

Metahuman Stream
Overview :
metahuman-stream is an open-source project for real-time interactive digital human models, facilitating synchronized audio and video dialogues between the digital persona and users. This project supports various digital human models, including ernerf, musetalk, and wav2lip, and features capabilities like voice cloning, interruption during speech, and full-body video stitching, showcasing significant commercial application potential.
Target Users :
This product is suitable for developers and businesses that need to create highly interactive and personalized digital personas for scenarios such as virtual customer service, online education, and entertainment interactions.
Use Cases
Used in online education platforms to provide a virtual teacher persona for interactive teaching.
Serves as a virtual customer service representative, offering 24/7 customer consultation.
Utilized in entertainment live streaming to enhance interactivity and engagement.
Features
Supports various digital human models such as ernerf, musetalk, and wav2lip.
Enables voice cloning for personalized voice customization.
Allows speech interruption for enhanced interactivity.
Supports full-body video stitching for a richer visual experience.
Compatible with RTMP and WebRTC streaming protocols.
Provides video orchestration, such as playing custom videos when the digital human is not speaking.
How to Use
1. Install required libraries, including Python and Pytorch.
2. Select and download the appropriate digital human model based on your needs.
3. Configure project files to set model paths, transmission protocols, and other parameters.
4. Launch the digital human service, either through the command line or a Docker container.
5. Access the relevant API interfaces using a browser to interact with the digital human.
6. Optimize the performance of the digital human based on feedback, including voice, expressions, and actions.
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