Installation

This is more likely to work on your computer but will be slower as it utilizes the CPU.

undefined1. Setup Your Platformundefined

• Python (3.10 recommended)
• pip
• git
• ffmpeg
• Visual Studio 2022 Runtimes (Windows)

undefined2. Clone Repositoryundefined

https://github.com/hacksider/Deep-Live-Cam.git

undefined3. Download Modelsundefined

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

Place these files in the “models” folder.

undefined4. Install Dependenciesundefined

We highly recommend using a venv to avoid issues.

pip install -r requirements.txt

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

brew install python-tk@3.10

undefinedRun: 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

undefinedCUDA Execution Provider (Nvidia)undefined

1. Install CUDA Toolkit 11.8
2. Install dependencies:

pip uninstall onnxruntime onnxruntime-gpu
pip install onnxruntime-gpu==1.16.3

3. Usage:

python run.py --execution-provider cuda

undefinedCoreML Execution Provider (Apple Silicon)undefined

1. Install dependencies:

pip uninstall onnxruntime onnxruntime-silicon
pip install onnxruntime-silicon==1.13.1

2. Usage:

python run.py --execution-provider coreml

undefinedCoreML Execution Provider (Apple Legacy)undefined

1. Install dependencies:

pip uninstall onnxruntime onnxruntime-coreml
pip install onnxruntime-coreml==1.13.1

2. Usage:

python run.py --execution-provider coreml

undefinedDirectML Execution Provider (Windows)undefined

1. Install dependencies:

pip uninstall onnxruntime onnxruntime-directml
pip install onnxruntime-directml==1.15.1

2. Usage:

python run.py --execution-provider directml

undefinedOpenVINO™ Execution Provider (Intel)undefined

1. Install dependencies:

pip uninstall onnxruntime onnxruntime-openvino
pip install onnxruntime-openvino==1.15.0

2. Usage:

python run.py --execution-provider openvino

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.

undefined1. Install WSL2 Ubuntuundefined

Install WSL2 Ubuntu from the Microsoft Store or using PowerShell:

undefined2. Enable USB Support in WSL2undefined

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:

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.

undefined3. Rebuild WSL2 Ubuntu Kernel with USB and Webcam Modulesundefined

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](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

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

undefined4. Set Up Deep-Live-Cam Projectundefined
Within Ubuntu:

1. Clone the repository:

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.

undefined5. Verify and Load Kernel Modulesundefined

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

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:

ls /lib/modules/$(uname -r)/kernel/drivers/media/usb/uvc/  

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

sudo modprobe uvcvideo  
dmesg | tail  

4. Verify video devices:

sudo ls -al /dev/video*  

undefined6. Set Up Permissionsundefined

1. Add user to video group and set permissions:

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:

sudo nano /etc/udev/rules.d/81-webcam.rules  

Add this content:

KERNEL=="video[0-9]*", GROUP="video", MODE="0660"  

3. Reload udev rules:

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.

undefinedFinal Notesundefined

• 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.

undefinedTroubleshooting CUDA Issuesundefined

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

/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

4. 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)

sudo apt-get -y install cuda-toolkit-11-8