frame processors to use new source face
-        global FRAME_PROCESSORS_MODULES
-        FRAME_PROCESSORS_MODULES = []
-        frame_processors = get_frame_processors_modules(modules.globals.frame_processors)
-
-def get_config_path() -> str:
-    """Get the path to the config file"""
-    config_dir = os.path.join(os.path.expanduser("~"), ".deep-live-cam")
-    os.makedirs(config_dir, exist_ok=True)
-    return os.path.join(config_dir, "switch_states.json")
@@ -1,24 +1,21 @@
--extra-index-url https://download.pytorch.org/whl/cu118
+--extra-index-url https://download.pytorch.org/whl/cu128

 numpy>=1.23.5,<2
+typing-extensions>=4.8.0
 opencv-python==4.10.0.84
 cv2_enumerate_cameras==1.1.15
-onnx==1.16.0
+onnx==1.18.0
 insightface==0.7.3
 psutil==5.9.8
 tk==0.1.0
 customtkinter==5.2.2
 pillow==11.1.0
-torch==2.0.1+cu118; sys_platform != 'darwin'
-torch==2.0.1; sys_platform == 'darwin'
-torchvision==0.15.2+cu118; sys_platform != 'darwin'
-torchvision==0.15.2; sys_platform == 'darwin'
+torch; sys_platform != 'darwin'
+torch==2.5.1; sys_platform == 'darwin'
+torchvision; sys_platform != 'darwin'
+torchvision==0.20.1; sys_platform == 'darwin'
 onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64'
-onnxruntime-gpu==1.16.3; sys_platform != 'darwin'
-tensorflow==2.12.1; sys_platform != 'darwin'
+onnxruntime-gpu==1.22.0; sys_platform != 'darwin'
+tensorflow; sys_platform != 'darwin'
 opennsfw2==0.10.2
-protobuf==4.23.2
-tqdm==4.66.4
-gfpgan==1.3.8
-tkinterdnd2==0.4.2
-pygrabber==0.2
+protobuf==4.25.1
Author	SHA1	Message	Date
Kenneth Estanislao	d0d90ecc03	Creating a fallback and switching of models Models switch depending on the execution provider	2025-08-02 02:56:20 +08:00
Kenneth Estanislao	2b70131e6a	Update requirements.txt	2025-07-09 17:19:26 +08:00
Kenneth Estanislao	fc86365a90	Delete .yml	2025-07-02 18:37:10 +08:00
Kenneth Estanislao	1dd0e8e509	Create .yml	2025-07-02 18:29:32 +08:00
Kenneth Estanislao	4e0ff540f0	Update requirements.txt faster and better requirements	2025-07-02 04:08:26 +08:00
Kenneth Estanislao	f0fae811d8	Update requirements.txt should improve the performance by 30%	2025-06-29 15:03:35 +08:00
Kenneth Estanislao	42687f5bd9	Update README.md	2025-06-29 14:58:13 +08:00
Kenneth Estanislao	9086072b8e	Update README.md	2025-06-23 17:06:34 +08:00
KRSHH	12fda0a3ed	fix formatting	2025-06-17 18:42:36 +05:30
KRSHH	d963430854	Add techlinked link	2025-06-17 18:42:10 +05:30
KRSHH	5855d15c09	Removed outdated links	2025-06-17 18:35:24 +05:30
KRSHH	fcc73d0add	Update Download Button	2025-06-16 14:37:41 +05:30
KRSHH	8d4a386a27	Upgrade prebuilt to 2.1	2025-06-15 22:19:49 +05:30
Chittimalla Krish	b98c5234d8	Revert `8bdc14a`	2025-06-15 20:08:43 +05:30
Chittimalla Krish	8bdc14a789	Update prebuilt version	2025-06-15 17:50:38 +05:30
Kenneth Estanislao	f121083bc8	Update README.md RTX 50xx support	2025-06-15 02:22:00 +08:00
Kenneth Estanislao	745d449ca6	Update README.md support for RTX 50xx	2025-06-09 00:34:26 +08:00
Kenneth Estanislao	ec6d7d2995	Merge pull request #1327 from zjy-dev/fix/add-cudnn-installation-docs docs: add cuDNN installation guidance for CUDA	2025-06-01 12:05:04 +08:00
zjy-dev	e791f2f18a	docs: add cuDNN installation guidance for CUDA	2025-06-01 00:40:29 +08:00
KRSHH	3795e41fd7	Merge pull request #1307 from Neurofix/main ADD locale ko.json	2025-05-28 08:09:02 +05:30
KRSHH	ab8a1c82c1	Merge pull request #1310 from Jocund96/main Add Russian locale file: ru.json	2025-05-26 02:34:03 +05:30
Jasurbek Odilov	e1842ae0ba	Merge pull request #1 from Jocund96/Jocund96-patch-1 Add locale Russian	2025-05-25 21:28:57 +02:00
Jasurbek Odilov	989106e914	Add files via upload	2025-05-25 21:28:07 +02:00
Neurofix	de27fb8a81	Create ko.json Add korean	2025-05-25 14:49:54 +09:00
KRSHH	28109e93bb	Merge pull request #1297 from j-hewett/main Add Spanish translation	2025-05-21 21:44:03 +05:30
Jonah Hewett	fc312516e3	Add Spanish translation	2025-05-21 16:35:37 +01:00
Chou Chamnan	72049f3e91	Add khmer translation (#1291 ) * Add khmer language * Fix khmer language --------- Co-authored-by: Chamnan dev	2025-05-18 23:03:53 +05:30
inwchamp1337	6cb5de01f8	Added a Thai translation (#1284 ) * Added a Thai translation * Update th.json	2025-05-18 23:03:19 +05:30
KRSHH	0bcf340217	Merge pull request #1281 from Giovannapls/add/pt-br-translate [Added] pt br translate	2025-05-18 23:01:00 +05:30
Giovanna	994a63c546	[Added] pt br translate	2025-05-14 19:24:13 -03:00
Kenneth Estanislao	d5a3fb0c47	Merge pull request #1268 from jiacheng-0/main Update __init__.py	2025-05-13 00:57:09 +08:00
Teo Jia Cheng	9690070399	Update __init__.py	2025-05-13 00:14:49 +08:00
Kenneth Estanislao	f3e83b985c	Merge pull request #1210 from KunjShah01/main Update __init__.py	2025-05-12 15:14:58 +08:00
Kenneth Estanislao	e3e3638b79	Merge pull request #1232 from gboeer/patch-1 Add german localization and fix minor typos	2025-05-12 15:14:32 +08:00
VilkkuKoo	4a7874a968	Added a Finnish translation (#1255 ) * Added finnish translations * Fixed a typo	2025-05-11 03:58:53 +05:30
Gordon Böer	75122da389	Create german localization	2025-05-07 13:30:22 +02:00
Gordon Böer	7063bba4b3	fix typos in zh.json	2025-05-07 13:24:54 +02:00
Gordon Böer	bdbd7dcfbc	fix typos in ui.py	2025-05-07 13:23:31 +02:00
KUNJ SHAH	a64940def7	update	2025-05-05 13:19:46 +00:00
KUNJ SHAH	fe4a87e8f2	update	2025-05-05 13:19:29 +00:00
KUNJ SHAH	9ecd2dab83	changes	2025-05-05 13:10:00 +00:00
KUNJ SHAH	c9f36eb350	Update __init__.py	2025-05-05 18:29:44 +05:30
Kenneth Estanislao	b1f610d432	Update README.md	2025-05-05 08:30:44 +08:00
KRSHH	d86c36dc47	Change Download URL	2025-05-04 23:44:01 +05:30
Kenneth Estanislao	532e7c05ee	Merge pull request #1155 from killerlux/patch-1 Added commands for linux	2025-05-03 10:16:02 +08:00
KRSHH	267a273cb2	Download for windows	2025-05-01 22:12:55 +05:30
KRSHH	938aa9eaf1	Delete media/download.png	2025-05-01 22:11:21 +05:30
KRSHH	37bac27302	Add files via upload	2025-05-01 22:10:52 +05:30
killerlux	84836932e6	Added cmomands for linux	2025-04-30 23:09:12 +02:00
Kenneth Estanislao	e879d2ca64	Merge pull request #1094 from NeuroDonu/main fix core.py for face_enhancer and add TRT support in face_enhancer	2025-04-30 22:28:46 +08:00
Kenneth Estanislao	181144ce33	Update requirements.txt	2025-04-20 03:02:23 +08:00
NeuroDonu	890beb0eae	fix & add trt support	2025-04-19 16:03:49 +03:00
NeuroDonu	75b5b096d6	fix	2025-04-19 16:03:24 +03:00
Kenneth Estanislao	40e47a469c	Update requirements.txt	2025-04-19 03:41:00 +08:00
KRSHH	874abb4e59	v2 prebuilt	2025-04-17 09:34:10 +05:30
Kenneth Estanislao	18b259da70	Update requirements.txt improves speed by 10 to 40%	2025-04-17 02:44:24 +08:00
Kenneth Estanislao	01900dcfb5	Revert "Update metadata.py" This reverts commit `90d5c28542`.	2025-04-17 02:39:05 +08:00
Kenneth Estanislao	07e30fe781	Revert "Update face_swapper.py" This reverts commit `104d8cf4d6`.	2025-04-17 02:03:34 +08:00
Kenneth Estanislao	3dda4f2179	Update requirements.txt	2025-04-14 17:45:07 +08:00
Kenneth Estanislao	71735e4f60	Update requirements.txt update requirements.txt	2025-04-13 03:36:51 +08:00
Kenneth Estanislao	90d5c28542	Update metadata.py - 40% faster than 1.8 - compatible with 50xx GPU - onnxruntime 1.21	2025-04-13 03:34:10 +08:00
Kenneth Estanislao	104d8cf4d6	Update face_swapper.py compatibility with inswapper 1.21	2025-04-13 01:13:40 +08:00
KRSHH	ac3696b69d	remove prebuilt	2025-04-04 16:02:28 +05:30
Kenneth Estanislao	76fb209e6c	Update README.md	2025-03-29 03:28:22 +08:00
Kenneth Estanislao	2dcd552c4b	Update README.md	2025-03-29 03:23:49 +08:00
Kenneth Estanislao	66248a37b4	Merge pull request #990 from wpoPR/pr/improve-macos-installation-instructions improve macOS Apple Silicon installation instructions	2025-03-24 18:26:28 +08:00
KRSHH	aa9b7ed3b6	Add Tips and Tricks to README	2025-03-22 19:59:40 +05:30
Wesley Oliveira	51a4246050	adding uninstalling conflict python versions follow sourcery-ai and add a note about uninstalling conflicting Python versions if users encounter issues.	2025-03-21 12:37:21 -03:00
Wesley Oliveira	3f1c072fac	improve macOS Apple Silicon installation instructions Followed the `README` but ran into some errors running it locally. Made a few tweaks and got it working on my M3 PRO. Found this PR (Failing to run on Apple Silicon Mac M3) and thought improving the instructions might help others. Hope this helps! great tool guys, thx a lot	2025-03-20 16:47:01 -03:00
KRSHH	f91f9203e7	Remove Mac Edition Temporarily	2025-03-19 03:00:32 +05:30
Kenneth Estanislao	80477676b4	Merge pull request #980 from aaddyy227/main Fix face swapping crash due to None face embeddings	2025-03-16 00:03:39 +08:00
Adrian Zimbran	c728994e6b	fixed import and log message	2025-03-10 23:41:28 +02:00
Adrian Zimbran	65da3be2a4	Fix face swapping crash due to None face embeddings - Add explicit checks for face detection results (source and target faces). - Handle cases when face embeddings are not available, preventing AttributeError. - Provide meaningful log messages for easier debugging in future scenarios.	2025-03-10 23:31:56 +02:00
Kenneth Estanislao	390b88216b	Update README.md	2025-02-14 17:33:33 +08:00
Kenneth Estanislao	dabaa64695	Merge pull request #932 from harmeetsingh-work/patch-1 Update requirements.txt	2025-02-12 15:21:27 +08:00
Harmeet Singh	1fad1cd43a	Update requirements.txt Made changes for apple silicon. Or getting ERROR: Could not find a version that satisfies the requirement torch==2.5.1+cu118 (from versions: 1.11.0, 1.12.0, 1.12.1, 1.13.0, 1.13.1, 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.1.2, 2.2.0, 2.2.1, 2.2.2, 2.3.0, 2.3.1, 2.4.0, 2.4.1, 2.5.0, 2.5.1, 2.6.0) ERROR: No matching distribution found for torch==2.5.1+cu118	2025-02-11 18:44:23 +05:30
Kenneth Estanislao	2f67e2f159	Update requirements.txt	2025-02-09 14:17:49 +08:00
Kenneth Estanislao	a3af249ea6	Update requirements.txt	2025-02-07 19:31:02 +08:00
Kenneth Estanislao	5bc3ada632	Update requirements.txt	2025-02-06 15:37:55 +08:00
KRSHH	650e89eb21	Reduced File Size	2025-02-06 10:40:32 +05:30
Kenneth Estanislao	4d2aea37b7	Update requirements.txt	2025-02-06 00:43:20 +08:00
Kenneth Estanislao	28c4b34db1	Merge pull request #911 from nimishgautam/main Fix cv2 size errors on first run in ui.py	2025-02-05 12:51:39 +08:00
Kenneth Estanislao	49e8f78513	Merge pull request #913 from soulee-dev/main fix: typo souce_target_map → source_target_map	2025-02-05 12:18:48 +08:00
Kenneth Estanislao	d753f5d4b0	Merge pull request #917 from carpusherw/patch-1 Fix requirements.txt	2025-02-05 12:17:42 +08:00
KRSHH	4fb69476d8	Change img dimensions	2025-02-05 12:16:08 +08:00
carpusherw	f3adfd194d	Fix requirements.txt	2025-02-05 12:16:08 +08:00
Kenneth Estanislao	e5f04cf917	Revert "Update requirements.txt" This reverts commit `d45dedc9a6`.	2025-02-05 12:08:19 +08:00
Kenneth Estanislao	67394a3157	Revert "Update requirements.txt" This reverts commit `f82cebf86e`.	2025-02-05 12:08:10 +08:00
carpusherw	186d155e1b	Fix requirements.txt	2025-02-05 09:17:11 +08:00
KRSHH	87081e78d0	Fixed typo	2025-02-04 21:20:54 +05:30
KRSHH	f79373d4db	Updated Features Section	2025-02-04 21:08:36 +05:30
Soul Lee	513e413956	fix: typo souce_target_map → source_target_map	2025-02-03 20:33:44 +09:00
Kenneth Estanislao	f82cebf86e	Update requirements.txt	2025-02-03 18:03:27 +08:00
Kenneth Estanislao	d45dedc9a6	Update requirements.txt	2025-02-03 16:38:18 +08:00
Kenneth Estanislao	2d489b57ec	Update README.md	2025-02-03 13:13:56 +08:00
Nimish Gåtam	ccc04983cf	Update ui.py removed unnecessary code as per AI code review (which is a thing now because of course it is)	2025-02-01 12:38:37 +01:00
Nimish Gåtam	2506c5a261	Update ui.py Some checks for first run when models are missing, so it doesn't error out with inv_scale_x > 0 in cv2	2025-02-01 11:52:49 +01:00
Kenneth Estanislao	e862ff1456	Update requirements.txt updated from CUDA 11.8 to CUDA 12.1	2025-02-01 12:21:55 +08:00