HeyGenClone

Welcome to the HeyGenClone, an open-source analogue of the HeyGen system.

I am a developer from Moscow 🇷🇺 who devotes his free time to studying new technologies. The project is in an active development phase, but I hope it will help you achieve your goals!

Currently, translation support is enabled only from English 🇬🇧!

Installation 🥸

• Clone this repo
• Install conda
• Create environment with Python 3.10 (for macOS refer to link)
• Activate environment
• Install requirements:

  cd path_to_project
  sh install.sh
  

• In config.json file change HF_TOKEN argument. It is your HuggingFace token. Visit speaker-diarization, segmentation and accept user conditions
• Download weights from drive, unzip downloaded file into weights folder
• Install ffmpeg

Configurations (config.json) 🧙‍♂️

Supported languages 🙂

English (en), Spanish (es), French (fr), German (de), Italian (it), Portuguese (pt), Polish (pl), Turkish (tr), Russian (ru), Dutch (nl), Czech (cs), Arabic (ar), Chinese (zh-cn), Japanese (ja), Hungarian (hu) and Korean (ko)

Usage 🤩

• Activate your environment:

  conda activate your_env_name

• Сd to project path:

  cd path_to_project

At the root of the project there is a translate script that translates the video you set.

• video_filename - the filename of your input video (.mp4)
• output_language - the language to be translated into. Provided here (you can also find it in my code)
• output_filename - the filename of output video (.mp4)

python translate.py video_filename output_language -o output_filename

I also added a script to overlay the voice on the video with lip sync, which allows you to create a video with a person pronouncing your speech. Сurrently it works for videos with one person.

• voice_filename - the filename of your speech (.wav)
• video_filename - the filename of your input video (.mp4)
• output_filename - the filename of output video (.mp4)

python speech_changer.py voice_filename video_filename -o output_filename

How it works 😱

1. Detecting scenes (PySceneDetect)
2. Face detection (yolov8-face)
3. Reidentification (deepface)
4. Speech enhancement (MDXNet)
5. Speakers transcriptions and diarization (whisperX)
6. Text translation (googletrans)
7. Voice cloning (TTS)
8. Lip sync (lipsync)
9. Face restoration (GFPGAN)
10. [Need to fix] Search for talking faces, determining what this person is saying

Translation results 🥺

Note that this example was created without GFPGAN usage!

Destination language	Source video	Output video
🇷🇺 (Russian)

Contributors 🫵🏻

To-Do List 🤷🏼‍♂️

• Fully GPU support
• Multithreading support (optimizations)
• Detecting talking faces (improvement)

Other 🤘🏻

• Tested on macOS
• ⚠️ The project is under development!