add Drag and drop functionality

Update ui.py
2025-03-26 13:08:18 +05:30 · 2025-03-26 12:14:29 +05:30
30 changed files with 709 additions and 2711 deletions
@@ -1,4 +1,4 @@
-<h1 align="center">Deep-Live-Cam 2.0.2c</h1>
+<h1 align="center">Deep-Live-Cam</h1>

 <p align="center">
  Real-time face swap and video deepfake with a single click and only a single image.
@@ -30,13 +30,14 @@ 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 v2.4 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.
 
-###### 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)
@@ -98,7 +99,7 @@ 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 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 +110,7 @@ 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)```
@@ -133,34 +134,26 @@ 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 3.11 (specific version is important)
-brew install python@3.11
+# Install Python 3.10 (specific version is important)
+brew install python@3.10

 # 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
+# Create and activate virtual environment with Python 3.10
+python3.10 -m venv venv
 source venv/bin/activate

 # Install dependencies
@@ -179,11 +172,6 @@ source venv/bin/activate

 # install the dependencies again
 pip install -r requirements.txt
-
-# gfpgan and basicsrs issue fix
-pip install git+https://github.com/xinntao/BasicSR.git@master
-pip uninstall gfpgan -y
-pip install git+https://github.com/TencentARC/GFPGAN.git@master
 ```

 **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).
@@ -192,16 +180,12 @@ pip install git+https://github.com/TencentARC/GFPGAN.git@master

 **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 11.8.0](https://developer.nvidia.com/cuda-11-8-0-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:
@@ -241,7 +225,7 @@ 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 3.11
+  # Keep only Python 3.10
  brew cleanup
  ```

@@ -251,7 +235,7 @@ python3.10 run.py --execution-provider coreml

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

 2. Usage:
@@ -266,7 +250,7 @@ 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:
@@ -281,7 +265,7 @@ 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:
@@ -309,6 +293,19 @@ 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)

 ```
@@ -352,15 +349,10 @@ 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)
- - [*"Als Sean Connery an der Redaktionskonferenz teilnahm"*](https://www.golem.de/news/deepfakes-als-sean-connery-an-der-redaktionskonferenz-teilnahm-2408-188172.html) - Golem.de (German)
- - [*"What the F***! Why do I look like Vinny Jr? I look exactly like Vinny Jr!? No, this shit is crazy! Bro This is F*** Crazy! "*](https://youtu.be/JbUPRmXRUtE?t=3964) - IShowSpeed
-

 ## Credits

 -   [ffmpeg](https://ffmpeg.org/): for making video-related operations easy
-   [Henry](https://github.com/henryruhs): One of the major contributor in this repo
 -   [deepinsight](https://github.com/deepinsight): for their [insightface](https://github.com/deepinsight/insightface) project which provided a well-made library and models. Please be reminded that the [use of the model is for non-commercial research purposes only](https://github.com/deepinsight/insightface?tab=readme-ov-file#license).
 -   [havok2-htwo](https://github.com/havok2-htwo): for sharing the code for webcam
 -   [GosuDRM](https://github.com/GosuDRM): for the open version of roop
@@ -386,4 +378,4 @@ Looking for a CLI mode? Using the -s/--source argument will make the run program
   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=hacksider/deep-live-cam&type=Date" />
   <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=hacksider/deep-live-cam&type=Date" />
 </picture>
-</a>
+</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": "Pemetaan Sumber x Target",
-    "select a source image": "Pilih gambar sumber",
-    "Preview": "Pratinjau",
-    "select a target image or video": "Pilih gambar atau video target",
-    "save image output file": "Simpan file keluaran gambar",
-    "save video output file": "Simpan file keluaran video",
-    "select a target image": "Pilih gambar target",
-    "source": "Sumber",
-    "Select a target": "Pilih target",
-    "Select a face": "Pilih wajah",
-    "Keep audio": "Pertahankan audio",
-    "Face Enhancer": "Peningkat wajah",
-    "Many faces": "Banyak wajah",
-    "Show FPS": "Tampilkan FPS",
-    "Keep fps": "Pertahankan FPS",
-    "Keep frames": "Pertahankan frame",
-    "Fix Blueish Cam": "Perbaiki kamera kebiruan",
-    "Mouth Mask": "Masker mulut",
-    "Show Mouth Mask Box": "Tampilkan kotak masker mulut",
-    "Start": "Mulai",
-    "Live": "Langsung",
-    "Destroy": "Hentikan",
-    "Map faces": "Petakan wajah",
-    "Processing...": "Sedang memproses...",
-    "Processing succeed!": "Pemrosesan berhasil!",
-    "Processing ignored!": "Pemrosesan diabaikan!",
-    "Failed to start camera": "Gagal memulai kamera",
-    "Please complete pop-up or close it.": "Harap selesaikan atau tutup pop-up.",
-    "Getting unique faces": "Mengambil wajah unik",
-    "Please select a source image first": "Silakan pilih gambar sumber terlebih dahulu",
-    "No faces found in target": "Tidak ada wajah ditemukan pada target",
-    "Add": "Tambah",
-    "Clear": "Bersihkan",
-    "Submit": "Kirim",
-    "Select source image": "Pilih gambar sumber",
-    "Select target image": "Pilih gambar target",
-    "Please provide mapping!": "Harap tentukan pemetaan!",
-    "At least 1 source with target is required!": "Minimal 1 sumber dengan target diperlukan!",
-    "Face could not be detected in last upload!": "Wajah tidak dapat terdeteksi pada unggahan terakhir!",
-    "Select Camera:": "Pilih Kamera:",
-    "All mappings cleared!": "Semua pemetaan telah dibersihkan!",
-    "Mappings successfully submitted!": "Pemetaan berhasil dikirim!",
-    "Source x Target Mapper is already open.": "Pemetaan Sumber x Target sudah terbuka."
-}
@@ -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
@@ -129,22 +129,11 @@ def suggest_execution_providers() -> List[str]:


 def suggest_execution_threads() -> int:
-    """Suggest optimal thread count based on hardware and execution provider."""
-    import os
-    
-    # Get CPU count
-    cpu_count = os.cpu_count() or 4
-    
    if 'DmlExecutionProvider' in modules.globals.execution_providers:
        return 1
    if 'ROCMExecutionProvider' in modules.globals.execution_providers:
        return 1
-    if 'CUDAExecutionProvider' in modules.globals.execution_providers:
-        # For CUDA, use more threads for parallel frame processing
-        return min(cpu_count, 16)
-    
-    # For CPU execution, use most cores but leave some for system
-    return max(4, min(cpu_count - 2, 16))
+    return 8


 def limit_resources() -> None:
@@ -187,16 +176,10 @@ def update_status(message: str, scope: str = 'DLC.CORE') -> None:
        ui.update_status(message)

 def start() -> None:
-    """Start processing with performance monitoring."""
-    import time
-    
-    start_time = time.time()
-    
    for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
        if not frame_processor.pre_start():
            return
    update_status('Processing...')
-    
    # process image to image
    if has_image_extension(modules.globals.target_path):
        if modules.globals.nsfw_filter and ui.check_and_ignore_nsfw(modules.globals.target_path, destroy):
@@ -210,40 +193,26 @@ def start() -> None:
            frame_processor.process_image(modules.globals.source_path, modules.globals.output_path, modules.globals.output_path)
            release_resources()
        if is_image(modules.globals.target_path):
-            elapsed = time.time() - start_time
-            update_status(f'Processing to image succeed! (Time: {elapsed:.2f}s)')
+            update_status('Processing to image succeed!')
        else:
            update_status('Processing to image failed!')
        return
-    
    # process image to videos
    if modules.globals.nsfw_filter and ui.check_and_ignore_nsfw(modules.globals.target_path, destroy):
        return

-    extraction_start = time.time()
    if not modules.globals.map_faces:
        update_status('Creating temp resources...')
        create_temp(modules.globals.target_path)
        update_status('Extracting frames...')
        extract_frames(modules.globals.target_path)
-    extraction_time = time.time() - extraction_start
-    update_status(f'Frame extraction completed in {extraction_time:.2f}s')

    temp_frame_paths = get_temp_frame_paths(modules.globals.target_path)
-    total_frames = len(temp_frame_paths)
-    update_status(f'Processing {total_frames} frames with {modules.globals.execution_threads} threads...')
-    
-    processing_start = time.time()
    for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
        update_status('Progressing...', frame_processor.NAME)
        frame_processor.process_video(modules.globals.source_path, temp_frame_paths)
        release_resources()
-    processing_time = time.time() - processing_start
-    fps_processing = total_frames / processing_time if processing_time > 0 else 0
-    update_status(f'Frame processing completed in {processing_time:.2f}s ({fps_processing:.2f} fps)')
-    
    # handles fps
-    encoding_start = time.time()
    if modules.globals.keep_fps:
        update_status('Detecting fps...')
        fps = detect_fps(modules.globals.target_path)
@@ -252,9 +221,6 @@ def start() -> None:
    else:
        update_status('Creating video with 30.0 fps...')
        create_video(modules.globals.target_path)
-    encoding_time = time.time() - encoding_start
-    update_status(f'Video encoding completed in {encoding_time:.2f}s')
-    
    # handle audio
    if modules.globals.keep_audio:
        if modules.globals.keep_fps:
@@ -264,13 +230,10 @@ def start() -> None:
        restore_audio(modules.globals.target_path, modules.globals.output_path)
    else:
        move_temp(modules.globals.target_path, modules.globals.output_path)
-    
    # clean and validate
    clean_temp(modules.globals.target_path)
-    
-    total_time = time.time() - start_time
    if is_video(modules.globals.target_path):
-        update_status(f'Processing to video succeed! Total time: {total_time:.2f}s')
+        update_status('Processing to video succeed!')
    else:
        update_status('Processing to video failed!')

@@ -1,7 +0,0 @@
-from typing import Any
-
-from insightface.app.common import Face
-import numpy
- 
-Face = Face
-Frame = numpy.ndarray[Any, Any] 
@@ -2,7 +2,6 @@ import os
 import shutil
 from typing import Any
 import insightface
-import threading

 import cv2
 import numpy as np
@@ -14,22 +13,14 @@ from modules.utilities import get_temp_directory_path, create_temp, extract_fram
 from pathlib import Path

 FACE_ANALYSER = None
-FACE_ANALYSER_LOCK = threading.Lock()


 def get_face_analyser() -> Any:
-    """Get face analyser with thread-safe initialization."""
    global FACE_ANALYSER

    if FACE_ANALYSER is None:
-        with FACE_ANALYSER_LOCK:
-            # Double-check after acquiring lock
-            if FACE_ANALYSER is None:
-                FACE_ANALYSER = insightface.app.FaceAnalysis(
-                    name='buffalo_l',
-                    providers=modules.globals.execution_providers
-                )
-                FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640))
+        FACE_ANALYSER = insightface.app.FaceAnalysis(name='buffalo_l', providers=modules.globals.execution_providers)
+        FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640))
    return FACE_ANALYSER


@@ -1,5 +1,3 @@
-# --- START OF FILE globals.py ---
-
 import os
 from typing import List, Dict, Any

@@ -11,62 +9,35 @@ file_types = [
    ("Video", ("*.mp4", "*.mkv")),
 ]

-# Face Mapping Data
-source_target_map: List[Dict[str, Any]] = [] # Stores detailed map for image/video processing
-simple_map: Dict[str, Any] = {}             # Stores simplified map (embeddings/faces) for live/simple mode
+source_target_map = []
+simple_map = {}

-# Paths
-source_path: str | None = None
-target_path: str | None = None
-output_path: str | None = None
-
-# Processing Options
+source_path = None
+target_path = None
+output_path = None
 frame_processors: List[str] = []
-keep_fps: bool = True
-keep_audio: bool = True
-keep_frames: bool = False
-many_faces: bool = False         # Process all detected faces with default source
-map_faces: bool = False          # Use source_target_map or simple_map for specific swaps
-poisson_blend: bool = False      # Enable Poisson Blending for smoother face swaps
-color_correction: bool = False   # Enable color correction (implementation specific)
-nsfw_filter: bool = False
-
-# Video Output Options
-video_encoder: str | None = None
-video_quality: int | None = None # Typically a CRF value or bitrate
-
-# Live Mode Options
-live_mirror: bool = False
-live_resizable: bool = True
-camera_input_combobox: Any | None = None # Placeholder for UI element if needed
-webcam_preview_running: bool = False
-show_fps: bool = False
-
-# System Configuration
-max_memory: int | None = None        # Memory limit in GB? (Needs clarification)
-execution_providers: List[str] = []  # e.g., ['CUDAExecutionProvider', 'CPUExecutionProvider']
-execution_threads: int | None = None # Number of threads for CPU execution
-headless: bool | None = None         # Run without UI?
-log_level: str = "error"             # Logging level (e.g., 'debug', 'info', 'warning', 'error')
-
-# Face Processor UI Toggles (Example)
+keep_fps = True
+keep_audio = True
+keep_frames = False
+many_faces = False
+map_faces = False
+color_correction = False  # New global variable for color correction toggle
+nsfw_filter = False
+video_encoder = None
+video_quality = None
+live_mirror = False
+live_resizable = True
+max_memory = None
+execution_providers: List[str] = []
+execution_threads = None
+headless = None
+log_level = "error"
 fp_ui: Dict[str, bool] = {"face_enhancer": False}
-
-# Face Swapper Specific Options
-face_swapper_enabled: bool = True # General toggle for the swapper processor
-opacity: float = 1.0              # Blend factor for the swapped face (0.0-1.0)
-sharpness: float = 0.0            # Sharpness enhancement for swapped face (0.0-1.0+)
-
-# Mouth Mask Options
-mouth_mask: bool = False           # Enable mouth area masking/pasting
-show_mouth_mask_box: bool = False  # Visualize the mouth mask area (for debugging)
-mask_feather_ratio: int = 12       # Denominator for feathering calculation (higher = smaller feather)
-mask_down_size: float = 0.1        # Expansion factor for lower lip mask (relative)
-mask_size: float = 1.0             # Expansion factor for upper lip mask (relative)
-
-# --- START: Added for Frame Interpolation ---
-enable_interpolation: bool = True # Toggle temporal smoothing
-interpolation_weight: float = 0  # Blend weight for current frame (0.0-1.0). Lower=smoother.
-# --- END: Added for Frame Interpolation ---
-
-# --- END OF FILE globals.py ---
+camera_input_combobox = None
+webcam_preview_running = False
+show_fps = False
+mouth_mask = False
+show_mouth_mask_box = False
+mask_feather_ratio = 8
+mask_down_size = 0.50
+mask_size = 1
@@ -1,3 +1,3 @@
 name = 'Deep-Live-Cam'
-version = '2.0.3c'
-edition = 'GitHub Edition'
+version = '1.8'
+edition = 'GitHub Edition'
@@ -42,54 +42,27 @@ 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:
-    """Process frames in parallel with optimized batching and memory management."""
-    max_workers = modules.globals.execution_threads
-    
-    # Determine optimal batch size based on available memory and thread count
-    # Process frames in batches to avoid memory overflow
-    batch_size = max(1, min(32, len(temp_frame_paths) // max(1, max_workers)))
-    
-    with ThreadPoolExecutor(max_workers=max_workers) as executor:
-        # Process in batches to manage memory better
-        for i in range(0, len(temp_frame_paths), batch_size):
-            batch = temp_frame_paths[i:i + batch_size]
-            futures = []
-            
-            for path in batch:
-                future = executor.submit(process_frames, source_path, [path], progress)
-                futures.append(future)
-            
-            # Wait for batch to complete before starting next batch
-            for future in futures:
-                try:
-                    future.result()
-                except Exception as e:
-                    print(f"Error processing frame: {e}")
+    with ThreadPoolExecutor(max_workers=modules.globals.execution_threads) as executor:
+        futures = []
+        for path in temp_frame_paths:
+            future = executor.submit(process_frames, source_path, [path], progress)
+            futures.append(future)
+        for future in futures:
+            future.result()


 def process_video(source_path: str, frame_paths: list[str], process_frames: Callable[[str, List[str], Any], None]) -> None:
@@ -1,18 +1,16 @@
-# --- START OF FILE face_enhancer.py ---
-
 from typing import Any, List
 import cv2
 import threading
 import gfpgan
 import os
-import platform
-import torch # Make sure torch is imported

 import modules.globals
 import modules.processors.frame.core
 from modules.core import update_status
 from modules.face_analyser import get_one_face
 from modules.typing import Frame, Face
+import platform
+import torch
 from modules.utilities import (
    conditional_download,
    is_image,
@@ -51,156 +49,61 @@ def pre_start() -> bool:


 def get_face_enhancer() -> Any:
-    """
-    Initializes and returns the GFPGAN face enhancer instance,
-    prioritizing CUDA, then MPS (Mac), then CPU.
-    """
    global FACE_ENHANCER

    with THREAD_LOCK:
        if FACE_ENHANCER is None:
            model_path = os.path.join(models_dir, "GFPGANv1.4.pth")
-            device = None
-            try:
-                # Priority 1: CUDA
-                if torch.cuda.is_available():
-                    device = torch.device("cuda")
-                    print(f"{NAME}: Using CUDA device.")
-                # Priority 2: MPS (Mac Silicon)
-                elif platform.system() == "Darwin" and torch.backends.mps.is_available():
-                    device = torch.device("mps")
-                    print(f"{NAME}: Using MPS device.")
-                # Priority 3: CPU
-                else:
-                    device = torch.device("cpu")
-                    print(f"{NAME}: Using CPU device.")
-
-                FACE_ENHANCER = gfpgan.GFPGANer(
-                    model_path=model_path,
-                    upscale=1,  # upscale=1 means enhancement only, no resizing
-                    arch='clean',
-                    channel_multiplier=2,
-                    bg_upsampler=None,
-                    device=device
-                )
-                print(f"{NAME}: GFPGANer initialized successfully on {device}.")
-
-            except Exception as e:
-                print(f"{NAME}: Error initializing GFPGANer: {e}")
-                # Fallback to CPU if initialization with GPU fails for some reason
-                if device is not None and device.type != 'cpu':
-                    print(f"{NAME}: Falling back to CPU due to error.")
-                    try:
-                        device = torch.device("cpu")
-                        FACE_ENHANCER = gfpgan.GFPGANer(
-                            model_path=model_path,
-                            upscale=1,
-                            arch='clean',
-                            channel_multiplier=2,
-                            bg_upsampler=None,
-                            device=device
-                        )
-                        print(f"{NAME}: GFPGANer initialized successfully on CPU after fallback.")
-                    except Exception as fallback_e:
-                         print(f"{NAME}: FATAL: Could not initialize GFPGANer even on CPU: {fallback_e}")
-                         FACE_ENHANCER = None # Ensure it's None if totally failed
-                else:
-                    # If it failed even on the first CPU attempt or device was already CPU
-                     print(f"{NAME}: FATAL: Could not initialize GFPGANer on CPU: {e}")
-                     FACE_ENHANCER = None # Ensure it's None if totally failed
-
-
-    # Check if enhancer is still None after attempting initialization
-    if FACE_ENHANCER is None:
-        raise RuntimeError(f"{NAME}: Failed to initialize GFPGANer. Check logs for errors.")
+            
+            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]

    return FACE_ENHANCER


 def enhance_face(temp_frame: Frame) -> Frame:
-    """Enhances faces in a single frame using the global GFPGANer instance."""
-    # Ensure enhancer is ready
-    enhancer = get_face_enhancer()
-    try:
-        with THREAD_SEMAPHORE:
-            # The enhance method returns: _, restored_faces, restored_img
-            _, _, restored_img = enhancer.enhance(
-                temp_frame,
-                has_aligned=False, # Assume faces are not pre-aligned
-                only_center_face=False, # Enhance all detected faces
-                paste_back=True # Paste enhanced faces back onto the original image
-            )
-        # GFPGAN might return None if no face is detected or an error occurs
-        if restored_img is None:
-            # print(f"{NAME}: Warning: GFPGAN enhancement returned None. Returning original frame.")
-            return temp_frame
-        return restored_img
-    except Exception as e:
-        print(f"{NAME}: Error during face enhancement: {e}")
-        # Return the original frame in case of error during enhancement
-        return temp_frame
+    with THREAD_SEMAPHORE:
+        _, _, temp_frame = get_face_enhancer().enhance(temp_frame, paste_back=True)
+    return temp_frame


-def process_frame(source_face: Face | None, temp_frame: Frame) -> Frame:
-    """Processes a frame: enhances face if detected."""
-    # We don't strictly need source_face for enhancement only
-    # Check if any face exists to potentially save processing time, though GFPGAN also does detection.
-    # For simplicity and ensuring enhancement is attempted if possible, we can rely on enhance_face.
-    # target_face = get_one_face(temp_frame) # This gets only ONE face
-    # If you want to enhance ONLY if a face is detected by your *own* analyser first:
-    # has_face = get_one_face(temp_frame) is not None # Or use get_many_faces
-    # if has_face:
-    #     temp_frame = enhance_face(temp_frame)
-    # else: # Enhance regardless, let GFPGAN handle detection
-    temp_frame = enhance_face(temp_frame)
+def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
+    target_face = get_one_face(temp_frame)
+    if target_face:
+        temp_frame = enhance_face(temp_frame)
    return temp_frame


 def process_frames(
-    source_path: str | None, temp_frame_paths: List[str], progress: Any = None
+    source_path: str, temp_frame_paths: List[str], progress: Any = None
 ) -> None:
-    """Processes multiple frames from file paths."""
    for temp_frame_path in temp_frame_paths:
-        if not os.path.exists(temp_frame_path):
-            print(f"{NAME}: Warning: Frame path not found {temp_frame_path}, skipping.")
-            if progress:
-                progress.update(1)
-            continue
-
        temp_frame = cv2.imread(temp_frame_path)
-        if temp_frame is None:
-            print(f"{NAME}: Warning: Failed to read frame {temp_frame_path}, skipping.")
-            if progress:
-                progress.update(1)
-            continue
-
-        result_frame = process_frame(None, temp_frame)
-        cv2.imwrite(temp_frame_path, result_frame)
+        result = process_frame(None, temp_frame)
+        cv2.imwrite(temp_frame_path, result)
        if progress:
            progress.update(1)


-def process_image(source_path: str | None, target_path: str, output_path: str) -> None:
-    """Processes a single image file."""
+def process_image(source_path: str, target_path: str, output_path: str) -> None:
    target_frame = cv2.imread(target_path)
-    if target_frame is None:
-        print(f"{NAME}: Error: Failed to read target image {target_path}")
-        return
-    result_frame = process_frame(None, target_frame)
-    cv2.imwrite(output_path, result_frame)
-    print(f"{NAME}: Enhanced image saved to {output_path}")
+    result = process_frame(None, target_frame)
+    cv2.imwrite(output_path, result)


-def process_video(source_path: str | None, temp_frame_paths: List[str]) -> None:
-    """Processes video frames using the frame processor core."""
-    # source_path might be optional depending on how process_video is called
-    modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)
+def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
+    modules.processors.frame.core.process_video(None, temp_frame_paths, process_frames)

-# Optional: Keep process_frame_v2 if it's used elsewhere, otherwise it's redundant
-# def process_frame_v2(temp_frame: Frame) -> Frame:
-#     target_face = get_one_face(temp_frame)
-#     if target_face:
-#         temp_frame = enhance_face(temp_frame)
-#     return temp_frame

-# --- END OF FILE face_enhancer.py ---
+def process_frame_v2(temp_frame: Frame) -> Frame:
+    target_face = get_one_face(temp_frame)
+    if target_face:
+        temp_frame = enhance_face(temp_frame)
+    return temp_frame
@@ -1,566 +0,0 @@
-import cv2
-import numpy as np
-from modules.typing import Face, Frame
-import modules.globals
-
-def apply_color_transfer(source, target):
-    """
-    Apply color transfer from target to source image
-    """
-    source = cv2.cvtColor(source, cv2.COLOR_BGR2LAB).astype("float32")
-    target = cv2.cvtColor(target, cv2.COLOR_BGR2LAB).astype("float32")
-
-    source_mean, source_std = cv2.meanStdDev(source)
-    target_mean, target_std = cv2.meanStdDev(target)
-
-    # Reshape mean and std to be broadcastable
-    source_mean = source_mean.reshape(1, 1, 3)
-    source_std = source_std.reshape(1, 1, 3)
-    target_mean = target_mean.reshape(1, 1, 3)
-    target_std = target_std.reshape(1, 1, 3)
-
-    # Perform the color transfer
-    source = (source - source_mean) * (target_std / source_std) + target_mean
-
-    return cv2.cvtColor(np.clip(source, 0, 255).astype("uint8"), cv2.COLOR_LAB2BGR)
-
-def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
-    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
-    landmarks = face.landmark_2d_106
-    if landmarks is not None:
-        # Convert landmarks to int32
-        landmarks = landmarks.astype(np.int32)
-
-        # Extract facial features
-        right_side_face = landmarks[0:16]
-        left_side_face = landmarks[17:32]
-        right_eye = landmarks[33:42]
-        right_eye_brow = landmarks[43:51]
-        left_eye = landmarks[87:96]
-        left_eye_brow = landmarks[97:105]
-
-        # Calculate 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
-        face_outline = landmarks[0:33]
-        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
-    lower_lip_polygon = None
-    mouth_box = (0,0,0,0)
-
-    landmarks = face.landmark_2d_106
-    if landmarks is not None:
-        # Use outer mouth landmarks (52-63) to capture the lips only
-        lower_lip_order = list(range(52, 64))
-        
-        if max(lower_lip_order) >= landmarks.shape[0]:
-            return mask, mouth_cutout, mouth_box, lower_lip_polygon
-
-        lower_lip_landmarks = landmarks[lower_lip_order].astype(np.float32)
-
-        # Calculate the center of the landmarks
-        center = np.mean(lower_lip_landmarks, axis=0)
-
-        # Expand the landmarks outward using the mouth_mask_size
-        # Use a more conservative expansion to avoid affecting face shape
-        expansion_factor = (
-            1 + modules.globals.mask_down_size * modules.globals.mouth_mask_size
-        )
-        expanded_landmarks = (lower_lip_landmarks - center) * expansion_factor + center
-
-        # Removed specific top/chin extensions to preserve face shape
-
-        # 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)
-        # Shift polygon coordinates relative to the ROI's top-left corner
-        polygon_relative_to_roi = expanded_landmarks - [min_x, min_y]
-        cv2.fillPoly(mask_roi, [polygon_relative_to_roi], 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
-        mouth_box = (min_x, min_y, max_x, max_y)
-
-    return mask, mouth_cutout, mouth_box, 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
@@ -1,9 +0,0 @@
-#!/usr/bin/env python3
-
-# Import the tkinter fix to patch the ScreenChanged error
-import tkinter_fix
-
-import core
-
-if __name__ == '__main__':
-    core.run()
@@ -1,26 +0,0 @@
-import tkinter
-
-# Only needs to be imported once at the beginning of the application
-def apply_patch():
-    # Create a monkey patch for the internal _tkinter module
-    original_init = tkinter.Tk.__init__
-    
-    def patched_init(self, *args, **kwargs):
-        # Call the original init
-        original_init(self, *args, **kwargs)
-        
-        # Define the missing ::tk::ScreenChanged procedure
-        self.tk.eval("""
-        if {[info commands ::tk::ScreenChanged] == ""} {
-            proc ::tk::ScreenChanged {args} {
-                # Do nothing
-                return
-            }
-        }
-        """)
-    
-    # Apply the monkey patch
-    tkinter.Tk.__init__ = patched_init
-
-# Apply the patch automatically when this module is imported
-apply_patch() 
@@ -7,6 +7,7 @@ from cv2_enumerate_cameras import enumerate_cameras  # Add this import
 from PIL import Image, ImageOps
 import time
 import json
+import tkinterdnd2 as tkdnd
 import modules.globals
 import modules.metadata
 from modules.face_analyser import (
@@ -27,7 +28,6 @@ from modules.utilities import (
 )
 from modules.video_capture import VideoCapturer
 from modules.gettext import LanguageManager
-from modules import globals
 import platform

 if platform.system() == "Windows":
@@ -36,7 +36,7 @@ if platform.system() == "Windows":
 ROOT = None
 POPUP = None
 POPUP_LIVE = None
-ROOT_HEIGHT = 800
+ROOT_HEIGHT = 700
 ROOT_WIDTH = 600

 PREVIEW = None
@@ -98,7 +98,6 @@ def save_switch_states():
        "keep_frames": modules.globals.keep_frames,
        "many_faces": modules.globals.many_faces,
        "map_faces": modules.globals.map_faces,
-        "poisson_blend": modules.globals.poisson_blend,
        "color_correction": modules.globals.color_correction,
        "nsfw_filter": modules.globals.nsfw_filter,
        "live_mirror": modules.globals.live_mirror,
@@ -121,7 +120,6 @@ def load_switch_states():
        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.poisson_blend = switch_states.get("poisson_blend", 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)
@@ -137,50 +135,65 @@ def load_switch_states():
        pass


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

    load_switch_states()

    ctk.deactivate_automatic_dpi_awareness()
-    ctk.set_appearance_mode("system")
+    ctk.set_appearance_mode("dark")
    ctk.set_default_color_theme(resolve_relative_path("ui.json"))

-    root = ctk.CTk()
+    root = tkdnd.TkinterDnD.Tk()
    root.minsize(ROOT_WIDTH, ROOT_HEIGHT)
    root.title(
        f"{modules.metadata.name} {modules.metadata.version} {modules.metadata.edition}"
    )
-    root.configure()
+    root.configure(bg="#050505")
    root.protocol("WM_DELETE_WINDOW", lambda: destroy())

-    source_label = ctk.CTkLabel(root, text=None)
-    source_label.place(relx=0.1, rely=0.05, relwidth=0.275, relheight=0.225)
+    main_frame = ctk.CTkFrame(root, fg_color="#181818", corner_radius=0)
+    main_frame.pack(fill="both", expand=True, padx=0, pady=0)

-    target_label = ctk.CTkLabel(root, text=None)
-    target_label.place(relx=0.6, rely=0.05, relwidth=0.275, relheight=0.225)
+    source_label = ctk.CTkLabel(main_frame, text=None)
+    source_label.place(relx=0.1, rely=0.1, relwidth=0.3, relheight=0.25)
+    
+    source_label.drop_target_register(tkdnd.DND_FILES)
+    source_label.dnd_bind("<<Drop>>", lambda event: handle_drop_source(event))
+
+    target_label = ctk.CTkLabel(main_frame, text=None)
+    target_label.place(relx=0.6, rely=0.1, relwidth=0.3, relheight=0.25)
+    
+    target_label.drop_target_register(tkdnd.DND_FILES)
+    target_label.dnd_bind("<<Drop>>", lambda event: handle_drop_target(event))

    select_face_button = ctk.CTkButton(
-        root, text=_("Select a face"), cursor="hand2", command=lambda: select_source_path()
+        main_frame, text=_("Select a face"), cursor="hand2", command=lambda: select_source_path()
    )
-    select_face_button.place(relx=0.1, rely=0.30, relwidth=0.3, relheight=0.1)
+    select_face_button.place(relx=0.1, rely=0.4, relwidth=0.3, relheight=0.1)
+    
+    select_face_button.drop_target_register(tkdnd.DND_FILES)
+    select_face_button.dnd_bind("<<Drop>>", lambda event: handle_drop_source(event))

    swap_faces_button = ctk.CTkButton(
-        root, text="↔", cursor="hand2", command=lambda: swap_faces_paths()
+        main_frame, text="↔", cursor="hand2", command=lambda: swap_faces_paths()
    )
-    swap_faces_button.place(relx=0.45, rely=0.30, relwidth=0.1, relheight=0.1)
+    swap_faces_button.place(relx=0.45, rely=0.4, relwidth=0.1, relheight=0.1)

    select_target_button = ctk.CTkButton(
-        root,
+        main_frame,
        text=_("Select a target"),
        cursor="hand2",
        command=lambda: select_target_path(),
    )
-    select_target_button.place(relx=0.6, rely=0.30, relwidth=0.3, relheight=0.1)
+    select_target_button.place(relx=0.6, rely=0.4, relwidth=0.3, relheight=0.1)
+    
+    select_target_button.drop_target_register(tkdnd.DND_FILES)
+    select_target_button.dnd_bind("<<Drop>>", lambda event: handle_drop_target(event))

    keep_fps_value = ctk.BooleanVar(value=modules.globals.keep_fps)
    keep_fps_checkbox = ctk.CTkSwitch(
-        root,
+        main_frame,
        text=_("Keep fps"),
        variable=keep_fps_value,
        cursor="hand2",
@@ -189,11 +202,11 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    keep_fps_checkbox.place(relx=0.1, rely=0.5)
+    keep_fps_checkbox.place(relx=0.1, rely=0.6)

    keep_frames_value = ctk.BooleanVar(value=modules.globals.keep_frames)
    keep_frames_switch = ctk.CTkSwitch(
-        root,
+        main_frame,
        text=_("Keep frames"),
        variable=keep_frames_value,
        cursor="hand2",
@@ -202,11 +215,11 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    keep_frames_switch.place(relx=0.1, rely=0.55)
+    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,
+        main_frame,
        text=_("Face Enhancer"),
        variable=enhancer_value,
        cursor="hand2",
@@ -215,11 +228,11 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    enhancer_switch.place(relx=0.1, rely=0.6)
+    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,
+        main_frame,
        text=_("Keep audio"),
        variable=keep_audio_value,
        cursor="hand2",
@@ -228,11 +241,11 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    keep_audio_switch.place(relx=0.6, rely=0.5)
+    keep_audio_switch.place(relx=0.6, rely=0.6)

    many_faces_value = ctk.BooleanVar(value=modules.globals.many_faces)
    many_faces_switch = ctk.CTkSwitch(
-        root,
+        main_frame,
        text=_("Many faces"),
        variable=many_faces_value,
        cursor="hand2",
@@ -241,11 +254,11 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    many_faces_switch.place(relx=0.6, rely=0.55)
+    many_faces_switch.place(relx=0.6, rely=0.65)

    color_correction_value = ctk.BooleanVar(value=modules.globals.color_correction)
    color_correction_switch = ctk.CTkSwitch(
-        root,
+        main_frame,
        text=_("Fix Blueish Cam"),
        variable=color_correction_value,
        cursor="hand2",
@@ -254,15 +267,11 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    color_correction_switch.place(relx=0.6, rely=0.6)
-
-    #    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)
+    color_correction_switch.place(relx=0.6, rely=0.70)

    map_faces = ctk.BooleanVar(value=modules.globals.map_faces)
    map_faces_switch = ctk.CTkSwitch(
-        root,
+        main_frame,
        text=_("Map faces"),
        variable=map_faces,
        cursor="hand2",
@@ -272,24 +281,11 @@ 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=0.65)
-
-    poisson_blend_value = ctk.BooleanVar(value=modules.globals.poisson_blend)
-    poisson_blend_switch = ctk.CTkSwitch(
-        root,
-        text=_("Poisson Blend"),
-        variable=poisson_blend_value,
-        cursor="hand2",
-        command=lambda: (
-            setattr(modules.globals, "poisson_blend", poisson_blend_value.get()),
-            save_switch_states(),
-        ),
-    )
-    poisson_blend_switch.place(relx=0.1, rely=0.7)
+    map_faces_switch.place(relx=0.1, rely=0.75)

    show_fps_value = ctk.BooleanVar(value=modules.globals.show_fps)
    show_fps_switch = ctk.CTkSwitch(
-        root,
+        main_frame,
        text=_("Show FPS"),
        variable=show_fps_value,
        cursor="hand2",
@@ -298,21 +294,21 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            save_switch_states(),
        ),
    )
-    show_fps_switch.place(relx=0.6, rely=0.65)
+    show_fps_switch.place(relx=0.6, rely=0.75)

    mouth_mask_var = ctk.BooleanVar(value=modules.globals.mouth_mask)
    mouth_mask_switch = ctk.CTkSwitch(
-        root,
+        main_frame,
        text=_("Mouth Mask"),
        variable=mouth_mask_var,
        cursor="hand2",
        command=lambda: setattr(modules.globals, "mouth_mask", mouth_mask_var.get()),
    )
-    mouth_mask_switch.place(relx=0.1, rely=0.45)
+    mouth_mask_switch.place(relx=0.1, rely=0.55)

    show_mouth_mask_box_var = ctk.BooleanVar(value=modules.globals.show_mouth_mask_box)
    show_mouth_mask_box_switch = ctk.CTkSwitch(
-        root,
+        main_frame,
        text=_("Show Mouth Mask Box"),
        variable=show_mouth_mask_box_var,
        cursor="hand2",
@@ -320,26 +316,26 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            modules.globals, "show_mouth_mask_box", show_mouth_mask_box_var.get()
        ),
    )
-    show_mouth_mask_box_switch.place(relx=0.6, rely=0.45)
+    show_mouth_mask_box_switch.place(relx=0.6, rely=0.55)

    start_button = ctk.CTkButton(
-        root, text=_("Start"), cursor="hand2", command=lambda: analyze_target(start, root)
+        main_frame, text=_("Start"), cursor="hand2", command=lambda: analyze_target(start, root)
    )
-    start_button.place(relx=0.15, rely=0.86, relwidth=0.2, relheight=0.05)
+    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()
+        main_frame, text=_("Destroy"), cursor="hand2", command=lambda: destroy()
    )
-    stop_button.place(relx=0.4, rely=0.86, relwidth=0.2, relheight=0.05)
+    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()
+        main_frame, text=_("Preview"), cursor="hand2", command=lambda: toggle_preview()
    )
-    preview_button.place(relx=0.65, rely=0.86, relwidth=0.2, relheight=0.05)
+    preview_button.place(relx=0.65, rely=0.80, relwidth=0.2, relheight=0.05)

    # --- Camera Selection ---
-    camera_label = ctk.CTkLabel(root, text=_("Select Camera:"))
-    camera_label.place(relx=0.1, rely=0.92, relwidth=0.2, relheight=0.05)
+    camera_label = ctk.CTkLabel(main_frame, text=_("Select Camera:"))
+    camera_label.place(relx=0.1, rely=0.86, relwidth=0.2, relheight=0.05)

    available_cameras = get_available_cameras()
    camera_indices, camera_names = available_cameras
@@ -347,7 +343,7 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
    if not camera_names or camera_names[0] == "No cameras found":
        camera_variable = ctk.StringVar(value="No cameras found")
        camera_optionmenu = ctk.CTkOptionMenu(
-            root,
+            main_frame,
            variable=camera_variable,
            values=["No cameras found"],
            state="disabled",
@@ -355,13 +351,13 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
    else:
        camera_variable = ctk.StringVar(value=camera_names[0])
        camera_optionmenu = ctk.CTkOptionMenu(
-            root, variable=camera_variable, values=camera_names
+            main_frame, variable=camera_variable, values=camera_names
        )

-    camera_optionmenu.place(relx=0.35, rely=0.92, relwidth=0.25, relheight=0.05)
+    camera_optionmenu.place(relx=0.35, rely=0.86, relwidth=0.25, relheight=0.05)

    live_button = ctk.CTkButton(
-        root,
+        main_frame,
        text=_("Live"),
        cursor="hand2",
        command=lambda: webcam_preview(
@@ -378,82 +374,16 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
            else "disabled"
        ),
    )
-    live_button.place(relx=0.65, rely=0.92, relwidth=0.2, relheight=0.05)
+    live_button.place(relx=0.65, rely=0.86, relwidth=0.2, relheight=0.05)
    # --- End Camera Selection ---

-    # 1) Define a DoubleVar for transparency (0 = fully transparent, 1 = fully opaque)
-    transparency_var = ctk.DoubleVar(value=1.0)
-
-    def on_transparency_change(value: float):
-        # Convert slider value to float
-        val = float(value)
-        modules.globals.opacity = val  # Set global opacity
-        percentage = int(val * 100)
-
-        if percentage == 0:
-            modules.globals.fp_ui["face_enhancer"] = False
-            update_status("Transparency set to 0% - Face swapping disabled.")
-        elif percentage == 100:
-            modules.globals.face_swapper_enabled = True
-            update_status("Transparency set to 100%.")
-        else:
-            modules.globals.face_swapper_enabled = True
-            update_status(f"Transparency set to {percentage}%")
-
-    # 2) Transparency label and slider (placed ABOVE sharpness)
-    transparency_label = ctk.CTkLabel(root, text="Transparency:")
-    transparency_label.place(relx=0.15, rely=0.75, relwidth=0.2, relheight=0.05)
-
-    transparency_slider = ctk.CTkSlider(
-        root,
-        from_=0.0,
-        to=1.0,
-        variable=transparency_var,
-        command=on_transparency_change,
-        fg_color="#E0E0E0",
-        progress_color="#007BFF",
-        button_color="#FFFFFF",
-        button_hover_color="#CCCCCC",
-        height=5,
-        border_width=1,
-        corner_radius=3,
-    )
-    transparency_slider.place(relx=0.35, rely=0.77, relwidth=0.5, relheight=0.02)
-
-    # 3) Sharpness label & slider
-    sharpness_var = ctk.DoubleVar(value=0.0)  # start at 0.0
-    def on_sharpness_change(value: float):
-        modules.globals.sharpness = float(value)
-        update_status(f"Sharpness set to {value:.1f}")
-
-    sharpness_label = ctk.CTkLabel(root, text="Sharpness:")
-    sharpness_label.place(relx=0.15, rely=0.80, relwidth=0.2, relheight=0.05)
-
-    sharpness_slider = ctk.CTkSlider(
-        root,
-        from_=0.0,
-        to=5.0,
-        variable=sharpness_var,
-        command=on_sharpness_change,
-        fg_color="#E0E0E0",
-        progress_color="#007BFF",
-        button_color="#FFFFFF",
-        button_hover_color="#CCCCCC",
-        height=5,
-        border_width=1,
-        corner_radius=3,
-    )
-    sharpness_slider.place(relx=0.35, rely=0.82, relwidth=0.5, relheight=0.02)
-
-    # Status and link at the bottom
-    global status_label
-    status_label = ctk.CTkLabel(root, text=None, justify="center")
-    status_label.place(relx=0.1, rely=0.96, relwidth=0.8)
+    status_label = ctk.CTkLabel(main_frame, text=None, justify="center")
+    status_label.place(relx=0.1, rely=0.9, relwidth=0.8)

    donate_label = ctk.CTkLabel(
-        root, text="Deep Live Cam", justify="center", cursor="hand2"
+        main_frame, text="Deep Live Cam", justify="center", cursor="hand2"
    )
-    donate_label.place(relx=0.1, rely=0.98, relwidth=0.8)
+    donate_label.place(relx=0.1, rely=0.95, relwidth=0.8)
    donate_label.configure(
        text_color=ctk.ThemeManager.theme.get("URL").get("text_color")
    )
@@ -463,7 +393,6 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C

    return root

-
 def close_mapper_window():
    global POPUP, POPUP_LIVE
    if POPUP and POPUP.winfo_exists():
@@ -779,17 +708,21 @@ def check_and_ignore_nsfw(target, destroy: Callable = None) -> bool:


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


@@ -876,7 +809,6 @@ def webcam_preview(root: ctk.CTk, camera_index: int):
        )


-
 def get_available_cameras():
    """Returns a list of available camera names and indices."""
    if platform.system() == "Windows":
@@ -1082,7 +1014,6 @@ def create_source_target_popup_for_webcam(
    close_button.place(relx=0.7, rely=0.92, relwidth=0.2, relheight=0.05)


-
 def clear_source_target_images(map: list):
    global source_label_dict_live, target_label_dict_live

@@ -1282,4 +1213,44 @@ def update_webcam_target(
            target_label_dict_live[button_num] = target_image
        else:
            update_pop_live_status("Face could not be detected in last upload!")
-        return map
+        return map
+
+
+# New drop handler functions
+def handle_drop_source(event):
+    """Handle files dropped on source button or label"""
+    file_path = event.data
+    # On Windows, file paths may be enclosed in {}
+    if file_path.startswith("{") and file_path.endswith("}"):
+        file_path = file_path[1:-1]
+
+    if is_image(file_path):
+        modules.globals.source_path = file_path
+        global RECENT_DIRECTORY_SOURCE
+        RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
+        image = render_image_preview(modules.globals.source_path, (200, 200))
+        source_label.configure(image=image)
+    else:
+        update_status("Please drop an image file for the source.")
+
+
+def handle_drop_target(event):
+    """Handle files dropped on target button or label"""
+    file_path = event.data
+    # On Windows, file paths may be enclosed in {}
+    if file_path.startswith("{") and file_path.endswith("}"):
+        file_path = file_path[1:-1]
+
+    if is_image(file_path) or is_video(file_path):
+        modules.globals.target_path = file_path
+        global RECENT_DIRECTORY_TARGET
+        RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
+        
+        if is_image(file_path):
+            image = render_image_preview(modules.globals.target_path, (200, 200))
+            target_label.configure(image=image)
+        elif is_video(file_path):
+            video_frame = render_video_preview(file_path, (200, 200))
+            target_label.configure(image=video_frame)
+    else:
+        update_status("Please drop an image or video file for the target.")
@@ -21,14 +21,13 @@ if platform.system().lower() == "darwin":


 def run_ffmpeg(args: List[str]) -> bool:
-    """Run ffmpeg with hardware acceleration and optimized settings."""
    commands = [
        "ffmpeg",
        "-hide_banner",
-        "-hwaccel", "auto",  # Auto-detect hardware acceleration
-        "-hwaccel_output_format", "auto",  # Use hardware format when possible
-        "-threads", str(modules.globals.execution_threads or 0),  # 0 = auto-detect optimal thread count
-        "-loglevel", modules.globals.log_level,
+        "-hwaccel",
+        "auto",
+        "-loglevel",
+        modules.globals.log_level,
    ]
    commands.extend(args)
    try:
@@ -62,131 +61,39 @@ def detect_fps(target_path: str) -> float:


 def extract_frames(target_path: str) -> None:
-    """Extract frames with hardware acceleration and optimized settings."""
    temp_directory_path = get_temp_directory_path(target_path)
-    
-    # Use hardware-accelerated decoding and optimized pixel format
    run_ffmpeg(
        [
-            "-i", target_path,
-            "-vf", "format=rgb24",  # Use video filter for format conversion (faster)
-            "-vsync", "0",  # Prevent frame duplication
-            "-frame_pts", "1",  # Preserve frame timing
+            "-i",
+            target_path,
+            "-pix_fmt",
+            "rgb24",
            os.path.join(temp_directory_path, "%04d.png"),
        ]
    )


 def create_video(target_path: str, fps: float = 30.0) -> None:
-    """Create video with hardware-accelerated encoding and optimized settings."""
    temp_output_path = get_temp_output_path(target_path)
    temp_directory_path = get_temp_directory_path(target_path)
-    
-    # Determine optimal encoder based on available hardware
-    encoder = modules.globals.video_encoder
-    encoder_options = []
-    
-    # GPU-accelerated encoding options
-    if 'CUDAExecutionProvider' in modules.globals.execution_providers:
-        # NVIDIA GPU encoding
-        if encoder == 'libx264':
-            encoder = 'h264_nvenc'
-            encoder_options = [
-                "-preset", "p7",  # Highest quality preset for NVENC
-                "-tune", "hq",  # High quality tuning
-                "-rc", "vbr",  # Variable bitrate
-                "-cq", str(modules.globals.video_quality),  # Quality level
-                "-b:v", "0",  # Let CQ control bitrate
-                "-multipass", "fullres",  # Two-pass encoding for better quality
-            ]
-        elif encoder == 'libx265':
-            encoder = 'hevc_nvenc'
-            encoder_options = [
-                "-preset", "p7",
-                "-tune", "hq",
-                "-rc", "vbr",
-                "-cq", str(modules.globals.video_quality),
-                "-b:v", "0",
-            ]
-    elif 'DmlExecutionProvider' in modules.globals.execution_providers:
-        # AMD/Intel GPU encoding (DirectML on Windows)
-        if encoder == 'libx264':
-            # Try AMD AMF encoder
-            encoder = 'h264_amf'
-            encoder_options = [
-                "-quality", "quality",  # Quality mode
-                "-rc", "vbr_latency",
-                "-qp_i", str(modules.globals.video_quality),
-                "-qp_p", str(modules.globals.video_quality),
-            ]
-        elif encoder == 'libx265':
-            encoder = 'hevc_amf'
-            encoder_options = [
-                "-quality", "quality",
-                "-rc", "vbr_latency",
-                "-qp_i", str(modules.globals.video_quality),
-                "-qp_p", str(modules.globals.video_quality),
-            ]
-    else:
-        # CPU encoding with optimized settings
-        if encoder == 'libx264':
-            encoder_options = [
-                "-preset", "medium",  # Balance speed/quality
-                "-crf", str(modules.globals.video_quality),
-                "-tune", "film",  # Optimize for film content
-            ]
-        elif encoder == 'libx265':
-            encoder_options = [
-                "-preset", "medium",
-                "-crf", str(modules.globals.video_quality),
-                "-x265-params", "log-level=error",
-            ]
-        elif encoder == 'libvpx-vp9':
-            encoder_options = [
-                "-crf", str(modules.globals.video_quality),
-                "-b:v", "0",  # Constant quality mode
-                "-cpu-used", "2",  # Speed vs quality (0-5, lower=slower/better)
-            ]
-    
-    # Build ffmpeg command
-    ffmpeg_args = [
-        "-r", str(fps),
-        "-i", os.path.join(temp_directory_path, "%04d.png"),
-        "-c:v", encoder,
-    ]
-    
-    # Add encoder-specific options
-    ffmpeg_args.extend(encoder_options)
-    
-    # Add common options
-    ffmpeg_args.extend([
-        "-pix_fmt", "yuv420p",
-        "-movflags", "+faststart",  # Enable fast start for web playback
-        "-vf", "colorspace=bt709:iall=bt601-6-625:fast=1",
-        "-y",
-        temp_output_path,
-    ])
-    
-    # Try with hardware encoder first, fallback to software if it fails
-    success = run_ffmpeg(ffmpeg_args)
-    
-    if not success and encoder in ['h264_nvenc', 'hevc_nvenc', 'h264_amf', 'hevc_amf']:
-        # Fallback to software encoding
-        print(f"Hardware encoding with {encoder} failed, falling back to software encoding...")
-        fallback_encoder = 'libx264' if 'h264' in encoder else 'libx265'
-        ffmpeg_args_fallback = [
-            "-r", str(fps),
-            "-i", os.path.join(temp_directory_path, "%04d.png"),
-            "-c:v", fallback_encoder,
-            "-preset", "medium",
-            "-crf", str(modules.globals.video_quality),
-            "-pix_fmt", "yuv420p",
-            "-movflags", "+faststart",
-            "-vf", "colorspace=bt709:iall=bt601-6-625:fast=1",
+    run_ffmpeg(
+        [
+            "-r",
+            str(fps),
+            "-i",
+            os.path.join(temp_directory_path, "%04d.png"),
+            "-c:v",
+            modules.globals.video_encoder,
+            "-crf",
+            str(modules.globals.video_quality),
+            "-pix_fmt",
+            "yuv420p",
+            "-vf",
+            "colorspace=bt709:iall=bt601-6-625:fast=1",
            "-y",
            temp_output_path,
        ]
-        run_ffmpeg(ffmpeg_args_fallback)
+    )


 def restore_audio(target_path: str, output_path: str) -> None:
@@ -1,24 +1,25 @@
--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==2.8.0+cu128; sys_platform == 'darwin'
-torchvision; sys_platform != 'darwin'
+torch==2.5.1+cu118; sys_platform != 'darwin'
+torch==2.5.1; sys_platform == 'darwin'
+torchvision==0.20.1; sys_platform != 'darwin'
 torchvision==0.20.1; sys_platform == 'darwin'
 onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64'
-onnxruntime-gpu==1.22.0; sys_platform != 'darwin'
+onnxruntime-gpu==1.16.3; sys_platform != 'darwin'
 tensorflow; sys_platform != 'darwin'
 opennsfw2==0.10.2
-protobuf==4.25.1
-git+https://github.com/xinntao/BasicSR.git@master
-git+https://github.com/TencentARC/GFPGAN.git@master
-pygrabber
+protobuf==4.23.2
+tqdm==4.66.4
+gfpgan==1.3.8
+tkinterdnd2==0.4.2
+pygrabber==0.2
@@ -1,8 +1,5 @@
 #!/usr/bin/env python3

-# Import the tkinter fix to patch the ScreenChanged error
-import tkinter_fix
-
 from modules import core

 if __name__ == '__main__':
@@ -1,26 +0,0 @@
-import tkinter
-
-# Only needs to be imported once at the beginning of the application
-def apply_patch():
-    # Create a monkey patch for the internal _tkinter module
-    original_init = tkinter.Tk.__init__
-    
-    def patched_init(self, *args, **kwargs):
-        # Call the original init
-        original_init(self, *args, **kwargs)
-        
-        # Define the missing ::tk::ScreenChanged procedure
-        self.tk.eval("""
-        if {[info commands ::tk::ScreenChanged] == ""} {
-            proc ::tk::ScreenChanged {args} {
-                # Do nothing
-                return
-            }
-        }
-        """)
-    
-    # Apply the monkey patch
-    tkinter.Tk.__init__ = patched_init
-
-# Apply the patch automatically when this module is imported
-apply_patch()
Author	SHA1	Message	Date
KRSHH	30ffbc1042	add Drag and drop functionality	2025-03-26 13:08:18 +05:30
KRSHH	2b2caf6aba	Update ui.py	2025-03-26 12:14:29 +05:30