Revert "Slight Performance Improvement"

This reverts commit 9a472e2435.
Revert "Update ui.py"
2024-11-07 14:58:03 +05:30 · 2024-11-07 14:57:47 +05:30 · 2024-10-29 14:53:19 +05:30 · 2024-10-29 14:07:47 +05:30 · 2024-10-28 16:53:55 +05:30 · 2024-10-28 13:50:44 +05:30
38 changed files with 3031 additions and 1108 deletions
@@ -0,0 +1,38 @@
+---
+name: Bug report
+about: Create a report to help us improve
+title: ''
+labels: ''
+assignees: ''
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**To Reproduce**
+Steps to reproduce the behavior:
+1. Go to '...'
+2. Click on '....'
+3. Scroll down to '....'
+4. See error
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**Screenshots**
+If applicable, add screenshots to help explain your problem.
+
+**Desktop (please complete the following information):**
+ - OS: [e.g. iOS]
+ - Browser [e.g. chrome, safari]
+ - Version [e.g. 22]
+
+**Smartphone (please complete the following information):**
+ - Device: [e.g. iPhone6]
+ - OS: [e.g. iOS8.1]
+ - Browser [e.g. stock browser, safari]
+ - Version [e.g. 22]
+
+**Additional context**
+Add any other context about the problem here.
@@ -6,17 +6,21 @@ __pycache__/
 .todo
 *.log
 *.backup
-
+tf_env/
 *.png
 *.mp4
 *.mkv

 .tmp/
 temp/
+.venv/
 venv/
+env/
 workflow/
 gfpgan/
 models/inswapper_128.onnx
 models/GFPGANv1.4.pth
 *.onnx
 models/DMDNet.pth
+faceswap/
+.vscode/
@@ -1 +0,0 @@
-3.10.14
@@ -0,0 +1 @@
+Please always push on the experimental to ensure we don't mess with the main branch. All the test will be done on the experimental and will be pushed to the main branch after few days of testing.
@@ -1,163 +1,213 @@
-![demo-gif](demo.gif)
+<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.
+</p>
+
+<p align="center">
+  <img src="media/demo.gif" alt="Demo GIF">
+  <img src="media/avgpcperformancedemo.gif" alt="Performance Demo GIF">
+</p>

 ## Disclaimer
-This software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.

-The developers of this software are aware of its possible unethical applications and are committed to take preventative measures against them. It has a built-in check which prevents the program from working on inappropriate media including but not limited to nudity, graphic content, sensitive material such as war footage etc. We will continue to develop this project in the positive direction while adhering to law and ethics. This project may be shut down or include watermarks on the output if requested by law.
+This software is intended as a productive contribution to the AI-generated media industry. It aims to assist artists with tasks like animating custom characters or using them as models for clothing, etc.

-Users of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers of this software will not be responsible for actions of end-users.
+We are aware of the potential for unethical applications and are committed to preventative measures. A built-in check prevents the program from processing inappropriate media (nudity, graphic content, sensitive material like war footage, etc.). We will continue to develop this project responsibly, adhering to law and ethics. We may shut down the project or add watermarks if legally required.

-## How do I install it?
+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.


-### Basic: It is more likely to work on your computer but it will also be very slow. You can follow instructions for the basic install (This usually runs via **CPU**)
-#### 1.Setup your platform
-   python (3.10 recommended)
-   pip
-   git
-   [ffmpeg](https://www.youtube.com/watch?v=OlNWCpFdVMA) 
-   [visual studio 2022 runtimes (windows)](https://visualstudio.microsoft.com/visual-cpp-build-tools/)
-#### 2. Clone Repository
-    https://github.com/hacksider/Deep-Live-Cam.git
+## Quick Start (Windows / Nvidia)

-#### 3. Download Models
+[![Download](media/download.png)](https://hacksider.gumroad.com/l/vccdmm) 

- 1. [GFPGANv1.4](https://huggingface.co/hacksider/deep-live-cam/resolve/main/GFPGANv1.4.pth)
- 2. [inswapper_128_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128.onnx)
+[Download latest pre-built version with CUDA support](https://hacksider.gumroad.com/l/vccdmm) - No Manual Installation/Downloading required.

-Then put those 2 files on the "**models**" folder
+## Installation (Manual)
+**Please be aware that the installation needs technical skills and is NOT for beginners, consider downloading the prebuilt. Please do NOT open platform and installation related issues on GitHub before discussing it on the discord server.**
+### Basic Installation (CPU)

-#### 4. Install dependency
-We highly recommend to work with a  `venv`  to avoid issues.
+This is more likely to work on your computer but will be slower as it utilizes the CPU.
+
+**1. Setup Your Platform**
+
+- Python (3.10 recommended)
+- pip
+- git
+- [ffmpeg](https://www.youtube.com/watch?v=OlNWCpFdVMA) 
+- [Visual Studio 2022 Runtimes (Windows)](https://visualstudio.microsoft.com/visual-cpp-build-tools/)
+
+**2. Clone Repository**
+
+```bash
+https://github.com/hacksider/Deep-Live-Cam.git
 ```
+
+**3. Download Models**
+
+1. [GFPGANv1.4](https://huggingface.co/hacksider/deep-live-cam/resolve/main/GFPGANv1.4.pth)
+2. [inswapper_128_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128.onnx) (Note: Use this [replacement version](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx) if you encounter issues)
+
+Place these files in the "**models**" folder.
+
+**4. Install Dependencies**
+
+We highly recommend using a `venv` to avoid issues.
+
+```bash
 pip install -r requirements.txt
 ```
-##### DONE!!! If you dont have any GPU, You should be able to run roop using `python run.py` command. Keep in mind that while running the program for first time, it will download some models which can take time depending on your network connection.

-### *Proceed if you want to use GPU Acceleration
-### CUDA Execution Provider (Nvidia)*
-
-1.  Install  [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive)
-    
-2.  Install dependencies:
-    
+**For macOS:** Install or upgrade the `python-tk` package:

+```bash
+brew install python-tk@3.10
 ```
+
+**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).
+
+
+### GPU Acceleration (Optional)
+
+<details>
+<summary>Click to see the details</summary>
+
+**CUDA Execution Provider (Nvidia)**
+
+1. Install [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive)
+2. Install dependencies:
+```bash
 pip uninstall onnxruntime onnxruntime-gpu
 pip install onnxruntime-gpu==1.16.3
-
-```
-
-3.  Usage in case the provider is available:
-
 ```
+3. Usage:
+```bash
 python run.py --execution-provider cuda
-
 ```

-### [](https://github.com/s0md3v/roop/wiki/2.-Acceleration#coreml-execution-provider-apple-silicon)CoreML Execution Provider (Apple Silicon)
+**CoreML Execution Provider (Apple Silicon)**

-1.  Install dependencies:
-
-```
+1. Install dependencies:
+```bash
 pip uninstall onnxruntime onnxruntime-silicon
 pip install onnxruntime-silicon==1.13.1
-
-```
-
-2.  Usage in case the provider is available:
-
 ```
+2. Usage:
+```bash
 python run.py --execution-provider coreml
-
 ```

-### [](https://github.com/s0md3v/roop/wiki/2.-Acceleration#coreml-execution-provider-apple-legacy)CoreML Execution Provider (Apple Legacy)
+**CoreML Execution Provider (Apple Legacy)**

-1.  Install dependencies:
-
-```
+1. Install dependencies:
+```bash
 pip uninstall onnxruntime onnxruntime-coreml
 pip install onnxruntime-coreml==1.13.1
-
-```
-
-2.  Usage in case the provider is available:
-
 ```
+2. Usage:
+```bash
 python run.py --execution-provider coreml
-
 ```

-### [](https://github.com/s0md3v/roop/wiki/2.-Acceleration#directml-execution-provider-windows)DirectML Execution Provider (Windows)
+**DirectML Execution Provider (Windows)**

-1.  Install dependencies:
-
-```
+1. Install dependencies:
+```bash
 pip uninstall onnxruntime onnxruntime-directml
 pip install onnxruntime-directml==1.15.1
-
-```
-
-2.  Usage in case the provider is available:
-
 ```
+2. Usage:
+```bash
 python run.py --execution-provider directml
-
 ```

-### [](https://github.com/s0md3v/roop/wiki/2.-Acceleration#openvino-execution-provider-intel)OpenVINO™ Execution Provider (Intel)
+**OpenVINO™ Execution Provider (Intel)**

-1.  Install dependencies:
-
-```
+1. Install dependencies:
+```bash
 pip uninstall onnxruntime onnxruntime-openvino
 pip install onnxruntime-openvino==1.15.0
-
-```
-
-2.  Usage in case the provider is available:
-
 ```
+2. Usage:
+```bash
 python run.py --execution-provider openvino
 ```

-## How do I use it?
-> Note: When you run this program for the first time, it will download some models ~300MB in size.
+</details>

-Executing `python run.py` command will launch this window:
-![gui-demo](instruction.png)

-Choose a face (image with desired face) and the target image/video (image/video in which you want to replace the face) and click on `Start`. Open file explorer and navigate to the directory you select your output to be in. You will find a directory named `<video_title>` where you can see the frames being swapped in realtime. Once the processing is done, it will create the output file. That's it.
+## Usage

-## For the webcam mode
-Just follow the clicks on the screenshot
-1. Select a face
-2. Click live
-3. Wait for a few second (it takes a longer time, usually 10 to 30 seconds before the preview shows up)
+**1. Image/Video Mode**

-![demo-gif](demo.gif)
+- Execute `python run.py`. 
+- Choose a source face image and a target image/video.
+- Click "Start".
+- The output will be saved in a directory named after the target video.

-Just use your favorite screencapture to stream like OBS
-> Note: In case you want to change your face, just select another picture, the preview mode will then restart (so just wait a bit).
+**2. Webcam Mode**

-You can now use the virtual camera output (uses pyvirtualcam) by turning on the `Virtual Cam Output (OBS)` toggle which should output to the OBS Virtual Camera. Note: this may not work on macOS. You will get a preview as before, but now you will also have a virtual camera output which can be used in applications like Zoom.
+- Execute `python run.py`.
+- Select a source face image.
+- Click "Live".
+- Wait for the preview to appear (10-30 seconds).
+- Use a screen capture tool like OBS to stream.
+- To change the face, select a new source image.

-Additional command line arguments are given below. To learn out what they do, check [this guide](https://github.com/s0md3v/roop/wiki/Advanced-Options).
+![demo-gif](media/demo.gif)

+## Features
+
+### Resizable Preview Window
+
+Dynamically improve performance using the `--live-resizable` parameter.
+
+![resizable-gif](media/resizable.gif)
+
+### Face Mapping
+
+Track and change faces on the fly.
+
+![face_mapping_source](media/face_mapping_source.gif)
+
+**Source Video:**
+
+![face-mapping](media/face_mapping.png)
+
+**Enable Face Mapping:**
+
+![face-mapping2](media/face_mapping2.png)
+
+**Map the Faces:**
+
+![face_mapping_result](media/face_mapping_result.gif)
+
+**See the Magic!**
+
+![movie](media/movie.gif)
+
+**Watch movies in realtime:**
+
+It's as simple as opening a movie on the screen, and selecting OBS as your camera!
+![image](media/movie_img.png)
+
+
+## Command Line Arguments

 ```
 options:
  -h, --help                                               show this help message and exit
-  -s SOURCE_PATH, --source SOURCE_PATH                     select an source image
-  -t TARGET_PATH, --target TARGET_PATH                     select an target image or video
+  -s SOURCE_PATH, --source SOURCE_PATH                     select a source image
+  -t TARGET_PATH, --target TARGET_PATH                     select a target image or video
  -o OUTPUT_PATH, --output OUTPUT_PATH                     select output file or directory
-  --frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...]  frame processors (choices: face_swapper, face_enhancer, super_resolution...)
+  --frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...]  frame processors (choices: face_swapper, face_enhancer, ...)
  --keep-fps                                               keep original fps
  --keep-audio                                             keep original audio
  --keep-frames                                            keep temporary frames
  --many-faces                                             process every face
+  --map-faces                                              map source target faces
+  --nsfw-filter                                            filter the NSFW image or video
  --video-encoder {libx264,libx265,libvpx-vp9}             adjust output video encoder
  --video-quality [0-51]                                   adjust output video quality
  --live-mirror                                            the live camera display as you see it in the front-facing camera frame
@@ -165,24 +215,198 @@ options:
  --max-memory MAX_MEMORY                                  maximum amount of RAM in GB
  --execution-provider {cpu} [{cpu} ...]                   available execution provider (choices: cpu, ...)
  --execution-threads EXECUTION_THREADS                    number of execution threads
-  --headless                                               run in headless mode
-  --enhancer-upscale-factor                                Sets the upscale factor for the enhancer. Only applies if `face_enhancer` is set as a frame-processor
-  --source-image-scaling-factor                            Set the upscale factor for source images. Only applies if `face_swapper` is set as a frame-processor
-  -r SCALE, --super-resolution-scale-factor SCALE          Super resolution scale factor, choices are 2, 3, 4
  -v, --version                                            show program's version number and exit
 ```

 Looking for a CLI mode? Using the -s/--source argument will make the run program in cli mode.

-To improve the video quality, you can use the `super_resolution` frame processor after swapping the faces. It will enhance the video quality by 2x, 3x or 4x. You can set the upscale factor using the `-r` or `--super-resolution-scale-factor` argument. 
-Processing time will increase with the upscale factor, but it's quite quick.

+## Webcam Mode on WSL2 Ubuntu (Optional)
+
+<details>
+<summary>Click to see the details</summary>
+
+If you want to use WSL2 on Windows 11 you will notice, that Ubuntu WSL2 doesn't come with USB-Webcam support in the Kernel. You need to do two things: Compile the Kernel with the right modules integrated and forward your USB Webcam from Windows to Ubuntu with the usbipd app. Here are detailed Steps:
+
+This tutorial will guide you through the process of setting up WSL2 Ubuntu with USB webcam support, rebuilding the kernel, and preparing the environment for the Deep-Live-Cam project.  
+  
+**1. Install WSL2 Ubuntu**  
+  
+Install WSL2 Ubuntu from the Microsoft Store or using PowerShell:  
+  
+**2. Enable USB Support in WSL2**  
+  
+1. Install the USB/IP tool for Windows:  
+[https://learn.microsoft.com/en-us/windows/wsl/connect-usb](https://learn.microsoft.com/en-us/windows/wsl/connect-usb)  
+  
+2. In Windows PowerShell (as Administrator), connect your webcam to WSL:  
+  
+```powershell  
+usbipd list  
+usbipd bind --busid x-x # Replace x-x with your webcam's bus ID  
+usbipd attach --wsl --busid x-x # Replace x-x with your webcam's bus ID  
+```  
+ You need to redo the above every time you reboot wsl or re-connect your webcam/usb device.
+ 
+**3. Rebuild WSL2 Ubuntu Kernel with USB and Webcam Modules**  
+  
+Follow these steps to rebuild the kernel:  
+  
+1. Start with this guide: [https://github.com/PINTO0309/wsl2_linux_kernel_usbcam_enable_conf](https://github.com/PINTO0309/wsl2_linux_kernel_usbcam_enable_conf)  
+  
+2. When you reach the `sudo wget [github.com](http://github.com/)...PINTO0309` step, which won't work for newer kernel versions, follow this video instead or alternatively follow the video tutorial from the beginning: 
+[https://www.youtube.com/watch?v=t_YnACEPmrM](https://www.youtube.com/watch?v=t_YnACEPmrM)  
+  
+Additional info: [https://askubuntu.com/questions/1413377/camera-not-working-in-cheese-in-wsl2](https://askubuntu.com/questions/1413377/camera-not-working-in-cheese-in-wsl2)  
+  
+3. After rebuilding, restart WSL with the new kernel. 
+  
+**4. Set Up Deep-Live-Cam Project**  
+ Within Ubuntu:
+1. Clone the repository:  
+  
+```bash  
+git clone [https://github.com/hacksider/Deep-Live-Cam](https://github.com/hacksider/Deep-Live-Cam)  
+```  
+  
+2. Follow the installation instructions in the repository, including cuda toolkit 11.8, make 100% sure it's not cuda toolkit 12.x.  
+   
+**5. Verify and Load Kernel Modules**  
+  
+1. Check if USB and webcam modules are built into the kernel:  
+  
+```bash  
+zcat /proc/config.gz | grep -i "CONFIG_USB_VIDEO_CLASS"  
+```  
+  
+2. If modules are loadable (m), not built-in (y), check if the file exists:  
+  
+```bash  
+ls /lib/modules/$(uname -r)/kernel/drivers/media/usb/uvc/  
+```  
+  
+3. Load the module and check for errors (optional if built-in):  
+  
+```bash  
+sudo modprobe uvcvideo  
+dmesg | tail  
+```  
+  
+4. Verify video devices:  
+  
+```bash  
+sudo ls -al /dev/video*  
+```  
+  
+**6. Set Up Permissions**  
+  
+1. Add user to video group and set permissions:  
+  
+```bash  
+sudo usermod -a -G video $USER  
+sudo chgrp video /dev/video0 /dev/video1  
+sudo chmod 660 /dev/video0 /dev/video1  
+```  
+  
+2. Create a udev rule for permanent permissions:  
+  
+```bash  
+sudo nano /etc/udev/rules.d/81-webcam.rules  
+```  
+  
+Add this content:  
+  
+```  
+KERNEL=="video[0-9]*", GROUP="video", MODE="0660"  
+```  
+  
+3. Reload udev rules:  
+  
+```bash  
+sudo udevadm control --reload-rules && sudo udevadm trigger  
+```  
+  
+4. Log out and log back into your WSL session.  
+  
+5. Start Deep-Live-Cam with `python run.py --execution-provider cuda --max-memory 8` where 8 can be changed to the number of GB VRAM of your GPU has, minus 1-2GB. If you have a RTX3080 with 10GB I suggest adding 8GB. Leave some left for Windows.
+
+**Final Notes**  
+  
+- Steps 6 and 7 may be optional if the modules are built into the kernel and permissions are already set correctly.  
+- Always ensure you're using compatible versions of CUDA, ONNX, and other dependencies.  
+- If issues persist, consider checking the Deep-Live-Cam project's specific requirements and troubleshooting steps.  
+  
+By following these steps, you should have a WSL2 Ubuntu environment with USB webcam support ready for the Deep-Live-Cam project. If you encounter any issues, refer back to the specific error messages and troubleshooting steps provided.
+
+**Troubleshooting CUDA Issues** 
+
+If you encounter this error:  
+  
+```  
+[ONNXRuntimeError] : 1 : FAIL : Failed to load library [libonnxruntime_providers_cuda.so](http://libonnxruntime_providers_cuda.so/) with error: libcufft.so.10: cannot open shared object file: No such file or directory  
+```  
+  
+Follow these steps:  
+  
+1. Install CUDA Toolkit 11.8 (ONNX 1.16.3 requires CUDA 11.x, not 12.x):  
+[https://developer.nvidia.com/cuda-11-8-0-download-archive](https://developer.nvidia.com/cuda-11-8-0-download-archive)  
+  select: Linux, x86_64, WSL-Ubuntu, 2.0, deb (local)
+2. Check CUDA version:  
+  
+```bash  
+/usr/local/cuda/bin/nvcc --version  
+```  
+  
+3. If the wrong version is installed, remove it completely:  
+[https://askubuntu.com/questions/530043/removing-nvidia-cuda-toolkit-and-installing-new-one](https://askubuntu.com/questions/530043/removing-nvidia-cuda-toolkit-and-installing-new-one)  
+  
+4. Install CUDA Toolkit 11.8 again [https://developer.nvidia.com/cuda-11-8-0-download-archive](https://developer.nvidia.com/cuda-11-8-0-download-archive), select: Linux, x86_64, WSL-Ubuntu, 2.0, deb (local)
+  
+```bash  
+sudo apt-get -y install cuda-toolkit-11-8  
 ```
+</details>
+
+
+## Future Updates & Roadmap
+
+For the latest experimental builds and features, see the [experimental branch](https://github.com/hacksider/Deep-Live-Cam/tree/experimental).
+
+**TODO:**
+
+- [ ] Develop a version for web app/service
+- [ ] Speed up model loading
+- [ ] Speed up real-time face swapping
+- [x] Support multiple faces 
+- [x] UI/UX enhancements for desktop app
+
+This is an open-source project developed in our free time. Updates may be delayed.
+
+**Tips and Links:**
+- [How to make the most of Deep-Live-Cam](https://hacksider.gumroad.com/p/how-to-make-the-most-on-deep-live-cam)
+- Face enhancer is good, but still very slow for any live streaming purpose.
+

 ## Credits
- [henryruhs](https://github.com/henryruhs): for being an irreplaceable contributor to the project
+
 - [ffmpeg](https://ffmpeg.org/): for making video related operations easy
- [deepinsight](https://github.com/deepinsight): for their [insightface](https://github.com/deepinsight/insightface) project which provided a well-made library and models.
+- [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/nsfw-roop) : for uncensoring roop
- and all developers behind libraries used in this project.
+- [GosuDRM](https://github.com/GosuDRM) : for open version of roop
+- [pereiraroland26](https://github.com/pereiraroland26) : Multiple faces support
+- [vic4key](https://github.com/vic4key) : For supporting/contributing on this project
+- [KRSHH](https://github.com/KRSHH) : For updating the UI
+- and [all developers](https://github.com/hacksider/Deep-Live-Cam/graphs/contributors) behind libraries used in this project.
+- Foot Note: [This is originally roop-cam, see the full history of the code here.](https://github.com/hacksider/roop-cam) Please be informed that the base author of the code is [s0md3v](https://github.com/s0md3v/roop)
+
+## Contributions
+![Alt](https://repobeats.axiom.co/api/embed/fec8e29c45dfdb9c5916f3a7830e1249308d20e1.svg "Repobeats analytics image")
+## Star History
+
+<a href="https://star-history.com/#hacksider/deep-live-cam&Date">
+ <picture>
+   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=hacksider/deep-live-cam&type=Date&theme=dark" />
+   <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>
@@ -1 +1,4 @@
-just put the models in this folder
+just put the models in this folder -
+
+https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128_fp16.onnx?download=true
+https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth
@@ -1,38 +1,32 @@
-from typing import Any, Optional
+from typing import Any
 import cv2
+import modules.globals  # Import the globals to check the color correction toggle

-def get_video_frame(video_path: str, frame_number: int = 0) -> Optional[Any]:
-    """Retrieve a specific frame from a video."""
+
+def get_video_frame(video_path: str, frame_number: int = 0) -> Any:
    capture = cv2.VideoCapture(video_path)

-    if not capture.isOpened():
-        print(f"Error: Cannot open video file {video_path}")
-        return None
-
-    frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
-
-    # Ensure frame_number is within the valid range
-    frame_number = max(0, min(frame_number, frame_total - 1))
-
-    capture.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
-    has_frame, frame = capture.read()
-    capture.release()
-
-    if not has_frame:
-        print(f"Error: Cannot read frame {frame_number} from {video_path}")
-        return None
+    # Set MJPEG format to ensure correct color space handling
+    capture.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*'MJPG'))
    
-    return frame
+    # Only force RGB conversion if color correction is enabled
+    if modules.globals.color_correction:
+        capture.set(cv2.CAP_PROP_CONVERT_RGB, 1)
+    
+    frame_total = capture.get(cv2.CAP_PROP_FRAME_COUNT)
+    capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1))
+    has_frame, frame = capture.read()
+
+    if has_frame and modules.globals.color_correction:
+        # Convert the frame color if necessary
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+
+    capture.release()
+    return frame if has_frame else None
+

 def get_video_frame_total(video_path: str) -> int:
-    """Get the total number of frames in a video."""
    capture = cv2.VideoCapture(video_path)
-
-    if not capture.isOpened():
-        print(f"Error: Cannot open video file {video_path}")
-        return 0
-    
-    frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
+    video_frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
    capture.release()
-
-    return frame_total
+    return video_frame_total
@@ -0,0 +1,32 @@
+import numpy as np
+from sklearn.cluster import KMeans
+from sklearn.metrics import silhouette_score
+from typing import Any
+
+
+def find_cluster_centroids(embeddings, max_k=10) -> Any:
+    inertia = []
+    cluster_centroids = []
+    K = range(1, max_k+1)
+
+    for k in K:
+        kmeans = KMeans(n_clusters=k, random_state=0)
+        kmeans.fit(embeddings)
+        inertia.append(kmeans.inertia_)
+        cluster_centroids.append({"k": k, "centroids": kmeans.cluster_centers_})
+
+    diffs = [inertia[i] - inertia[i+1] for i in range(len(inertia)-1)]
+    optimal_centroids = cluster_centroids[diffs.index(max(diffs)) + 1]['centroids']
+
+    return optimal_centroids
+
+def find_closest_centroid(centroids: list, normed_face_embedding) -> list:
+    try:
+        centroids = np.array(centroids)
+        normed_face_embedding = np.array(normed_face_embedding)
+        similarities = np.dot(centroids, normed_face_embedding)
+        closest_centroid_index = np.argmax(similarities)
+        
+        return closest_centroid_index, centroids[closest_centroid_index]
+    except ValueError:
+        return None
@@ -1,17 +1,16 @@
 import os
 import sys
+# single thread doubles cuda performance - needs to be set before torch import
+if any(arg.startswith('--execution-provider') for arg in sys.argv):
+    os.environ['OMP_NUM_THREADS'] = '1'
+# reduce tensorflow log level
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
 import warnings
+from typing import List
 import platform
 import signal
 import shutil
 import argparse
-from typing import List
-
-# Set environment variables for CUDA performance and TensorFlow logging
-if any(arg.startswith('--execution-provider') for arg in sys.argv):
-    os.environ['OMP_NUM_THREADS'] = '1'
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
-
 import torch
 import onnxruntime
 import tensorflow
@@ -20,73 +19,38 @@ import modules.globals
 import modules.metadata
 import modules.ui as ui
 from modules.processors.frame.core import get_frame_processors_modules
-from modules.utilities import (
-    has_image_extension,
-    is_image,
-    is_video,
-    detect_fps,
-    create_video,
-    extract_frames,
-    get_temp_frame_paths,
-    restore_audio,
-    create_temp,
-    move_temp,
-    clean_temp,
-    normalize_output_path
-)
+from modules.utilities import has_image_extension, is_image, is_video, detect_fps, create_video, extract_frames, get_temp_frame_paths, restore_audio, create_temp, move_temp, clean_temp, normalize_output_path
+
+if 'ROCMExecutionProvider' in modules.globals.execution_providers:
+    del torch

-# Filter warnings
 warnings.filterwarnings('ignore', category=FutureWarning, module='insightface')
 warnings.filterwarnings('ignore', category=UserWarning, module='torchvision')

-# Cross-platform resource management
-if platform.system() == 'Darwin' and 'ROCMExecutionProvider' in modules.globals.execution_providers:
-    del torch
-

 def parse_args() -> None:
    signal.signal(signal.SIGINT, lambda signal_number, frame: destroy())
    program = argparse.ArgumentParser()
-    program.add_argument('-s', '--source', help='Select a source image', dest='source_path')
-    program.add_argument('-t', '--target', help='Select a target image or video', dest='target_path')
-    program.add_argument('-o', '--output', help='Select output file or directory', dest='output_path')
-    program.add_argument('--frame-processor', help='Pipeline of frame processors', dest='frame_processor',
-                         default=['face_swapper'], choices=['face_swapper', 'face_enhancer', 'super_resolution'],
-                         nargs='+')
-    program.add_argument('--keep-fps', help='Keep original fps', dest='keep_fps', action='store_true', default=False)
-    program.add_argument('--keep-audio', help='Keep original audio', dest='keep_audio', action='store_true',
-                         default=True)
-    program.add_argument('--keep-frames', help='Keep temporary frames', dest='keep_frames', action='store_true',
-                         default=False)
-    program.add_argument('--many-faces', help='Process every face', dest='many_faces', action='store_true',
-                         default=False)
-    program.add_argument('--video-encoder', help='Adjust output video encoder', dest='video_encoder', default='libx264',
-                         choices=['libx264', 'libx265', 'libvpx-vp9'])
-    program.add_argument('--video-quality', help='Adjust output video quality', dest='video_quality', type=int,
-                         default=18,
-                         choices=range(52), metavar='[0-51]')
-    program.add_argument('--live-mirror', help='The live camera display as you see it in the front-facing camera frame',
-                         dest='live_mirror', action='store_true', default=False)
-    program.add_argument('--live-resizable', help='The live camera frame is resizable',
-                         dest='live_resizable', action='store_true', default=False)
-    program.add_argument('--max-memory', help='Maximum amount of RAM in GB', dest='max_memory', type=int,
-                         default=suggest_max_memory())
-    program.add_argument('--execution-provider', help='Execution provider', dest='execution_provider', default=['cpu'],
-                         choices=suggest_execution_providers(), nargs='+')
-    program.add_argument('--execution-threads', help='Number of execution threads', dest='execution_threads', type=int,
-                         default=suggest_execution_threads())
-    program.add_argument('--headless', help='Run in headless mode', dest='headless', default=False, action='store_true')
-    program.add_argument('--enhancer-upscale-factor',
-                         help='Sets the upscale factor for the enhancer. Only applies if `face_enhancer` is set as a frame-processor',
-                         dest='enhancer_upscale_factor', type=int, default=1)
-    program.add_argument('--source-image-scaling-factor', help='Set the upscale factor for source images',
-                         dest='source_image_scaling_factor', default=2, type=int)
-    program.add_argument('-r', '--super-resolution-scale-factor', dest='super_resolution_scale_factor',
-                         help='Set the upscale factor for super resolution', default=4, choices=[2, 3, 4], type=int)
-    program.add_argument('-v', '--version', action='version',
-                         version=f'{modules.metadata.name} {modules.metadata.version}')
+    program.add_argument('-s', '--source', help='select an source image', dest='source_path')
+    program.add_argument('-t', '--target', help='select an target image or video', dest='target_path')
+    program.add_argument('-o', '--output', help='select output file or directory', dest='output_path')
+    program.add_argument('--frame-processor', help='pipeline of frame processors', dest='frame_processor', default=['face_swapper'], choices=['face_swapper', 'face_enhancer'], nargs='+')
+    program.add_argument('--keep-fps', help='keep original fps', dest='keep_fps', action='store_true', default=False)
+    program.add_argument('--keep-audio', help='keep original audio', dest='keep_audio', action='store_true', default=True)
+    program.add_argument('--keep-frames', help='keep temporary frames', dest='keep_frames', action='store_true', default=False)
+    program.add_argument('--many-faces', help='process every face', dest='many_faces', action='store_true', default=False)
+    program.add_argument('--nsfw-filter', help='filter the NSFW image or video', dest='nsfw_filter', action='store_true', default=False)
+    program.add_argument('--map-faces', help='map source target faces', dest='map_faces', action='store_true', default=False)
+    program.add_argument('--video-encoder', help='adjust output video encoder', dest='video_encoder', default='libx264', choices=['libx264', 'libx265', 'libvpx-vp9'])
+    program.add_argument('--video-quality', help='adjust output video quality', dest='video_quality', type=int, default=18, choices=range(52), metavar='[0-51]')
+    program.add_argument('--live-mirror', help='The live camera display as you see it in the front-facing camera frame', dest='live_mirror', action='store_true', default=False)
+    program.add_argument('--live-resizable', help='The live camera frame is resizable', dest='live_resizable', action='store_true', default=False)
+    program.add_argument('--max-memory', help='maximum amount of RAM in GB', dest='max_memory', type=int, default=suggest_max_memory())
+    program.add_argument('--execution-provider', help='execution provider', dest='execution_provider', default=['cpu'], choices=suggest_execution_providers(), nargs='+')
+    program.add_argument('--execution-threads', help='number of execution threads', dest='execution_threads', type=int, default=suggest_execution_threads())
+    program.add_argument('-v', '--version', action='version', version=f'{modules.metadata.name} {modules.metadata.version}')

-    # Register deprecated args
+    # register deprecated args
    program.add_argument('-f', '--face', help=argparse.SUPPRESS, dest='source_path_deprecated')
    program.add_argument('--cpu-cores', help=argparse.SUPPRESS, dest='cpu_cores_deprecated', type=int)
    program.add_argument('--gpu-vendor', help=argparse.SUPPRESS, dest='gpu_vendor_deprecated')
@@ -96,14 +60,15 @@ def parse_args() -> None:

    modules.globals.source_path = args.source_path
    modules.globals.target_path = args.target_path
-    modules.globals.output_path = normalize_output_path(modules.globals.source_path, modules.globals.target_path,
-                                                        args.output_path)
+    modules.globals.output_path = normalize_output_path(modules.globals.source_path, modules.globals.target_path, args.output_path)
    modules.globals.frame_processors = args.frame_processor
    modules.globals.headless = args.source_path or args.target_path or args.output_path
    modules.globals.keep_fps = args.keep_fps
    modules.globals.keep_audio = args.keep_audio
    modules.globals.keep_frames = args.keep_frames
    modules.globals.many_faces = args.many_faces
+    modules.globals.nsfw_filter = args.nsfw_filter
+    modules.globals.map_faces = args.map_faces
    modules.globals.video_encoder = args.video_encoder
    modules.globals.video_quality = args.video_quality
    modules.globals.live_mirror = args.live_mirror
@@ -111,26 +76,18 @@ def parse_args() -> None:
    modules.globals.max_memory = args.max_memory
    modules.globals.execution_providers = decode_execution_providers(args.execution_provider)
    modules.globals.execution_threads = args.execution_threads
-    modules.globals.headless = args.headless
-    modules.globals.enhancer_upscale_factor = args.enhancer_upscale_factor
-    modules.globals.source_image_scaling_factor = args.source_image_scaling_factor
-    modules.globals.sr_scale_factor = args.super_resolution_scale_factor
-    # Handle face enhancer tumbler
-    modules.globals.fp_ui['face_enhancer'] = 'face_enhancer' in args.frame_processor

-    modules.globals.nsfw = False
+    #for ENHANCER tumbler:
+    if 'face_enhancer' in args.frame_processor:
+        modules.globals.fp_ui['face_enhancer'] = True
+    else:
+        modules.globals.fp_ui['face_enhancer'] = False

-    # Handle deprecated arguments
-    handle_deprecated_args(args)
-
-
-def handle_deprecated_args(args) -> None:
-    """Handle deprecated arguments by translating them to the new format."""
+    # translate deprecated args
    if args.source_path_deprecated:
        print('\033[33mArgument -f and --face are deprecated. Use -s and --source instead.\033[0m')
        modules.globals.source_path = args.source_path_deprecated
-        modules.globals.output_path = normalize_output_path(args.source_path_deprecated, modules.globals.target_path,
-                                                            args.output_path)
+        modules.globals.output_path = normalize_output_path(args.source_path_deprecated, modules.globals.target_path, args.output_path)
    if args.cpu_cores_deprecated:
        print('\033[33mArgument --cpu-cores is deprecated. Use --execution-threads instead.\033[0m')
        modules.globals.execution_threads = args.cpu_cores_deprecated
@@ -141,7 +98,7 @@ def handle_deprecated_args(args) -> None:
        print('\033[33mArgument --gpu-vendor nvidia is deprecated. Use --execution-provider cuda instead.\033[0m')
        modules.globals.execution_providers = decode_execution_providers(['cuda'])
    if args.gpu_vendor_deprecated == 'amd':
-        print('\033[33mArgument --gpu-vendor amd is deprecated. Use --execution-provider rocm instead.\033[0m')
+        print('\033[33mArgument --gpu-vendor amd is deprecated. Use --execution-provider cuda instead.\033[0m')
        modules.globals.execution_providers = decode_execution_providers(['rocm'])
    if args.gpu_threads_deprecated:
        print('\033[33mArgument --gpu-threads is deprecated. Use --execution-threads instead.\033[0m')
@@ -149,22 +106,18 @@ def handle_deprecated_args(args) -> None:


 def encode_execution_providers(execution_providers: List[str]) -> List[str]:
-    return [provider.replace('ExecutionProvider', '').lower() for provider in execution_providers]
+    return [execution_provider.replace('ExecutionProvider', '').lower() for execution_provider in execution_providers]


 def decode_execution_providers(execution_providers: List[str]) -> List[str]:
-    available_providers = onnxruntime.get_available_providers()
-    encoded_providers = encode_execution_providers(available_providers)
-
-    selected_providers = [available_providers[encoded_providers.index(req)] for req in execution_providers
-                          if req in encoded_providers]
-
-    # Default to CPU if no suitable providers are found
-    return selected_providers if selected_providers else ['CPUExecutionProvider']
+    return [provider for provider, encoded_execution_provider in zip(onnxruntime.get_available_providers(), encode_execution_providers(onnxruntime.get_available_providers()))
+            if any(execution_provider in encoded_execution_provider for execution_provider in execution_providers)]


 def suggest_max_memory() -> int:
-    return 4 if platform.system().lower() == 'darwin' else 16
+    if platform.system().lower() == 'darwin':
+        return 4
+    return 16


 def suggest_execution_providers() -> List[str]:
@@ -172,43 +125,34 @@ def suggest_execution_providers() -> List[str]:


 def suggest_execution_threads() -> int:
-    if 'dml' in modules.globals.execution_providers:
+    if 'DmlExecutionProvider' in modules.globals.execution_providers:
        return 1
-    if 'rocm' in modules.globals.execution_providers:
+    if 'ROCMExecutionProvider' in modules.globals.execution_providers:
        return 1
    return 8


 def limit_resources() -> None:
-    # Prevent TensorFlow memory leak
+    # prevent tensorflow memory leak
    gpus = tensorflow.config.experimental.list_physical_devices('GPU')
    for gpu in gpus:
        tensorflow.config.experimental.set_memory_growth(gpu, True)
-
-    # Limit memory usage
+    # limit memory usage
    if modules.globals.max_memory:
        memory = modules.globals.max_memory * 1024 ** 3
        if platform.system().lower() == 'darwin':
-            memory = modules.globals.max_memory * 1024 ** 3
-        elif platform.system().lower() == 'windows':
+            memory = modules.globals.max_memory * 1024 ** 6
+        if platform.system().lower() == 'windows':
            import ctypes
            kernel32 = ctypes.windll.kernel32
            kernel32.SetProcessWorkingSetSize(-1, ctypes.c_size_t(memory), ctypes.c_size_t(memory))
        else:
            import resource
-            try:
-                soft, hard = resource.getrlimit(resource.RLIMIT_DATA)
-                if memory > hard:
-                    print(
-                        f"Warning: Requested memory limit {memory / (1024 ** 3)} GB exceeds system's hard limit. Setting to maximum allowed {hard / (1024 ** 3)} GB.")
-                    memory = hard
-                resource.setrlimit(resource.RLIMIT_DATA, (memory, memory))
-            except ValueError as e:
-                print(f"Warning: Could not set memory limit: {e}. Continuing with default limits.")
+            resource.setrlimit(resource.RLIMIT_DATA, (memory, memory))


 def release_resources() -> None:
-    if 'cuda' in modules.globals.execution_providers:
+    if 'CUDAExecutionProvider' in modules.globals.execution_providers:
        torch.cuda.empty_cache()


@@ -219,86 +163,52 @@ def pre_check() -> bool:
    if not shutil.which('ffmpeg'):
        update_status('ffmpeg is not installed.')
        return False
-    if 'cuda' in modules.globals.execution_providers and not torch.cuda.is_available():
-        update_status('CUDA is not available. Please check your GPU or CUDA installation.')
-        return False
    return True


 def update_status(message: str, scope: str = 'DLC.CORE') -> None:
    print(f'[{scope}] {message}')
-    if not modules.globals.headless and ui.status_label:
+    if not modules.globals.headless:
        ui.update_status(message)

-
 def start() -> None:
    for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
        if not frame_processor.pre_start():
            return
-
-    # Process image to image
+    update_status('Processing...')
+    # process image to image
    if has_image_extension(modules.globals.target_path):
-        process_image_to_image()
+        if modules.globals.nsfw_filter and ui.check_and_ignore_nsfw(modules.globals.target_path, destroy):
+            return
+        try:
+            shutil.copy2(modules.globals.target_path, modules.globals.output_path)
+        except Exception as e:
+            print("Error copying file:", str(e))
+        for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
+            update_status('Progressing...', frame_processor.NAME)
+            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):
+            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

-    # Process image to video
-    process_image_to_video()
+    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)

-
-def process_image_to_image() -> None:
-    if modules.globals.nsfw:
-        from modules.predicter import predict_image
-        if predict_image(modules.globals.target_path):
-            destroy(to_quit=False)
-            update_status('Processing to image ignored!')
-            return
-
-    try:
-        shutil.copy2(modules.globals.target_path, modules.globals.output_path)
-    except Exception as e:
-        print("Error copying file:", str(e))
-
-    for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
-        update_status('Processing...', frame_processor.NAME)
-        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):
-        update_status('Processing to image succeeded!')
-    else:
-        update_status('Processing to image failed!')
-
-
-def process_image_to_video() -> None:
-    if modules.globals.nsfw:
-        from modules.predicter import predict_video
-        if predict_video(modules.globals.target_path):
-            destroy(to_quit=False)
-            update_status('Processing to video ignored!')
-            return
-
-    update_status('Creating temporary resources...')
-    create_temp(modules.globals.target_path)
-    update_status('Extracting frames...')
-    extract_frames(modules.globals.target_path)
    temp_frame_paths = get_temp_frame_paths(modules.globals.target_path)
    for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
-        update_status('Processing...', frame_processor.NAME)
+        update_status('Progressing...', frame_processor.NAME)
        frame_processor.process_video(modules.globals.source_path, temp_frame_paths)
        release_resources()
-
-    handle_video_fps()
-    handle_video_audio()
-    clean_temp(modules.globals.target_path)
-
-    if is_video(modules.globals.target_path):
-        update_status('Processing to video succeeded!')
-    else:
-        update_status('Processing to video failed!')
-
-
-def handle_video_fps() -> None:
+    # handles fps
    if modules.globals.keep_fps:
        update_status('Detecting fps...')
        fps = detect_fps(modules.globals.target_path)
@@ -307,9 +217,7 @@ def handle_video_fps() -> None:
    else:
        update_status('Creating video with 30.0 fps...')
        create_video(modules.globals.target_path)
-
-
-def handle_video_audio() -> None:
+    # handle audio
    if modules.globals.keep_audio:
        if modules.globals.keep_fps:
            update_status('Restoring audio...')
@@ -318,6 +226,12 @@ def handle_video_audio() -> 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)
+    if is_video(modules.globals.target_path):
+        update_status('Processing to video succeed!')
+    else:
+        update_status('Processing to video failed!')


 def destroy(to_quit=True) -> None:
@@ -327,20 +241,15 @@ def destroy(to_quit=True) -> None:


 def run() -> None:
-    try:
-        parse_args()
-        if not pre_check():
+    parse_args()
+    if not pre_check():
+        return
+    for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
+        if not frame_processor.pre_check():
            return
-        for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
-            if not frame_processor.pre_check():
-                return
-        limit_resources()
-        if modules.globals.headless:
-            start()
-        else:
-            window = ui.init(start, destroy)
-            window.mainloop()
-    except Exception as e:
-        print(f"UI initialization failed: {str(e)}")
-        update_status(f"UI initialization failed: {str(e)}")
-        destroy()  # Ensure any resources are cleaned up on failure
+    limit_resources()
+    if modules.globals.headless:
+        start()
+    else:
+        window = ui.init(start, destroy)
+        window.mainloop()
@@ -1,27 +1,189 @@
-from typing import Any, Optional
+import os
+import shutil
+from typing import Any
 import insightface

+import cv2
+import numpy as np
 import modules.globals
+from tqdm import tqdm
 from modules.typing import Frame
+from modules.cluster_analysis import find_cluster_centroids, find_closest_centroid
+from modules.utilities import get_temp_directory_path, create_temp, extract_frames, clean_temp, get_temp_frame_paths
+from pathlib import Path

-FACE_ANALYSER: Optional[insightface.app.FaceAnalysis] = None
+FACE_ANALYSER = None

-def get_face_analyser() -> insightface.app.FaceAnalysis:
+
+def get_face_analyser() -> Any:
    global FACE_ANALYSER

    if FACE_ANALYSER is None:
-        FACE_ANALYSER = insightface.app.FaceAnalysis(
-            name='buffalo_l', 
-            providers=modules.globals.execution_providers
-        )
+        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

-def get_one_face(frame: Frame) -> Optional[Any]:
-    faces = get_face_analyser().get(frame)
-    return min(faces, key=lambda x: x.bbox[0], default=None)

-def get_many_faces(frame: Frame) -> Optional[Any]:
-    faces = get_face_analyser().get(frame)
-    return faces if faces else None
+def get_one_face(frame: Frame) -> Any:
+    face = get_face_analyser().get(frame)
+    try:
+        return min(face, key=lambda x: x.bbox[0])
+    except ValueError:
+        return None
+
+
+def get_many_faces(frame: Frame) -> Any:
+    try:
+        return get_face_analyser().get(frame)
+    except IndexError:
+        return None
+
+def has_valid_map() -> bool:
+    for map in modules.globals.souce_target_map:
+        if "source" in map and "target" in map:
+            return True
+    return False
+
+def default_source_face() -> Any:
+    for map in modules.globals.souce_target_map:
+        if "source" in map:
+            return map['source']['face']
+    return None
+
+def simplify_maps() -> Any:
+    centroids = []
+    faces = []
+    for map in modules.globals.souce_target_map:
+        if "source" in map and "target" in map:
+            centroids.append(map['target']['face'].normed_embedding)
+            faces.append(map['source']['face'])
+
+    modules.globals.simple_map = {'source_faces': faces, 'target_embeddings': centroids}
+    return None
+
+def add_blank_map() -> Any:
+    try:
+        max_id = -1
+        if len(modules.globals.souce_target_map) > 0:
+            max_id = max(modules.globals.souce_target_map, key=lambda x: x['id'])['id']
+
+        modules.globals.souce_target_map.append({
+                'id' : max_id + 1
+                })
+    except ValueError:
+        return None
+    
+def get_unique_faces_from_target_image() -> Any:
+    try:
+        modules.globals.souce_target_map = []
+        target_frame = cv2.imread(modules.globals.target_path)
+        many_faces = get_many_faces(target_frame)
+        i = 0
+
+        for face in many_faces:
+            x_min, y_min, x_max, y_max = face['bbox']
+            modules.globals.souce_target_map.append({
+                'id' : i, 
+                'target' : {
+                            'cv2' : target_frame[int(y_min):int(y_max), int(x_min):int(x_max)],
+                            'face' : face
+                            }
+                })
+            i = i + 1
+    except ValueError:
+        return None
+    
+    
+def get_unique_faces_from_target_video() -> Any:
+    try:
+        modules.globals.souce_target_map = []
+        frame_face_embeddings = []
+        face_embeddings = []
+    
+        print('Creating temp resources...')
+        clean_temp(modules.globals.target_path)
+        create_temp(modules.globals.target_path)
+        print('Extracting frames...')
+        extract_frames(modules.globals.target_path)
+
+        temp_frame_paths = get_temp_frame_paths(modules.globals.target_path)
+
+        i = 0
+        for temp_frame_path in tqdm(temp_frame_paths, desc="Extracting face embeddings from frames"):
+            temp_frame = cv2.imread(temp_frame_path)
+            many_faces = get_many_faces(temp_frame)
+
+            for face in many_faces:
+                face_embeddings.append(face.normed_embedding)
+            
+            frame_face_embeddings.append({'frame': i, 'faces': many_faces, 'location': temp_frame_path})
+            i += 1
+
+        centroids = find_cluster_centroids(face_embeddings)
+
+        for frame in frame_face_embeddings:
+            for face in frame['faces']:
+                closest_centroid_index, _ = find_closest_centroid(centroids, face.normed_embedding)
+                face['target_centroid'] = closest_centroid_index
+
+        for i in range(len(centroids)):
+            modules.globals.souce_target_map.append({
+                'id' : i
+            })
+
+            temp = []
+            for frame in tqdm(frame_face_embeddings, desc=f"Mapping frame embeddings to centroids-{i}"):
+                temp.append({'frame': frame['frame'], 'faces': [face for face in frame['faces'] if face['target_centroid'] == i], 'location': frame['location']})
+
+            modules.globals.souce_target_map[i]['target_faces_in_frame'] = temp
+
+        # dump_faces(centroids, frame_face_embeddings)
+        default_target_face()
+    except ValueError:
+        return None
+    
+
+def default_target_face():
+    for map in modules.globals.souce_target_map:
+        best_face = None
+        best_frame = None
+        for frame in map['target_faces_in_frame']:
+            if len(frame['faces']) > 0:
+                best_face = frame['faces'][0]
+                best_frame = frame
+                break
+
+        for frame in map['target_faces_in_frame']:
+            for face in frame['faces']:
+                if face['det_score'] > best_face['det_score']:
+                    best_face = face
+                    best_frame = frame
+
+        x_min, y_min, x_max, y_max = best_face['bbox']
+
+        target_frame = cv2.imread(best_frame['location'])
+        map['target'] = {
+                        'cv2' : target_frame[int(y_min):int(y_max), int(x_min):int(x_max)],
+                        'face' : best_face
+                        }
+
+
+def dump_faces(centroids: Any, frame_face_embeddings: list):
+    temp_directory_path = get_temp_directory_path(modules.globals.target_path)
+
+    for i in range(len(centroids)):
+        if os.path.exists(temp_directory_path + f"/{i}") and os.path.isdir(temp_directory_path + f"/{i}"):
+            shutil.rmtree(temp_directory_path + f"/{i}")
+        Path(temp_directory_path + f"/{i}").mkdir(parents=True, exist_ok=True)
+
+        for frame in tqdm(frame_face_embeddings, desc=f"Copying faces to temp/./{i}"):
+            temp_frame = cv2.imread(frame['location'])
+
+            j = 0
+            for face in frame['faces']:
+                if face['target_centroid'] == i:
+                    x_min, y_min, x_max, y_max = face['bbox']
+
+                    if temp_frame[int(y_min):int(y_max), int(x_min):int(x_max)].size > 0:
+                        cv2.imwrite(temp_directory_path + f"/{i}/{frame['frame']}_{j}.png", temp_frame[int(y_min):int(y_max), int(x_min):int(x_max)])
+                j += 1
@@ -1,35 +1,46 @@
 import os
-from typing import List, Dict
+from typing import List, Dict, Any

 ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
-WORKFLOW_DIR = os.path.join(ROOT_DIR, 'workflow')
+WORKFLOW_DIR = os.path.join(ROOT_DIR, "workflow")

 file_types = [
-    ('Image', ('*.png','*.jpg','*.jpeg','*.gif','*.bmp')),
-    ('Video', ('*.mp4','*.mkv'))
+    ("Image", ("*.png", "*.jpg", "*.jpeg", "*.gif", "*.bmp")),
+    ("Video", ("*.mp4", "*.mkv")),
 ]

+souce_target_map = []
+simple_map = {}
+
 source_path = None
 target_path = None
 output_path = None
 frame_processors: List[str] = []
-keep_fps = None
-keep_audio = None
-keep_frames = None
-many_faces = None
+keep_fps = True  # Initialize with default value
+keep_audio = True  # Initialize with default value
+keep_frames = False  # Initialize with default value
+many_faces = False  # Initialize with default value
+map_faces = False  # Initialize with default value
+color_correction = False  # Initialize with default value
+nsfw_filter = False  # Initialize with default value
 video_encoder = None
 video_quality = None
-live_mirror = None
-live_resizable = None
+live_mirror = False  # Initialize with default value
+live_resizable = False  # Initialize with default value
 max_memory = None
 execution_providers: List[str] = []
 execution_threads = None
 headless = None
-log_level = 'error'
-fp_ui: Dict[str, bool] = {}
-nsfw = None
+log_level = "error"
+fp_ui: Dict[str, bool] = {"face_enhancer": False}  # Initialize with default value
 camera_input_combobox = None
 webcam_preview_running = False
-enhancer_upscale_factor = 1
-source_image_scaling_factor = 2
-sr_scale_factor = 4
+show_fps = False  # Initialize with default value
+mouth_mask = False
+show_mouth_mask_box = False
+mask_down_size = 0.5
+mask_size = 1.0
+mask_feather_ratio = 8
+opacity_switch = False
+face_opacity = 100
+selected_camera = None
@@ -1,3 +1,3 @@
 name = 'Deep Live Cam'
-version = '1.3.0'
+version = '1.6.0'
 edition = 'Portable'
@@ -1,6 +1,9 @@
-import numpy as np
+import numpy
 import opennsfw2
 from PIL import Image
+import cv2  # Add OpenCV import
+import modules.globals  # Import globals to access the color correction toggle
+
 from modules.typing import Frame

 MAX_PROBABILITY = 0.85
@@ -9,17 +12,24 @@ MAX_PROBABILITY = 0.85
 model = None

 def predict_frame(target_frame: Frame) -> bool:
-    global model
-    if model is None: model = opennsfw2.make_open_nsfw_model()
+    # Convert the frame to RGB before processing if color correction is enabled
+    if modules.globals.color_correction:
+        target_frame = cv2.cvtColor(target_frame, cv2.COLOR_BGR2RGB)
+        
    image = Image.fromarray(target_frame)
    image = opennsfw2.preprocess_image(image, opennsfw2.Preprocessing.YAHOO)
-    views = np.expand_dims(image, axis=0)
+    global model
+    if model is None: 
+        model = opennsfw2.make_open_nsfw_model()
+        
+    views = numpy.expand_dims(image, axis=0)
    _, probability = model.predict(views)[0]
    return probability > MAX_PROBABILITY

+
 def predict_image(target_path: str) -> bool:
-    probability = opennsfw2.predict_image(target_path)
-    return probability > MAX_PROBABILITY
+    return opennsfw2.predict_image(target_path) > MAX_PROBABILITY
+

 def predict_video(target_path: str) -> bool:
    _, probabilities = opennsfw2.predict_video_frames(video_path=target_path, frame_interval=100)
@@ -17,56 +17,57 @@ FRAME_PROCESSORS_INTERFACE = [
    'process_video'
 ]

-def load_frame_processor_module(frame_processor: str) -> ModuleType:
+
+def load_frame_processor_module(frame_processor: str) -> Any:
    try:
        frame_processor_module = importlib.import_module(f'modules.processors.frame.{frame_processor}')
-        # Ensure all required methods are present
        for method_name in FRAME_PROCESSORS_INTERFACE:
            if not hasattr(frame_processor_module, method_name):
-                raise AttributeError(f"Missing required method {method_name} in {frame_processor} module.")
+                sys.exit()
    except ImportError:
-        print(f"Error: Frame processor '{frame_processor}' not found.")
-        sys.exit(1)
-    except AttributeError as e:
-        print(e)
-        sys.exit(1)
-    
+        print(f"Frame processor {frame_processor} not found")
+        sys.exit()
    return frame_processor_module

+
 def get_frame_processors_modules(frame_processors: List[str]) -> List[ModuleType]:
    global FRAME_PROCESSORS_MODULES

    if not FRAME_PROCESSORS_MODULES:
-        FRAME_PROCESSORS_MODULES = [load_frame_processor_module(fp) for fp in frame_processors]
-    
+        for frame_processor in frame_processors:
+            frame_processor_module = load_frame_processor_module(frame_processor)
+            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
    set_frame_processors_modules_from_ui(frame_processors)
    return FRAME_PROCESSORS_MODULES

 def set_frame_processors_modules_from_ui(frame_processors: List[str]) -> None:
    global FRAME_PROCESSORS_MODULES
    for frame_processor, state in modules.globals.fp_ui.items():
-        if state and frame_processor not in frame_processors:
-            module = load_frame_processor_module(frame_processor)
-            FRAME_PROCESSORS_MODULES.append(module)
+        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)
-        elif not state and frame_processor in frame_processors:
-            module = load_frame_processor_module(frame_processor)
-            FRAME_PROCESSORS_MODULES.remove(module)
-            modules.globals.frame_processors.remove(frame_processor)
+        if state == False:
+            try:
+                frame_processor_module = load_frame_processor_module(frame_processor)
+                FRAME_PROCESSORS_MODULES.remove(frame_processor_module)
+                modules.globals.frame_processors.remove(frame_processor)
+            except:
+                pass

 def multi_process_frame(source_path: str, temp_frame_paths: List[str], process_frames: Callable[[str, List[str], Any], None], progress: Any = None) -> None:
    with ThreadPoolExecutor(max_workers=modules.globals.execution_threads) as executor:
-        futures = [executor.submit(process_frames, source_path, [path], progress) for path in temp_frame_paths]
+        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:
+
+def process_video(source_path: str, frame_paths: list[str], process_frames: Callable[[str, List[str], Any], None]) -> None:
    progress_bar_format = '{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]'
    total = len(frame_paths)
    with tqdm(total=total, desc='Processing', unit='frame', dynamic_ncols=True, bar_format=progress_bar_format) as progress:
-        progress.set_postfix({
-            'execution_providers': modules.globals.execution_providers, 
-            'execution_threads': modules.globals.execution_threads, 
-            'max_memory': modules.globals.max_memory
-        })
+        progress.set_postfix({'execution_providers': modules.globals.execution_providers, 'execution_threads': modules.globals.execution_threads, 'max_memory': modules.globals.max_memory})
        multi_process_frame(source_path, frame_paths, process_frames, progress)
@@ -8,7 +8,7 @@ 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  # Ensure these are imported
+from modules.typing import Frame, Face
 from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video

 FACE_ENHANCER = None
@@ -16,29 +16,34 @@ THREAD_SEMAPHORE = threading.Semaphore()
 THREAD_LOCK = threading.Lock()
 NAME = 'DLC.FACE-ENHANCER'

+
 def pre_check() -> bool:
    download_directory_path = resolve_relative_path('..\models')
    conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'])
    return True

+
 def pre_start() -> bool:
    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
        update_status('Select an image or video for target path.', NAME)
        return False
    return True

+
 def get_face_enhancer() -> Any:
    global FACE_ENHANCER

    with THREAD_LOCK:
        if FACE_ENHANCER is None:
-            model_path = resolve_relative_path('../models/GFPGANv1.4.pth')
-            FACE_ENHANCER = gfpgan.GFPGANer(
-                model_path=model_path,
-                upscale=modules.globals.enhancer_upscale_factor
-            )  # type: ignore[attr-defined]
+            if os.name == 'nt':
+                model_path = resolve_relative_path('..\models\GFPGANv1.4.pth')
+                # todo: set models path https://github.com/TencentARC/GFPGAN/issues/399
+            else:
+                model_path = resolve_relative_path('../models/GFPGANv1.4.pth')
+            FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1) # type: ignore[attr-defined]
    return FACE_ENHANCER

+
 def enhance_face(temp_frame: Frame) -> Frame:
    with THREAD_SEMAPHORE:
        _, _, temp_frame = get_face_enhancer().enhance(
@@ -47,12 +52,14 @@ def enhance_face(temp_frame: Frame) -> Frame:
        )
    return 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, temp_frame_paths: List[str], progress: Any = None) -> None:
    for temp_frame_path in temp_frame_paths:
        temp_frame = cv2.imread(temp_frame_path)
@@ -61,10 +68,12 @@ def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any
        if progress:
            progress.update(1)

+
 def process_image(source_path: str, target_path: str, output_path: str) -> None:
    target_frame = cv2.imread(target_path)
    result = process_frame(None, target_frame)
    cv2.imwrite(output_path, result)

+
 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
    modules.processors.frame.core.process_video(None, temp_frame_paths, process_frames)
@@ -2,68 +2,101 @@ from typing import Any, List
 import cv2
 import insightface
 import threading
-import os
-
+import numpy as np
 import modules.globals
 import modules.processors.frame.core
 from modules.core import update_status
-from modules.face_analyser import get_one_face, get_many_faces
+from modules.face_analyser import get_one_face, get_many_faces, default_source_face
 from modules.typing import Face, Frame
-from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
-import numpy as np
+from modules.utilities import (
+    conditional_download,
+    resolve_relative_path,
+    is_image,
+    is_video,
+)
+from modules.cluster_analysis import find_closest_centroid

 FACE_SWAPPER = None
 THREAD_LOCK = threading.Lock()
-NAME = 'DLC.FACE-SWAPPER'
+NAME = "DLC.FACE-SWAPPER"
+

 def pre_check() -> bool:
-    download_directory_path = resolve_relative_path('../models')
-    conditional_download(download_directory_path, [
-        'https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128.onnx'
-    ])
+    download_directory_path = resolve_relative_path("../models")
+    conditional_download(
+        download_directory_path,
+        [
+            "https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx"
+        ],
+    )
    return True

+
 def pre_start() -> bool:
-    if not is_image(modules.globals.source_path):
-        update_status('Select an image for source path.', NAME)
+    if not modules.globals.map_faces and not is_image(modules.globals.source_path):
+        update_status("Select an image for source path.", NAME)
        return False
-    elif not get_one_face(cv2.imread(modules.globals.source_path)):
-        update_status('No face detected in the source path.', NAME)
+    elif not modules.globals.map_faces and not get_one_face(
+        cv2.imread(modules.globals.source_path)
+    ):
+        update_status("No face in source path detected.", NAME)
        return False
-    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
-        update_status('Select an image or video for target path.', NAME)
+    if not is_image(modules.globals.target_path) and not is_video(
+        modules.globals.target_path
+    ):
+        update_status("Select an image or video for target path.", NAME)
        return False
    return True

+
 def get_face_swapper() -> Any:
    global FACE_SWAPPER

    with THREAD_LOCK:
        if FACE_SWAPPER is None:
-            model_path = resolve_relative_path('../models/inswapper_128.onnx')
-            FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=modules.globals.execution_providers)
+            model_path = resolve_relative_path("../models/inswapper_128_fp16.onnx")
+            FACE_SWAPPER = insightface.model_zoo.get_model(
+                model_path, providers=modules.globals.execution_providers
+            )
    return FACE_SWAPPER

-def upscale_image(image: np.ndarray, scaling_factor: int = modules.globals.source_image_scaling_factor) -> np.ndarray:
-    """
-    Upscales the given image by the specified scaling factor.
-
-    Args:
-        image (np.ndarray): The input image to upscale.
-        scaling_factor (int): The factor by which to upscale the image.
-
-    Returns:
-        np.ndarray: The upscaled image.
-    """
-    height, width = image.shape[:2]
-    new_size = (width * scaling_factor, height * scaling_factor)
-    upscaled_image = cv2.resize(image, new_size, interpolation=cv2.INTER_CUBIC)
-    return upscaled_image

 def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
-    return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True)
+    swapped_frame = get_face_swapper().get(
+        temp_frame, target_face, source_face, paste_back=True
+    )
+
+    # Apply opacity if enabled
+    if modules.globals.opacity_switch:
+        opacity = modules.globals.face_opacity / 100
+        swapped_frame = cv2.addWeighted(
+            swapped_frame, opacity, temp_frame, 1 - opacity, 0
+        )
+
+    # Apply mouth mask if enabled
+    if modules.globals.mouth_mask:
+        face_mask = create_face_mask(target_face, temp_frame)
+        mouth_mask_data = create_lower_mouth_mask(target_face, temp_frame)
+        mouth_mask, mouth_cutout, mouth_box, lower_lip_polygon = mouth_mask_data
+
+        if mouth_box is not None:
+            swapped_frame = apply_mouth_area(
+                swapped_frame, mouth_cutout, mouth_box, face_mask, lower_lip_polygon
+            )
+
+            if modules.globals.show_mouth_mask_box:
+                swapped_frame = draw_mouth_mask_visualization(
+                    swapped_frame, target_face, mouth_mask_data
+                )
+
+    return swapped_frame
+

 def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
+    # Ensure the frame is in RGB format if color correction is enabled
+    if modules.globals.color_correction:
+        temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)
+
    if modules.globals.many_faces:
        many_faces = get_many_faces(temp_frame)
        if many_faces:
@@ -75,30 +108,386 @@ def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
            temp_frame = swap_face(source_face, target_face, temp_frame)
    return temp_frame

-def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
-    source_image = cv2.imread(source_path)
-    if source_image is None:
-        print(f"Failed to load source image from {source_path}")
-        return
-    # Upscale the source image for better quality
-    source_image_upscaled = upscale_image(source_image, scaling_factor=2)
-    source_face = get_one_face(source_image_upscaled)

-    for temp_frame_path in temp_frame_paths:
-        temp_frame = cv2.imread(temp_frame_path)
-        try:
-            result = process_frame(source_face, temp_frame)
-            cv2.imwrite(temp_frame_path, result)
-        except Exception as exception:
-            print(f"Error processing frame {temp_frame_path}: {exception}")
-        if progress:
-            progress.update(1)
+def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
+    if is_image(modules.globals.target_path):
+        if modules.globals.many_faces:
+            source_face = default_source_face()
+            for map in modules.globals.souce_target_map:
+                target_face = map["target"]["face"]
+                temp_frame = swap_face(source_face, target_face, temp_frame)
+
+        elif not modules.globals.many_faces:
+            for map in modules.globals.souce_target_map:
+                if "source" in map:
+                    source_face = map["source"]["face"]
+                    target_face = map["target"]["face"]
+                    temp_frame = swap_face(source_face, target_face, temp_frame)
+
+    elif is_video(modules.globals.target_path):
+        if modules.globals.many_faces:
+            source_face = default_source_face()
+            for map in modules.globals.souce_target_map:
+                target_frame = [
+                    f
+                    for f in map["target_faces_in_frame"]
+                    if f["location"] == temp_frame_path
+                ]
+
+                for frame in target_frame:
+                    for target_face in frame["faces"]:
+                        temp_frame = swap_face(source_face, target_face, temp_frame)
+
+        elif not modules.globals.many_faces:
+            for map in modules.globals.souce_target_map:
+                if "source" in map:
+                    target_frame = [
+                        f
+                        for f in map["target_faces_in_frame"]
+                        if f["location"] == temp_frame_path
+                    ]
+                    source_face = map["source"]["face"]
+
+                    for frame in target_frame:
+                        for target_face in frame["faces"]:
+                            temp_frame = swap_face(source_face, target_face, temp_frame)
+    else:
+        detected_faces = get_many_faces(temp_frame)
+        if modules.globals.many_faces:
+            if detected_faces:
+                source_face = default_source_face()
+                for target_face in detected_faces:
+                    temp_frame = swap_face(source_face, target_face, temp_frame)
+
+        elif not modules.globals.many_faces:
+            if detected_faces:
+                if len(detected_faces) <= len(
+                    modules.globals.simple_map["target_embeddings"]
+                ):
+                    for detected_face in detected_faces:
+                        closest_centroid_index, _ = find_closest_centroid(
+                            modules.globals.simple_map["target_embeddings"],
+                            detected_face.normed_embedding,
+                        )
+
+                        temp_frame = swap_face(
+                            modules.globals.simple_map["source_faces"][
+                                closest_centroid_index
+                            ],
+                            detected_face,
+                            temp_frame,
+                        )
+                else:
+                    detected_faces_centroids = []
+                    for face in detected_faces:
+                        detected_faces_centroids.append(face.normed_embedding)
+                    i = 0
+                    for target_embedding in modules.globals.simple_map[
+                        "target_embeddings"
+                    ]:
+                        closest_centroid_index, _ = find_closest_centroid(
+                            detected_faces_centroids, target_embedding
+                        )
+
+                        temp_frame = swap_face(
+                            modules.globals.simple_map["source_faces"][i],
+                            detected_faces[closest_centroid_index],
+                            temp_frame,
+                        )
+                        i += 1
+    return temp_frame
+
+
+def process_frames(
+    source_path: str, temp_frame_paths: List[str], progress: Any = None
+) -> None:
+    if not modules.globals.map_faces:
+        source_face = get_one_face(cv2.imread(source_path))
+        for temp_frame_path in temp_frame_paths:
+            temp_frame = cv2.imread(temp_frame_path)
+            try:
+                result = process_frame(source_face, temp_frame)
+                cv2.imwrite(temp_frame_path, result)
+            except Exception as exception:
+                print(exception)
+                pass
+            if progress:
+                progress.update(1)
+    else:
+        for temp_frame_path in temp_frame_paths:
+            temp_frame = cv2.imread(temp_frame_path)
+            try:
+                result = process_frame_v2(temp_frame, temp_frame_path)
+                cv2.imwrite(temp_frame_path, result)
+            except Exception as exception:
+                print(exception)
+                pass
+            if progress:
+                progress.update(1)
+

 def process_image(source_path: str, target_path: str, output_path: str) -> None:
-    source_face = get_one_face(cv2.imread(source_path))
-    target_frame = cv2.imread(target_path)
-    result = process_frame(source_face, target_frame)
-    cv2.imwrite(output_path, result)
+    if not modules.globals.map_faces:
+        source_face = get_one_face(cv2.imread(source_path))
+        target_frame = cv2.imread(target_path)
+        result = process_frame(source_face, target_frame)
+        cv2.imwrite(output_path, result)
+    else:
+        if modules.globals.many_faces:
+            update_status(
+                "Many faces enabled. Using first source image. Progressing...", NAME
+            )
+        target_frame = cv2.imread(output_path)
+        result = process_frame_v2(target_frame)
+        cv2.imwrite(output_path, result)
+

 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
-    modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)
+    if modules.globals.map_faces and modules.globals.many_faces:
+        update_status(
+            "Many faces enabled. Using first source image. Progressing...", NAME
+        )
+    modules.processors.frame.core.process_video(
+        source_path, temp_frame_paths, process_frames
+    )
+
+
+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:
+        landmarks = landmarks.astype(np.int32)
+
+        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]
+
+        right_eyebrow_top = np.min(right_eye_brow[:, 1])
+        left_eyebrow_top = np.min(left_eye_brow[:, 1])
+        eyebrow_top = min(right_eyebrow_top, left_eyebrow_top)
+
+        face_top = np.min([right_side_face[0, 1], left_side_face[-1, 1]])
+        forehead_height = face_top - eyebrow_top
+        extended_forehead_height = int(forehead_height * 5.0)
+
+        forehead_left = right_side_face[0].copy()
+        forehead_right = left_side_face[-1].copy()
+        forehead_left[1] -= extended_forehead_height
+        forehead_right[1] -= extended_forehead_height
+
+        face_outline = np.vstack(
+            [
+                [forehead_left],
+                right_side_face,
+                left_side_face[::-1],
+                [forehead_right],
+            ]
+        )
+
+        padding = int(np.linalg.norm(right_side_face[0] - left_side_face[-1]) * 0.05)
+
+        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)
+        cv2.fillConvexPoly(mask, hull_padded, 255)
+        mask = cv2.GaussianBlur(mask, (5, 5), 3)
+
+    return mask
+
+
+def create_lower_mouth_mask(face: Face, frame: Frame) -> tuple:
+    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
+    mouth_cutout = None
+    landmarks = face.landmark_2d_106
+    if landmarks is not None:
+        lower_lip_order = [
+            65,
+            66,
+            62,
+            70,
+            69,
+            18,
+            19,
+            20,
+            21,
+            22,
+            23,
+            24,
+            0,
+            8,
+            7,
+            6,
+            5,
+            4,
+            3,
+            2,
+            65,
+        ]
+        lower_lip_landmarks = landmarks[lower_lip_order].astype(np.float32)
+
+        center = np.mean(lower_lip_landmarks, axis=0)
+        expansion_factor = 1 + modules.globals.mask_down_size
+        expanded_landmarks = (lower_lip_landmarks - center) * expansion_factor + center
+
+        toplip_indices = [20, 0, 1, 2, 3, 4, 5]
+        toplip_extension = modules.globals.mask_size * 0.5
+        for idx in toplip_indices:
+            direction = expanded_landmarks[idx] - center
+            direction = direction / np.linalg.norm(direction)
+            expanded_landmarks[idx] += direction * toplip_extension
+
+        chin_indices = [11, 12, 13, 14, 15, 16]
+        chin_extension = 2 * 0.2
+        for idx in chin_indices:
+            expanded_landmarks[idx][1] += (
+                expanded_landmarks[idx][1] - center[1]
+            ) * chin_extension
+
+        expanded_landmarks = expanded_landmarks.astype(np.int32)
+
+        min_x, min_y = np.min(expanded_landmarks, axis=0)
+        max_x, max_y = np.max(expanded_landmarks, axis=0)
+
+        padding = int((max_x - min_x) * 0.1)
+        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)
+
+        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
+
+        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
+        cv2.fillPoly(mask_roi, [expanded_landmarks - [min_x, min_y]], 255)
+        mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
+        mask[min_y:max_y, min_x:max_x] = mask_roi
+        mouth_cutout = frame[min_y:max_y, min_x:max_x].copy()
+
+        return mask, mouth_cutout, (min_x, min_y, max_x, max_y), expanded_landmarks
+
+    return mask, mouth_cutout, None, None
+
+
+def apply_mouth_area(
+    frame: Frame,
+    mouth_cutout: np.ndarray,
+    mouth_box: tuple,
+    face_mask: np.ndarray,
+    mouth_polygon: np.ndarray,
+) -> Frame:
+    min_x, min_y, max_x, max_y = mouth_box
+    box_width = max_x - min_x
+    box_height = max_y - min_y
+
+    if (
+        mouth_cutout is None
+        or box_width is None
+        or box_height is None
+        or face_mask is None
+        or mouth_polygon is None
+    ):
+        return frame
+
+    try:
+        resized_mouth_cutout = cv2.resize(mouth_cutout, (box_width, box_height))
+        roi = frame[min_y:max_y, min_x:max_x]
+
+        if roi.shape != resized_mouth_cutout.shape:
+            resized_mouth_cutout = cv2.resize(
+                resized_mouth_cutout, (roi.shape[1], roi.shape[0])
+            )
+
+        color_corrected_mouth = apply_color_transfer(resized_mouth_cutout, roi)
+
+        polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
+        adjusted_polygon = mouth_polygon - [min_x, min_y]
+        cv2.fillPoly(polygon_mask, [adjusted_polygon], 255)
+
+        feather_amount = min(
+            30,
+            box_width // modules.globals.mask_feather_ratio,
+            box_height // modules.globals.mask_feather_ratio,
+        )
+        feathered_mask = cv2.GaussianBlur(
+            polygon_mask.astype(float), (0, 0), feather_amount
+        )
+        feathered_mask = feathered_mask / feathered_mask.max()
+
+        face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
+        combined_mask = feathered_mask * (face_mask_roi / 255.0)
+
+        combined_mask = combined_mask[:, :, np.newaxis]
+        blended = (
+            color_corrected_mouth * combined_mask + roi * (1 - combined_mask)
+        ).astype(np.uint8)
+
+        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 apply_color_transfer(source: np.ndarray, target: np.ndarray) -> np.ndarray:
+    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)
+
+    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)
+
+    source = (source - source_mean) * (target_std / source_std) + target_mean
+
+    return cv2.cvtColor(np.clip(source, 0, 255).astype("uint8"), cv2.COLOR_LAB2BGR)
+
+
+def draw_mouth_mask_visualization(
+    frame: Frame, face: Face, mouth_mask_data: tuple
+) -> Frame:
+    landmarks = face.landmark_2d_106
+    if landmarks is not None and mouth_mask_data is not None:
+        mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon = (
+            mouth_mask_data
+        )
+
+        vis_frame = frame.copy()
+
+        # Draw the lower lip polygon
+        cv2.polylines(vis_frame, [lower_lip_polygon], True, (0, 255, 0), 2)
+
+        # Add labels
+        cv2.putText(
+            vis_frame,
+            "Mouth Mask",
+            (min_x, min_y - 10),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.5,
+            (255, 255, 255),
+            1,
+        )
+
+        return vis_frame
+    return frame
@@ -1,197 +0,0 @@
-import threading
-import traceback
-from typing import Any, List
-import cv2
-
-import os
-
-import modules.globals
-import modules.processors.frame.core
-from modules.core import update_status
-from modules.face_analyser import get_one_face
-from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
-import numpy as np
-
-NAME = 'DLC.SUPER-RESOLUTION'
-THREAD_SEMAPHORE = threading.Semaphore()
-
-# Singleton class for Super-Resolution
-class SuperResolutionModel:
-    _instance = None
-    _lock = threading.Lock()
-
-    def __init__(self, sr_model_path: str = f'ESPCN_x{modules.globals.sr_scale_factor}.pb'):
-        if SuperResolutionModel._instance is not None:
-            raise Exception("This class is a singleton!")
-        self.sr = cv2.dnn_superres.DnnSuperResImpl_create()
-        self.model_path = os.path.join(resolve_relative_path('../models'), sr_model_path)
-        if not os.path.exists(self.model_path):
-            raise FileNotFoundError(f"Super-resolution model not found at {self.model_path}")
-        try:
-            self.sr.readModel(self.model_path)
-            self.sr.setModel("espcn", modules.globals.sr_scale_factor)  # Using ESPCN with 2,3 or 4x upscaling
-        except Exception as e:
-            print(f"Error during super-resolution model initialization: {e}")
-            raise e
-
-    @classmethod
-    def get_instance(cls, sr_model_path: str = f'ESPCN_x{modules.globals.sr_scale_factor}.pb'):
-        if cls._instance is None:
-            with cls._lock:
-                if cls._instance is None:
-                    try:
-                        cls._instance = cls(sr_model_path)
-                    except Exception as e:
-                        raise RuntimeError(f"Failed to initialize SuperResolution: {str(e)}")
-        return cls._instance
-
-
-def pre_check() -> bool:
-    """
-    Checks and downloads necessary models before starting the face swapper.
-    """
-    download_directory_path = resolve_relative_path('../models')
-    # Download the super-resolution model as well
-    conditional_download(download_directory_path, [
-        f'https://huggingface.co/spaces/PabloGabrielSch/AI_Resolution_Upscaler_And_Resizer/resolve/bcd13b766a9499196e8becbe453c4a848673b3b6/models/ESPCN_x{modules.globals.sr_scale_factor}.pb'
-    ])
-    return True
-
-def pre_start() -> bool:
-    if not is_image(modules.globals.source_path):
-        update_status('Select an image for source path.', NAME)
-        return False
-    elif not get_one_face(cv2.imread(modules.globals.source_path)):
-        update_status('No face detected in the source path.', NAME)
-        return False
-    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
-        update_status('Select an image or video for target path.', NAME)
-        return False
-    return True
-
-
-def apply_super_resolution(image: np.ndarray) -> np.ndarray:
-    """
-    Applies super-resolution to the given image using the provided super-resolver.
-
-    Args:
-        image (np.ndarray): The input image to enhance.
-        sr_model_path (str): ESPCN model path for super-resolution.
-
-    Returns:
-        np.ndarray: The super-resolved image.
-    """
-    with THREAD_SEMAPHORE:
-        sr_model = SuperResolutionModel.get_instance()
-
-        if sr_model is None:
-            print("Super-resolution model is not initialized.")
-            return image
-        try:
-            upscaled_image = sr_model.sr.upsample(image)
-            return upscaled_image
-        except Exception as e:
-            print(f"Error during super-resolution: {e}")
-            return image
-
-
-def process_frame(frame: np.ndarray) -> np.ndarray:
-    """
-    Processes a single frame by swapping the source face into detected target faces.
-
-    Args:
-
-        frame (np.ndarray): The target frame image.
-
-    Returns:
-        np.ndarray: The processed frame with swapped faces.
-    """
-
-    # Apply super-resolution to the entire frame
-    frame = apply_super_resolution(frame)
-
-    return frame
-
-def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
-    """
-    Processes multiple frames by swapping the source face into each target frame.
-
-    Args:
-        source_path (str): Path to the source image.
-        temp_frame_paths (List[str]): List of paths to target frame images.
-        progress (Any, optional): Progress tracker. Defaults to None.
-    """
-    for idx, temp_frame_path in enumerate(temp_frame_paths):
-        frame = cv2.imread(temp_frame_path)
-        if frame is None:
-            print(f"Failed to load frame from {temp_frame_path}")
-            continue
-        try:
-            result = process_frame(frame)
-            cv2.imwrite(temp_frame_path, result)
-        except Exception as exception:
-            traceback.print_exc()
-            print(f"Error processing frame {temp_frame_path}: {exception}")
-        if progress:
-            progress.update(1)
-
-def upscale_image(image: np.ndarray, scaling_factor: int = 2) -> np.ndarray:
-    """
-    Upscales the given image by the specified scaling factor.
-
-    Args:
-        image (np.ndarray): The input image to upscale.
-        scaling_factor (int): The factor by which to upscale the image.
-
-    Returns:
-        np.ndarray: The upscaled image.
-    """
-    height, width = image.shape[:2]
-    new_size = (width * scaling_factor, height * scaling_factor)
-    upscaled_image = cv2.resize(image, new_size, interpolation=cv2.INTER_CUBIC)
-    return upscaled_image
-
-def process_image(source_path: str, target_path: str, output_path: str) -> None:
-    """
-    Processes a single image by swapping the source face into the target image.
-
-    Args:
-        source_path (str): Path to the source image.
-        target_path (str): Path to the target image.
-        output_path (str): Path to save the output image.
-    """
-    source_image = cv2.imread(source_path)
-    if source_image is None:
-        print(f"Failed to load source image from {source_path}")
-        return
-
-    # Upscale the source image for better quality before face detection
-    source_image_upscaled = upscale_image(source_image, scaling_factor=2)
-
-    # Detect source face from the upscaled image
-    source_face = get_one_face(source_image_upscaled)
-    if source_face is None:
-        print("No source face detected.")
-        return
-
-    target_frame = cv2.imread(target_path)
-    if target_frame is None:
-        print(f"Failed to load target image from {target_path}")
-        return
-
-    # Process the frame
-    result = process_frame(target_frame)
-
-    # Save the processed frame
-    cv2.imwrite(output_path, result)
-
-
-def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
-    """
-    Processes a video by swapping the source face into each frame.
-
-    Args:
-        source_path (str): Path to the source image.
-        temp_frame_paths (List[str]): List of paths to video frame images.
-    """
-    modules.processors.frame.core.process_video(None, temp_frame_paths, process_frames)
@@ -1,57 +1,76 @@
 {
  "CTk": {
-    "fg_color": ["#FFFFFF", "#2D2D2D"]
+    "fg_color": ["gray95", "gray10"]
  },
  "CTkToplevel": {
-    "fg_color": ["#FFFFFF", "#2D2D2D"]
+    "fg_color": ["gray95", "gray10"]
  },
  "CTkFrame": {
    "corner_radius": 0,
    "border_width": 0,
-    "fg_color": ["#F0F0F0", "#3C3C3C"],
-    "top_fg_color": ["#E0E0E0", "#4B4B4B"],
-    "border_color": ["#B0B0B0", "#5A5A5A"]
+    "fg_color": ["gray90", "gray13"],
+    "top_fg_color": ["gray85", "gray16"],
+    "border_color": ["gray65", "gray28"]
  },
  "CTkButton": {
    "corner_radius": 0,
    "border_width": 0,
-    "fg_color": ["#007ACC", "#007ACC"],
-    "hover_color": ["#005EA3", "#005EA3"],
-    "border_color": ["#004C8A", "#004C8A"],
-    "text_color": ["#FFFFFF", "#FFFFFF"],
+    "fg_color": ["#2aa666", "#1f538d"],
+    "hover_color": ["#3cb666", "#14375e"],
+    "border_color": ["#3e4a40", "#949A9F"],
+    "text_color": ["#f3faf6", "#f3faf6"],
    "text_color_disabled": ["gray74", "gray60"]
  },
  "CTkLabel": {
    "corner_radius": 0,
    "fg_color": "transparent",
-    "text_color": ["#000000", "#FFFFFF"]
+    "text_color": ["gray14", "gray84"]
  },
  "CTkEntry": {
    "corner_radius": 0,
    "border_width": 2,
-    "fg_color": ["#FFFFFF", "#333333"],
-    "border_color": ["#A0A0A0", "#5A5A5A"],
-    "text_color": ["#000000", "#FFFFFF"],
+    "fg_color": ["#F9F9FA", "#343638"],
+    "border_color": ["#979DA2", "#565B5E"],
+    "text_color": ["gray14", "gray84"],
    "placeholder_text_color": ["gray52", "gray62"]
  },
+  "CTkCheckbox": {
+    "corner_radius": 0,
+    "border_width": 3,
+    "fg_color": ["#2aa666", "#1f538d"],
+    "border_color": ["#3e4a40", "#949A9F"],
+    "hover_color": ["#3cb666", "#14375e"],
+    "checkmark_color": ["#f3faf6", "gray90"],
+    "text_color": ["gray14", "gray84"],
+    "text_color_disabled": ["gray60", "gray45"]
+  },
  "CTkSwitch": {
    "corner_radius": 1000,
    "border_width": 3,
    "button_length": 0,
    "fg_color": ["#939BA2", "#4A4D50"],
    "progress_color": ["#2aa666", "#1f538d"],
-    "button_color": ["#444444", "#D5D9DE"],
-    "button_hover_color": ["#333333", "#FFFFFF"],
-    "text_color": ["#000000", "#FFFFFF"],
+    "button_color": ["gray36", "#D5D9DE"],
+    "button_hover_color": ["gray20", "gray100"],
+    "text_color": ["gray14", "gray84"],
    "text_color_disabled": ["gray60", "gray45"]
  },
-  "CTkOptionMenu": {
-    "corner_radius": 0,
+  "CTkRadiobutton": {
+    "corner_radius": 1000,
+    "border_width_checked": 6,
+    "border_width_unchecked": 3,
    "fg_color": ["#2aa666", "#1f538d"],
-    "button_color": ["#3cb666", "#14375e"],
-    "button_hover_color": ["#234567", "#1e2c40"],
-    "text_color": ["#FFFFFF", "#FFFFFF"],
-    "text_color_disabled": ["gray74", "gray60"]
+    "border_color": ["#3e4a40", "#949A9F"],
+    "hover_color": ["#3cb666", "#14375e"],
+    "text_color": ["gray14", "gray84"],
+    "text_color_disabled": ["gray60", "gray45"]
+  },
+  "CTkProgressBar": {
+    "corner_radius": 1000,
+    "border_width": 0,
+    "fg_color": ["#939BA2", "#4A4D50"],
+    "progress_color": ["#2aa666", "#1f538d"],
+    "border_color": ["gray", "gray"]
  },
  "CTkSlider": {
    "corner_radius": 1000,
@@ -63,6 +82,59 @@
    "button_color": ["#2aa666", "#1f538d"],
    "button_hover_color": ["#3cb666", "#14375e"]
  },
+  "CTkOptionMenu": {
+    "corner_radius": 0,
+    "fg_color": ["#2aa666", "#1f538d"],
+    "button_color": ["#3cb666", "#14375e"],
+    "button_hover_color": ["#234567", "#1e2c40"],
+    "text_color": ["#f3faf6", "#f3faf6"],
+    "text_color_disabled": ["gray74", "gray60"]
+  },
+  "CTkComboBox": {
+    "corner_radius": 0,
+    "border_width": 2,
+    "fg_color": ["#F9F9FA", "#343638"],
+    "border_color": ["#979DA2", "#565B5E"],
+    "button_color": ["#979DA2", "#565B5E"],
+    "button_hover_color": ["#6E7174", "#7A848D"],
+    "text_color": ["gray14", "gray84"],
+    "text_color_disabled": ["gray50", "gray45"]
+  },
+  "CTkScrollbar": {
+    "corner_radius": 1000,
+    "border_spacing": 4,
+    "fg_color": "transparent",
+    "button_color": ["gray55", "gray41"],
+    "button_hover_color": ["gray40", "gray53"]
+  },
+  "CTkSegmentedButton": {
+    "corner_radius": 0,
+    "border_width": 2,
+    "fg_color": ["#979DA2", "gray29"],
+    "selected_color": ["#2aa666", "#1f538d"],
+    "selected_hover_color": ["#3cb666", "#14375e"],
+    "unselected_color": ["#979DA2", "gray29"],
+    "unselected_hover_color": ["gray70", "gray41"],
+    "text_color": ["#f3faf6", "#f3faf6"],
+    "text_color_disabled": ["gray74", "gray60"]
+  },
+  "CTkTextbox": {
+    "corner_radius": 0,
+    "border_width": 0,
+    "fg_color": ["gray100", "gray20"],
+    "border_color": ["#979DA2", "#565B5E"],
+    "text_color": ["gray14", "gray84"],
+    "scrollbar_button_color": ["gray55", "gray41"],
+    "scrollbar_button_hover_color": ["gray40", "gray53"]
+  },
+  "CTkScrollableFrame": {
+    "label_fg_color": ["gray80", "gray21"]
+  },
+  "DropdownMenu": {
+    "fg_color": ["gray90", "gray20"],
+    "hover_color": ["gray75", "gray28"],
+    "text_color": ["gray14", "gray84"]
+  },
  "CTkFont": {
    "macOS": {
      "family": "Avenir",
@@ -80,12 +152,7 @@
      "weight": "normal"
    }
  },
-  "DropdownMenu": {
-    "fg_color": ["#FFFFFF", "#2D2D2D"],
-    "hover_color": ["#E0E0E0", "#4B4B4B"],
-    "text_color": ["#000000", "#FFFFFF"]
-  },
  "URL": {
-    "text_color": ["#007ACC", "#1E90FF"]
+    "text_color": ["gray74", "gray60"]
  }
 }
@@ -5,7 +5,7 @@ import platform
 import shutil
 import ssl
 import subprocess
-import urllib.request
+import urllib
 from pathlib import Path
 from typing import List, Any
 from tqdm import tqdm
@@ -15,123 +15,127 @@ import modules.globals
 TEMP_FILE = 'temp.mp4'
 TEMP_DIRECTORY = 'temp'

-# Monkey patch SSL for macOS to handle issues with some HTTPS requests
+# monkey patch ssl for mac
 if platform.system().lower() == 'darwin':
    ssl._create_default_https_context = ssl._create_unverified_context

+
 def run_ffmpeg(args: List[str]) -> bool:
    commands = ['ffmpeg', '-hide_banner', '-hwaccel', 'auto', '-loglevel', modules.globals.log_level]
    commands.extend(args)
    try:
        subprocess.check_output(commands, stderr=subprocess.STDOUT)
        return True
-    except subprocess.CalledProcessError as e:
-        print(f"FFmpeg error: {e.output.decode()}")
+    except Exception:
+        pass
    return False

+
 def detect_fps(target_path: str) -> float:
-    command = [
-        'ffprobe', '-v', 'error', '-select_streams', 'v:0', 
-        '-show_entries', 'stream=r_frame_rate', 
-        '-of', 'default=noprint_wrappers=1:nokey=1', target_path
-    ]
+    command = ['ffprobe', '-v', 'error', '-select_streams', 'v:0', '-show_entries', 'stream=r_frame_rate', '-of', 'default=noprint_wrappers=1:nokey=1', target_path]
+    output = subprocess.check_output(command).decode().strip().split('/')
    try:
-        output = subprocess.check_output(command).decode().strip().split('/')
        numerator, denominator = map(int, output)
        return numerator / denominator
-    except (subprocess.CalledProcessError, ValueError):
-        print("Failed to detect FPS, defaulting to 30.0 FPS.")
+    except Exception:
+        pass
    return 30.0

+
 def extract_frames(target_path: str) -> None:
    temp_directory_path = get_temp_directory_path(target_path)
-    create_temp(target_path)
    run_ffmpeg(['-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:
    temp_output_path = get_temp_output_path(target_path)
    temp_directory_path = get_temp_directory_path(target_path)
-    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(['-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])
+

 def restore_audio(target_path: str, output_path: str) -> None:
    temp_output_path = get_temp_output_path(target_path)
-    done = run_ffmpeg([
-        '-i', temp_output_path, '-i', target_path, 
-        '-c:v', 'copy', '-map', '0:v:0', '-map', '1:a:0', '-y', output_path
-    ])
+    done = run_ffmpeg(['-i', temp_output_path, '-i', target_path, '-c:v', 'copy', '-map', '0:v:0', '-map', '1:a:0', '-y', output_path])
    if not done:
        move_temp(target_path, output_path)

+
 def get_temp_frame_paths(target_path: str) -> List[str]:
    temp_directory_path = get_temp_directory_path(target_path)
-    return glob.glob(os.path.join(glob.escape(temp_directory_path), '*.png'))
+    return glob.glob((os.path.join(glob.escape(temp_directory_path), '*.png')))
+

 def get_temp_directory_path(target_path: str) -> str:
-    target_name = Path(target_path).stem
-    target_directory_path = Path(target_path).parent
-    return str(target_directory_path / TEMP_DIRECTORY / target_name)
+    target_name, _ = os.path.splitext(os.path.basename(target_path))
+    target_directory_path = os.path.dirname(target_path)
+    return os.path.join(target_directory_path, TEMP_DIRECTORY, target_name)
+

 def get_temp_output_path(target_path: str) -> str:
    temp_directory_path = get_temp_directory_path(target_path)
-    return str(Path(temp_directory_path) / TEMP_FILE)
+    return os.path.join(temp_directory_path, TEMP_FILE)

-def normalize_output_path(source_path: str, target_path: str, output_path: str) -> str:
-    if source_path and target_path and os.path.isdir(output_path):
-        source_name = Path(source_path).stem
-        target_name = Path(target_path).stem
-        target_extension = Path(target_path).suffix
-        return str(Path(output_path) / f"{source_name}-{target_name}{target_extension}")
+
+def normalize_output_path(source_path: str, target_path: str, output_path: str) -> Any:
+    if source_path and target_path:
+        source_name, _ = os.path.splitext(os.path.basename(source_path))
+        target_name, target_extension = os.path.splitext(os.path.basename(target_path))
+        if os.path.isdir(output_path):
+            return os.path.join(output_path, source_name + '-' + target_name + target_extension)
    return output_path

+
 def create_temp(target_path: str) -> None:
    temp_directory_path = get_temp_directory_path(target_path)
    Path(temp_directory_path).mkdir(parents=True, exist_ok=True)

+
 def move_temp(target_path: str, output_path: str) -> None:
    temp_output_path = get_temp_output_path(target_path)
    if os.path.isfile(temp_output_path):
+        if os.path.isfile(output_path):
+            os.remove(output_path)
        shutil.move(temp_output_path, output_path)

+
 def clean_temp(target_path: str) -> None:
    temp_directory_path = get_temp_directory_path(target_path)
-    parent_directory_path = Path(temp_directory_path).parent
+    parent_directory_path = os.path.dirname(temp_directory_path)
    if not modules.globals.keep_frames and os.path.isdir(temp_directory_path):
        shutil.rmtree(temp_directory_path)
-    if parent_directory_path.exists() and not list(parent_directory_path.iterdir()):
-        parent_directory_path.rmdir()
+    if os.path.exists(parent_directory_path) and not os.listdir(parent_directory_path):
+        os.rmdir(parent_directory_path)
+

 def has_image_extension(image_path: str) -> bool:
    return image_path.lower().endswith(('png', 'jpg', 'jpeg'))

+
 def is_image(image_path: str) -> bool:
    if image_path and os.path.isfile(image_path):
        mimetype, _ = mimetypes.guess_type(image_path)
-        return mimetype and mimetype.startswith('image/')
+        return bool(mimetype and mimetype.startswith('image/'))
    return False

+
 def is_video(video_path: str) -> bool:
    if video_path and os.path.isfile(video_path):
        mimetype, _ = mimetypes.guess_type(video_path)
-        return mimetype and mimetype.startswith('video/')
+        return bool(mimetype and mimetype.startswith('video/'))
    return False

+
 def conditional_download(download_directory_path: str, urls: List[str]) -> None:
-    download_directory = Path(download_directory_path)
-    download_directory.mkdir(parents=True, exist_ok=True)
+    if not os.path.exists(download_directory_path):
+        os.makedirs(download_directory_path)
    for url in urls:
-        download_file_path = download_directory / Path(url).name
-        if not download_file_path.exists():
-            with urllib.request.urlopen(url) as request:
-                total = int(request.headers.get('Content-Length', 0))
-                with tqdm(total=total, desc='Downloading', unit='B', unit_scale=True, unit_divisor=1024) as progress:
-                    urllib.request.urlretrieve(url, download_file_path, reporthook=lambda count, block_size, total_size: progress.update(block_size))
+        download_file_path = os.path.join(download_directory_path, os.path.basename(url))
+        if not os.path.exists(download_file_path):
+            request = urllib.request.urlopen(url) # type: ignore[attr-defined]
+            total = int(request.headers.get('Content-Length', 0))
+            with tqdm(total=total, desc='Downloading', unit='B', unit_scale=True, unit_divisor=1024) as progress:
+                urllib.request.urlretrieve(url, download_file_path, reporthook=lambda count, block_size, total_size: progress.update(block_size)) # type: ignore[attr-defined]
+

 def resolve_relative_path(path: str) -> str:
-    return str(Path(__file__).parent / path)
+    return os.path.abspath(os.path.join(os.path.dirname(__file__), path))
@@ -1,27 +1,23 @@
 --extra-index-url https://download.pytorch.org/whl/cu118

-numpy==1.23.5
-opencv-contrib-python==4.10.0.84
+numpy>=1.23.5,<2
+opencv-python==4.8.1.78
+cv2_enumerate_cameras==1.1.15
 onnx==1.16.0
 insightface==0.7.3
 psutil==5.9.8
 tk==0.1.0
-customtkinter==5.2.2
 pillow==9.5.0
 torch==2.0.1+cu118; sys_platform != 'darwin'
 torch==2.0.1; sys_platform == 'darwin'
 torchvision==0.15.2+cu118; sys_platform != 'darwin'
 torchvision==0.15.2; sys_platform == 'darwin'
-onnxruntime==1.18.0; sys_platform == 'darwin' and platform_machine != 'arm64'
 onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64'
-onnxruntime-gpu==1.18.0; sys_platform != 'darwin'
-tensorflow==2.13.0rc1; sys_platform == 'darwin'
+onnxruntime-gpu==1.16.3; sys_platform != 'darwin'
 tensorflow==2.12.1; sys_platform != 'darwin'
 opennsfw2==0.10.2
 protobuf==4.23.2
 tqdm==4.66.4
 gfpgan==1.3.8
-pyobjc==9.1; sys_platform == 'darwin'
-pygrabber==0.2
-pyvirtualcam==0.12.0
-pyobjc-framework-AVFoundation==10.3.1; sys_platform == 'darwin'
+tkinterdnd2==0.4.2
+customtkinter==5.2.2
@@ -3,35 +3,73 @@ setlocal EnableDelayedExpansion

 :: 1. Setup your platform
 echo Setting up your platform...
-call :check_installation python "Python 3.10 or later"
-call :check_installation pip "Pip"
-call :install_if_missing git "Git" "winget install --id Git.Git -e --source winget"
-call :install_if_missing ffmpeg "FFMPEG" "winget install --id Gyan.FFmpeg -e --source winget"
+
+:: Python
+where python >nul 2>&1
+if %ERRORLEVEL% neq 0 (
+    echo Python is not installed. Please install Python 3.10 or later.
+    pause
+    exit /b
+)
+
+:: Pip
+where pip >nul 2>&1
+if %ERRORLEVEL% neq 0 (
+    echo Pip is not installed. Please install Pip.
+    pause
+    exit /b
+)
+
+:: Git
+where git >nul 2>&1
+if %ERRORLEVEL% neq 0 (
+    echo Git is not installed. Installing Git...
+    winget install --id Git.Git -e --source winget
+)
+
+:: FFMPEG
+where ffmpeg >nul 2>&1
+if %ERRORLEVEL% neq 0 (
+    echo FFMPEG is not installed. Installing FFMPEG...
+    winget install --id Gyan.FFmpeg -e --source winget
+)

 :: Visual Studio 2022 Runtimes
 echo Installing Visual Studio 2022 Runtimes...
 winget install --id Microsoft.VC++2015-2022Redist-x64 -e --source winget

 :: 2. Clone Repository
-call :clone_repository "https://github.com/iVideoGameBoss/iRoopDeepFaceCam.git" "iRoopDeepFaceCam"
+if exist Deep-Live-Cam (
+    echo Deep-Live-Cam directory already exists.
+    set /p overwrite="Do you want to overwrite? (Y/N): "
+    if /i "%overwrite%"=="Y" (
+        rmdir /s /q Deep-Live-Cam
+        git clone https://github.com/hacksider/Deep-Live-Cam.git
+    ) else (
+        echo Skipping clone, using existing directory.
+    )
+) else (
+    git clone https://github.com/hacksider/Deep-Live-Cam.git
+)
+cd Deep-Live-Cam

 :: 3. Download Models
 echo Downloading models...
-if not exist models mkdir models
-curl -L -o models\GFPGANv1.4.pth https://huggingface.co/ivideogameboss/iroopdeepfacecam/resolve/main/GFPGANv1.4.pth
-curl -L -o models\inswapper_128_fp16.onnx https://huggingface.co/ivideogameboss/iroopdeepfacecam/resolve/main/inswapper_128_fp16.onnx
+mkdir models
+curl -L -o models/GFPGANv1.4.pth https://path.to.model/GFPGANv1.4.pth
+curl -L -o models/inswapper_128_fp16.onnx https://path.to.model/inswapper_128_fp16.onnx

 :: 4. Install dependencies
 echo Creating a virtual environment...
 python -m venv venv
-call venv\Scripts\activate.bat
+call venv\Scripts\activate

 echo Installing required Python packages...
 pip install --upgrade pip
 pip install -r requirements.txt
+
 echo Setup complete. You can now run the application.

-:menu
 :: GPU Acceleration Options
 echo.
 echo Choose the GPU Acceleration Option if applicable:
@@ -43,83 +81,42 @@ echo 5. OpenVINO (Intel)
 echo 6. None
 set /p choice="Enter your choice (1-6): "

-set "exec_provider="
-call :set_execution_provider %choice%
-
-:end_choice
-echo.
-echo GPU Acceleration setup complete.
-echo Selected provider: !exec_provider!
-echo.
+if "%choice%"=="1" (
+    echo Installing CUDA dependencies...
+    pip uninstall -y onnxruntime onnxruntime-gpu
+    pip install onnxruntime-gpu==1.16.3
+    set exec_provider="cuda"
+) else if "%choice%"=="2" (
+    echo Installing CoreML (Apple Silicon) dependencies...
+    pip uninstall -y onnxruntime onnxruntime-silicon
+    pip install onnxruntime-silicon==1.13.1
+    set exec_provider="coreml"
+) else if "%choice%"=="3" (
+    echo Installing CoreML (Apple Legacy) dependencies...
+    pip uninstall -y onnxruntime onnxruntime-coreml
+    pip install onnxruntime-coreml==1.13.1
+    set exec_provider="coreml"
+) else if "%choice%"=="4" (
+    echo Installing DirectML dependencies...
+    pip uninstall -y onnxruntime onnxruntime-directml
+    pip install onnxruntime-directml==1.15.1
+    set exec_provider="directml"
+) else if "%choice%"=="5" (
+    echo Installing OpenVINO dependencies...
+    pip uninstall -y onnxruntime onnxruntime-openvino
+    pip install onnxruntime-openvino==1.15.0
+    set exec_provider="openvino"
+) else (
+    echo Skipping GPU acceleration setup.
+)

 :: Run the application
 if defined exec_provider (
-    echo Running the application with !exec_provider! execution provider...
-    python run.py --execution-provider !exec_provider!
+    echo Running the application with %exec_provider% execution provider...
+    python run.py --execution-provider %exec_provider%
 ) else (
    echo Running the application...
    python run.py
 )

-:: Deactivate the virtual environment
-call venv\Scripts\deactivate.bat
-
-echo.
-echo Script execution completed.
 pause
-exit /b
-
-:check_installation
-where %1 >nul 2>&1
-if %ERRORLEVEL% neq 0 (
-    echo %2 is not installed. Please install %2.
-    pause
-    exit /b
-)
-
-:install_if_missing
-where %1 >nul 2>&1
-if %ERRORLEVEL% neq 0 (
-    echo %2 is not installed. Installing %2...
-    %3
-)
-
-:clone_repository
-if exist %2 (
-    echo %2 directory already exists.
-    set /p overwrite="Do you want to overwrite? (Y/N): "
-    if /i "%overwrite%"=="Y" (
-        rmdir /s /q %2
-        git clone %1
-    ) else (
-        echo Skipping clone, using existing directory.
-    )
-) else (
-    git clone %1
-)
-
-:set_execution_provider
-if "%1"=="1" (
-    call :install_onnxruntime "onnxruntime-gpu" "1.16.3" "cuda"
-) else if "%1"=="2" (
-    call :install_onnxruntime "onnxruntime-silicon" "1.13.1" "coreml"
-) else if "%1"=="3" (
-    call :install_onnxruntime "onnxruntime-coreml" "1.13.1" "coreml"
-) else if "%1"=="4" (
-    call :install_onnxruntime "onnxruntime-directml" "1.15.1" "directml"
-) else if "%1"=="5" (
-    call :install_onnxruntime "onnxruntime-openvino" "1.15.0" "openvino"
-) else if "%1"=="6" (
-    echo Skipping GPU acceleration setup.
-    set "exec_provider=none"
-) else (
-    echo Invalid choice. Please try again.
-    goto menu
-)
-
-:install_onnxruntime
-echo Installing %1 dependencies...
-pip uninstall -y onnxruntime %1
-pip install %1==%2
-set "exec_provider=%3"
-goto end_choice
Author	SHA1	Message	Date
KRSHH	51b38fe253	Revert "Slight Performance Improvement" This reverts commit `9a472e2435`.	2024-11-07 14:58:03 +05:30
KRSHH	97a76c5e5b	Revert "Update ui.py" This reverts commit `df72a5431b`.	2024-11-07 14:57:47 +05:30
KRSHH	df72a5431b	Update ui.py	2024-10-29 14:53:19 +05:30
KRSHH	9a472e2435	Slight Performance Improvement avg 9.5 to avg 10	2024-10-29 14:07:47 +05:30
KRSHH	a581b81bd9	Change Switch/Slider positions	2024-10-28 16:53:55 +05:30
KRSHH	69b7970b87	Improved Camera Selection Menu	2024-10-28 13:50:44 +05:30
KRSHH	7fce1fd8b4	Update instructions.txt Links to Models in Instructions	2024-10-28 13:15:13 +05:30
KRSHH	c2918a52df	Minimum Windows Size	2024-10-28 13:12:02 +05:30
KRSHH	64c0f085b1	Change Switch positions	2024-10-28 12:20:54 +05:30
KRSHH	3c30ab8a5d	Opacity	2024-10-28 11:45:50 +05:30
KRSHH	acc8e778b6	Mouth Mask And UI	2024-10-28 10:56:01 +05:30
KRSHH	4b6f60f59b	Delete files from main	2024-10-21 19:15:21 +05:30
KRSHH	1178232268	Upload images to folder	2024-10-21 19:12:46 +05:30
KRSHH	ad918c5523	Shift Media to a folder	2024-10-21 19:10:21 +05:30
KRSHH	7b8d6171b7	Frame by Frame Navigation	2024-10-19 14:04:05 +05:30
KRSHH	6b86b0a72d	Preview Window Slider	2024-10-19 13:58:55 +05:30
KRSHH	936e78f93b	Fix Mapper for Live	2024-10-17 13:06:00 +05:30
KRSHH	aca0bcb7ce	Formatting Fix	2024-10-14 21:48:57 +05:30
KRSHH	966cb5a7df	Removed Package Repetition	2024-10-14 21:46:22 +05:30
KRSHH	1ab4bf06b1	Tips for DLC	2024-10-14 21:26:34 +05:30
KRSHH	6649e2a5df	remember/save switch states	2024-10-14 20:32:17 +05:30
KRSHH	72d4c9e9c4	Update metadata.py - 1.6	2024-10-14 19:50:09 +05:30
KRSHH	76d65247b7	improved performance enhancement	2024-10-14 19:49:51 +05:30
KRSHH	37f224cb47	FPS Counter	2024-10-14 19:46:48 +05:30
KRSHH	b58ffffd37	Fix the button position and bugs	2024-10-14 19:11:44 +05:30
KRSHH	75decc5838	Hotswap Source image - switch faces without closing live	2024-10-04 18:17:22 +05:30
Kenneth Estanislao	f38ebb485a	Update ui.py removed opacity, will work on it later to optimize	2024-10-04 15:39:08 +08:00
Kenneth Estanislao	95742c8fd5	Merge pull request #686 from GhoulBoii/main BOUNTY - Webcam Merged (tested)	2024-10-04 14:46:06 +08:00
Kenneth Estanislao	60e27f4755	Revert "Merge pull request #685 from KRSHH/main" This reverts commit `d4e5b8078d`, reversing changes made to `c08bec22e3`.	2024-10-03 14:51:38 +08:00
KRSHH	3d741bd269	Update README.md	2024-10-02 18:38:37 +05:30
KRSHH	d4e5b8078d	Merge pull request #685 from KRSHH/main Live faceswap opacity slider	2024-10-02 15:24:53 +05:30
KRSHH	61b51fc5d4	Move the slider from live to root	2024-10-02 14:37:19 +05:30
KRSHH	f19e425143	Update ui.py	2024-10-02 14:20:56 +05:30
KRSHH	7d6bdad086	Default opacity global	2024-10-02 13:24:23 +05:30
KRSHH	12c0a7ac86	Faceswap live opacity slider	2024-10-02 13:23:39 +05:30
Kenneth Estanislao	c08bec22e3	Update issue templates	2024-10-01 14:26:03 +08:00
KRSHH	bdd7c593e1	Update README.md	2024-09-28 20:53:29 +05:30
KRSHH	6e618baf34	Update README.md	2024-09-28 17:22:21 +05:30
KRSHH	0edcaae713	Merge pull request #650 from KRSHH/main Preview video Frame by Frame using left and right arrow keys	2024-09-28 12:37:40 +05:30
KRSHH	dff6cec2f9	Comment Indention fix	2024-09-27 20:59:48 +05:30
KRSHH	4d1d2c86af	Preview video Frame by Frame using left and right arrow keys	2024-09-27 20:40:32 +05:30
KRSHH	e00c398825	Merge branch 'hacksider:main' into main	2024-09-27 20:20:22 +05:30
KRSHH	0e481609ea	Update README.md	2024-09-27 19:59:13 +05:30
KRSHH	683481804c	Delete outdated docs directory	2024-09-26 11:03:46 +05:30
KRSHH	5845b9c480	Update README.md	2024-09-26 00:57:11 +05:30
Kenneth Estanislao	71cf39fd98	Update metadata.py changes of version from 1.4 to 1.5 (UI modified)	2024-09-26 00:57:45 +08:00
KRSHH	92db20eba4	Merge pull request #632 from KRSHH/main Unreverting New UI after Fixes, Unreverted README	2024-09-25 17:51:30 +05:30
KRSHH	f1e365799e	Updated README, (Images - TBU)	2024-09-25 17:42:09 +05:30
KRSHH	6d1238212a	New Fixed UI	2024-09-25 17:36:50 +05:30
Kenneth Estanislao	92a0994f01	Update README.md	2024-09-21 19:56:00 +08:00
Kenneth Estanislao	cad40b25dc	Update face_swapper.py added the missing ' , my bad on this...	2024-09-19 21:00:29 +08:00
Kenneth Estanislao	1b4c0ce43e	Update face_swapper.py should fix issues for those who dont have nvidia cards	2024-09-19 17:43:05 +08:00
Kenneth Estanislao	fd4e3f546d	reverted to the old version fixing the issue #597	2024-09-19 17:38:02 +08:00
Kenneth Estanislao	5bcd6dabde	Update ui.py	2024-09-19 15:54:57 +08:00
Kenneth Estanislao	3e1f333e5e	Revert "Merge pull request #594 from KRSHH/main" This reverts commit `2641f9e344`, reversing changes made to `9bf2080ac8`.	2024-09-19 02:36:35 +08:00
Kenneth Estanislao	1f71d274b5	Revert "Merge pull request #599 from KRSHH/main" This reverts commit `80de3dc32e`, reversing changes made to `375d4ae620`.	2024-09-19 02:01:47 +08:00
Kenneth Estanislao	bbfdf83267	Update requirements.txt	2024-09-19 00:38:41 +08:00
Kenneth Estanislao	88254c3952	Merge pull request #604 from bkosowski/bugfix/fix_onnxruntime_version Downgrade onnxruntime version to 1.16.0 to fix requirements installation	2024-09-19 00:33:05 +08:00
bkosowski	069e9b46e6	Downgrade onnxruntime version to 1.16.0 to fix requirements installation	2024-09-18 15:58:50 +02:00
Kenneth Estanislao	80de3dc32e	Merge pull request #599 from KRSHH/main Update README.md	2024-09-17 21:47:44 +08:00
KRSHH	911148cc6b	README.md Update Thanks to all the contributors	2024-09-17 19:03:06 +05:30
KRSHH	b229545454	Update README.md Fix formatting, structure etc.	2024-09-17 18:24:43 +05:30
Kenneth Estanislao	375d4ae620	Update README.md added KRSHH	2024-09-17 20:27:27 +08:00
Kenneth Estanislao	bcfb9f24ea	Merge pull request #598 from KRSHH/main Fixed the Face mapper issue in Live Cam - New UI PR	2024-09-17 20:25:33 +08:00
KRSHH	a905d161e5	Add files via upload	2024-09-17 20:25:08 +08:00
KRSHH	d78df54721	Fixed the Face Mapper issue on live cam	2024-09-17 20:20:14 +08:00
KRSHH	4067d24c26	Fix Popup Live width	2024-09-17 20:18:59 +08:00
KRSHH	9c22e63d7b	Fix Popup Live width	2024-09-17 17:46:14 +05:30
KRSHH	0350f23519	Fixed the Face Mapper issue on live cam	2024-09-17 16:51:28 +05:30
KRSHH	d1ec0a17b2	Minor Fixes	2024-09-16 21:58:24 +05:30
KRSHH	bd8ed6e7eb	Add files via upload	2024-09-16 21:48:13 +05:30
Kenneth Estanislao	ea7bbd49fe	Revert "Merge pull request #592 from KRSHH/main" This reverts commit `2f29d323d9`.	2024-09-16 23:34:35 +08:00
Kenneth Estanislao	2f29d323d9	Merge pull request #592 from KRSHH/main Better UI	2024-09-16 23:32:39 +08:00
Kenneth Estanislao	c6e00796c8	Merge pull request #588 from KRSHH/main Enhance UI with drag and drop, modern look using customtkinter, and improved webcam mapping	2024-09-16 23:30:12 +08:00
Kenneth Estanislao	2641f9e344	Merge pull request #594 from KRSHH/main UI Change	2024-09-16 23:26:29 +08:00
KRSHH	5dd621b2b0	Fixed Typo	2024-09-16 20:47:02 +05:30
KRSHH	05413cc989	Update README.md For avoiding ToS violation	2024-09-16 20:38:56 +05:30
KRSHH	c49d0e0e3c	Bug fixes	2024-09-16 20:36:28 +05:30
unknown	88e3274d96	Backk	2024-09-16 20:24:04 +05:30
Kenneth Estanislao	9bf2080ac8	Revert "Merge pull request #588 from KRSHH/main" This reverts commit `8c6d0134a8`, reversing changes made to `621c3f035e`.	2024-09-16 22:18:59 +08:00
Kenneth Estanislao	5ab00388b7	Revert "Merge pull request #592 from KRSHH/main" This reverts commit `4768488653`, reversing changes made to `8c6d0134a8`.	2024-09-16 22:18:53 +08:00
Kenneth Estanislao	4768488653	Merge pull request #592 from KRSHH/main Better UI	2024-09-16 22:10:42 +08:00
KRSHH	569c9ca25a	Resizable Root window	2024-09-16 19:13:54 +05:30
KRSHH	c9f8537a15	Switch alignment	2024-09-16 18:53:19 +05:30
KRSHH	2d99e392ff	Vertical switches	2024-09-16 18:48:05 +05:30
KRSHH	1725ba95e9	Accurate Average PC Performance GIF	2024-09-16 18:32:29 +05:30
KRSHH	abe1e67c0e	adding avg pc performance demo	2024-09-16 18:31:18 +05:30
KRSHH	2b9d10f182	Donation button, close option button	2024-09-16 16:54:49 +05:30
K	674f584895	UI Change Changes in UI	2024-09-16 13:31:20 +05:30
K	325187b513	Fix Text Font Change, Larger, Bolder	2024-09-16 11:22:38 +05:30
Kenneth Estanislao	8c6d0134a8	Merge pull request #588 from KRSHH/main Enhance UI with drag and drop, modern look using customtkinter, and improved webcam mapping	2024-09-16 12:21:39 +08:00
K	d2f57fa4dd	Minor UI Fixes	2024-09-16 01:46:40 +05:30
K	2f2380b98d	Delete modules/ui.json	2024-09-16 01:00:03 +05:30
K	e5c29749bb	UI Redone	2024-09-16 00:37:34 +05:30
K	b505ae7b90	Add customtkinter in requirements.txt	2024-09-16 00:33:49 +05:30
CH. Krish	373134cfa1	Add tkinterdnd2 to requirements.txt	2024-09-15 23:02:25 +05:30
CH. Krish	523d80550d	Adding Drag and Drop feature to Face Mapper and Source and Target	2024-09-15 23:00:28 +05:30
Kenneth Estanislao	621c3f035e	Update README.md fixed the gumroad link	2024-09-15 19:15:02 +08:00
Vic P.	83529c8ca8	Update README.md	2024-09-15 14:57:31 +07:00
Kenneth Estanislao	d38a816b55	Update README.md	2024-09-14 02:17:34 +08:00
Kenneth Estanislao	9fccb069df	Update README.md	2024-09-14 02:15:51 +08:00
Kenneth Estanislao	1829d5650b	easy installer link	2024-09-14 02:08:33 +08:00
Kenneth Estanislao	be36016a69	Update metadata.py	2024-09-14 01:58:34 +08:00
Kenneth Estanislao	26e764c842	Create gumroad.png	2024-09-14 01:56:27 +08:00
Kenneth Estanislao	08b7d56b47	Update README.md	2024-09-13 16:57:46 +08:00
Kenneth Estanislao	969c8796d5	Update README.md	2024-09-13 16:57:09 +08:00
Kenneth Estanislao	0d8fe7f930	Merge branch 'main' of https://github.com/hacksider/Deep-Live-Cam	2024-09-13 16:53:16 +08:00
Kenneth Estanislao	7be92ac3e5	Update face_mapping2.png	2024-09-13 16:52:59 +08:00
Kenneth Estanislao	24414e8d75	Update README.md	2024-09-13 16:40:45 +08:00
Kenneth Estanislao	c6309136ad	Update README.md	2024-09-13 16:39:34 +08:00
Kenneth Estanislao	cec588f1c1	Update README.md added features	2024-09-13 16:38:47 +08:00
Kenneth Estanislao	e899707542	facemapping data demo data for facemapping	2024-09-13 16:30:44 +08:00
Kenneth Estanislao	336ce2d0d6	Update README.md	2024-09-13 15:49:03 +08:00
Kenneth Estanislao	3f58bdc714	Create resizable.gif	2024-09-13 15:48:47 +08:00
Kenneth Estanislao	a2d2f20b5a	Update README.md	2024-09-13 14:27:22 +08:00
Kenneth Estanislao	1415493327	Update README.md	2024-09-13 14:16:28 +08:00
Kenneth Estanislao	c8851038fa	Update README.md	2024-09-13 14:15:51 +08:00
Kenneth Estanislao	e74b6ebe42	Update README.md completed multiple face feature, thanks to @pereiraroland26 for this	2024-09-13 14:12:45 +08:00
Kenneth Estanislao	b2fa95e2fc	Merge pull request #572 from pereiraroland26/main Updates to multiple face support (webcam scenario)	2024-09-12 22:27:07 +08:00
Roland Pereira	f133d48f60	handled webcam scenario where detected faces are greater than maps provided	2024-09-11 21:42:38 +05:30
Kenneth Estanislao	e1a01cfba2	Merge pull request #568 from cyf1r3/main Update README.md	2024-09-11 13:24:10 +08:00
Anant Singh	06e5e76797	Update README.md Changed the keyword 'roop' to 'Deep-Live-Cam'.	2024-09-11 10:37:11 +05:30
Kenneth Estanislao	16c1b44927	Revert "recommit webcam option" This reverts commit `49d3f9a3cc`.	2024-09-11 02:49:53 +08:00
Kenneth Estanislao	229375465d	Update README.md added some credits	2024-09-11 00:05:06 +08:00
Kenneth Estanislao	49d3f9a3cc	recommit webcam option	2024-09-11 00:02:45 +08:00
Kenneth Estanislao	39238ee80f	Merge pull request #566 from pereiraroland26/main Added support for multiple faces	2024-09-10 23:35:19 +08:00
Roland Pereira	d7c6226eb7	updated button widths on popup	2024-09-10 18:53:25 +05:30
Roland Pereira	eb140e59c2	commiting gitignore	2024-09-10 16:00:24 +05:30
pereiraroland26	f122006024	updated README.md and created variables for pop dimensions	2024-09-10 14:28:33 +05:30
Roland Pereira	0a144ec57f	Merge branch 'hacksider:main' into main	2024-09-10 13:48:40 +05:30
Kenneth Estanislao	9acf77b6ed	Revert "Merge pull request #556 from Highpressure/main" This reverts commit `fd07185043`, reversing changes made to `f762b61a12`.	2024-09-10 14:59:05 +08:00
Kenneth Estanislao	fd07185043	Merge pull request #556 from Highpressure/main multi camera device support	2024-09-10 13:47:43 +08:00
pereiraroland26	da3498c36f	Merge branch 'main' of https://github.com/pereiraroland26/Deep-Live-Cam_v2.0	2024-09-10 05:41:46 +05:30
pereiraroland26@gmail.com	53fc65ca7c	Added ability to map faces	2024-09-10 05:40:55 +05:30
james	397c84fa8b	Added ability to map faces	2024-09-10 04:37:58 +05:30
Highpressure	6381f63722	Update ui.py option switches went missing in last commit	2024-09-06 21:56:13 +02:00
Highpressure	83ca917c66	Update capturer.py added change to support multi camera device support as my device 0 is a virtual cam for iphone redirection, device 1 is obs and device 2 is my real camera	2024-09-06 20:59:35 +02:00
Highpressure	2d34201cfc	Update ui.py added dropdown for multi camera device selection	2024-09-06 20:58:38 +02:00
Kenneth Estanislao	f762b61a12	Update README.md	2024-09-05 16:09:31 +08:00
Kenneth Estanislao	14625dbfde	Update README.md includes licensing of insightface	2024-09-05 16:01:11 +08:00
Vic P.	dc8563372d	Update README.md to collapse optional sections for better readability	2024-09-01 01:29:57 +07:00
Vic P.	5dcd30e587	Merge pull request #507 from duhow/patch-1 Update README.md to add an additional model file for the face swapper function	2024-09-01 00:55:36 +07:00
Vic P.	e84369862e	Update README.md	2024-09-01 00:47:45 +07:00
Vic P.	a9f869e491	Merge pull request #510 from underlines/feature/color_space_conversion Feature/color space conversion	2024-09-01 00:34:46 +07:00
underlines	03fb6bf619	Update readme.md with Windows 11 WSL2 Ubuntu tutorial for Webcams	2024-08-30 23:49:14 +02:00
underlines	c91ab8bbd2	add toggle button for blueish cam fix (Force OpenCV2 BGR2RGB)	2024-08-30 22:02:23 +02:00
underlines	79c6615a68	use mjpeg and convert bgr to rgb	2024-08-30 21:49:01 +02:00
David Girón	3c708b0fcb	fix model face-swapper	2024-08-30 16:21:57 +02:00
Kenneth Estanislao	3107f74165	Merge pull request #506 from duhow/patch-1 fix: requirements ResolutionImpossible	2024-08-30 19:09:02 +08:00
David Girón	99704f3a18	fix: requirements ResolutionImpossible	2024-08-30 09:07:40 +02:00
Kenneth Estanislao	40598daea9	Merge pull request #455 from barongello/main Adding a swap faces button to easily swap source/target images	2024-08-27 12:29:55 +08:00
barongello	528c30e3ba	Adding a swap faces button to easily swap source/target images	2024-08-25 12:25:19 -03:00
Kenneth Estanislao	446487a70c	Update ui.py Disable NSFW in accordance to github rules	2024-08-24 17:38:49 +08:00
Vic P.	7f95b69bc5	Add TODO to README.md	2024-08-24 00:45:14 +07:00
Kenneth Estanislao	540dad346e	Update README.md	2024-08-23 01:56:13 +08:00
Vic P.	aa94f2ae7e	Merge pull request #429 from vic4key/main @refer to the PR https://github.com/hacksider/Deep-Live-Cam/pull/293 in the `experimental` branch.	2024-08-22 00:54:10 +07:00
Vic P	3755198ecd	Update codes following the comments of @sourcery-ai. Signed-off-by: Vic P <vic4key@gmail.com>	2024-08-22 00:50:14 +07:00
Vic P	4f62119c2e	Support the following options: - The live camera display as you see it in the front-facing camera frame (like iPhone's Mirror Front Camera). - The live camera frame is resizable. Note: These options are turned off by default. Enabling both options may reduce performance by ~2%. Signed-off-by: Vic P <vic4key@gmail.com>	2024-08-22 00:35:05 +07:00
Vic P.	42b54ef330	Merge pull request #421 from vic4key/main Re-enabled the NSFW function (turn-off by default) with its bug fixes at PR https://github.com/hacksider/Deep-Live-Cam/pull/237.	2024-08-21 02:22:12 +07:00
Vic P	6d28a52869	Update codes following the comments of @sourcery-ai. Signed-off-by: Vic P <vic4key@gmail.com>	2024-08-21 02:16:06 +07:00
Vic P	7313a332c8	Re-enabled the NSFW function (turn-off by default). @refer to the PR #237 in the `experimental` branch. Signed-off-by: Vic P <vic4key@gmail.com>	2024-08-21 02:02:00 +07:00
Kenneth Estanislao	e4b494174d	Merge pull request #324 from vietjovi/main Update README.md to address the issue with the GTK package on MAC OS	2024-08-18 13:47:57 +08:00
Kenneth Estanislao	69d863b44a	Revert "Merge remote-tracking branch 'parent/experimental' into experimental" This reverts commit `df99f6ca17`.	2024-08-16 21:03:14 +08:00
Kenneth Estanislao	d10314c8d6	Revert "Update ui.py" This reverts commit `9d20e04336`.	2024-08-16 21:03:07 +08:00
Kenneth Estanislao	9d20e04336	Update ui.py Hides NSFW	2024-08-16 20:29:55 +08:00
Aleksandr Spiridonov	df99f6ca17	Merge remote-tracking branch 'parent/experimental' into experimental	2024-08-16 20:28:57 +08:00
Kenneth Estanislao	22abb8c25f	Revert "Merge pull request #293 from vic4key/experimental" This reverts commit `eab5ba7027`.	2024-08-16 13:47:12 +08:00
Kenneth Estanislao	eab5ba7027	Merge pull request #293 from vic4key/experimental To fix bugs and support more options for the Live function (see details in Commits tab)	2024-08-15 14:21:58 +08:00
Viet Nguyen	c288d82713	Fix spelling 'package'	2024-08-15 02:36:01 +07:00
Viet Nguyen	c8d526157a	Update README.md	2024-08-15 02:22:06 +07:00
Kenneth Estanislao	4324b41b9e	Update ui.py hides NSFW button	2024-08-15 03:03:57 +08:00
Kenneth Estanislao	a6e00211f0	Merge pull request #321 from gianpaj/stop-live-mode-if-preview-is-closed Stop live mode when the preview window is closed	2024-08-15 03:01:37 +08:00
Gianfranco Palumbo	99214c7ab1	Stop live mode the preview window is closed	2024-08-14 17:52:42 +02:00
Kenneth Estanislao	080d6f5110	Merge pull request #282 from jasonkneen/main-macos-metal-gpu-optimisation macOS optimisations for Silicon Macs for GPU / Metal usage (reduced CPU load from 600% to 150%)	2024-08-13 20:30:26 +08:00
Jason Kneen	155546b937	Update .gitignore	2024-08-13 13:23:13 +01:00
Kenneth Estanislao	79fbb7998c	Merge pull request #281 from snewell92/patch-1	2024-08-13 20:09:04 +08:00
Sean Newell	5ce2fd298b	sourcery update Grammar updates Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>	2024-08-13 14:03:05 +02:00
Sean Newell	740410dd73	Strengthen ethical consideration Nothing we say is legally binding in here, but it behooves us to be stronger in our language - getting consent to be digitally reproduced should be required and standard procedure.	2024-08-13 13:50:02 +02:00
Kenneth Estanislao	cbc7c22f1c	Create CONTRIBUTING.md	2024-08-13 03:12:58 +08:00
Kenneth Estanislao	a31e81fa66	Update README.md https://www.reddit.com/r/singularity/comments/1eo4sne/comment/lhl7odv/	2024-08-11 21:59:31 +08:00
Kenneth Estanislao	e8a8acca9f	Update README.md	2024-08-11 21:17:04 +08:00
Kenneth Estanislao	a9d4564726	Update README.md relinking this to the old repo	2024-08-11 21:08:38 +08:00
Kenneth Estanislao	fc47cffb18	Update README.md	2024-08-11 16:35:38 +08:00
Kenneth Estanislao	fff3009c80	Merge pull request #152 from Saharsha-N/patch-1 Update README.md	2024-08-10 22:08:08 +08:00
Saharsha-N	84c10400b9	Update README.md Fixed a typo.	2024-08-10 09:55:36 -04:00
Kenneth Estanislao	9f58dfeee1	Merge pull request #140 from rahulbansal16/main Fix this cyclic dependency issue which was coming while installing rquirements	2024-08-10 20:29:59 +08:00
Rahul Bansal	04e72a85c3	Fix this cyclic dependency issue which was coming while doing the pip install requirements. Now the code is working. You are able to run it on your Windows machine.	2024-08-10 17:43:39 +05:30
Kenneth Estanislao	6a17297e2f	Update README.md	2024-08-10 14:19:20 +08:00
Kenneth Estanislao	ddd19474da	Merge pull request #115 from hacksider/revert-88-main Revert "Enable to choose a camera device in UI" Will put it on experimental as of this moment	2024-08-10 13:57:37 +08:00
Kenneth Estanislao	d49a77b3a3	Revert "Enable to choose a camera device in UI"	2024-08-10 13:54:12 +08:00
				`@@ -0,0 +1 @@`
				`Please always push on the experimental to ensure we don't mess with the main branch. All the test will be done on the experimental and will be pushed to the main branch after few days of testing.`