DeepFace® is a Neural network system designed to swap multiple faces in videos with impressive accuracy. In short, DeepFace® deepfake tool that allows users to create high-quality face swaps using deep learning techniques.
It offers a user-friendly interface and supports various deep learning models.
Take a video and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training.
Clone Repository
git clone https://github.com/skytells-research/deepfaceInstall dependencies We highly recommend to work with a venv or conda to avoid issues.
pip install -r requirements.txtYou should be able to run deepface 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.
Keep in mind that the installation needs technical skills and is not for beginners.
Basic - It is more likely to work on your computer, but will be quite slow
Acceleration - Unleash the full potential of your CPU and GPU
Start the program with arguments:
python run.py Done.
For advanced usage:
python run.py [options]
-h, --help show this help message and exit
-s SOURCE_PATH, --source SOURCE_PATH select an source image
-t TARGET_PATH, --target TARGET_PATH select an target image or video
-o OUTPUT_PATH, --output OUTPUT_PATH select output file or directory
--frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...] frame processors (choices: face_swapper, face_enhancer, ...)
--keep-fps keep target fps
--keep-frames keep temporary frames
--skip-audio skip target audio
--many-faces process every face
--reference-face-position REFERENCE_FACE_POSITION position of the reference face
--reference-frame-number REFERENCE_FRAME_NUMBER number of the reference frame
--similar-face-distance SIMILAR_FACE_DISTANCE face distance used for recognition
--temp-frame-format {jpg,png} image format used for frame extraction
--temp-frame-quality [0-100] image quality used for frame extraction
--output-video-encoder {libx264,libx265,libvpx-vp9,h264_nvenc,hevc_nvenc} encoder used for the output video
--output-video-quality [0-100] quality used for the output video
--max-memory MAX_MEMORY maximum amount of RAM in GB
--execution-provider {cpu} [{cpu} ...] available execution provider (choices: cpu, ...)
--execution-threads EXECUTION_THREADS number of execution threads
-v, --version show program's version number and exit
Headless
Using the -s/--source, -t/--target and -o/--output argument will run the program in headless mode.
This software is designed to contribute positively to the AI-generated media industry, assisting artists with tasks like character animation and models for clothing, We are aware of the potential ethical issues and have implemented measures to prevent the software from being used for inappropriate content, such as nudity.
- Users are expected to follow local laws and use the software responsibly.
- If using real faces, get consent and clearly label deepfakes when sharing.
- The developers aren't liable for user actions.
Our software uses a lot of third party libraries as well pre-trained models. The users should keep in mind that these third party components have their own license and terms, therefore our license is not being applied.
- deepinsight for their insightface project which provided a well-made library and models.