no message

.gitattributes 2

@@ -0,0 +1,2 @@
+# Auto detect text files and perform LF normalization
+* text=auto

.gitignore

@@ -0,0 +1,26 @@
+__pycache__/
+*.py[cod]
+*$py.class
+*.pyc
+.idea
+.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/

CONTRIBUTING.md

@@ -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.

Dockerfile

@@ -1,16 +1,28 @@
-# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
-# you will also find guides on how best to write your Dockerfile
+# 使用官方 Python 镜像作为基础镜像
+FROM python:3.9-slim
 
-FROM python:3.9
+# 设置工作目录
+WORKDIR /app
 
-RUN useradd -m -u 1000 user
-USER user
-ENV PATH="/home/user/.local/bin:$PATH"
+# 安装系统依赖
+RUN apt-get update && apt-get install -y \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
 
-WORKDIR /app
+# 复制项目文件到容器中
+COPY . /app
+
+# 安装 Python 依赖
+RUN pip install --no-cache-dir -r requirements.txt
+
+# 设置环境变量
+ENV PYTHONUNBUFFERED=1
+ENV LANG=C.UTF-8
+ENV LC_ALL=C.UTF-8
 
-COPY --chown=user ./requirements.txt requirements.txt
-RUN pip install --no-cache-dir --upgrade -r requirements.txt
+# 暴露端口（如果您的应用需要的话）
+# EXPOSE 8000
 
-COPY --chown=user . /app
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
+# 运行应用
+CMD ["python", "main.py"]

LICENSE

@@ -0,0 +1,661 @@
+                    GNU AFFERO GENERAL PUBLIC LICENSE
+                       Version 3, 19 November 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
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+
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+following paragraph.
+
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+permission to link or combine any covered work with a work licensed
+under version 3 of the GNU General Public License into a single
+combined work, and to convey the resulting work.  The terms of this
+License will continue to apply to the part which is the covered work,
+but the work with which it is combined will remain governed by version
+3 of the GNU General Public License.
+
+  14. Revised Versions of this License.
+
+  The Free Software Foundation may publish revised and/or new versions of
+the GNU Affero General Public License from time to time.  Such new versions
+will be similar in spirit to the present version, but may differ in detail to
+address new problems or concerns.
+
+  Each version is given a distinguishing version number.  If the
+Program specifies that a certain numbered version of the GNU Affero General
+Public License "or any later version" applies to it, you have the
+option of following the terms and conditions either of that numbered
+version or of any later version published by the Free Software
+Foundation.  If the Program does not specify a version number of the
+GNU Affero General Public License, you may choose any version ever published
+by the Free Software Foundation.
+
+  If the Program specifies that a proxy can decide which future
+versions of the GNU Affero General Public License can be used, that proxy's
+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+  Later license versions may give you additional or different
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+
+  15. Disclaimer of Warranty.
+
+  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
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+IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
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+  16. Limitation of Liability.
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+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
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+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
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+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU Affero General Public License as published
+    by the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU Affero General Public License for more details.
+
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+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
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+
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+solutions will be better for different programs; see section 13 for the
+specific requirements.
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU AGPL, see
+<https://www.gnu.org/licenses/>.

README 2.md

@@ -0,0 +1,388 @@
+
+![demo-gif](demo.gif)
+![demo-gif](avgpcperformancedemo.gif)
+
+## Deep Live Cam
+
+Real-time face swap and video deepfake with a single click and only a single image.
+
+## Disclaimer
+
+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.
+
+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.
+
+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.
+
+
+## Features
+
+### Resizable Preview Window
+
+Dynamically improve performance using the `--live-resizable` parameter.
+
+![resizable-gif](resizable.gif)
+
+### Face Mapping
+
+Track and change faces on the fly.
+
+![face_mapping_source](face_mapping_source.gif)
+
+**Source Video:**
+
+![face-mapping](face_mapping.png)
+
+**Enable Face Mapping:**
+
+![face-mapping2](face_mapping2.png)
+
+**Map the Faces:**
+
+![face_mapping_result](face_mapping_result.gif)
+
+**See the Magic!**
+
+## Quick Start (Windows / Nvidia)
+
+[Download latest pre-built version with CUDA support](https://hacksider.gumroad.com/l/vccdmm) - No Manual Installation/Downloading required.
+
+## Installation (Manual)
+
+### Basic Installation (CPU)
+
+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
+```
+
+**For macOS:** Install or upgrade the `python-tk` package:
+
+```bash
+brew install [email protected]
+```
+
+**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:
+```bash
+python run.py --execution-provider cuda
+```
+
+**CoreML Execution Provider (Apple Silicon)**
+
+1. Install dependencies:
+```bash
+pip uninstall onnxruntime onnxruntime-silicon
+pip install onnxruntime-silicon==1.13.1
+```
+2. Usage:
+```bash
+python run.py --execution-provider coreml
+```
+
+**CoreML Execution Provider (Apple Legacy)**
+
+1. Install dependencies:
+```bash
+pip uninstall onnxruntime onnxruntime-coreml
+pip install onnxruntime-coreml==1.13.1
+```
+2. Usage:
+```bash
+python run.py --execution-provider coreml
+```
+
+**DirectML Execution Provider (Windows)**
+
+1. Install dependencies:
+```bash
+pip uninstall onnxruntime onnxruntime-directml
+pip install onnxruntime-directml==1.15.1
+```
+2. Usage:
+```bash
+python run.py --execution-provider directml
+```
+
+**OpenVINO™ Execution Provider (Intel)**
+
+1. Install dependencies:
+```bash
+pip uninstall onnxruntime onnxruntime-openvino
+pip install onnxruntime-openvino==1.15.0
+```
+2. Usage:
+```bash
+python run.py --execution-provider openvino
+```
+
+</details>
+
+
+## Usage
+
+**1. Image/Video Mode**
+
+- 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.
+
+**2. Webcam Mode**
+
+- 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.
+
+![demo-gif](demo.gif)
+
+## Command Line Arguments
+
+```
+options:
+  -h, --help                                               show this help message and exit
+  -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, ...)
+  --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
+  --live-resizable                                         the live camera frame is resizable
+  --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
+  -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.
+
+
+## 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:**
+
+- [x] Support multiple faces 
+- [ ] Develop a version for web app/service
+- [ ] UI/UX enhancements for desktop app
+- [ ] Speed up model loading
+- [ ] Speed up real-time face swapping
+
+This is an open-source project developed in our free time. Updates may be delayed.
+
+
+## Credits
+
+- [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. Please be reminded that the [use of the model is for non-commercial research purposes only](https://github.com/deepinsight/insightface?tab=readme-ov-file#license).
+- [havok2-htwo](https://github.com/havok2-htwo) : for sharing the code for webcam
+- [GosuDRM](https://github.com/GosuDRM) : for 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)
+
+## Thanks to all the contributors
+<a href="https://github.com/hacksider/Deep-Live-Cam/graphs/contributors" target="_blank">
+  <img src="https://contrib.rocks/image?repo=hacksider/Deep-Live-Cam" />
+</a>

models/instructions.txt

@@ -0,0 +1 @@
+just put the models in this folder

modules/capturer.py

@@ -0,0 +1,32 @@
+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) -> Any:
+    capture = cv2.VideoCapture(video_path)
+
+    # Set MJPEG format to ensure correct color space handling
+    capture.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*'MJPG'))
+    
+    # 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:
+    capture = cv2.VideoCapture(video_path)
+    video_frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
+    capture.release()
+    return video_frame_total

modules/cluster_analysis.py

@@ -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

modules/core.py

@@ -0,0 +1,255 @@
+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
+import torch
+import onnxruntime
+import tensorflow
+
+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
+
+if 'ROCMExecutionProvider' in modules.globals.execution_providers:
+    del torch
+
+warnings.filterwarnings('ignore', category=FutureWarning, module='insightface')
+warnings.filterwarnings('ignore', category=UserWarning, module='torchvision')
+
+
+def parse_args() -> None:
+    signal.signal(signal.SIGINT, lambda signal_number, frame: destroy())
+    program = argparse.ArgumentParser()
+    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
+    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')
+    program.add_argument('--gpu-threads', help=argparse.SUPPRESS, dest='gpu_threads_deprecated', type=int)
+
+    args = program.parse_args()
+
+    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.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
+    modules.globals.live_resizable = args.live_resizable
+    modules.globals.max_memory = args.max_memory
+    modules.globals.execution_providers = decode_execution_providers(args.execution_provider)
+    modules.globals.execution_threads = args.execution_threads
+
+    #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
+
+    # 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)
+    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
+    if args.gpu_vendor_deprecated == 'apple':
+        print('\033[33mArgument --gpu-vendor apple is deprecated. Use --execution-provider coreml instead.\033[0m')
+        modules.globals.execution_providers = decode_execution_providers(['coreml'])
+    if args.gpu_vendor_deprecated == 'nvidia':
+        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 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')
+        modules.globals.execution_threads = args.gpu_threads_deprecated
+
+
+def encode_execution_providers(execution_providers: List[str]) -> List[str]:
+    return [execution_provider.replace('ExecutionProvider', '').lower() for execution_provider in execution_providers]
+
+
+def decode_execution_providers(execution_providers: List[str]) -> List[str]:
+    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:
+    if platform.system().lower() == 'darwin':
+        return 4
+    return 16
+
+
+def suggest_execution_providers() -> List[str]:
+    return encode_execution_providers(onnxruntime.get_available_providers())
+
+
+def suggest_execution_threads() -> int:
+    if 'DmlExecutionProvider' in modules.globals.execution_providers:
+        return 1
+    if 'ROCMExecutionProvider' in modules.globals.execution_providers:
+        return 1
+    return 8
+
+
+def limit_resources() -> None:
+    # 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
+    if modules.globals.max_memory:
+        memory = modules.globals.max_memory * 1024 ** 3
+        if platform.system().lower() == 'darwin':
+            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
+            resource.setrlimit(resource.RLIMIT_DATA, (memory, memory))
+
+
+def release_resources() -> None:
+    if 'CUDAExecutionProvider' in modules.globals.execution_providers:
+        torch.cuda.empty_cache()
+
+
+def pre_check() -> bool:
+    if sys.version_info < (3, 9):
+        update_status('Python version is not supported - please upgrade to 3.9 or higher.')
+        return False
+    if not shutil.which('ffmpeg'):
+        update_status('ffmpeg is not installed.')
+        return False
+    return True
+
+
+def update_status(message: str, scope: str = 'DLC.CORE') -> None:
+    print(f'[{scope}] {message}')
+    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
+    update_status('Processing...')
+    # process image to image
+    if has_image_extension(modules.globals.target_path):
+        if modules.globals.nsfw_filter and ui.check_and_ignore_nsfw(modules.globals.target_path, destroy):
+            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
+
+    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)
+
+    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('Progressing...', frame_processor.NAME)
+        frame_processor.process_video(modules.globals.source_path, temp_frame_paths)
+        release_resources()
+    # handles fps
+    if modules.globals.keep_fps:
+        update_status('Detecting fps...')
+        fps = detect_fps(modules.globals.target_path)
+        update_status(f'Creating video with {fps} fps...')
+        create_video(modules.globals.target_path, fps)
+    else:
+        update_status('Creating video with 30.0 fps...')
+        create_video(modules.globals.target_path)
+    # handle audio
+    if modules.globals.keep_audio:
+        if modules.globals.keep_fps:
+            update_status('Restoring audio...')
+        else:
+            update_status('Restoring audio might cause issues as fps are not kept...')
+        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:
+    if modules.globals.target_path:
+        clean_temp(modules.globals.target_path)
+    if to_quit: quit()
+
+
+def run() -> None:
+    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
+    limit_resources()
+    if modules.globals.headless:
+        start()
+    else:
+        window = ui.init(start, destroy)
+        window.mainloop()

modules/face_analyser.py

@@ -0,0 +1,189 @@
+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 = None
+
+
+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.prepare(ctx_id=0, det_size=(640, 640))
+    return FACE_ANALYSER
+
+
+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

modules/globals.py

@@ -0,0 +1,37 @@
+import os
+from typing import List, Dict, Any
+
+ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
+WORKFLOW_DIR = os.path.join(ROOT_DIR, 'workflow')
+
+file_types = [
+    ('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
+map_faces = None
+color_correction = None  # New global variable for color correction toggle
+nsfw_filter = None
+video_encoder = None
+video_quality = None
+live_mirror = None
+live_resizable = None
+max_memory = None
+execution_providers: List[str] = []
+execution_threads = None
+headless = None
+log_level = 'error'
+fp_ui: Dict[str, bool] = {}
+camera_input_combobox = None
+webcam_preview_running = False

modules/metadata.py

@@ -0,0 +1,3 @@
+name = 'Deep Live Cam'
+version = '1.5.0'
+edition = 'Portable'

modules/predicter.py

@@ -0,0 +1,36 @@
+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
+
+# Preload the model once for efficiency
+model = None
+
+def predict_frame(target_frame: Frame) -> bool:
+    # 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)
+    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:
+    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)
+    return any(probability > MAX_PROBABILITY for probability in probabilities)

modules/processors/frame/core.py

@@ -0,0 +1,73 @@
+import sys
+import importlib
+from concurrent.futures import ThreadPoolExecutor
+from types import ModuleType
+from typing import Any, List, Callable
+from tqdm import tqdm
+
+import modules
+import modules.globals                   
+
+FRAME_PROCESSORS_MODULES: List[ModuleType] = []
+FRAME_PROCESSORS_INTERFACE = [
+    'pre_check',
+    'pre_start',
+    'process_frame',
+    'process_image',
+    'process_video'
+]
+
+
+def load_frame_processor_module(frame_processor: str) -> Any:
+    try:
+        frame_processor_module = importlib.import_module(f'modules.processors.frame.{frame_processor}')
+        for method_name in FRAME_PROCESSORS_INTERFACE:
+            if not hasattr(frame_processor_module, method_name):
+                sys.exit()
+    except ImportError:
+        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:
+        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 == True and frame_processor not in frame_processors:
+            frame_processor_module = load_frame_processor_module(frame_processor)
+            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
+            modules.globals.frame_processors.append(frame_processor)
+        if state == False:
+            try:
+                frame_processor_module = load_frame_processor_module(frame_processor)
+                FRAME_PROCESSORS_MODULES.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 = []
+        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:
+    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})
+        multi_process_frame(source_path, frame_paths, process_frames, progress)

modules/processors/frame/face_enhancer.py

@@ -0,0 +1,79 @@
+from typing import Any, List
+import cv2
+import threading
+import gfpgan
+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.typing import Frame, Face
+from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
+
+FACE_ENHANCER = None
+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:
+            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(
+            temp_frame,
+            paste_back=True
+        )
+    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)
+        result = process_frame(None, temp_frame)
+        cv2.imwrite(temp_frame_path, result)
+        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)

modules/processors/frame/face_swapper.py

@@ -0,0 +1,174 @@
+from typing import Any, List
+import cv2
+import insightface
+import threading
+
+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, default_source_face
+from modules.typing import Face, Frame
+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'
+
+
+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'])
+    return True
+
+
+def pre_start() -> bool:
+    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 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)
+        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)
+    return FACE_SWAPPER
+
+
+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)
+
+
+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:
+            for target_face in many_faces:
+                temp_frame = swap_face(source_face, target_face, temp_frame)
+    else:
+        target_face = get_one_face(temp_frame)
+        if target_face:
+            temp_frame = swap_face(source_face, target_face, temp_frame)
+    return temp_frame
+
+
+def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
+    if is_image(modules.globals.target_path):
+        if modules.globals.many_faces:
+            source_face = default_source_face()
+            for map in modules.globals.souce_target_map:
+                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:
+    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:
+    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)

modules/typing.py

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

modules/ui.json

@@ -0,0 +1,158 @@
+{
+  "CTk": {
+    "fg_color": ["gray95", "gray10"]
+  },
+  "CTkToplevel": {
+    "fg_color": ["gray95", "gray10"]
+  },
+  "CTkFrame": {
+    "corner_radius": 0,
+    "border_width": 0,
+    "fg_color": ["gray90", "gray13"],
+    "top_fg_color": ["gray85", "gray16"],
+    "border_color": ["gray65", "gray28"]
+  },
+  "CTkButton": {
+    "corner_radius": 0,
+    "border_width": 0,
+    "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": ["gray14", "gray84"]
+  },
+  "CTkEntry": {
+    "corner_radius": 0,
+    "border_width": 2,
+    "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": ["gray36", "#D5D9DE"],
+    "button_hover_color": ["gray20", "gray100"],
+    "text_color": ["gray14", "gray84"],
+    "text_color_disabled": ["gray60", "gray45"]
+  },
+  "CTkRadiobutton": {
+    "corner_radius": 1000,
+    "border_width_checked": 6,
+    "border_width_unchecked": 3,
+    "fg_color": ["#2aa666", "#1f538d"],
+    "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,
+    "button_corner_radius": 1000,
+    "border_width": 6,
+    "button_length": 0,
+    "fg_color": ["#939BA2", "#4A4D50"],
+    "progress_color": ["gray40", "#AAB0B5"],
+    "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",
+      "size": 18,
+      "weight": "normal"
+    },
+    "Windows": {
+      "family": "Corbel",
+      "size": 18,
+      "weight": "normal"
+    },
+    "Linux": {
+      "family": "Montserrat",
+      "size": 18,
+      "weight": "normal"
+    }
+  },
+  "URL": {
+    "text_color": ["gray74", "gray60"]
+  }
+}

modules/ui.py

@@ -0,0 +1,1262 @@
+import os
+import webbrowser
+import customtkinter as ctk
+from typing import Callable, Tuple
+import cv2
+from PIL import Image, ImageOps
+import tkinterdnd2 as tkdnd
+
+import modules.globals
+import modules.metadata
+from modules.face_analyser import (
+    get_one_face,
+    get_unique_faces_from_target_image,
+    get_unique_faces_from_target_video,
+    add_blank_map,
+    has_valid_map,
+    simplify_maps,
+)
+from modules.capturer import get_video_frame, get_video_frame_total
+from modules.processors.frame.core import get_frame_processors_modules
+from modules.utilities import (
+    is_image,
+    is_video,
+    resolve_relative_path,
+    has_image_extension,
+)
+
+os.environ["QT_AUTO_SCREEN_SCALE_FACTOR"] = "1"
+os.environ["QT_SCREEN_SCALE_FACTORS"] = "1"
+os.environ["QT_SCALE_FACTOR"] = "1"
+
+ROOT = None
+POPUP = None
+POPUP_LIVE = None
+ROOT_HEIGHT = 800
+ROOT_WIDTH = 1000
+
+PREVIEW = None
+PREVIEW_MAX_HEIGHT = 800
+PREVIEW_MAX_WIDTH = 1400
+PREVIEW_DEFAULT_WIDTH = 1280
+PREVIEW_DEFAULT_HEIGHT = 720
+
+POPUP_WIDTH = 700
+POPUP_HEIGHT = 800
+POPUP_SCROLL_WIDTH = 680
+POPUP_SCROLL_HEIGHT = 600
+
+POPUP_LIVE_WIDTH = 850
+POPUP_LIVE_HEIGHT = 700
+POPUP_LIVE_SCROLL_WIDTH = 830
+POPUP_LIVE_SCROLL_HEIGHT = 600
+
+MAPPER_PREVIEW_MAX_HEIGHT = 120
+MAPPER_PREVIEW_MAX_WIDTH = 120
+
+DEFAULT_BUTTON_WIDTH = 200
+DEFAULT_BUTTON_HEIGHT = 40
+
+RECENT_DIRECTORY_SOURCE = None
+RECENT_DIRECTORY_TARGET = None
+RECENT_DIRECTORY_OUTPUT = None
+
+preview_label = None
+preview_slider = None
+source_label = None
+target_label = None
+status_label = None
+popup_status_label = None
+popup_status_label_live = None
+source_label_dict = {}
+source_label_dict_live = {}
+target_label_dict_live = {}
+
+img_ft, vid_ft = modules.globals.file_types
+
+
+class ModernButton(ctk.CTkButton):
+    def __init__(self, master, **kwargs):
+        super().__init__(master, **kwargs)
+        self.configure(
+            font=("Roboto", 16, "bold"),
+            corner_radius=15,
+            border_width=2,
+            border_color="#3a7ebf",
+            hover_color="#2b5d8b",
+            fg_color="#3a7ebf",
+            text_color="white",
+        )
+
+
+class DragDropButton(ModernButton):
+    def __init__(self, master, **kwargs):
+        super().__init__(master, **kwargs)
+        self.drop_target_register(tkdnd.DND_FILES)
+        self.dnd_bind("<<Drop>>", self.drop)
+
+    def drop(self, event):
+        file_path = event.data
+        if file_path.startswith("{"):
+            file_path = file_path[1:-1]
+        self.handle_drop(file_path)
+
+    def handle_drop(self, file_path):
+        pass
+
+
+class SourceButton(DragDropButton):
+    def handle_drop(self, file_path):
+        if is_image(file_path):
+            modules.globals.source_path = file_path
+            global RECENT_DIRECTORY_SOURCE
+            RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
+            image = render_image_preview(modules.globals.source_path, (250, 250))
+            source_label.configure(image=image)
+            source_label.configure(text="")
+
+
+class SourceMapperButton(DragDropButton):
+    def __init__(self, master, map, button_num, **kwargs):
+        super().__init__(master, **kwargs)
+        self.map = map
+        self.button_num = button_num
+
+    def handle_drop(self, file_path):
+        if is_image(file_path):
+            update_popup_source(
+                self.master.master, self.map, self.button_num, file_path
+            )
+
+
+class TargetButton(DragDropButton):
+    def handle_drop(self, file_path):
+        global RECENT_DIRECTORY_TARGET
+        if is_image(file_path) or is_video(file_path):
+            modules.globals.target_path = file_path
+            RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
+            if is_image(file_path):
+                image = render_image_preview(modules.globals.target_path, (250, 250))
+                target_label.configure(image=image)
+                target_label.configure(text="")
+            elif is_video(file_path):
+                video_frame = render_video_preview(file_path, (250, 250))
+                target_label.configure(image=video_frame)
+                target_label.configure(text="")
+
+
+class ModernLabel(ctk.CTkLabel):
+    def __init__(self, master, **kwargs):
+        super().__init__(master, **kwargs)
+        self.configure(
+            font=("Roboto", 16),
+            corner_radius=10,
+            fg_color="#2a2d2e",
+            text_color="white",
+        )
+
+
+class DragDropLabel(ModernLabel):
+    def __init__(self, master, **kwargs):
+        super().__init__(master, **kwargs)
+        self.drop_target_register(tkdnd.DND_FILES)
+        self.dnd_bind("<<Drop>>", self.drop)
+
+    def drop(self, event):
+        file_path = event.data
+        if file_path.startswith("{"):
+            file_path = file_path[1:-1]
+        self.handle_drop(file_path)
+
+    def handle_drop(self, file_path):
+        pass
+
+
+class SourceLabel(DragDropLabel):
+    def handle_drop(self, file_path):
+        if is_image(file_path):
+            modules.globals.source_path = file_path
+            global RECENT_DIRECTORY_SOURCE
+            RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
+            image = render_image_preview(modules.globals.source_path, (250, 250))
+            source_label.configure(image=image)
+            source_label.configure(text="")
+
+
+class TargetLabel(DragDropLabel):
+    def handle_drop(self, file_path):
+        global RECENT_DIRECTORY_TARGET
+        if is_image(file_path) or is_video(file_path):
+            modules.globals.target_path = file_path
+            RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
+            if is_image(file_path):
+                image = render_image_preview(modules.globals.target_path, (250, 250))
+                target_label.configure(image=image)
+                target_label.configure(text="")
+            elif is_video(file_path):
+                video_frame = render_video_preview(file_path, (250, 250))
+                target_label.configure(image=video_frame)
+                target_label.configure(text="")
+
+
+def init(start: Callable[[], None], destroy: Callable[[], None]) -> tkdnd.TkinterDnD.Tk:
+    global ROOT, PREVIEW
+
+    ROOT = create_root(start, destroy)
+    PREVIEW = create_preview(ROOT)
+
+    return ROOT
+
+
+def create_root(
+    start: Callable[[], None], destroy: Callable[[], None]
+) -> tkdnd.TkinterDnD.Tk:
+    global source_label, target_label, status_label
+
+    ctk.set_appearance_mode("dark")
+    ctk.set_default_color_theme("blue")
+
+    root = tkdnd.TkinterDnD.Tk()
+    root.title(
+        f"{modules.metadata.name} {modules.metadata.version} {modules.metadata.edition}"
+    )
+    root.configure(bg="#1a1a1a")
+    root.protocol("WM_DELETE_WINDOW", lambda: destroy())
+    root.resizable(True, True)
+    root.attributes("-alpha", 1.0)  # Set window opacity to fully opaque
+
+    main_frame = ctk.CTkFrame(root, fg_color="#1a1a1a")
+    main_frame.pack(fill="both", expand=True, padx=20, pady=20)
+
+    # Create two vertical frames for source and target
+    source_frame = ctk.CTkFrame(main_frame, fg_color="#2a2d2e", corner_radius=15)
+    source_frame.grid(row=0, column=0, padx=10, pady=10, sticky="nsew")
+
+    target_frame = ctk.CTkFrame(main_frame, fg_color="#2a2d2e", corner_radius=15)
+    target_frame.grid(row=0, column=2, padx=10, pady=10, sticky="nsew")
+
+    # Create a middle frame for swap button
+    middle_frame = ctk.CTkFrame(main_frame, fg_color="#1a1a1a")
+    middle_frame.grid(row=0, column=1, padx=5, pady=10, sticky="ns")
+
+    source_label = SourceLabel(
+        source_frame,
+        text="Drag & Drop\nSource Image Here",
+        justify="center",
+        width=250,
+        height=250,
+    )
+    source_label.pack(pady=(20, 10))
+
+    target_label = TargetLabel(
+        target_frame,
+        text="Drag & Drop\nTarget Image/Video Here",
+        justify="center",
+        width=250,
+        height=250,
+    )
+    target_label.pack(pady=(20, 10))
+
+    select_face_button = SourceButton(
+        source_frame,
+        text="Select a face",
+        cursor="hand2",
+        command=lambda: select_source_path(),
+    )
+    select_face_button.pack(pady=10)
+
+    select_target_button = TargetButton(
+        target_frame,
+        text="Select a target",
+        cursor="hand2",
+        command=lambda: select_target_path(),
+    )
+    select_target_button.pack(pady=10)
+
+    swap_faces_button = ModernButton(
+        middle_frame,
+        text="↔",
+        cursor="hand2",
+        command=lambda: swap_faces_paths(),
+        width=50,
+        height=50,
+    )
+    swap_faces_button.pack(expand=True)
+
+    options_frame = ctk.CTkFrame(main_frame, fg_color="#2a2d2e", corner_radius=15)
+    options_frame.grid(row=1, column=0, columnspan=3, padx=10, pady=10, sticky="nsew")
+
+    # Create a single column for options, centered
+    options_column = ctk.CTkFrame(options_frame, fg_color="#2a2d2e")
+    options_column.pack(expand=True)
+
+    # Switches
+    keep_fps_value = ctk.BooleanVar(value=modules.globals.keep_fps)
+    keep_fps_checkbox = ctk.CTkSwitch(
+        options_column,
+        text="Keep fps",
+        variable=keep_fps_value,
+        cursor="hand2",
+        command=lambda: setattr(
+            modules.globals, "keep_fps", not modules.globals.keep_fps
+        ),
+        progress_color="#3a7ebf",
+        font=("Roboto", 14, "bold"),
+    )
+    keep_fps_checkbox.pack(pady=5, anchor="w")
+
+    keep_frames_value = ctk.BooleanVar(value=modules.globals.keep_frames)
+    keep_frames_switch = ctk.CTkSwitch(
+        options_column,
+        text="Keep frames",
+        variable=keep_frames_value,
+        cursor="hand2",
+        command=lambda: setattr(
+            modules.globals, "keep_frames", keep_frames_value.get()
+        ),
+        progress_color="#3a7ebf",
+        font=("Roboto", 14, "bold"),
+    )
+    keep_frames_switch.pack(pady=5, anchor="w")
+
+    enhancer_value = ctk.BooleanVar(value=modules.globals.fp_ui["face_enhancer"])
+    enhancer_switch = ctk.CTkSwitch(
+        options_column,
+        text="Face Enhancer",
+        variable=enhancer_value,
+        cursor="hand2",
+        command=lambda: update_tumbler("face_enhancer", enhancer_value.get()),
+        progress_color="#3a7ebf",
+        font=("Roboto", 14, "bold"),
+    )
+    enhancer_switch.pack(pady=5, anchor="w")
+
+    keep_audio_value = ctk.BooleanVar(value=modules.globals.keep_audio)
+    keep_audio_switch = ctk.CTkSwitch(
+        options_column,
+        text="Keep audio",
+        variable=keep_audio_value,
+        cursor="hand2",
+        command=lambda: setattr(modules.globals, "keep_audio", keep_audio_value.get()),
+        progress_color="#3a7ebf",
+        font=("Roboto", 14, "bold"),
+    )
+    keep_audio_switch.pack(pady=5, anchor="w")
+
+    many_faces_value = ctk.BooleanVar(value=modules.globals.many_faces)
+    many_faces_switch = ctk.CTkSwitch(
+        options_column,
+        text="Many faces",
+        variable=many_faces_value,
+        cursor="hand2",
+        command=lambda: setattr(modules.globals, "many_faces", many_faces_value.get()),
+        progress_color="#3a7ebf",
+        font=("Roboto", 14, "bold"),
+    )
+    many_faces_switch.pack(pady=5, anchor="w")
+
+    color_correction_value = ctk.BooleanVar(value=modules.globals.color_correction)
+    color_correction_switch = ctk.CTkSwitch(
+        options_column,
+        text="Fix Blueish Cam",
+        variable=color_correction_value,
+        cursor="hand2",
+        command=lambda: setattr(
+            modules.globals, "color_correction", color_correction_value.get()
+        ),
+        progress_color="#3a7ebf",
+        font=("Roboto", 14, "bold"),
+    )
+    color_correction_switch.pack(pady=5, anchor="w")
+
+    map_faces = ctk.BooleanVar(value=modules.globals.map_faces)
+    map_faces_switch = ctk.CTkSwitch(
+        options_column,
+        text="Map faces",
+        variable=map_faces,
+        cursor="hand2",
+        command=lambda: setattr(modules.globals, "map_faces", map_faces.get()),
+        progress_color="#3a7ebf",
+        font=("Roboto", 14, "bold"),
+    )
+    map_faces_switch.pack(pady=5, anchor="w")
+
+    button_frame = ctk.CTkFrame(main_frame, fg_color="#1a1a1a")
+    button_frame.grid(row=2, column=0, columnspan=3, padx=10, pady=10, sticky="nsew")
+
+    start_button = ModernButton(
+        button_frame,
+        text="Start",
+        cursor="hand2",
+        command=lambda: analyze_target(start, root),
+        fg_color="#4CAF50",
+        hover_color="#45a049",
+    )
+    start_button.pack(side="left", padx=10, expand=True)
+
+    preview_button = ModernButton(
+        button_frame,
+        text="Preview",
+        cursor="hand2",
+        command=lambda: toggle_preview(),
+    )
+    preview_button.pack(side="left", padx=10, expand=True)
+
+    live_button = ModernButton(
+        button_frame,
+        text="Live",
+        cursor="hand2",
+        command=lambda: webcam_preview(root),
+    )
+    live_button.pack(side="left", padx=10, expand=True)
+
+    stop_button = ModernButton(
+        button_frame,
+        text="Destroy",
+        cursor="hand2",
+        command=lambda: destroy(),
+        fg_color="#f44336",
+        hover_color="#d32f2f",
+    )
+    stop_button.pack(side="left", padx=10, expand=True)
+
+    status_label = ModernLabel(
+        main_frame, text=None, justify="center", fg_color="#1a1a1a"
+    )
+    status_label.grid(row=3, column=0, columnspan=3, pady=10, sticky="ew")
+
+    donate_frame = ctk.CTkFrame(main_frame, fg_color="#1a1a1a")
+    donate_frame.grid(row=4, column=0, columnspan=3, pady=5, sticky="ew")
+
+    donate_label = ModernLabel(
+        donate_frame,
+        text="Donate",
+        justify="center",
+        cursor="hand2",
+        fg_color="#1870c4",
+        text_color="#1870c4",
+    )
+    donate_label.pack(side="left", expand=True)
+
+    donate_label.bind(
+        "<Button>", lambda event: webbrowser.open("https://paypal.me/hacksider")
+    )
+
+    remove_donate_button = ModernButton(
+        donate_frame,
+        text="X",
+        cursor="hand2",
+        command=lambda: donate_frame.destroy(),
+        width=30,
+        height=30,
+        fg_color="#f44336",
+        hover_color="#d32f2f",
+    )
+    remove_donate_button.pack(side="right", padx=(10, 0))
+
+    main_frame.grid_columnconfigure((0, 2), weight=1)
+    main_frame.grid_rowconfigure((0, 1, 2), weight=1)
+
+    root.grid_columnconfigure(0, weight=1)
+    root.grid_rowconfigure(0, weight=1)
+
+    return root
+
+
+def analyze_target(start: Callable[[], None], root: ctk.CTk):
+    if POPUP is not None and POPUP.winfo_exists():
+        update_status("Please complete pop-up or close it.")
+        return
+
+    if modules.globals.map_faces:
+        modules.globals.souce_target_map = []
+
+        if is_image(modules.globals.target_path):
+            update_status("Getting unique faces")
+            get_unique_faces_from_target_image()
+        elif is_video(modules.globals.target_path):
+            update_status("Getting unique faces")
+            get_unique_faces_from_target_video()
+        else:
+            update_status("Invalid target file. Please select an image or video.")
+            return
+
+        if len(modules.globals.souce_target_map) > 0:
+            create_source_target_popup(start, root, modules.globals.souce_target_map)
+        else:
+            update_status("No faces found in target")
+    else:
+        select_output_path(start)
+
+
+def create_source_target_popup(
+    start: Callable[[], None], root: ctk.CTk, map: list
+) -> None:
+    global POPUP, popup_status_label
+
+    POPUP = ctk.CTkToplevel(root)
+    POPUP.title("Source x Target Mapper")
+    POPUP.geometry(f"{POPUP_WIDTH}x{POPUP_HEIGHT}")
+    POPUP.focus()
+    POPUP.resizable(True, True)
+
+    def on_submit_click(start):
+        if has_valid_map():
+            POPUP.destroy()
+            select_output_path(start)
+        else:
+            update_pop_status("At least 1 source with target is required!")
+
+    scrollable_frame = ctk.CTkScrollableFrame(
+        POPUP, width=POPUP_SCROLL_WIDTH, height=POPUP_SCROLL_HEIGHT
+    )
+    scrollable_frame.pack(fill="both", expand=True, padx=10, pady=10)
+
+    def on_button_click(map, button_num):
+        update_popup_source(scrollable_frame, map, button_num)
+
+    # Create a frame to hold the table
+    table_frame = ctk.CTkFrame(scrollable_frame)
+    table_frame.pack(expand=True)
+
+    for item in map:
+        id = item["id"]
+
+        row_frame = ctk.CTkFrame(table_frame)
+        row_frame.pack(fill="x", pady=5)
+
+        source_button = SourceMapperButton(
+            row_frame,
+            map,
+            id,
+            text="Select source image",
+            command=lambda id=id: on_button_click(map, id),
+            width=DEFAULT_BUTTON_WIDTH,
+            height=DEFAULT_BUTTON_HEIGHT,
+            fg_color=("gray75", "gray25"),
+            hover_color=("gray85", "gray35"),
+            corner_radius=10,
+        )
+        source_button.pack(side="left", padx=(0, 10))
+
+        source_image = ctk.CTkLabel(
+            row_frame,
+            text=f"S-{id}",
+            width=MAPPER_PREVIEW_MAX_WIDTH,
+            height=MAPPER_PREVIEW_MAX_HEIGHT,
+            font=("Arial", 14, "bold"),
+        )
+        source_image.pack(side="left", padx=(0, 10))
+
+        x_label = ctk.CTkLabel(
+            row_frame,
+            text=f"X",
+            width=30,
+            font=("Arial", 14, "bold"),
+        )
+        x_label.pack(side="left", padx=(0, 10))
+
+        image = Image.fromarray(cv2.cvtColor(item["target"]["cv2"], cv2.COLOR_BGR2RGB))
+        image = image.resize(
+            (MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS
+        )
+        tk_image = ctk.CTkImage(image, size=image.size)
+
+        target_image = ctk.CTkLabel(
+            row_frame,
+            text=f"T-{id}",
+            width=MAPPER_PREVIEW_MAX_WIDTH,
+            height=MAPPER_PREVIEW_MAX_HEIGHT,
+            font=("Arial", 14, "bold"),
+        )
+        target_image.pack(side="left")
+        target_image.configure(image=tk_image)
+
+    popup_status_label = ctk.CTkLabel(
+        POPUP, text=None, justify="center", font=("Arial", 14, "bold")
+    )
+    popup_status_label.pack(pady=10)
+
+    submit_button = ctk.CTkButton(
+        POPUP,
+        text="Submit",
+        command=lambda: on_submit_click(start),
+        fg_color=("DodgerBlue", "DodgerBlue"),
+        hover_color=("RoyalBlue", "RoyalBlue"),
+        corner_radius=10,
+        font=("Arial", 16, "bold"),
+        width=200,
+        height=50,
+    )
+    submit_button.pack(pady=10)
+
+    POPUP.update()
+    POPUP.minsize(POPUP.winfo_width(), POPUP.winfo_height())
+
+
+def update_popup_source(
+    scrollable_frame: ctk.CTkScrollableFrame,
+    map: list,
+    button_num: int,
+    source_path: str = None,
+) -> list:
+    global source_label_dict, RECENT_DIRECTORY_SOURCE
+
+    if source_path is None:
+        source_path = ctk.filedialog.askopenfilename(
+            title="select an source image",
+            initialdir=RECENT_DIRECTORY_SOURCE,
+            filetypes=[img_ft],
+        )
+
+    if "source" in map[button_num]:
+        map[button_num].pop("source")
+        if button_num in source_label_dict:
+            source_label_dict[button_num].destroy()
+            del source_label_dict[button_num]
+
+    if source_path == "":
+        return map
+    else:
+        RECENT_DIRECTORY_SOURCE = os.path.dirname(source_path)
+        cv2_img = cv2.imread(source_path)
+        face = get_one_face(cv2_img)
+
+        if face:
+            x_min, y_min, x_max, y_max = face["bbox"]
+
+            map[button_num]["source"] = {
+                "cv2": cv2_img[int(y_min) : int(y_max), int(x_min) : int(x_max)],
+                "face": face,
+            }
+
+            image = Image.fromarray(
+                cv2.cvtColor(map[button_num]["source"]["cv2"], cv2.COLOR_BGR2RGB)
+            )
+            image = image.resize(
+                (MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS
+            )
+            tk_image = ctk.CTkImage(image, size=image.size)
+
+            source_image = ctk.CTkLabel(
+                scrollable_frame.winfo_children()[button_num],
+                text=f"S-{button_num}",
+                width=MAPPER_PREVIEW_MAX_WIDTH,
+                height=MAPPER_PREVIEW_MAX_HEIGHT,
+                font=("Arial", 14, "bold"),
+            )
+            source_image.pack(
+                side="left",
+                padx=(0, 10),
+                after=scrollable_frame.winfo_children()[button_num].winfo_children()[0],
+            )
+            source_image.configure(image=tk_image)
+            source_label_dict[button_num] = source_image
+        else:
+            update_pop_status("Face could not be detected in last upload!")
+        return map
+
+
+def create_preview(parent: ctk.CTkToplevel) -> ctk.CTkToplevel:
+    global preview_label, preview_slider
+
+    preview = ctk.CTkToplevel(parent)
+    preview.withdraw()
+    preview.title("Preview")
+    preview.configure()
+    preview.protocol("WM_DELETE_WINDOW", lambda: toggle_preview())
+    preview.resizable(width=True, height=True)
+
+    preview_label = ctk.CTkLabel(preview, text=None, font=("Arial", 14, "bold"))
+    preview_label.pack(fill="both", expand=True)
+
+    preview_slider = ctk.CTkSlider(
+        preview,
+        from_=0,
+        to=0,
+        command=lambda frame_value: update_preview(int(frame_value)),
+        fg_color=("gray75", "gray25"),
+        progress_color=("DodgerBlue", "DodgerBlue"),
+        button_color=("DodgerBlue", "DodgerBlue"),
+        button_hover_color=("RoyalBlue", "RoyalBlue"),
+    )
+    preview_slider.pack(fill="x", padx=20, pady=10)
+
+    return preview
+
+
+def update_status(text: str) -> None:
+    status_label.configure(text=text)
+    ROOT.update()
+
+
+def update_pop_status(text: str) -> None:
+    popup_status_label.configure(text=text)
+
+
+def update_pop_live_status(text: str) -> None:
+    popup_status_label_live.configure(text=text)
+
+
+def update_tumbler(var: str, value: bool) -> None:
+    modules.globals.fp_ui[var] = value
+
+
+def select_source_path() -> None:
+    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft
+
+    PREVIEW.withdraw()
+    source_path = ctk.filedialog.askopenfilename(
+        title="select an source image",
+        initialdir=RECENT_DIRECTORY_SOURCE,
+        filetypes=[img_ft],
+    )
+    if is_image(source_path):
+        modules.globals.source_path = source_path
+        RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
+        image = render_image_preview(modules.globals.source_path, (200, 200))
+        source_label.configure(image=image)
+        source_label.configure(text="")
+    else:
+        modules.globals.source_path = None
+        source_label.configure(image=None)
+        source_label.configure(text="Drag & Drop Source Image Here")
+
+
+def swap_faces_paths() -> None:
+    global RECENT_DIRECTORY_SOURCE, RECENT_DIRECTORY_TARGET
+
+    source_path = modules.globals.source_path
+    target_path = modules.globals.target_path
+
+    if not is_image(source_path) or not is_image(target_path):
+        return
+
+    modules.globals.source_path = target_path
+    modules.globals.target_path = source_path
+
+    RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
+    RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
+
+    PREVIEW.withdraw()
+
+    source_image = render_image_preview(modules.globals.source_path, (200, 200))
+    source_label.configure(image=source_image)
+    source_label.configure(text="")
+
+    target_image = render_image_preview(modules.globals.target_path, (200, 200))
+    target_label.configure(image=target_image)
+    target_label.configure(text="")
+
+
+def select_target_path() -> None:
+    global RECENT_DIRECTORY_TARGET, img_ft, vid_ft
+
+    PREVIEW.withdraw()
+    target_path = ctk.filedialog.askopenfilename(
+        title="select an target image or video",
+        initialdir=RECENT_DIRECTORY_TARGET,
+        filetypes=[img_ft, vid_ft],
+    )
+    if is_image(target_path):
+        modules.globals.target_path = target_path
+        RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
+        image = render_image_preview(modules.globals.target_path, (200, 200))
+        target_label.configure(image=image)
+        target_label.configure(text="")
+    elif is_video(target_path):
+        modules.globals.target_path = target_path
+        RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
+        video_frame = render_video_preview(target_path, (200, 200))
+        target_label.configure(image=video_frame)
+        target_label.configure(text="")
+    else:
+        modules.globals.target_path = None
+        target_label.configure(image=None)
+        target_label.configure(text="Drag & Drop Target Image/Video Here")
+
+
+def select_output_path(start: Callable[[], None]) -> None:
+    global RECENT_DIRECTORY_OUTPUT, img_ft, vid_ft
+
+    if is_image(modules.globals.target_path):
+        output_path = ctk.filedialog.asksaveasfilename(
+            title="save image output file",
+            filetypes=[img_ft],
+            defaultextension=".png",
+            initialfile="output.png",
+            initialdir=RECENT_DIRECTORY_OUTPUT,
+        )
+    elif is_video(modules.globals.target_path):
+        output_path = ctk.filedialog.asksaveasfilename(
+            title="save video output file",
+            filetypes=[vid_ft],
+            defaultextension=".mp4",
+            initialfile="output.mp4",
+            initialdir=RECENT_DIRECTORY_OUTPUT,
+        )
+    else:
+        output_path = None
+    if output_path:
+        modules.globals.output_path = output_path
+        RECENT_DIRECTORY_OUTPUT = os.path.dirname(modules.globals.output_path)
+        start()
+
+
+def check_and_ignore_nsfw(target, destroy: Callable = None) -> bool:
+    """Check if the target is NSFW.
+    TODO: Consider to make blur the target.
+    """
+    from numpy import ndarray
+    from modules.predicter import predict_image, predict_video, predict_frame
+
+    if type(target) is str:  # image/video file path
+        check_nsfw = predict_image if has_image_extension(target) else predict_video
+    elif type(target) is ndarray:  # frame object
+        check_nsfw = predict_frame
+    if check_nsfw and check_nsfw(target):
+        if destroy:
+            destroy(
+                to_quit=False
+            )  # Do not need to destroy the window frame if the target is NSFW
+        update_status("Processing ignored!")
+        return True
+    else:
+        return False
+
+
+def fit_image_to_size(image, width: int, height: int):
+    if width is None and height is None:
+        return image
+    h, w, _ = image.shape
+    ratio_h = 0.0
+    ratio_w = 0.0
+    if width > height:
+        ratio_h = height / h
+    else:
+        ratio_w = width / w
+    ratio = max(ratio_w, ratio_h)
+    new_size = (int(ratio * w), int(ratio * h))
+    return cv2.resize(image, dsize=new_size)
+
+
+def render_image_preview(image_path: str, size: Tuple[int, int]) -> ctk.CTkImage:
+    image = Image.open(image_path)
+    if size:
+        image = ImageOps.fit(image, size, Image.LANCZOS)
+    return ctk.CTkImage(image, size=image.size)
+
+
+def render_video_preview(
+    video_path: str, size: Tuple[int, int], frame_number: int = 0
+) -> ctk.CTkImage:
+    capture = cv2.VideoCapture(video_path)
+    if frame_number:
+        capture.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
+    has_frame, frame = capture.read()
+    if has_frame:
+        image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+        if size:
+            image = ImageOps.fit(image, size, Image.LANCZOS)
+        return ctk.CTkImage(image, size=image.size)
+    capture.release()
+    cv2.destroyAllWindows()
+
+
+def toggle_preview() -> None:
+    if PREVIEW.state() == "normal":
+        PREVIEW.withdraw()
+    elif modules.globals.source_path and modules.globals.target_path:
+        init_preview()
+        update_preview()
+
+
+def init_preview() -> None:
+    if is_image(modules.globals.target_path):
+        preview_slider.pack_forget()
+    if is_video(modules.globals.target_path):
+        video_frame_total = get_video_frame_total(modules.globals.target_path)
+        preview_slider.configure(to=video_frame_total)
+        preview_slider.pack(fill="x")
+        preview_slider.set(0)
+
+
+def update_preview(frame_number: int = 0) -> None:
+    if modules.globals.source_path and modules.globals.target_path:
+        update_status("Processing...")
+
+        # Debug: Print the target path and frame number
+        print(
+            f"Target path: {modules.globals.target_path}, Frame number: {frame_number}"
+        )
+
+        temp_frame = None
+        if is_video(modules.globals.target_path):
+            temp_frame = get_video_frame(modules.globals.target_path, frame_number)
+        elif is_image(modules.globals.target_path):
+            temp_frame = cv2.imread(modules.globals.target_path)
+
+        # Debug: Check if temp_frame is None
+        if temp_frame is None:
+            print("Error: temp_frame is None")
+            update_status("Error: Could not read frame from video or image.")
+            return
+
+        if modules.globals.nsfw_filter and check_and_ignore_nsfw(temp_frame):
+            return
+
+        for frame_processor in get_frame_processors_modules(
+            modules.globals.frame_processors
+        ):
+            # Debug: Print the type of frame_processor
+            print(f"Processing frame with: {type(frame_processor).__name__}")
+
+            temp_frame = frame_processor.process_frame(
+                get_one_face(cv2.imread(modules.globals.source_path)), temp_frame
+            )
+
+            # Debug: Check if temp_frame is None after processing
+            if temp_frame is None:
+                print("Error: temp_frame is None after processing")
+                update_status("Error: Frame processing failed.")
+                return
+
+        image = Image.fromarray(cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB))
+        image = ImageOps.contain(
+            image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS
+        )
+        image = ctk.CTkImage(image, size=image.size)
+        preview_label.configure(image=image)
+        update_status("Processing succeed!")
+        PREVIEW.deiconify()
+
+
+def webcam_preview(root: ctk.CTk):
+    if not modules.globals.map_faces:
+        if modules.globals.source_path is None:
+            # No image selected
+            return
+        create_webcam_preview()
+    else:
+        modules.globals.souce_target_map = []
+        create_source_target_popup_for_webcam(root, modules.globals.souce_target_map)
+
+
+def create_webcam_preview():
+    global preview_label, PREVIEW
+
+    camera = cv2.VideoCapture(
+        0
+    )  # Use index for the webcam (adjust the index accordingly if necessary)
+    camera.set(
+        cv2.CAP_PROP_FRAME_WIDTH, PREVIEW_DEFAULT_WIDTH
+    )  # Set the width of the resolution
+    camera.set(
+        cv2.CAP_PROP_FRAME_HEIGHT, PREVIEW_DEFAULT_HEIGHT
+    )  # Set the height of the resolution
+    camera.set(cv2.CAP_PROP_FPS, 60)  # Set the frame rate of the webcam
+
+    preview_label.configure(
+        width=PREVIEW_DEFAULT_WIDTH, height=PREVIEW_DEFAULT_HEIGHT
+    )  # Reset the preview image before startup
+
+    PREVIEW.deiconify()  # Open preview window
+
+    frame_processors = get_frame_processors_modules(modules.globals.frame_processors)
+
+    source_image = None  # Initialize variable for the selected face image
+
+    while camera:
+        ret, frame = camera.read()
+        if not ret:
+            break
+
+        temp_frame = frame.copy()  # Create a copy of the frame
+
+        if modules.globals.live_mirror:
+            temp_frame = cv2.flip(temp_frame, 1)  # horizontal flipping
+
+        if modules.globals.live_resizable:
+            temp_frame = fit_image_to_size(
+                temp_frame, PREVIEW.winfo_width(), PREVIEW.winfo_height()
+            )
+
+        if not modules.globals.map_faces:
+            # Select and save face image only once
+            if source_image is None and modules.globals.source_path:
+                source_image = get_one_face(cv2.imread(modules.globals.source_path))
+
+            for frame_processor in frame_processors:
+                temp_frame = frame_processor.process_frame(source_image, temp_frame)
+        else:
+            modules.globals.target_path = None
+
+            for frame_processor in frame_processors:
+                temp_frame = frame_processor.process_frame_v2(temp_frame)
+
+        image = cv2.cvtColor(
+            temp_frame, cv2.COLOR_BGR2RGB
+        )  # Convert the image to RGB format to display it with Tkinter
+        image = Image.fromarray(image)
+        image = ImageOps.contain(
+            image, (temp_frame.shape[1], temp_frame.shape[0]), Image.LANCZOS
+        )
+        image = ctk.CTkImage(image, size=image.size)
+        preview_label.configure(image=image)
+        ROOT.update()
+
+        if PREVIEW.state() == "withdrawn":
+            break
+
+    camera.release()
+    PREVIEW.withdraw()  # Close preview window when loop is finished
+
+
+def create_source_target_popup_for_webcam(root: ctk.CTk, map: list) -> None:
+    global POPUP_LIVE, popup_status_label_live
+
+    POPUP_LIVE = ctk.CTkToplevel(root)
+    POPUP_LIVE.title("Source x Target Mapper")
+    POPUP_LIVE.geometry(f"{POPUP_LIVE_WIDTH}x{POPUP_LIVE_HEIGHT}")
+    POPUP_LIVE.focus()
+
+    def on_submit_click():
+        if has_valid_map():
+            POPUP_LIVE.destroy()
+            simplify_maps()
+            create_webcam_preview()
+        else:
+            update_pop_live_status("At least 1 source with target is required!")
+
+    def on_add_click():
+        add_blank_map()
+        refresh_data(map)
+        update_pop_live_status("Please provide mapping!")
+
+    popup_status_label_live = ctk.CTkLabel(POPUP_LIVE, text=None, justify="center")
+    popup_status_label_live.grid(row=1, column=0, pady=15)
+
+    add_button = ctk.CTkButton(
+        POPUP_LIVE,
+        text="Add",
+        command=lambda: on_add_click(),
+        fg_color=("gray75", "gray25"),
+        hover_color=("gray85", "gray35"),
+        corner_radius=10,
+    )
+    add_button.place(relx=0.2, rely=0.92, relwidth=0.2, relheight=0.05)
+
+    close_button = ctk.CTkButton(
+        POPUP_LIVE,
+        text="Submit",
+        command=lambda: on_submit_click(),
+        fg_color=("DodgerBlue", "DodgerBlue"),
+        hover_color=("RoyalBlue", "RoyalBlue"),
+        corner_radius=10,
+    )
+    close_button.place(relx=0.6, rely=0.92, relwidth=0.2, relheight=0.05)
+
+    refresh_data(map)  # Initial data refresh
+
+
+def refresh_data(map: list):
+    global POPUP_LIVE
+
+    # Destroy existing widgets in the scrollable frame
+    for widget in POPUP_LIVE.winfo_children():
+        if isinstance(widget, ctk.CTkScrollableFrame):
+            widget.destroy()
+
+    scrollable_frame = ctk.CTkScrollableFrame(
+        POPUP_LIVE, width=POPUP_LIVE_SCROLL_WIDTH, height=POPUP_LIVE_SCROLL_HEIGHT
+    )
+    scrollable_frame.grid(row=0, column=0, padx=0, pady=0, sticky="nsew")
+
+    def on_sbutton_click(map, button_num):
+        map = update_webcam_source(scrollable_frame, map, button_num)
+
+    def on_tbutton_click(map, button_num):
+        map = update_webcam_target(scrollable_frame, map, button_num)
+
+    for item in map:
+        id = item["id"]
+
+        row_frame = ctk.CTkFrame(scrollable_frame)
+        row_frame.pack(fill="x", pady=5)
+
+        source_button = SourceMapperButton(  # Use SourceMapperButton here
+            row_frame,
+            map,
+            id,
+            text="Select source image",
+            command=lambda id=id: on_sbutton_click(map, id),
+            width=DEFAULT_BUTTON_WIDTH,
+            height=DEFAULT_BUTTON_HEIGHT,
+            fg_color=("gray75", "gray25"),
+            hover_color=("gray85", "gray35"),
+            corner_radius=10,
+        )
+        source_button.pack(side="left", padx=(0, 10))
+
+        source_image_label = ctk.CTkLabel(  # Create a label for source image
+            row_frame,
+            text=f"S-{id}",
+            width=MAPPER_PREVIEW_MAX_WIDTH,
+            height=MAPPER_PREVIEW_MAX_HEIGHT,
+        )
+        source_image_label.pack(side="left", padx=(0, 10))
+
+        if "source" in item:
+            image = Image.fromarray(
+                cv2.cvtColor(item["source"]["cv2"], cv2.COLOR_BGR2RGB)
+            )
+            image = image.resize(
+                (MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS
+            )
+            tk_image = ctk.CTkImage(image, size=image.size)
+            source_image_label.configure(image=tk_image)
+
+        x_label = ctk.CTkLabel(
+            row_frame,
+            text=f"X",
+            width=30,
+        )
+        x_label.pack(side="left", padx=(0, 10))
+
+        target_button = DragDropButton(  # Use DragDropButton for target
+            row_frame,
+            text="Select target image",
+            command=lambda id=id: on_tbutton_click(map, id),
+            width=DEFAULT_BUTTON_WIDTH,
+            height=DEFAULT_BUTTON_HEIGHT,
+            fg_color=("gray75", "gray25"),
+            hover_color=("gray85", "gray35"),
+            corner_radius=10,
+        )
+
+        target_button.handle_drop = lambda file_path, id=id: update_webcam_target(
+            scrollable_frame, map, id, file_path
+        )  # Add handle_drop for drag and drop
+        target_button.pack(side="left", padx=(0, 10))
+
+        target_image_label = ctk.CTkLabel(  # Create a label for target image
+            row_frame,
+            text=f"T-{id}",
+            width=MAPPER_PREVIEW_MAX_WIDTH,
+            height=MAPPER_PREVIEW_MAX_HEIGHT,
+        )
+        target_image_label.pack(side="left")
+
+        if "target" in item:
+            image = Image.fromarray(
+                cv2.cvtColor(item["target"]["cv2"], cv2.COLOR_BGR2RGB)
+            )
+            image = image.resize(
+                (MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS
+            )
+            tk_image = ctk.CTkImage(image, size=image.size)
+            target_image_label.configure(image=tk_image)
+
+
+def update_webcam_source(
+    scrollable_frame: ctk.CTkScrollableFrame, map: list, button_num: int
+) -> list:
+    global source_label_dict_live
+
+    source_path = ctk.filedialog.askopenfilename(
+        title="select an source image",
+        initialdir=RECENT_DIRECTORY_SOURCE,
+        filetypes=[img_ft],
+    )
+
+    if "source" in map[button_num]:
+        map[button_num].pop("source")
+        if button_num in source_label_dict_live:
+            source_label_dict_live[button_num].destroy()
+            del source_label_dict_live[button_num]
+
+    if source_path == "":
+        return map
+    else:
+        cv2_img = cv2.imread(source_path)
+        face = get_one_face(cv2_img)
+
+        if face:
+            x_min, y_min, x_max, y_max = face["bbox"]
+
+            map[button_num]["source"] = {
+                "cv2": cv2_img[int(y_min) : int(y_max), int(x_min) : int(x_max)],
+                "face": face,
+            }
+
+            image = Image.fromarray(
+                cv2.cvtColor(map[button_num]["source"]["cv2"], cv2.COLOR_BGR2RGB)
+            )
+            image = image.resize(
+                (MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS
+            )
+            tk_image = ctk.CTkImage(image, size=image.size)
+
+            # Find the source image label in the row frame
+            row_frame = scrollable_frame.winfo_children()[button_num]
+            source_image_label = row_frame.winfo_children()[1]
+
+            source_image_label.configure(image=tk_image)
+            source_label_dict_live[button_num] = source_image_label
+        else:
+            update_pop_live_status("Face could not be detected in last upload!")
+        return map
+
+
+def update_webcam_target(
+    scrollable_frame: ctk.CTkScrollableFrame,
+    map: list,
+    button_num: int,
+    target_path: str = None,
+) -> list:
+    global target_label_dict_live
+
+    if target_path is None:
+        target_path = ctk.filedialog.askopenfilename(
+            title="select an target image",
+            initialdir=RECENT_DIRECTORY_SOURCE,
+            filetypes=[img_ft],
+        )
+
+    if "target" in map[button_num]:
+        map[button_num].pop("target")
+        if button_num in target_label_dict_live:
+            target_label_dict_live[button_num].destroy()
+            del target_label_dict_live[button_num]
+
+    if target_path == "":
+        return map
+    else:
+        cv2_img = cv2.imread(target_path)
+        face = get_one_face(cv2_img)
+
+        if face:
+            x_min, y_min, x_max, y_max = face["bbox"]
+
+            map[button_num]["target"] = {
+                "cv2": cv2_img[int(y_min) : int(y_max), int(x_min) : int(x_max)],
+                "face": face,
+            }
+
+            image = Image.fromarray(
+                cv2.cvtColor(map[button_num]["target"]["cv2"], cv2.COLOR_BGR2RGB)
+            )
+            image = image.resize(
+                (MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS
+            )
+            tk_image = ctk.CTkImage(image, size=image.size)
+
+            # Find the target image label in the row frame
+            row_frame = scrollable_frame.winfo_children()[button_num]
+            target_image_label = row_frame.winfo_children()[4]
+
+            target_image_label.configure(image=tk_image)
+            target_label_dict_live[button_num] = target_image_label
+        else:
+            update_pop_live_status("Face could not be detected in last upload!")
+        return map

modules/utilities.py

@@ -0,0 +1,141 @@
+import glob
+import mimetypes
+import os
+import platform
+import shutil
+import ssl
+import subprocess
+import urllib
+from pathlib import Path
+from typing import List, Any
+from tqdm import tqdm
+
+import modules.globals
+
+TEMP_FILE = 'temp.mp4'
+TEMP_DIRECTORY = 'temp'
+
+# 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 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]
+    output = subprocess.check_output(command).decode().strip().split('/')
+    try:
+        numerator, denominator = map(int, output)
+        return numerator / denominator
+    except Exception:
+        pass
+    return 30.0
+
+
+def extract_frames(target_path: str) -> None:
+    temp_directory_path = get_temp_directory_path(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])
+
+
+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])
+    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')))
+
+
+def get_temp_directory_path(target_path: str) -> str:
+    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 os.path.join(temp_directory_path, TEMP_FILE)
+
+
+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 = 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 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 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 bool(mimetype and mimetype.startswith('video/'))
+    return False
+
+
+def conditional_download(download_directory_path: str, urls: List[str]) -> None:
+    if not os.path.exists(download_directory_path):
+        os.makedirs(download_directory_path)
+    for url in urls:
+        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 os.path.abspath(os.path.join(os.path.dirname(__file__), path))

mypi.ini

@@ -0,0 +1,7 @@
+[mypy]
+check_untyped_defs = True
+disallow_any_generics = True
+disallow_untyped_calls = True
+disallow_untyped_defs = True
+ignore_missing_imports = True
+strict_optional = False

requirements.txt

@@ -1,2 +1,22 @@
-fastapi
-uvicorn[standard]
+--extra-index-url https://download.pytorch.org/whl/cu118
+
+numpy>=1.23.5,<2
+opencv-python==4.8.1.78
+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
+torchvision==0.15.2+cu118; sys_platform != 'darwin'
+torchvision==0.15.2; sys_platform == 'darwin'
+onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64'
+onnxruntime-gpu==1.16.3; 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
+tkinterdnd2==0.4.2
+customtkinter==5.2.2

run-cuda.bat

@@ -0,0 +1 @@
+python run.py --execution-provider cuda --execution-threads 60 --max-memory 60

run-laptop-gpu.bat

@@ -0,0 +1 @@
+python run.py --execution-provider dml

run.py

@@ -0,0 +1,6 @@
+#!/usr/bin/env python3
+
+from modules import core
+
+if __name__ == '__main__':
+    core.run()

run_with_chocolatey.bat

@@ -0,0 +1,13 @@
+@echo off
+	:: Installing Microsoft Visual C++ Runtime - all versions 1.0.1 if it's not already installed
+	choco install vcredist-all
+	:: Installing CUDA if it's not already installed
+	choco install cuda
+	:: Inatalling ffmpeg if it's not already installed
+	choco install ffmpeg
+	:: Installing Python if it's not already installed
+	choco install python -y
+	:: Assuming successful installation, we ensure pip is upgraded
+	python -m ensurepip --upgrade
+	:: Use pip to install the packages listed in 'requirements.txt'
+	pip install -r requirements.txt

setup_deep_live_cam.bat

@@ -0,0 +1,122 @@
+@echo off
+setlocal EnableDelayedExpansion
+
+:: 1. Setup your platform
+echo Setting up your platform...
+
+:: 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
+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...
+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
+
+echo Installing required Python packages...
+pip install --upgrade pip
+pip install -r requirements.txt
+
+echo Setup complete. You can now run the application.
+
+:: GPU Acceleration Options
+echo.
+echo Choose the GPU Acceleration Option if applicable:
+echo 1. CUDA (Nvidia)
+echo 2. CoreML (Apple Silicon)
+echo 3. CoreML (Apple Legacy)
+echo 4. DirectML (Windows)
+echo 5. OpenVINO (Intel)
+echo 6. None
+set /p choice="Enter your choice (1-6): "
+
+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%
+) else (
+    echo Running the application...
+    python run.py
+)
+
+pause