Creating a fallback and switching of models

Models switch depending on the execution provider

README.md

@@ -30,6 +30,13 @@ By using this software, you agree to these terms and commit to using it in a man
 
 Users are expected to use this software responsibly and legally. If using a real person's face, obtain their consent and clearly label any output as a deepfake when sharing online. We are not responsible for end-user actions.
 
+## Exclusive v2.1 Quick Start - Pre-built (Windows/Mac Silicon)
+
+  <a href="https://deeplivecam.net/index.php/quickstart"> <img src="media/Download.png" width="285" height="77" />
+
+##### This is the fastest build you can get if you have a discrete NVIDIA or AMD GPU or Mac Silicon, And you'll receive special priority support.
+ 
+###### These Pre-builts are perfect for non-technical users or those who don't have time to, or can't manually install all the requirements. Just a heads-up: this is an open-source project, so you can also install it manually. 
 
 ## TLDR; Live Deepfake in just 3 Clicks
 ![easysteps](https://github.com/user-attachments/assets/af825228-852c-411b-b787-ffd9aac72fc6)
@@ -91,7 +98,7 @@ Users are expected to use this software responsibly and legally. If using a real
 
 ## Installation (Manual)
 
-**Please be aware that the installation requires technical skills and is not for beginners. Consider downloading the prebuilt version.**
+**Please be aware that the installation requires technical skills and is not for beginners. Consider downloading the quickstart version.**
 
 <details>
 <summary>Click to see the process</summary>
@@ -102,7 +109,7 @@ This is more likely to work on your computer but will be slower as it utilizes t
 
 **1. Set up Your Platform**
 
--   Python (3.10 recommended)
+-   Python (3.11 recommended)
 -   pip
 -   git
 -   [ffmpeg](https://www.youtube.com/watch?v=OlNWCpFdVMA) - ```iex (irm ffmpeg.tc.ht)```
@@ -126,26 +133,34 @@ 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:
 
 ```bash
-# Install Python 3.10 (specific version is important)
+# Install Python 3.11 (specific version is important)
-brew install python@3.10
+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 3.10
+# Create and activate virtual environment with Python 3.11
-python3.10 -m venv venv
+python3.11 -m venv venv
 source venv/bin/activate
 
 # Install dependencies
@@ -172,12 +187,16 @@ pip install -r requirements.txt
 
 **CUDA Execution Provider (Nvidia)**
 
-1. Install [CUDA Toolkit 11.8.0](https://developer.nvidia.com/cuda-11-8-0-download-archive)
+1. Install [CUDA Toolkit 12.8.0](https://developer.nvidia.com/cuda-12-8-0-download-archive)
-2. Install dependencies:
+2. Install [cuDNN v8.9.7 for CUDA 12.x](https://developer.nvidia.com/rdp/cudnn-archive) (required for onnxruntime-gpu):
+   - Download cuDNN v8.9.7 for CUDA 12.x
+   - Make sure the cuDNN bin directory is in your system PATH
+3. Install dependencies:
 
 ```bash
+pip install -U torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128
 pip uninstall onnxruntime onnxruntime-gpu
-pip install onnxruntime-gpu==1.16.3
+pip install onnxruntime-gpu==1.21.0
 ```
 
 3. Usage:
@@ -217,7 +236,7 @@ python3.10 run.py --execution-provider coreml
   # Uninstall conflicting versions if needed
   brew uninstall --ignore-dependencies python@3.11 python@3.13
   
-  # Keep only Python 3.10
+  # Keep only Python 3.11
   brew cleanup
   ```
 
@@ -227,7 +246,7 @@ python3.10 run.py --execution-provider coreml
 
 ```bash
 pip uninstall onnxruntime onnxruntime-coreml
-pip install onnxruntime-coreml==1.13.1
+pip install onnxruntime-coreml==1.21.0
 ```
 
 2. Usage:
@@ -242,7 +261,7 @@ python run.py --execution-provider coreml
 
 ```bash
 pip uninstall onnxruntime onnxruntime-directml
-pip install onnxruntime-directml==1.15.1
+pip install onnxruntime-directml==1.21.0
 ```
 
 2. Usage:
@@ -257,7 +276,7 @@ python run.py --execution-provider directml
 
 ```bash
 pip uninstall onnxruntime onnxruntime-openvino
-pip install onnxruntime-openvino==1.15.0
+pip install onnxruntime-openvino==1.21.0
 ```
 
 2. Usage:
@@ -285,19 +304,6 @@ python run.py --execution-provider openvino
 -   Use a screen capture tool like OBS to stream.
 -   To change the face, select a new source image.
 
-## Tips and Tricks
-
-Check out these helpful guides to get the most out of Deep-Live-Cam:
-
-- [Unlocking the Secrets to the Perfect Deepfake Image](https://deeplivecam.net/index.php/blog/tips-and-tricks/unlocking-the-secrets-to-the-perfect-deepfake-image) - Learn how to create the best deepfake with full head coverage
-- [Video Call with DeepLiveCam](https://deeplivecam.net/index.php/blog/tips-and-tricks/video-call-with-deeplivecam) - Make your meetings livelier by using DeepLiveCam with OBS and meeting software
-- [Have a Special Guest!](https://deeplivecam.net/index.php/blog/tips-and-tricks/have-a-special-guest) - Tutorial on how to use face mapping to add special guests to your stream
-- [Watch Deepfake Movies in Realtime](https://deeplivecam.net/index.php/blog/tips-and-tricks/watch-deepfake-movies-in-realtime) - See yourself star in any video without processing the video
-- [Better Quality without Sacrificing Speed](https://deeplivecam.net/index.php/blog/tips-and-tricks/better-quality-without-sacrificing-speed) - Tips for achieving better results without impacting performance
-- [Instant Vtuber!](https://deeplivecam.net/index.php/blog/tips-and-tricks/instant-vtuber) - Create a new persona/vtuber easily using Metahuman Creator
-
-Visit our [official blog](https://deeplivecam.net/index.php/blog/tips-and-tricks) for more tips and tutorials.
-
 ## Command Line Arguments (Unmaintained)
 
 ```
@@ -341,6 +347,8 @@ Looking for a CLI mode? Using the -s/--source argument will make the run program
  - [*"This real-time webcam deepfake tool raises alarms about the future of identity theft"*](https://www.diyphotography.net/this-real-time-webcam-deepfake-tool-raises-alarms-about-the-future-of-identity-theft/) - DIYPhotography
  - [*"That's Crazy, Oh God. That's Fucking Freaky Dude... That's So Wild Dude"*](https://www.youtube.com/watch?time_continue=1074&v=py4Tc-Y8BcY) - SomeOrdinaryGamers
  - [*"Alright look look look, now look chat, we can do any face we want to look like chat"*](https://www.youtube.com/live/mFsCe7AIxq8?feature=shared&t=2686) - IShowSpeed
+ - [*"They do a pretty good job matching poses, expression and even the lighting"*](https://www.youtube.com/watch?v=wnCghLjqv3s&t=551s) - TechLinked (LTT)
+
 
 ## Credits
 

locales/de.json

@@ -0,0 +1,46 @@
+{
+    "Source x Target Mapper": "Quelle x Ziel Zuordnung",
+    "select a source image": "Wähle ein Quellbild",
+    "Preview": "Vorschau",
+    "select a target image or video": "Wähle ein Zielbild oder Video",
+    "save image output file": "Bildausgabedatei speichern",
+    "save video output file": "Videoausgabedatei speichern",
+    "select a target image": "Wähle ein Zielbild",
+    "source": "Quelle",
+    "Select a target": "Wähle ein Ziel",
+    "Select a face": "Wähle ein Gesicht",
+    "Keep audio": "Audio beibehalten",
+    "Face Enhancer": "Gesichtsverbesserung",
+    "Many faces": "Mehrere Gesichter",
+    "Show FPS": "FPS anzeigen",
+    "Keep fps": "FPS beibehalten",
+    "Keep frames": "Frames beibehalten",
+    "Fix Blueish Cam": "Bläuliche Kamera korrigieren",
+    "Mouth Mask": "Mundmaske",
+    "Show Mouth Mask Box": "Mundmaskenrahmen anzeigen",
+    "Start": "Starten",
+    "Live": "Live",
+    "Destroy": "Beenden",
+    "Map faces": "Gesichter zuordnen",
+    "Processing...": "Verarbeitung läuft...",
+    "Processing succeed!": "Verarbeitung erfolgreich!",
+    "Processing ignored!": "Verarbeitung ignoriert!",
+    "Failed to start camera": "Kamera konnte nicht gestartet werden",
+    "Please complete pop-up or close it.": "Bitte das Pop-up komplettieren oder schließen.",
+    "Getting unique faces": "Einzigartige Gesichter erfassen",
+    "Please select a source image first": "Bitte zuerst ein Quellbild auswählen",
+    "No faces found in target": "Keine Gesichter im Zielbild gefunden",
+    "Add": "Hinzufügen",
+    "Clear": "Löschen",
+    "Submit": "Absenden",
+    "Select source image": "Quellbild auswählen",
+    "Select target image": "Zielbild auswählen",
+    "Please provide mapping!": "Bitte eine Zuordnung angeben!",
+    "At least 1 source with target is required!": "Mindestens eine Quelle mit einem Ziel ist erforderlich!",
+    "At least 1 source with target is required!": "Mindestens eine Quelle mit einem Ziel ist erforderlich!",
+    "Face could not be detected in last upload!": "Im letzten Upload konnte kein Gesicht erkannt werden!",
+    "Select Camera:": "Kamera auswählen:",
+    "All mappings cleared!": "Alle Zuordnungen gelöscht!",
+    "Mappings successfully submitted!": "Zuordnungen erfolgreich übermittelt!",
+    "Source x Target Mapper is already open.": "Quell-zu-Ziel-Zuordnung ist bereits geöffnet."
+}

locales/es.json

@@ -0,0 +1,46 @@
+{
+    "Source x Target Mapper": "Mapeador de fuente x destino",
+    "select a source image": "Seleccionar imagen fuente",
+    "Preview": "Vista previa",
+    "select a target image or video": "elegir un video o una imagen fuente",
+    "save image output file": "guardar imagen final",
+    "save video output file": "guardar video final",
+    "select a target image": "elegir una imagen objetiva",
+    "source": "fuente",
+    "Select a target": "Elegir un destino",
+    "Select a face": "Elegir una cara",
+    "Keep audio": "Mantener audio original",
+    "Face Enhancer": "Potenciador de caras",
+    "Many faces": "Varias caras",
+    "Show FPS": "Mostrar fps",
+    "Keep fps": "Mantener fps",
+    "Keep frames": "Mantener frames",
+    "Fix Blueish Cam": "Corregir tono azul de video",
+    "Mouth Mask": "Máscara de boca",
+    "Show Mouth Mask Box": "Mostrar área de la máscara de boca",
+    "Start": "Iniciar",
+    "Live": "En vivo",
+    "Destroy": "Borrar",
+    "Map faces": "Mapear caras",
+    "Processing...": "Procesando...",
+    "Processing succeed!": "¡Proceso terminado con éxito!",
+    "Processing ignored!": "¡Procesamiento omitido!",
+    "Failed to start camera": "No se pudo iniciar la cámara",
+    "Please complete pop-up or close it.": "Complete o cierre el pop-up",
+    "Getting unique faces": "Buscando caras únicas",
+    "Please select a source image first": "Primero, seleccione una imagen fuente",
+    "No faces found in target": "No se encontró una cara en el destino",
+    "Add": "Agregar",
+    "Clear": "Limpiar",
+    "Submit": "Enviar",
+    "Select source image": "Seleccionar imagen fuente",
+    "Select target image": "Seleccionar imagen destino",
+    "Please provide mapping!": "Por favor, proporcione un mapeo",
+    "At least 1 source with target is required!": "Se requiere al menos una fuente con un destino.",
+    "At least 1 source with target is required!": "Se requiere al menos una fuente con un destino.",
+    "Face could not be detected in last upload!": "¡No se pudo encontrar una cara en el último video o imagen!",
+    "Select Camera:": "Elegir cámara:",
+    "All mappings cleared!": "¡Todos los mapeos fueron borrados!",
+    "Mappings successfully submitted!": "Mapeos enviados con éxito!",
+    "Source x Target Mapper is already open.": "El mapeador de fuente x destino ya está abierto."
+}

locales/fi.json

@@ -0,0 +1,46 @@
+{
+    "Source x Target Mapper": "Source x Target Kartoitin",
+    "select an source image": "Valitse lähde kuva",
+    "Preview": "Esikatsele",
+    "select an target image or video": "Valitse kohde kuva tai video",
+    "save image output file": "tallenna kuva",
+    "save video output file": "tallenna video",
+    "select an target image": "Valitse kohde kuva",
+    "source": "lähde",
+    "Select a target": "Valitse kohde",
+    "Select a face": "Valitse kasvot",
+    "Keep audio": "Säilytä ääni",
+    "Face Enhancer": "Kasvojen Parantaja",
+    "Many faces": "Useampia kasvoja",
+    "Show FPS": "Näytä FPS",
+    "Keep fps": "Säilytä FPS",
+    "Keep frames": "Säilytä ruudut",
+    "Fix Blueish Cam": "Korjaa Sinertävä Kamera",
+    "Mouth Mask": "Suu Maski",
+    "Show Mouth Mask Box": "Näytä Suu Maski Laatiko",
+    "Start": "Aloita",
+    "Live": "Live",
+    "Destroy": "Tuhoa",
+    "Map faces": "Kartoita kasvot",
+    "Processing...": "Prosessoi...",
+    "Processing succeed!": "Prosessointi onnistui!",
+    "Processing ignored!": "Prosessointi lopetettu!",
+    "Failed to start camera": "Kameran käynnistäminen epäonnistui",
+    "Please complete pop-up or close it.": "Viimeistele tai sulje ponnahdusikkuna",
+    "Getting unique faces": "Hankitaan uniikkeja kasvoja",
+    "Please select a source image first": "Valitse ensin lähde kuva",
+    "No faces found in target": "Kasvoja ei löydetty kohteessa",
+    "Add": "Lisää",
+    "Clear": "Tyhjennä",
+    "Submit": "Lähetä",
+    "Select source image": "Valitse lähde kuva",
+    "Select target image": "Valitse kohde kuva",
+    "Please provide mapping!": "Tarjoa kartoitus!",
+    "Atleast 1 source with target is required!": "Vähintään 1 lähde kohteen kanssa on vaadittu!",
+    "At least 1 source with target is required!": "Vähintään 1 lähde kohteen kanssa on vaadittu!",
+    "Face could not be detected in last upload!": "Kasvoja ei voitu tunnistaa edellisessä latauksessa!",
+    "Select Camera:": "Valitse Kamera:",
+    "All mappings cleared!": "Kaikki kartoitukset tyhjennetty!",
+    "Mappings successfully submitted!": "Kartoitukset lähetety onnistuneesti!",
+    "Source x Target Mapper is already open.": "Lähde x Kohde Kartoittaja on jo auki."
+}

locales/km.json

@@ -0,0 +1,45 @@
+{
+    "Source x Target Mapper": "ប្រភប x បន្ថែម Mapper",
+    "select a source image": "ជ្រើសរើសប្រភពរូបភាព",
+    "Preview": "បង្ហាញ",
+    "select a target image or video": "ជ្រើសរើសគោលដៅរូបភាពឬវីដេអូ",
+    "save image output file": "រក្សាទុកលទ្ធផលឯកសាររូបភាព",
+    "save video output file": "រក្សាទុកលទ្ធផលឯកសារវីដេអូ",
+    "select a target image": "ជ្រើសរើសគោលដៅរូបភាព",
+    "source": "ប្រភព",
+    "Select a target": "ជ្រើសរើសគោលដៅ",
+    "Select a face": "ជ្រើសរើសមុខ",
+    "Keep audio": "រម្លងសម្លេង",
+    "Face Enhancer": "ឧបករណ៍ពង្រឹងមុខ",
+    "Many faces": "ទម្រង់មុខច្រើន",
+    "Show FPS": "បង្ហាញ FPS",
+    "Keep fps": "រម្លង fps",
+    "Keep frames": "រម្លងទម្រង់",
+    "Fix Blueish Cam": "ជួសជុល Cam Blueish",
+    "Mouth Mask": "របាំងមាត់",
+    "Show Mouth Mask Box": "បង្ហាញប្រអប់របាំងមាត់",
+    "Start": "ចាប់ផ្ដើម",
+    "Live": "ផ្សាយផ្ទាល់",
+    "Destroy": "លុប",
+    "Map faces": "ផែនទីមុខ",
+    "Processing...": "កំពុងដំណើរការ...",
+    "Processing succeed!": "ការដំណើរការទទួលបានជោគជ័យ!",
+    "Processing ignored!": "ការដំណើរការមិនទទួលបានជោគជ័យ!",
+    "Failed to start camera": "បរាជ័យដើម្បីចាប់ផ្ដើមបើកកាមេរ៉ា",
+    "Please complete pop-up or close it.": "សូមបញ្ចប់ផ្ទាំងផុស ឬបិទវា.",
+    "Getting unique faces": "ការចាប់ផ្ដើមទម្រង់មុខប្លែក",
+    "Please select a source image first": "សូមជ្រើសរើសប្រភពរូបភាពដំបូង",
+    "No faces found in target": "រកអត់ឃើញមុខនៅក្នុងគោលដៅ",
+    "Add": "បន្ថែម",
+    "Clear": "សម្អាត",
+    "Submit": "បញ្ចូន",
+    "Select source image": "ជ្រើសរើសប្រភពរូបភាព",
+    "Select target image": "ជ្រើសរើសគោលដៅរូបភាព",
+    "Please provide mapping!": "សូមផ្ដល់នៅផែនទី",
+    "At least 1 source with target is required!": "ត្រូវការប្រភពយ៉ាងហោចណាស់ ១ ដែលមានគោលដៅ!",
+    "Face could not be detected in last upload!": "មុខមិនអាចភ្ជាប់នៅក្នុងការបង្ហេាះចុងក្រោយ!",
+    "Select Camera:": "ជ្រើសរើសកាមេរ៉ា",
+    "All mappings cleared!": "ផែនទីទាំងអស់ត្រូវបានសម្អាត!",
+    "Mappings successfully submitted!": "ផែនទីត្រូវបានបញ្ជូនជោគជ័យ!",
+    "Source x Target Mapper is already open.": "ប្រភព x Target Mapper បានបើករួចហើយ។"
+}

locales/ko.json

@@ -0,0 +1,45 @@
+{
+    "Source x Target Mapper": "소스 x 타겟 매퍼",
+    "select a source image": "소스 이미지 선택",
+    "Preview": "미리보기",
+    "select a target image or video": "타겟 이미지 또는 영상 선택",
+    "save image output file": "이미지 출력 파일 저장",
+    "save video output file": "영상 출력 파일 저장",
+    "select a target image": "타겟 이미지 선택",
+    "source": "소스",
+    "Select a target": "타겟 선택",
+    "Select a face": "얼굴 선택",
+    "Keep audio": "오디오 유지",
+    "Face Enhancer": "얼굴 향상",
+    "Many faces": "여러 얼굴",
+    "Show FPS": "FPS 표시",
+    "Keep fps": "FPS 유지",
+    "Keep frames": "프레임 유지",
+    "Fix Blueish Cam": "푸른빛 카메라 보정",
+    "Mouth Mask": "입 마스크",
+    "Show Mouth Mask Box": "입 마스크 박스 표시",
+    "Start": "시작",
+    "Live": "라이브",
+    "Destroy": "종료",
+    "Map faces": "얼굴 매핑",
+    "Processing...": "처리 중...",
+    "Processing succeed!": "처리 성공!",
+    "Processing ignored!": "처리 무시됨!",
+    "Failed to start camera": "카메라 시작 실패",
+    "Please complete pop-up or close it.": "팝업을 완료하거나 닫아주세요.",
+    "Getting unique faces": "고유 얼굴 가져오는 중",
+    "Please select a source image first": "먼저 소스 이미지를 선택해주세요",
+    "No faces found in target": "타겟에서 얼굴을 찾을 수 없음",
+    "Add": "추가",
+    "Clear": "지우기",
+    "Submit": "제출",
+    "Select source image": "소스 이미지 선택",
+    "Select target image": "타겟 이미지 선택",
+    "Please provide mapping!": "매핑을 입력해주세요!",
+    "At least 1 source with target is required!": "최소 하나의 소스와 타겟이 필요합니다!",
+    "Face could not be detected in last upload!": "최근 업로드에서 얼굴을 감지할 수 없습니다!",
+    "Select Camera:": "카메라 선택:",
+    "All mappings cleared!": "모든 매핑이 삭제되었습니다!",
+    "Mappings successfully submitted!": "매핑이 성공적으로 제출되었습니다!",
+    "Source x Target Mapper is already open.": "소스 x 타겟 매퍼가 이미 열려 있습니다."
+}

locales/pt-br.json

@@ -0,0 +1,46 @@
+{
+    "Source x Target Mapper": "Mapeador de Origem x Destino",
+    "select an source image": "Escolha uma imagem de origem",
+    "Preview": "Prévia",
+    "select an target image or video": "Escolha uma imagem ou vídeo de destino",
+    "save image output file": "Salvar imagem final",
+    "save video output file": "Salvar vídeo final",
+    "select an target image": "Escolha uma imagem de destino",
+    "source": "Origem",
+    "Select a target": "Escolha o destino",
+    "Select a face": "Escolha um rosto",
+    "Keep audio": "Manter o áudio original",
+    "Face Enhancer": "Melhorar rosto",
+    "Many faces": "Vários rostos",
+    "Show FPS": "Mostrar FPS",
+    "Keep fps": "Manter FPS",
+    "Keep frames": "Manter frames",
+    "Fix Blueish Cam": "Corrigir tom azulado da câmera",
+    "Mouth Mask": "Máscara da boca",
+    "Show Mouth Mask Box": "Mostrar área da máscara da boca",
+    "Start": "Começar",
+    "Live": "Ao vivo",
+    "Destroy": "Destruir",
+    "Map faces": "Mapear rostos",
+    "Processing...": "Processando...",
+    "Processing succeed!": "Tudo certo!",
+    "Processing ignored!": "Processamento ignorado!",
+    "Failed to start camera": "Não foi possível iniciar a câmera",
+    "Please complete pop-up or close it.": "Finalize ou feche o pop-up",
+    "Getting unique faces": "Buscando rostos diferentes",
+    "Please select a source image first": "Selecione primeiro uma imagem de origem",
+    "No faces found in target": "Nenhum rosto encontrado na imagem de destino",
+    "Add": "Adicionar",
+    "Clear": "Limpar",
+    "Submit": "Enviar",
+    "Select source image": "Escolha a imagem de origem",
+    "Select target image": "Escolha a imagem de destino",
+    "Please provide mapping!": "Você precisa realizar o mapeamento!",
+    "Atleast 1 source with target is required!": "É necessária pelo menos uma origem com um destino!",
+    "At least 1 source with target is required!": "É necessária pelo menos uma origem com um destino!",
+    "Face could not be detected in last upload!": "Não conseguimos detectar o rosto na última imagem!",
+    "Select Camera:": "Escolher câmera:",
+    "All mappings cleared!": "Todos os mapeamentos foram removidos!",
+    "Mappings successfully submitted!": "Mapeamentos enviados com sucesso!",
+    "Source x Target Mapper is already open.": "O Mapeador de Origem x Destino já está aberto."
+}

locales/ru.json

@@ -0,0 +1,45 @@
+{
+    "Source x Target Mapper": "Сопоставитель Источник x Цель",
+    "select a source image": "выберите исходное изображение",
+    "Preview": "Предпросмотр",
+    "select a target image or video": "выберите целевое изображение или видео",
+    "save image output file": "сохранить выходной файл изображения",
+    "save video output file": "сохранить выходной файл видео",
+    "select a target image": "выберите целевое изображение",
+    "source": "источник",
+    "Select a target": "Выберите целевое изображение",
+    "Select a face": "Выберите лицо",
+    "Keep audio": "Сохранить аудио",
+    "Face Enhancer": "Улучшение лица",
+    "Many faces": "Несколько лиц",
+    "Show FPS": "Показать FPS",
+    "Keep fps": "Сохранить FPS",
+    "Keep frames": "Сохранить кадры",
+    "Fix Blueish Cam": "Исправить синеву камеры",
+    "Mouth Mask": "Маска рта",
+    "Show Mouth Mask Box": "Показать рамку маски рта",
+    "Start": "Старт",
+    "Live": "В реальном времени",
+    "Destroy": "Остановить",
+    "Map faces": "Сопоставить лица",
+    "Processing...": "Обработка...",
+    "Processing succeed!": "Обработка успешна!",
+    "Processing ignored!": "Обработка проигнорирована!",
+    "Failed to start camera": "Не удалось запустить камеру",
+    "Please complete pop-up or close it.": "Пожалуйста, заполните всплывающее окно или закройте его.",
+    "Getting unique faces": "Получение уникальных лиц",
+    "Please select a source image first": "Сначала выберите исходное изображение, пожалуйста",
+    "No faces found in target": "В целевом изображении не найдено лиц",
+    "Add": "Добавить",
+    "Clear": "Очистить",
+    "Submit": "Отправить",
+    "Select source image": "Выбрать исходное изображение",
+    "Select target image": "Выбрать целевое изображение",
+    "Please provide mapping!": "Пожалуйста, укажите сопоставление!",
+    "At least 1 source with target is required!": "Требуется хотя бы 1 источник с целью!",
+    "Face could not be detected in last upload!": "Лицо не обнаружено в последнем загруженном изображении!",
+    "Select Camera:": "Выберите камеру:",
+    "All mappings cleared!": "Все сопоставления очищены!",
+    "Mappings successfully submitted!": "Сопоставления успешно отправлены!",
+    "Source x Target Mapper is already open.": "Сопоставитель Источник-Цель уже открыт."
+}

locales/th.json

@@ -0,0 +1,45 @@
+{
+    "Source x Target Mapper": "ตัวจับคู่ต้นทาง x ปลายทาง",
+    "select a source image": "เลือกรูปภาพต้นฉบับ",
+    "Preview": "ตัวอย่าง",
+    "select a target image or video": "เลือกรูปภาพหรือวิดีโอเป้าหมาย",
+    "save image output file": "บันทึกไฟล์รูปภาพ",
+    "save video output file": "บันทึกไฟล์วิดีโอ",
+    "select a target image": "เลือกรูปภาพเป้าหมาย",
+    "source": "ต้นฉบับ",
+    "Select a target": "เลือกเป้าหมาย",
+    "Select a face": "เลือกใบหน้า",
+    "Keep audio": "เก็บเสียง",
+    "Face Enhancer": "ปรับปรุงใบหน้า",
+    "Many faces": "หลายใบหน้า",
+    "Show FPS": "แสดง FPS",
+    "Keep fps": "คงค่า FPS",
+    "Keep frames": "คงค่าเฟรม",
+    "Fix Blueish Cam": "แก้ไขภาพอมฟ้าจากกล้อง",
+    "Mouth Mask": "มาสก์ปาก",
+    "Show Mouth Mask Box": "แสดงกรอบมาสก์ปาก",
+    "Start": "เริ่ม",
+    "Live": "สด",
+    "Destroy": "หยุด",
+    "Map faces": "จับคู่ใบหน้า",
+    "Processing...": "กำลังประมวลผล...",
+    "Processing succeed!": "ประมวลผลสำเร็จแล้ว!",
+    "Processing ignored!": "การประมวลผลถูกละเว้น",
+    "Failed to start camera": "ไม่สามารถเริ่มกล้องได้",
+    "Please complete pop-up or close it.": "โปรดดำเนินการในป๊อปอัปให้เสร็จสิ้น หรือปิด",
+    "Getting unique faces": "กำลังค้นหาใบหน้าที่ไม่ซ้ำกัน",
+    "Please select a source image first": "โปรดเลือกภาพต้นฉบับก่อน",
+    "No faces found in target": "ไม่พบใบหน้าในภาพเป้าหมาย",
+    "Add": "เพิ่ม",
+    "Clear": "ล้าง",
+    "Submit": "ส่ง",
+    "Select source image": "เลือกภาพต้นฉบับ",
+    "Select target image": "เลือกภาพเป้าหมาย",
+    "Please provide mapping!": "โปรดระบุการจับคู่!",
+    "At least 1 source with target is required!": "ต้องมีการจับคู่ต้นฉบับกับเป้าหมายอย่างน้อย 1 คู่!",
+    "Face could not be detected in last upload!": "ไม่สามารถตรวจพบใบหน้าในไฟล์อัปโหลดล่าสุด!",
+    "Select Camera:": "เลือกกล้อง:",
+    "All mappings cleared!": "ล้างการจับคู่ทั้งหมดแล้ว!",
+    "Mappings successfully submitted!": "ส่งการจับคู่สำเร็จแล้ว!",
+    "Source x Target Mapper is already open.": "ตัวจับคู่ต้นทาง x ปลายทาง เปิดอยู่แล้ว"
+}

locales/zh.json

@@ -1,11 +1,11 @@
 {
     "Source x Target Mapper": "Source x Target Mapper",
-    "select an source image": "选择一个源图像",
+    "select a source image": "选择一个源图像",
     "Preview": "预览",
-    "select an target image or video": "选择一个目标图像或视频",
+    "select a target image or video": "选择一个目标图像或视频",
     "save image output file": "保存图像输出文件",
     "save video output file": "保存视频输出文件",
-    "select an target image": "选择一个目标图像",
+    "select a target image": "选择一个目标图像",
     "source": "源",
     "Select a target": "选择一个目标",
     "Select a face": "选择一张脸",
@@ -36,11 +36,11 @@
     "Select source image": "请选取源图像",
     "Select target image": "请选取目标图像",
     "Please provide mapping!": "请提供映射",
-    "Atleast 1 source with target is required!": "至少需要一个来源图像与目标图像相关！",
+    "At least 1 source with target is required!": "至少需要一个来源图像与目标图像相关！",
     "At least 1 source with target is required!": "至少需要一个来源图像与目标图像相关！",
     "Face could not be detected in last upload!": "最近上传的图像中没有检测到人脸!",
     "Select Camera:": "选择摄像头",
     "All mappings cleared!": "所有映射均已清除!",
     "Mappings successfully submitted!": "成功提交映射！",
     "Source x Target Mapper is already open.": "源 x 目标映射器已打开。"
-}
+}

modules/__init__.py

@@ -0,0 +1,18 @@
+import os 
+import cv2
+import numpy as np
+
+# Utility function to support unicode characters in file paths for reading
+def imread_unicode(path, flags=cv2.IMREAD_COLOR):
+    return cv2.imdecode(np.fromfile(path, dtype=np.uint8), flags)
+
+# Utility function to support unicode characters in file paths for writing
+def imwrite_unicode(path, img, params=None):
+    root, ext = os.path.splitext(path)
+    if not ext:
+        ext = ".png"
+        result, encoded_img = cv2.imencode(ext, img, params if params else [])
+        result, encoded_img = cv2.imencode(f".{ext}", img, params if params is not None else [])
+        encoded_img.tofile(path)
+        return True
+    return False

modules/metadata.py

@@ -1,3 +1,3 @@
 name = 'Deep-Live-Cam'
-version = '1.9'
+version = '1.8.1'
 edition = 'GitHub Edition'

modules/processors/frame/core.py

@@ -42,18 +42,29 @@ def get_frame_processors_modules(frame_processors: List[str]) -> List[ModuleType
 
 def set_frame_processors_modules_from_ui(frame_processors: List[str]) -> None:
     global FRAME_PROCESSORS_MODULES
+    current_processor_names = [proc.__name__.split('.')[-1] for proc in FRAME_PROCESSORS_MODULES]
+
     for frame_processor, state in modules.globals.fp_ui.items():
-        if state == True and frame_processor not in frame_processors:
+        if state == True and frame_processor not in current_processor_names:
-            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.remove(frame_processor_module)
+                FRAME_PROCESSORS_MODULES.append(frame_processor_module)
-                modules.globals.frame_processors.remove(frame_processor)
+                if frame_processor not in modules.globals.frame_processors:
-            except:
+                     modules.globals.frame_processors.append(frame_processor)
-                pass
+            except SystemExit:
+                 print(f"Warning: Failed to load frame processor {frame_processor} requested by UI state.")
+            except Exception as e:
+                 print(f"Warning: Error loading frame processor {frame_processor} requested by UI state: {e}")
+
+        elif state == False and frame_processor in current_processor_names:
+            try:
+                module_to_remove = next((mod for mod in FRAME_PROCESSORS_MODULES if mod.__name__.endswith(f'.{frame_processor}')), None)
+                if module_to_remove:
+                    FRAME_PROCESSORS_MODULES.remove(module_to_remove)
+                if frame_processor in modules.globals.frame_processors:
+                    modules.globals.frame_processors.remove(frame_processor)
+            except Exception as e:
+                 print(f"Warning: Error removing frame processor {frame_processor}: {e}")
 
 def multi_process_frame(source_path: str, temp_frame_paths: List[str], process_frames: Callable[[str, List[str], Any], None], progress: Any = None) -> None:
     with ThreadPoolExecutor(max_workers=modules.globals.execution_threads) as executor:

modules/processors/frame/face_enhancer.py

@@ -48,6 +48,17 @@ def pre_start() -> bool:
     return True
 
 
+TENSORRT_AVAILABLE = False
+try:
+    import torch_tensorrt
+    TENSORRT_AVAILABLE = True
+except ImportError as im:
+    print(f"TensorRT is not available: {im}")
+    pass
+except Exception as e:
+    print(f"TensorRT is not available: {e}")
+    pass
+
 def get_face_enhancer() -> Any:
     global FACE_ENHANCER
 
@@ -55,16 +66,26 @@ def get_face_enhancer() -> Any:
         if FACE_ENHANCER is None:
             model_path = os.path.join(models_dir, "GFPGANv1.4.pth")
             
-            match platform.system():
+            selected_device = None
-                case "Darwin":  # Mac OS
+            device_priority = []
-                    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
 
 

modules/processors/frame/face_swapper.py

@@ -1,44 +1,58 @@
-import os # <-- Added for os.path.exists
 from typing import Any, List
 import cv2
 import insightface
 import threading
-
+import numpy as np
 import modules.globals
+import logging
 import modules.processors.frame.core
-# Ensure update_status is imported if not already globally accessible
-# If it's part of modules.core, it might already be accessible via modules.core.update_status
 from modules.core import update_status
 from modules.face_analyser import get_one_face, get_many_faces, default_source_face
 from modules.typing import Face, Frame
-from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
+from modules.utilities import (
+    conditional_download,
+    is_image,
+    is_video,
+)
 from modules.cluster_analysis import find_closest_centroid
+import os
 
 FACE_SWAPPER = None
 THREAD_LOCK = threading.Lock()
-NAME = 'DLC.FACE-SWAPPER'
+NAME = "DLC.FACE-SWAPPER"
+
+abs_dir = os.path.dirname(os.path.abspath(__file__))
+models_dir = os.path.join(
+    os.path.dirname(os.path.dirname(os.path.dirname(abs_dir))), "models"
+)
 
 
 def pre_check() -> bool:
-    download_directory_path = resolve_relative_path('../models')
+    download_directory_path = models_dir
-    # Ensure both models are mentioned or downloaded if necessary
+    model_url = "https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128.onnx"
-    # Conditional download might need adjustment if you want it to fetch FP32 too
+    if "CUDAExecutionProvider" in modules.globals.execution_providers:
-    conditional_download(download_directory_path, ['https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx'])
+        model_url = "https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128_fp16.onnx"
-    # Add a check or download for the FP32 model if you have a URL
+
-    # conditional_download(download_directory_path, ['URL_TO_FP32_MODEL_HERE'])
+    conditional_download(
+        download_directory_path,
+        [model_url],
+    )
     return True
 
 
 def pre_start() -> bool:
-    # --- No changes needed in pre_start ---
     if not modules.globals.map_faces and not is_image(modules.globals.source_path):
-        update_status('Select an image for source path.', NAME)
+        update_status("Select an image for source path.", NAME)
         return False
-    elif not modules.globals.map_faces and not get_one_face(cv2.imread(modules.globals.source_path)):
+    elif not modules.globals.map_faces and not get_one_face(
-        update_status('No face in source path detected.', NAME)
+        cv2.imread(modules.globals.source_path)
+    ):
+        update_status("No face in source path detected.", NAME)
         return False
-    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
+    if not is_image(modules.globals.target_path) and not is_video(
-        update_status('Select an image or video for target path.', NAME)
+        modules.globals.target_path
+    ):
+        update_status("Select an image or video for target path.", NAME)
         return False
     return True
 
@@ -48,112 +62,113 @@ def get_face_swapper() -> Any:
 
     with THREAD_LOCK:
         if FACE_SWAPPER is None:
-            # --- MODIFICATION START ---
+            model_name = "inswapper_128.onnx"
-            # Define paths for both FP32 and FP16 models
+            if "CUDAExecutionProvider" in modules.globals.execution_providers:
-            model_dir = resolve_relative_path('../models')
+                model_name = "inswapper_128_fp16.onnx"
-            model_path_fp32 = os.path.join(model_dir, 'inswapper_128.onnx')
+            model_path = os.path.join(models_dir, model_name)
-            model_path_fp16 = os.path.join(model_dir, 'inswapper_128_fp16.onnx')
+            FACE_SWAPPER = insightface.model_zoo.get_model(
-            chosen_model_path = None
+                model_path, providers=modules.globals.execution_providers
-
+            )
-            # Prioritize FP32 model
-            if os.path.exists(model_path_fp32):
-                chosen_model_path = model_path_fp32
-                update_status(f"Loading FP32 model: {os.path.basename(chosen_model_path)}", NAME)
-            # Fallback to FP16 model
-            elif os.path.exists(model_path_fp16):
-                chosen_model_path = model_path_fp16
-                update_status(f"FP32 model not found. Loading FP16 model: {os.path.basename(chosen_model_path)}", NAME)
-            # Error if neither model is found
-            else:
-                error_message = f"Face Swapper model not found. Please ensure 'inswapper_128.onnx' (recommended) or 'inswapper_128_fp16.onnx' exists in the '{model_dir}' directory."
-                update_status(error_message, NAME)
-                raise FileNotFoundError(error_message)
-
-            # Load the chosen model
-            try:
-                FACE_SWAPPER = insightface.model_zoo.get_model(chosen_model_path, providers=modules.globals.execution_providers)
-            except Exception as e:
-                update_status(f"Error loading Face Swapper model {os.path.basename(chosen_model_path)}: {e}", NAME)
-                # Optionally, re-raise the exception or handle it more gracefully
-                raise e
-            # --- MODIFICATION END ---
     return FACE_SWAPPER
 
 
 def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
-    # --- No changes needed in swap_face ---
+    face_swapper = get_face_swapper()
-    swapper = get_face_swapper()
+
-    if swapper is None:
+    # Apply the face swap
-         # Handle case where model failed to load
+    swapped_frame = face_swapper.get(
-         update_status("Face swapper model not loaded, skipping swap.", NAME)
+        temp_frame, target_face, source_face, paste_back=True
-         return temp_frame
+    )
-    return swapper.get(temp_frame, target_face, source_face, paste_back=True)
+
+    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
+        )
+
+        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
+            )
+
+    return swapped_frame
 
 
 def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
-    # --- No changes needed in process_frame ---
+    if modules.globals.color_correction:
-    # Ensure the frame is in RGB format if color correction is enabled
+        temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)
-    # Note: InsightFace swapper often expects BGR by default. Double-check if color issues appear.
-    # If color correction is needed *before* swapping and insightface needs BGR:
-    # original_was_bgr = True # Assume input is BGR
-    # if modules.globals.color_correction:
-    #     temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)
-    #     original_was_bgr = False # Now it's RGB
 
     if modules.globals.many_faces:
         many_faces = get_many_faces(temp_frame)
         if many_faces:
             for target_face in many_faces:
-                temp_frame = swap_face(source_face, target_face, temp_frame)
+                if source_face and target_face:
+                    temp_frame = swap_face(source_face, target_face, temp_frame)
+                else:
+                    print("Face detection failed for target/source.")
     else:
         target_face = get_one_face(temp_frame)
-        if target_face:
+        if target_face and source_face:
             temp_frame = swap_face(source_face, target_face, temp_frame)
-
+        else:
-    # Convert back if necessary (example, might not be needed depending on workflow)
+            logging.error("Face detection failed for target or source.")
-    # if modules.globals.color_correction and not original_was_bgr:
-    #      temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_RGB2BGR)
-
     return temp_frame
 
 
+
 def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
-    # --- No changes needed in process_frame_v2 ---
-    # (Assuming swap_face handles the potential None return from get_face_swapper)
     if is_image(modules.globals.target_path):
         if modules.globals.many_faces:
             source_face = default_source_face()
-            for map_entry in modules.globals.souce_target_map: # Renamed 'map' to 'map_entry'
+            for map in modules.globals.source_target_map:
-                target_face = map_entry['target']['face']
+                target_face = map["target"]["face"]
                 temp_frame = swap_face(source_face, target_face, temp_frame)
 
         elif not modules.globals.many_faces:
-            for map_entry in modules.globals.souce_target_map: # Renamed 'map' to 'map_entry'
+            for map in modules.globals.source_target_map:
-                if "source" in map_entry:
+                if "source" in map:
-                    source_face = map_entry['source']['face']
+                    source_face = map["source"]["face"]
-                    target_face = map_entry['target']['face']
+                    target_face = map["target"]["face"]
                     temp_frame = swap_face(source_face, target_face, temp_frame)
 
     elif is_video(modules.globals.target_path):
         if modules.globals.many_faces:
             source_face = default_source_face()
-            for map_entry in modules.globals.souce_target_map: # Renamed 'map' to 'map_entry'
+            for map in modules.globals.source_target_map:
-                target_frame = [f for f in map_entry['target_faces_in_frame'] if f['location'] == temp_frame_path]
+                target_frame = [
+                    f
+                    for f in map["target_faces_in_frame"]
+                    if f["location"] == temp_frame_path
+                ]
 
                 for frame in target_frame:
-                    for target_face in frame['faces']:
+                    for target_face in frame["faces"]:
                         temp_frame = swap_face(source_face, target_face, temp_frame)
 
         elif not modules.globals.many_faces:
-            for map_entry in modules.globals.souce_target_map: # Renamed 'map' to 'map_entry'
+            for map in modules.globals.source_target_map:
-                if "source" in map_entry:
+                if "source" in map:
-                    target_frame = [f for f in map_entry['target_faces_in_frame'] if f['location'] == temp_frame_path]
+                    target_frame = [
-                    source_face = map_entry['source']['face']
+                        f
+                        for f in map["target_faces_in_frame"]
+                        if f["location"] == temp_frame_path
+                    ]
+                    source_face = map["source"]["face"]
 
                     for frame in target_frame:
-                        for target_face in frame['faces']:
+                        for target_face in frame["faces"]:
                             temp_frame = swap_face(source_face, target_face, temp_frame)
-    else: # Fallback for neither image nor video (e.g., live feed?)
+
+    else:
         detected_faces = get_many_faces(temp_frame)
         if modules.globals.many_faces:
             if detected_faces:
@@ -162,97 +177,451 @@ 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:
-            if detected_faces and hasattr(modules.globals, 'simple_map') and modules.globals.simple_map: # Check simple_map exists
+            if detected_faces:
-                if len(detected_faces) <= len(modules.globals.simple_map['target_embeddings']):
+                if len(detected_faces) <= len(
+                    modules.globals.simple_map["target_embeddings"]
+                ):
                     for detected_face in detected_faces:
-                        closest_centroid_index, _ = find_closest_centroid(modules.globals.simple_map['target_embeddings'], detected_face.normed_embedding)
+                        closest_centroid_index, _ = find_closest_centroid(
-                        temp_frame = swap_face(modules.globals.simple_map['source_faces'][closest_centroid_index], detected_face, temp_frame)
+                            modules.globals.simple_map["target_embeddings"],
+                            detected_face.normed_embedding,
+                        )
+
+                        temp_frame = swap_face(
+                            modules.globals.simple_map["source_faces"][
+                                closest_centroid_index
+                            ],
+                            detected_face,
+                            temp_frame,
+                        )
                 else:
-                    detected_faces_centroids = [face.normed_embedding for face in detected_faces]
+                    detected_faces_centroids = []
+                    for face in detected_faces:
+                        detected_faces_centroids.append(face.normed_embedding)
                     i = 0
-                    for target_embedding in modules.globals.simple_map['target_embeddings']:
+                    for target_embedding in modules.globals.simple_map[
-                        closest_centroid_index, _ = find_closest_centroid(detected_faces_centroids, target_embedding)
+                        "target_embeddings"
-                        # Ensure index is valid before accessing detected_faces
+                    ]:
-                        if closest_centroid_index < len(detected_faces):
+                        closest_centroid_index, _ = find_closest_centroid(
-                            temp_frame = swap_face(modules.globals.simple_map['source_faces'][i], detected_faces[closest_centroid_index], temp_frame)
+                            detected_faces_centroids, target_embedding
+                        )
+
+                        temp_frame = swap_face(
+                            modules.globals.simple_map["source_faces"][i],
+                            detected_faces[closest_centroid_index],
+                            temp_frame,
+                        )
                         i += 1
     return temp_frame
 
 
-def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
+def process_frames(
-    # --- No changes needed in process_frames ---
+    source_path: str, temp_frame_paths: List[str], progress: Any = None
-    # Note: Ensure get_one_face is called only once if possible for efficiency if !map_faces
+) -> None:
-    source_face = None
     if not modules.globals.map_faces:
-        source_img = cv2.imread(source_path)
+        source_face = get_one_face(cv2.imread(source_path))
-        if source_img is not None:
+        for temp_frame_path in temp_frame_paths:
-            source_face = get_one_face(source_img)
+            temp_frame = cv2.imread(temp_frame_path)
-        if source_face is None:
+            try:
-             update_status(f"Could not find face in source image: {source_path}, skipping swap.", NAME)
+                result = process_frame(source_face, temp_frame)
-             # If no source face, maybe skip processing? Or handle differently.
+                cv2.imwrite(temp_frame_path, result)
-             # For now, it will proceed but swap_face might fail later.
+            except Exception as exception:
-
+                print(exception)
-    for temp_frame_path in temp_frame_paths:
+                pass
-        temp_frame = cv2.imread(temp_frame_path)
+            if progress:
-        if temp_frame is None:
+                progress.update(1)
-            update_status(f"Warning: Could not read frame {temp_frame_path}", NAME)
+    else:
-            if progress: progress.update(1) # Still update progress even if frame fails
+        for temp_frame_path in temp_frame_paths:
-            continue # Skip to next frame
+            temp_frame = cv2.imread(temp_frame_path)
-
+            try:
-        try:
+                result = process_frame_v2(temp_frame, temp_frame_path)
-            if not modules.globals.map_faces:
+                cv2.imwrite(temp_frame_path, result)
-                if source_face: # Only process if source face was found
+            except Exception as exception:
-                    result = process_frame(source_face, temp_frame)
+                print(exception)
-                else:
+                pass
-                    result = temp_frame # No source face, return original frame
-            else:
-                 result = process_frame_v2(temp_frame, temp_frame_path)
-
-            cv2.imwrite(temp_frame_path, result)
-        except Exception as exception:
-            update_status(f"Error processing frame {os.path.basename(temp_frame_path)}: {exception}", NAME)
-            # Decide whether to 'pass' (continue processing other frames) or raise
-            pass # Continue processing other frames
-        finally:
             if progress:
                 progress.update(1)
 
 
 def process_image(source_path: str, target_path: str, output_path: str) -> None:
-    # --- No changes needed in process_image ---
-    # Note: Added checks for successful image reads and face detection
-    target_frame = cv2.imread(target_path) # Read original target for processing
-    if target_frame is None:
-        update_status(f"Error: Could not read target image: {target_path}", NAME)
-        return
-
     if not modules.globals.map_faces:
-        source_img = cv2.imread(source_path)
+        source_face = get_one_face(cv2.imread(source_path))
-        if source_img is None:
+        target_frame = cv2.imread(target_path)
-             update_status(f"Error: Could not read source image: {source_path}", NAME)
-             return
-        source_face = get_one_face(source_img)
-        if source_face is None:
-            update_status(f"Error: No face found in source image: {source_path}", NAME)
-            return
-
         result = process_frame(source_face, target_frame)
+        cv2.imwrite(output_path, result)
     else:
         if modules.globals.many_faces:
-            update_status('Many faces enabled. Using first source image (if applicable in v2). Processing...', NAME)
+            update_status(
-        # For process_frame_v2 on single image, it reads the 'output_path' which should be a copy
+                "Many faces enabled. Using first source image. Progressing...", NAME
-        # Let's process the 'target_frame' we read instead.
+            )
-        result = process_frame_v2(target_frame) # Process the frame directly
+        target_frame = cv2.imread(output_path)
-
+        result = process_frame_v2(target_frame)
-    # Write the final result to the output path
+        cv2.imwrite(output_path, result)
-    success = cv2.imwrite(output_path, result)
-    if not success:
-        update_status(f"Error: Failed to write output image to: {output_path}", NAME)
 
 
 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
-    # --- No changes needed in process_video ---
     if modules.globals.map_faces and modules.globals.many_faces:
-        update_status('Many faces enabled. Using first source image (if applicable in v2). Processing...', NAME)
+        update_status(
-    # The core processing logic is delegated, which is good.
+            "Many faces enabled. Using first source image. Progressing...", NAME
-    modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)
+        )
+    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)

modules/ui.py

@@ -429,7 +429,7 @@ def create_source_target_popup(
             POPUP.destroy()
             select_output_path(start)
         else:
-            update_pop_status("Atleast 1 source with target is required!")
+            update_pop_status("At least 1 source with target is required!")
 
     scrollable_frame = ctk.CTkScrollableFrame(
         POPUP, width=POPUP_SCROLL_WIDTH, height=POPUP_SCROLL_HEIGHT
@@ -489,7 +489,7 @@ def update_popup_source(
     global source_label_dict
 
     source_path = ctk.filedialog.askopenfilename(
-        title=_("select an source image"),
+        title=_("select a source image"),
         initialdir=RECENT_DIRECTORY_SOURCE,
         filetypes=[img_ft],
     )
@@ -584,7 +584,7 @@ def select_source_path() -> None:
 
     PREVIEW.withdraw()
     source_path = ctk.filedialog.askopenfilename(
-        title=_("select an source image"),
+        title=_("select a source image"),
         initialdir=RECENT_DIRECTORY_SOURCE,
         filetypes=[img_ft],
     )
@@ -627,7 +627,7 @@ def select_target_path() -> None:
 
     PREVIEW.withdraw()
     target_path = ctk.filedialog.askopenfilename(
-        title=_("select an target image or video"),
+        title=_("select a target image or video"),
         initialdir=RECENT_DIRECTORY_TARGET,
         filetypes=[img_ft, vid_ft],
     )
@@ -1108,7 +1108,7 @@ def update_webcam_source(
     global source_label_dict_live
 
     source_path = ctk.filedialog.askopenfilename(
-        title=_("select an source image"),
+        title=_("select a source image"),
         initialdir=RECENT_DIRECTORY_SOURCE,
         filetypes=[img_ft],
     )
@@ -1160,7 +1160,7 @@ def update_webcam_target(
     global target_label_dict_live
 
     target_path = ctk.filedialog.askopenfilename(
-        title=_("select an target image"),
+        title=_("select a target image"),
         initialdir=RECENT_DIRECTORY_SOURCE,
         filetypes=[img_ft],
     )

requirements.txt

@@ -1,23 +1,21 @@
+--extra-index-url https://download.pytorch.org/whl/cu128
+
 numpy>=1.23.5,<2
 typing-extensions>=4.8.0
-opencv-python==4.11.0.86
+opencv-python==4.10.0.84
-onnx==1.17.0
+cv2_enumerate_cameras==1.1.15
-cv2_enumerate_cameras==1.1.18.3
+onnx==1.18.0
 insightface==0.7.3
 psutil==5.9.8
 tk==0.1.0
 customtkinter==5.2.2
 pillow==11.1.0
-torch; sys_platform != 'darwin' --index-url https://download.pytorch.org/whl/cu126
+torch; sys_platform != 'darwin'
-torch; sys_platform == 'darwin' --index-url https://download.pytorch.org/whl/cu126
+torch==2.5.1; sys_platform == 'darwin'
-torchvision; sys_platform != 'darwin' --index-url https://download.pytorch.org/whl/cu126
+torchvision; sys_platform != 'darwin'
-torchvision; sys_platform == 'darwin' --index-url https://download.pytorch.org/whl/cu126
+torchvision==0.20.1; sys_platform == 'darwin'
 onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64'
-onnxruntime-gpu==1.21; sys_platform != 'darwin'
+onnxruntime-gpu==1.22.0; sys_platform != 'darwin'
 tensorflow; sys_platform != 'darwin'
 opennsfw2==0.10.2
-protobuf==4.23.2
+protobuf==4.25.1
-tqdm==4.66.4
-gfpgan==1.3.8
-tkinterdnd2==0.4.2
-pygrabber==0.2