Heygem - Open Source Alternative to Heygen 【切换中文】
Dear Heygem Open Source Community Members:
We sincerely thank you for your enthusiastic attention and active participation in the Heygem digital human open source project! We have noticed that some developers face challenges during local deployment. To better meet the needs of different scenarios, we are now announcing two parallel service solutions:
| Project | HeyGem Open Source Local Deployment | Digital Human/Clone Voice API Service |
|---|---|---|
| Usage | Open Source Local Deployment | Rapid Clone API Service |
| Recommended | Technical Users | Business Users |
| Technical Threshold | Developers with deep learning framework experience/pursuing deep customization/wishing to participate in community co-construction | Quick business integration/focus on upper-level application development/need enterprise-level SLA assurance for commercial scenarios |
| Hardware Requirements | Need to purchase GPU server | No need to purchase GPU server |
| Customization | Can modify and extend the code according to your needs, fully controlling the software's functions and behavior | Cannot directly modify the source code, can only extend functions through API-provided interfaces, less flexible than open source projects |
| Technical Support | Community Support | Dynamic expansion support + professional technical response team |
| Maintenance Cost | High maintenance cost | Simple maintenance |
| Lip Sync Effect | Usable effect | Stunning and higher definition effect |
| Commercial Authorization | Commercial use in Mainland China, Hong Kong, and Macau requires prior application, while other countries are unrestricted. | Commercial use allowed |
| Iteration Speed | Slow updates, bug fixes depend on the community | Latest models/algorithms are prioritized, fast problem resolution |
We always adhere to the open source spirit, and the launch of the API service aims to provide a more complete solution matrix for developers with different needs. No matter which method you choose, you can always obtain technical support documents through end_sub@hotmail.com. We look forward to working with you to promote the inclusive development of digital human technology!
Silicon-based Intelligent Developer Team
Rapid Clone API | API Documentation Center
Real-time Interaction SDK | SDK Documentation Center
Heygem is a fully offline video synthesis tool designed for Windows systems that can precisely clone your appearance and voice, digitalizing your image. You can create videos by driving virtual avatars through text and voice. No internet connection is required, protecting your privacy while enjoying convenient and efficient digital experiences.
- Core Features
- Precise Appearance and Voice Cloning: Using advanced AI algorithms to capture human facial features with high precision, including facial features, contours, etc., to build realistic virtual models. It can also precisely clone voices, capturing and reproducing subtle characteristics of human voices, supporting various voice parameter settings to create highly similar cloning effects.
- Text and Voice-Driven Virtual Avatars: Understanding text content through natural language processing technology, converting text into natural and fluent speech to drive virtual avatars. Voice input can also be used directly, allowing virtual avatars to perform corresponding actions and facial expressions based on the rhythm and intonation of the voice, making the virtual avatar's performance more natural and vivid.
- Efficient Video Synthesis: Highly synchronizing digital human video images with sound, achieving natural and smooth lip-syncing, intelligently optimizing audio-video synchronization effects.
- Multi-language Support: Scripts support eight languages - English, Japanese, Korean, Chinese, French, German, Arabic, and Spanish.
- Key Advantages
- Fully Offline Operation: No internet connection required, effectively protecting user privacy, allowing users to create in a secure, independent environment, avoiding potential data leaks during network transmission.
- User-Friendly: Clean and intuitive interface, easy to use even for beginners with no technical background, quickly mastering the software's usage to start their digital human creation journey.
- Multiple Model Support: Supports importing multiple models and managing them through one-click startup packages, making it convenient for users to choose suitable models based on different creative needs and application scenarios.
- Technical Support
- Voice Cloning Technology: Using advanced technologies like artificial intelligence to generate similar or identical voices based on given voice samples, covering context, intonation, speed, and other aspects of speech.
- Automatic Speech Recognition: Technology that converts human speech vocabulary content into computer-readable input (text format), enabling computers to "understand" human speech.
- Computer Vision Technology: Used in video synthesis for visual processing, including facial recognition and lip movement analysis, ensuring virtual avatar lip movements match voice and text content.
- Nodejs 18
- Docker Images
- docker pull guiji2025/fun-asr
- docker pull guiji2025/fish-speech-ziming
- docker pull guiji2025/heygem.ai
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Must have D Drive: Mainly used for storing digital human and project data
- Free space requirement: More than 30GB
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C Drive: Used for storing service image files
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Free space requirement: More than 100GB
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If less than 100GB is available, after installing Docker, you can choose a different disk folder with more than 100GB of remaining space at the location shown below.
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System Requirements:
- Currently supports Windows 10 19042.1526 or higher
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Recommended Configuration:
- CPU: 13th Gen Intel Core i5-13400F
- Memory: 32GB
- Graphics Card: RTX 4070
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Ensure you have an NVIDIA graphics card with properly installed drivers
NVIDIA driver download link: https://www.nvidia.cn/drivers/lookup/
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Use the command
wsl --list --verboseto check if WSL is installed. If it shows as below, it's already installed and no further installation is needed.
- WSL installation command:
wsl --install- May fail due to network issues, try multiple times
- During installation, you'll need to set and remember a new username and password
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Update WSL using
wsl --update. -
Download Docker for Windows, choose the appropriate installation package based on your CPU architecture.
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When you see this interface, installation is successful.
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Run Docker
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Accept the agreement and skip login on first run
Installation using Docker, docker-compose as follows:
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The
docker-compose.ymlfile is in the/deploydirectory. -
Execute
docker-compose up -din the/deploydirectory -
Wait patiently (about half an hour, speed depends on network), download will consume about 70GB of traffic, make sure to use WiFi
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When you see three services in Docker, it indicates success
- Directly download the officially built installation package
- Double-click
HeyGem-x.x.x-setup.exeto install
We have opened APIs for model training and video synthesis. After Docker starts, several ports will be exposed locally, accessible through http://127.0.0.1.
For specific code, refer to:
- src/main/service/model.js
- src/main/service/video.js
- src/main/service/voice.js
- Separate video into silent video + audio
- Place audio in
D:\heygem_data\voice\dataD:\heygem_data\voice\datais agreed with theguiji2025/fish-speech-zimingservice, can be modified in docker-compose - Call the
http://127.0.0.1:18180/v1/preprocess_and_traninterfaceParameter example:
{ "format": ".wav", "reference_audio": "xxxxxx/xxxxx.wav", "lang": "zh" }Response example:
{ "asr_format_audio_url": "xxxx/x/xxx/xxx.wav", "reference_audio_text": "xxxxxxxxxxxx" }Record the response results as they will be needed for subsequent audio synthesis
Interface: http://127.0.0.1:18180/v1/invoke
// Request parameters
{
"speaker": "{uuid}", // A unique UUID
"text": "xxxxxxxxxx", // Text content to synthesize
"format": "wav", // Fixed parameter
"topP": 0.7, // Fixed parameter
"max_new_tokens": 1024, // Fixed parameter
"chunk_length": 100, // Fixed parameter
"repetition_penalty": 1.2, // Fixed parameter
"temperature": 0.7, // Fixed parameter
"need_asr": false, // Fixed parameter
"streaming": false, // Fixed parameter
"is_fixed_seed": 0, // Fixed parameter
"is_norm": 0, // Fixed parameter
"reference_audio": "{voice.asr_format_audio_url}", // Return value from previous "Model Training" step
"reference_text": "{voice.reference_audio_text}" // Return value from previous "Model Training" step
}-
Synthesis interface:
http://127.0.0.1:8383/easy/submit// Request parameters { "audio_url": "{audioPath}", // Audio path "video_url": "{videoPath}", // Video path "code": "{uuid}", // Unique key "chaofen": 0, // Fixed value "watermark_switch": 0, // Fixed value "pn": 1 // Fixed value }
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Progress query:
http://127.0.0.1:8383/easy/query?code=${taskCode}GET request, parameter
taskCodeis the return value from the above synthesis interface
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Check if all three services are in Running status
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Confirm that your machine has an NVIDIA graphics card and drivers are correctly installed.
All computing power for this project is local. The three services won't start without an NVIDIA graphics card or proper drivers.
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Ensure both server and client are updated to the latest version. The project is newly open-sourced, the community is very active, and updates are frequent. Your issue might have been resolved in a new version.
- Server: Go to
/deploydirectory and re-executedocker-compose up -d - Client:
pullcode and re-build
- Server: Go to
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GitHub Issues are continuously updated, issues are being resolved and closed daily. Check frequently, your issue might already be resolved.
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Problem Description
Describe the reproduction steps in detail, with screenshots if possible.
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Provide Error Logs
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How to get client logs:
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Server logs:
Find the key location, or click on our three Docker services, and "Copy" as shown below.
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end_sub@hotmail.com
- ASR based on fun-asr
- TTS based on fish-speech-ziming