Deep Live Cam is a project for creating real-time face swaps and one-click video deepfakes using a single image. This tutorial will guide you through the installation and basic usage.
Prerequisites
- Python (3.10 recommended)
- pip
- git
- FFmpeg
- Visual Studio 2022 runtimes (for Windows users)
Installation
Step 1: Clone the Repository
- Open a terminal or command prompt.
- Run the following command:
git clone https://github.com/hacksider/Deep-Live-Cam.git - Navigate to the cloned directory:
cd Deep-Live-Cam
Step 2: Download Required Models
- Visit the project's Hugging Face page.
- Download the following models:
- GFPGANv1.4
- inswapper_128_fp16.onnx
- Place these files in the
modelsfolder of the cloned repository.
Step 3: Install Dependencies
- Install the required packages:
pip install -r requirements.txt
Step 4: GPU Acceleration Setup (Optional)
For NVIDIA GPUs:
- Install CUDA Toolkit 11.8
- Install additional dependencies:
pip uninstall onnxruntime onnxruntime-gpu pip install onnxruntime-gpu==1.16.3
For Apple Silicon:
- Install CoreML dependencies:
pip uninstall onnxruntime onnxruntime-silicon pip install onnxruntime-silicon==1.13.1
For Windows DirectML:
- Install DirectML dependencies:
pip uninstall onnxruntime onnxruntime-directml pip install onnxruntime-directml==1.15.1
For Intel OpenVINO:
- Install OpenVINO dependencies:
pip uninstall onnxruntime onnxruntime-openvino pip install onnxruntime-openvino==1.15.0
Usage
Basic Usage
Run the application with:
python run.py
GPU-Accelerated Usage
For NVIDIA GPUs:
python run.py --execution-provider cuda
For Apple Silicon:
python run.py --execution-provider coreml
For Windows DirectML:
python run.py --execution-provider directml
For Intel OpenVINO:
python run.py --execution-provider openvino
Interface
- Select a face image using the "Choose Face" button.
- For live webcam mode:
- Click "Live" to use your webcam feed.
- For video processing:
- Select a target video using the "Choose Target" button.
- Click "Start" to begin processing.
Additional Options
- Face Enhancer: Improves output quality (may slow down processing)
- Many Faces: Processes every face in the frame
- Keep FPS: Maintains original video frame rate
- Keep Audio: Preserves original audio
Command Line Arguments
For advanced usage, you can use the following command line arguments:
-
-s,--source: Select source image -
-t,--target: Select target image or video -
-o,--output: Specify output file or directory -
--frame-processor: Choose frame processors -
--keep-fps: Keep original FPS -
--keep-audio: Keep original audio -
--many-faces: Process every face -
--video-encoder: Adjust output video encoder -
--video-quality: Adjust output video quality -
--max-memory: Set maximum RAM usage -
--execution-threads: Set number of execution threads
Notes
- Processing speed depends on your hardware. GPU acceleration significantly improves performance.
- For live webcam mode, ensure your webcam is properly connected and recognized by your system.
- Always use this software responsibly and ethically. ## Common Installation Errors and Fixes {#troubleshooting}
Most failed installs come down to one of six things.
ModuleNotFoundError: No module named 'tkinter' — the GUI depends on Tk, which is not
bundled with every Python build. On Debian or Ubuntu install python3-tk. On macOS,
install Python from python.org rather than a bare Homebrew build, or add python-tk.
Both onnxruntime and onnxruntime-gpu installed — when both packages share an
environment the app silently falls back to CPU and you get a few frames per second with no
error message. Uninstall both, then reinstall only the one matching your hardware, exactly
as listed in Step 4.
Models not found at launch — GFPGANv1.4.pth and inswapper_128_fp16.onnx must sit
directly inside the models/ folder at the repository root. A nested folder will not be
picked up.
ffmpeg not found — video export fails without FFmpeg on your PATH, sometimes without
a clear message. Confirm with ffmpeg -version before you process any video.
CUDA version mismatch — the onnxruntime-gpu build has to match your installed CUDA
toolkit. If the app starts but ignores --execution-provider cuda, this is almost always
why. Either install the onnxruntime build matching your CUDA version, or install CUDA 11.8
to match the pinned version above.
Out of memory on longer videos — cap usage with --max-memory and reduce
--execution-threads. Splitting a long video into segments and rejoining them afterwards
is more reliable than forcing a single pass.
What Performance to Expect
Live webcam mode is far more demanding than processing a file, because every frame has to
be detected, swapped and enhanced inside one frame interval. A discrete NVIDIA GPU with
CUDA is the only configuration that holds a comfortable live frame rate; Apple Silicon via
CoreML is usable but slower; CPU-only is fine for processing a video file in the background
and not much else.
Two settings dominate speed. Face Enhancer noticeably improves output quality and
noticeably reduces frame rate — leave it off while you frame your shot, then enable it for
the final render. Many Faces multiplies work by the number of faces detected, so leave
it off unless you actually need every face in frame swapped.
Legal and Ethical Use
Face-swap tools sit in a genuinely regulated area, and the rules tightened considerably
through 2025 and 2026. Several jurisdictions now treat non-consensual synthetic imagery of
a real person as a criminal matter, and platform policies are stricter than the law in most
cases.
The practical rule: obtain explicit consent from anyone whose likeness you use, disclose
synthetic media when you publish it, and never use it to impersonate someone for
verification, financial or reputational purposes. Check the rules where you live before you
publish — this guide covers how the software works, not whether your intended use is lawful.
FAQ
Does Deep Live Cam work without a GPU?
Yes, but slowly. CPU-only execution is workable for processing a saved video file and
impractical for live webcam use.
Can I use it as a webcam in Zoom, OBS or Meet?
Not directly. Deep Live Cam renders to its own preview window. To feed another application
you need a virtual camera — capture the preview window in OBS and route it through OBS
Virtual Camera, then select that device inside your conferencing app.
Why does the swapped face look blurry or low-detail?
The base swap model works at a low internal resolution, which is what the Face Enhancer
option exists to correct. Enable it for final output. A higher-resolution, well-lit,
front-facing source image also makes a large difference.
Does one source image really need to be enough?
Yes — the model is designed around a single reference image. Quality depends far more on
that image being sharp, evenly lit and close to front-facing than on providing more images.
Which execution provider should I choose?
cuda for NVIDIA, coreml for Apple Silicon, directml for AMD or Intel GPUs on Windows,
and openvino for Intel hardware. Each requires its matching onnxruntime package.
Last reviewed and updated: July 2026.
Top comments (1)
Please what’s the minimum requirement for gpu i have nvidia rtx 3070
Am i good to go?