size

update branch
2025-02-03 20:59:06 +05:30 · 2025-01-31 22:32:47 +05:30 · 2025-01-30 20:20:04 +05:30 · 2025-01-30 20:14:16 +05:30 · 2025-01-30 20:04:31 +05:30 · 2025-01-30 19:58:15 +05:30
26 changed files with 1186 additions and 1103 deletions
@@ -0,0 +1 @@
+3.10.0
@@ -30,13 +30,18 @@ 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)

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

-##### 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.
+  <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" />
 
-###### 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)
@@ -44,7 +49,7 @@ 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 in real-time
+## Features & Uses - Everything is real-time

 ### Mouth Mask

@@ -80,7 +85,7 @@ 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"> 
@@ -88,17 +93,10 @@ 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 quickstart version.**
+**Please be aware that the installation requires technical skills and is not for beginners. Consider downloading the prebuilt version.**

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

 **1. Set up Your Platform**

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

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

 **3. Download the Models**
@@ -133,52 +130,14 @@ 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:**
-
-Apple Silicon (M1/M2/M3) requires specific setup:
+**For macOS:** Install or upgrade the `python-tk` package:

 ```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).
@@ -187,16 +146,12 @@ pip install -r requirements.txt

 **CUDA Execution Provider (Nvidia)**

-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:
+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:

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

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

 **CoreML Execution Provider (Apple Silicon)**

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

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

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

 ```bash
-python3.10 run.py --execution-provider coreml
+python 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==1.21.0
+pip install onnxruntime-coreml==1.13.1
 ```

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

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

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

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

 2. Usage:
@@ -284,6 +219,7 @@ pip install onnxruntime-openvino==1.21.0
 ```bash
 python run.py --execution-provider openvino
 ```
+
 </details>

 ## Usage
@@ -347,8 +283,6 @@ 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

@@ -379,3 +313,5 @@ 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>
+
+
@@ -1,46 +0,0 @@
-{
-    "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."
-}
@@ -1,46 +0,0 @@
-{
-    "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."
-}
@@ -1,46 +0,0 @@
-{
-    "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."
-}
@@ -1,45 +0,0 @@
-{
-    "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។"
-}
@@ -1,45 +0,0 @@
-{
-    "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."
-}
@@ -1,46 +0,0 @@
-{
-    "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."
-}
@@ -1,45 +0,0 @@
-{
-    "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."
-}
@@ -1,45 +0,0 @@
-{
-    "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 a source image": "选择一个源图像",
+    "select an source image": "选择一个源图像",
    "Preview": "预览",
-    "select a target image or video": "选择一个目标图像或视频",
+    "select an 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 a target image": "选择一个目标图像",
+    "select an 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",
-    "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！",
+    "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！",
    "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。"
-}
+}
@@ -1,18 +0,0 @@
-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
@@ -20,6 +20,7 @@ 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
@@ -35,9 +36,7 @@ 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)
@@ -65,9 +64,9 @@ 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 = args.keep_fps
+    modules.globals.keep_fps = True
+    modules.globals.keep_frames = True
    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
@@ -241,6 +240,7 @@ 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.source_target_map:
+    for map in modules.globals.souce_target_map:
        if "source" in map and "target" in map:
            return True
    return False

 def default_source_face() -> Any:
-    for map in modules.globals.source_target_map:
+    for map in modules.globals.souce_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.source_target_map:
+    for map in modules.globals.souce_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.source_target_map) > 0:
-            max_id = max(modules.globals.source_target_map, key=lambda x: x['id'])['id']
+        if len(modules.globals.souce_target_map) > 0:
+            max_id = max(modules.globals.souce_target_map, key=lambda x: x['id'])['id']

-        modules.globals.source_target_map.append({
+        modules.globals.souce_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.source_target_map = []
+        modules.globals.souce_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.source_target_map.append({
+            modules.globals.souce_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.source_target_map = []
+        modules.globals.souce_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.source_target_map.append({
+            modules.globals.souce_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.source_target_map[i]['target_faces_in_frame'] = temp
+            modules.globals.souce_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.source_target_map:
+    for map in modules.globals.souce_target_map:
        best_face = None
        best_frame = None
        for frame in map['target_faces_in_frame']:
@@ -0,0 +1,120 @@
+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")),
 ]

-source_target_map = []
+souce_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  # New global variable for color correction toggle
+color_correction = False
 nsfw_filter = False
 video_encoder = None
 video_quality = None
@@ -41,3 +41,12 @@ 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 = '1.8.1'
+version = '1.8'
 edition = 'GitHub Edition'
@@ -42,29 +42,18 @@ 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 current_processor_names:
+        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:
            try:
                frame_processor_module = load_frame_processor_module(frame_processor)
-                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}")
+                FRAME_PROCESSORS_MODULES.remove(frame_processor_module)
+                modules.globals.frame_processors.remove(frame_processor)
+            except:
+                pass

 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:
@@ -48,17 +48,6 @@ 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

@@ -66,26 +55,16 @@ def get_face_enhancer() -> Any:
        if FACE_ENHANCER is None:
            model_path = os.path.join(models_dir, "GFPGANv1.4.pth")
            
-            selected_device = None
-            device_priority = []
+            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]

-            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


@@ -0,0 +1,634 @@
+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 
@@ -4,7 +4,6 @@ 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
@@ -15,6 +14,14 @@ 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
@@ -28,14 +35,12 @@ models_dir = os.path.join(


 def pre_check() -> bool:
-    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"
-
+    download_directory_path = abs_dir
    conditional_download(
        download_directory_path,
-        [model_url],
+        [
+            "https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx"
+        ],
    )
    return True

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

    with THREAD_LOCK:
        if FACE_SWAPPER is None:
-            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)
+            model_path = os.path.join(models_dir, "inswapper_128_fp16.onnx")
            FACE_SWAPPER = insightface.model_zoo.get_model(
                model_path, providers=modules.globals.execution_providers
            )
@@ -80,24 +82,62 @@ 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 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
+        # 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
        )

        if modules.globals.show_mouth_mask_box:
-            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
+            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"
            )

    return swapped_frame
@@ -111,30 +151,24 @@ 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:
-                if source_face and target_face:
-                    temp_frame = swap_face(source_face, target_face, temp_frame)
-                else:
-                    print("Face detection failed for target/source.")
+                temp_frame = swap_face(source_face, target_face, temp_frame)
    else:
        target_face = get_one_face(temp_frame)
-        if target_face and source_face:
+        if target_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.source_target_map:
+            for map in modules.globals.souce_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.source_target_map:
+            for map in modules.globals.souce_target_map:
                if "source" in map:
                    source_face = map["source"]["face"]
                    target_face = map["target"]["face"]
@@ -143,7 +177,7 @@ 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.source_target_map:
+            for map in modules.globals.souce_target_map:
                target_frame = [
                    f
                    for f in map["target_faces_in_frame"]
@@ -155,7 +189,7 @@ 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.source_target_map:
+            for map in modules.globals.souce_target_map:
                if "source" in map:
                    target_frame = [
                        f
@@ -267,361 +301,3 @@ 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  # Add this import
+from cv2_enumerate_cameras import enumerate_cameras
 from PIL import Image, ImageOps
 import time
 import json
@@ -28,6 +28,7 @@ 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
@@ -35,7 +36,7 @@ if platform.system() == "Windows":
 ROOT = None
 POPUP = None
 POPUP_LIVE = None
-ROOT_HEIGHT = 700
+ROOT_HEIGHT = 730
 ROOT_WIDTH = 600

 PREVIEW = None
@@ -78,9 +79,12 @@ 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, _
+    global ROOT, PREVIEW, _, fake_face_switch, fake_face_value

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


 def save_switch_states():
-    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)
+    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)}")


 def load_switch_states():
    try:
-        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
+        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)}")


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

    load_switch_states()

@@ -150,22 +159,28 @@ 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=0.1, relwidth=0.3, relheight=0.25)
+    source_label.place(relx=0.1, rely=0.05, relwidth=0.3, relheight=0.25)

    target_label = ctk.CTkLabel(root, text=None)
-    target_label.place(relx=0.6, rely=0.1, relwidth=0.3, relheight=0.25)
+    target_label.place(relx=0.6, rely=0.05, 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=0.4, relwidth=0.3, relheight=0.1)
+    select_face_button.place(relx=0.1, rely=0.35, 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=0.4, relwidth=0.1, relheight=0.1)
+    swap_faces_button.place(relx=0.45, rely=0.35, relwidth=0.1, relheight=0.1)

    select_target_button = ctk.CTkButton(
        root,
@@ -173,60 +188,30 @@ 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=0.4, relwidth=0.3, relheight=0.1)
+    select_target_button.place(relx=0.6, rely=0.35, relwidth=0.3, relheight=0.1)

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

-    keep_frames_value = ctk.BooleanVar(value=modules.globals.keep_frames)
-    keep_frames_switch = ctk.CTkSwitch(
+    # Add refresh button next to the switch
+    refresh_face_button = ctk.CTkButton(
        root,
-        text=_("Keep frames"),
-        variable=keep_frames_value,
+        text="↻",
+        width=30,
        cursor="hand2",
-        command=lambda: (
-            setattr(modules.globals, "keep_frames", keep_frames_value.get()),
-            save_switch_states(),
-        ),
+        command=lambda: refresh_fake_face_clicked()
    )
-    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)
+    refresh_face_button.place(relx=0.35, rely=0.50)

+    # Face Processing Options (Middle Left)
    many_faces_value = ctk.BooleanVar(value=modules.globals.many_faces)
    many_faces_switch = ctk.CTkSwitch(
        root,
@@ -238,24 +223,7 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    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)
+    many_faces_switch.place(relx=0.1, rely=0.55)

    map_faces = ctk.BooleanVar(value=modules.globals.map_faces)
    map_faces_switch = ctk.CTkSwitch(
@@ -269,8 +237,35 @@ 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=0.75)
+    map_faces_switch.place(relx=0.1, rely=0.60)

+    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,
@@ -282,8 +277,9 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    show_fps_switch.place(relx=0.6, rely=0.75)
+    show_fps_switch.place(relx=0.1, 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,
@@ -292,38 +288,117 @@ 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=0.1, rely=0.55)
+    mouth_mask_switch.place(relx=0.6, rely=0.50)

+    # 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 Mask Box"),
+        text=_("Show Mouth 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=0.55)
+    show_mouth_mask_box_switch.place(relx=0.6, rely=0.65)

+    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)

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

-    # --- Camera Selection ---
+    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)
+
+    # Camera Section (Bottom)
    camera_label = ctk.CTkLabel(root, text=_("Select Camera:"))
-    camera_label.place(relx=0.1, rely=0.86, relwidth=0.2, relheight=0.05)
+    camera_label.place(relx=0.1, rely=0.87, relwidth=0.2, relheight=0.05)

    available_cameras = get_available_cameras()
    camera_indices, camera_names = available_cameras
@@ -342,7 +417,7 @@ 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=0.86, relwidth=0.25, relheight=0.05)
+    camera_optionmenu.place(relx=0.35, rely=0.87, relwidth=0.25, relheight=0.05)

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

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

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

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

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

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

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

    source_path = ctk.filedialog.askopenfilename(
-        title=_("select a source image"),
+        title=_("select an source image"),
        initialdir=RECENT_DIRECTORY_SOURCE,
        filetypes=[img_ft],
    )
@@ -544,6 +619,11 @@ 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)
@@ -580,15 +660,19 @@ def update_tumbler(var: str, value: bool) -> None:


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

    PREVIEW.withdraw()
    source_path = ctk.filedialog.askopenfilename(
-        title=_("select a source image"),
+        title=_("select an 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))
@@ -627,7 +711,7 @@ def select_target_path() -> None:

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


 def fit_image_to_size(image, width: int, height: int):
-    if width is None or height is None or width <= 0 or height <= 0:
+    if width is None and height is None:
        return image
    h, w, _ = image.shape
    ratio_h = 0.0
    ratio_w = 0.0
-    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)
-
+    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))
    return cv2.resize(image, dsize=new_size)


@@ -765,8 +845,7 @@ 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
@@ -791,9 +870,9 @@ def webcam_preview(root: ctk.CTk, camera_index: int):
            return
        create_webcam_preview(camera_index)
    else:
-        modules.globals.source_target_map = []
+        modules.globals.souce_target_map = []
        create_source_target_popup_for_webcam(
-            root, modules.globals.source_target_map, camera_index
+            root, modules.globals.souce_target_map, camera_index
        )


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

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

    target_path = ctk.filedialog.askopenfilename(
-        title=_("select a target image"),
+        title=_("select an target image"),
        initialdir=RECENT_DIRECTORY_SOURCE,
        filetypes=[img_ft],
    )
@@ -1204,3 +1283,42 @@ 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")
@@ -1,21 +1,24 @@
--extra-index-url https://download.pytorch.org/whl/cu128
+--extra-index-url https://download.pytorch.org/whl/cu118

 numpy>=1.23.5,<2
-typing-extensions>=4.8.0
 opencv-python==4.10.0.84
 cv2_enumerate_cameras==1.1.15
-onnx==1.18.0
+onnx==1.16.0
 insightface==0.7.3
 psutil==5.9.8
 tk==0.1.0
 customtkinter==5.2.2
 pillow==11.1.0
-torch; sys_platform != 'darwin'
-torch==2.5.1; sys_platform == 'darwin'
-torchvision; sys_platform != 'darwin'
-torchvision==0.20.1; sys_platform == 'darwin'
+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'
 onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64'
-onnxruntime-gpu==1.22.0; sys_platform != 'darwin'
-tensorflow; sys_platform != 'darwin'
+onnxruntime-gpu==1.16.3; sys_platform != 'darwin'
+tensorflow==2.12.1; sys_platform != 'darwin'
 opennsfw2==0.10.2
-protobuf==4.25.1
+protobuf==4.23.2
+tqdm==4.66.4
+gfpgan==1.3.8
+tkinterdnd2==0.4.2
+pygrabber==0.2
Author	SHA1	Message	Date
KRSHH	48c83151a4	size	2025-02-03 20:59:06 +05:30
KRSHH	bb3502d9bd	update branch update branch	2025-01-31 22:32:47 +05:30
KRSHH	a101a1f3f1	Reorganized switches	2025-01-30 20:20:04 +05:30
KRSHH	01ef955372	Improve eyebrow mask	2025-01-30 20:14:16 +05:30
KRSHH	ab3b73631b	Shift masking features to face_masking.py	2025-01-30 20:04:31 +05:30
KRSHH	d8fc1ffa04	Eyebrow Mask	2025-01-30 19:58:15 +05:30
KRSHH	5dfd1c0ced	Eye Mask	2025-01-30 19:20:58 +05:30
KRSHH	59cd3be0f9	Simplify Privacy mode switch state	2025-01-27 00:47:34 +05:30
KRSHH	ccb676ac17	FPS Switch re-enable	2025-01-26 23:41:44 +05:30
KRSHH	f0c66732e7	Use Logo	2025-01-26 23:20:08 +05:30
KRSHH	8055d79daf	Privacy Mode	2025-01-26 23:10:45 +05:30
KRSHH	3c7dd1a574	Hardcoded Keep FPS and Keep Frames	2025-01-23 18:45:43 +05:30