视频实时换脸

 

demo-gif

Disclaimer

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

The developers of this software are aware of its possible unethical applications and are committed to take preventative measures against them. It has a built-in check which prevents the program from working on inappropriate media including but not limited to nudity, graphic content, sensitive material such as war footage etc. We will continue to develop this project in the positive direction while adhering to law and ethics. This project may be shut down or include watermarks on the output if requested by law.

Users of this software are expected to use this software responsibly while abiding by local laws. If the face of a real person is being used, users are required to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers of this software will not be responsible for actions of end-users.

New Features

Resizable Preview Window

Dynamically improve the performance by using the --resizable parameter resizable-gif

Face Mapping

Track faces and change it on the fly

face_mapping_source

source video

face-mapping

Tick this switch

face-mapping2

Map the faces

face_mapping_result

And see the magic!

Want to skip the installation and just run it?

Here's the link without the tedious installation script below

Windows / Nvidia CUDA still required

How do I install it?

Basic: It is more likely to work on your computer but it will also be very slow. You can follow instructions for the basic install (This usually runs via CPU)

1.Setup your platform

2. Clone Repository

3. Download Models

  1. GFPGANv1.4

  2. inswapper_128_fp16.onnx (Note: Use this replacement version if an issue occurs on your computer)

Then put those 2 files on the "models" folder

4. Install dependency

We highly recommend to work with a venv to avoid issues.

For MAC OS, You have to install or upgrade python-tk package:

DONE!!! If you don't have any GPU, You should be able to run Deep-Live-Cam using python run.py command. Keep in mind that while running the program for first time, it will download some models which can take time depending on your network connection.

5. Proceed if you want to use GPU acceleration (optional)

Click to see the details

CUDA Execution Provider (Nvidia)*

  1. Install CUDA Toolkit 11.8

  2. Install dependencies:

  1. Usage in case the provider is available:

CoreML Execution Provider (Apple Silicon)

  1. Install dependencies:

  1. Usage in case the provider is available:

CoreML Execution Provider (Apple Legacy)

  1. Install dependencies:

  1. Usage in case the provider is available:

DirectML Execution Provider (Windows)

  1. Install dependencies:

  1. Usage in case the provider is available:

OpenVINO™ Execution Provider (Intel)

  1. Install dependencies:

  1. Usage in case the provider is available:

How do I use it?

Note: When you run this program for the first time, it will download some models ~300MB in size.

Executing python run.py command will launch this window: gui-demo

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

For the webcam mode

Just follow the clicks on the screenshot

  1. Select a face

  2. Click live

  3. Wait for a few seconds (it takes a longer time, usually 10 to 30 seconds before the preview shows up)

demo-gif

Just use your favorite screencapture to stream like OBS

Note: In case you want to change your face, just select another picture, the preview mode will then restart (so just wait a bit).

Additional command line arguments are given below. To learn out what they do, check this guide.

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

Webcam mode on Windows 11 using 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

  1. Install the USB/IP tool for Windows:
    https://learn.microsoft.com/en-us/windows/wsl/connect-usb

  2. 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:

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

  2. When you reach the sudo wget [github.com](./real_face_exchange/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

  1. After rebuilding, restart WSL with the new kernel.

4. Set Up Deep-Live-Cam Project

Within Ubuntu:

  1. Clone the repository:

  1. 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:

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

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

  1. Verify video devices:

6. Set Up Permissions

  1. Add user to video group and set permissions:

  1. Create a udev rule for permanent permissions:

Add this content:

  1. Reload udev rules:

  1. Log out and log back into your WSL session.

  2. 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:

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

  2. Check CUDA version:

  1. If the wrong version is installed, remove it completely:
    https://askubuntu.com/questions/530043/removing-nvidia-cuda-toolkit-and-installing-new-one

  2. 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)

Want the Next Update Now?

If you want the latest and greatest build, or want to see some new great features, go to our experimental branch and experience what the contributors have given.

TODO

✔️ Support multiple faces feature

Note: This is an open-source project, and we’re working on it in our free time. Therefore, features, replies, bug fixes, etc., might be delayed. We hope you understand. Thanks.

Credits