Setting Up FaceFusion on Ubuntu 24.04: Your Guide to AI-Powered Face Swapping and Deepfakes

FaceFusion is a powerful tool for facial recognition and analysis, often used for AI face swap applications, digital face replacement, and deepfake projects. Here’s how to install it on Ubuntu, ensuring you utilize the best tools and libraries. FaceFusion can be used with just a CPU and does not require a GPU to operate.

Prerequisites

• Ubuntu 18.04 or later
• Python 3.6 or later
• Optional : NVIDIA GPU with CUDA support (for GPU acceleration)
• At least 8GB of RAM

Step 1: Update and Upgrade Your System

sudo apt update
sudo apt upgrade -y

Step 2: Install Essential Packages

sudo apt install -y build-essential cmake git-all curl python3 python3-pip python3-venv libopenblas-dev liblapack-dev libjpeg-dev libpng-dev ffmpeg mesa-va-drivers

Step 3: Install Miniconda

Download and install either Miniconda or Anaconda to manage your Python environment. The article below provides detailed instructions on installing Miniconda.

Step 4: Create and Activate Conda Environment

Create a dedicated Conda environment for FaceFusion to manage dependencies cleanly.

conda create --name facefusion python=3.10
conda activate facefusion

Step 5: Install CUDA and cuDNN (Optional for GPU Acceleration)

For GPU acceleration, which significantly enhances performance in AI face swap and deepfake tasks:

Install CUDA Toolkit and cuDNN using Conda:

conda install conda-forge::cuda-toolkit=12.4.1 cudnn=8.9.2.26 conda-forge::gputil=1.4.0

Step 6: Install OpenVINO (Optional for Intel Hardware Acceleration)

For those using Intel hardware, OpenVINO offers great optimization for AI workloads.

conda install conda-forge::openvino=2023.1.0

Step 7: Clone FaceFusion Repository

FaceFusion’s source code is available on GitHub. Clone the repository to get started.

git clone https://github.com/facefusion/facefusion
cd facefusion

Step 8: Install FaceFusion

Run the installation script to set up FaceFusion.

python install.py --onnxruntime "default"

Step 9: Reload Conda Environment

conda deactivate

conda activate facefusion

Step 10: Run FaceFusion

Start FaceFusion to begin working with facial recognition and analysis.

python facefusion.py run --open-browser

Step 11: Verify Installation

Ensure that FaceFusion is installed correctly by checking its version.

import facefusion
print(facefusion.__version__)

Additional Configuration

Refer to the FaceFusion documentation for detailed environment and accelerator setup, especially if you’re working with tools like Google Colab for remote processing or implementing NSFW filters.

Troubleshooting

Consult the Linux Installation Guide and Environment Setup Guide. For GPU-related issues, refer to the Accelerator Configuration Guide.

For comprehensive instructions and troubleshooting, visit the official FaceFusion Documentation.

Related Tools and Technologies

FaceFusion is often compared with tools like DeepFaceLab, Reface AI, and Wav2Lip. Platforms like Vidnoz and Akool also provide similar AI face swap and deepfake functionalities. Python scripting, combined with libraries such as NumPy and the Open Neural Network Exchange (ONNX), forms the backbone of these applications. Using Google Colab can also help in leveraging powerful GPUs for free, making it easier to handle computationally intensive tasks like video face swap and stable diffusion modeling. FaceFusion with tools like Stable Diffusion can create innovative face swap and deepfake projects.

Embrace the future of AI-driven facial recognition and deepfake technology with FaceFusion and its comprehensive installation process on Ubuntu.