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.

Quick Start (Windows / Nvidia)

Download latest pre-built version with CUDA support - No Manual Installation/Downloading required.

Installation (Manual)

Please be aware that the installation needs technical skills and is NOT for beginners, consider downloading the prebuilt. Please do NOT open platform and installation related issues on GitHub before discussing it on the discord server.

Basic Installation (CPU)

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
Visual Studio 2022 Runtimes (Windows)

2. Clone Repository

3. Download Models

GFPGANv1.4
inswapper_128_fp16.onnx (Note: Use this replacement version if you encounter issues)

Place these files in the "models" folder.

4. Install Dependencies

We highly recommend using a venv to avoid issues.

For macOS: Install or upgrade the python-tk package:

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)

Click to see the details

CUDA Execution Provider (Nvidia)

Install CUDA Toolkit 11.8
Install dependencies:

Usage:

CoreML Execution Provider (Apple Silicon)

Install dependencies:

Usage:

CoreML Execution Provider (Apple Legacy)

Install dependencies:

Usage:

DirectML Execution Provider (Windows)

Install dependencies:

Usage:

OpenVINO™ Execution Provider (Intel)

Install dependencies:

Usage:

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.

Features

Resizable Preview Window

Dynamically improve performance using the --live-resizable parameter.

Face Mapping

Track and change faces on the fly.

Source Video:

Enable Face Mapping:

Map the Faces:

See the Magic!

Command Line Arguments

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

Webcam Mode on WSL2 Ubuntu (Optional)

Click to see the details

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

Install the USB/IP tool for Windows:
https://learn.microsoft.com/en-us/windows/wsl/connect-usb
In Windows PowerShell (as Administrator), connect your webcam to WSL:

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:

Start with this guide: https://github.com/PINTO0309/wsl2_linux_kernel_usbcam_enable_conf
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

Additional info: https://askubuntu.com/questions/1413377/camera-not-working-in-cheese-in-wsl2

After rebuilding, restart WSL with the new kernel.

4. Set Up Deep-Live-Cam Project
Within Ubuntu:

Clone the repository:

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

Check if USB and webcam modules are built into the kernel:

If modules are loadable (m), not built-in (y), check if the file exists:

Load the module and check for errors (optional if built-in):

Verify video devices:

6. Set Up Permissions

Add user to video group and set permissions:

Create a udev rule for permanent permissions:

Add this content:

Reload udev rules:

Log out and log back into your WSL session.
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:

Follow these steps:

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
select: Linux, x86_64, WSL-Ubuntu, 2.0, deb (local)
Check CUDA version:

If the wrong version is installed, remove it completely:
https://askubuntu.com/questions/530043/removing-nvidia-cuda-toolkit-and-installing-new-one
Install CUDA Toolkit 11.8 again https://developer.nvidia.com/cuda-11-8-0-download-archive, select: Linux, x86_64, WSL-Ubuntu, 2.0, deb (local)

Future Updates & Roadmap

For the latest experimental builds and features, see the experimental branch.

TODO:

Develop a version for web app/service
Speed up model loading
Speed up real-time face swapping
Support multiple faces
UI/UX enhancements for desktop app

This is an open-source project developed in our free time. Updates may be delayed.

Credits

ffmpeg: for making video related operations easy
deepinsight: for their 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.
havok2-htwo : for sharing the code for webcam
GosuDRM : for open version of roop
pereiraroland26 : Multiple faces support
vic4key : For supporting/contributing on this project
KRSHH : For updating the UI
and all developers behind libraries used in this project.
Foot Note: This is originally roop-cam, see the full history of the code here. Please be informed that the base author of the code is s0md3v