README.md

metadata

title: LipSync - LatentSync 1.6
emoji: 👄
colorFrom: purple
colorTo: pink
sdk: gradio
sdk_version: 5.24.0
python_version: '3.10'
app_file: app.py
pinned: false
short_description: Lipsync video (English only) - LatentSync 1.6

OutofLipSync - LatentSync 1.6

Lipsync video with custom audio (English only) using LatentSync 1.6 from ByteDance.

Features

• Resolution: 512x512 (LatentSync 1.6)
• Auto-download: Checkpoints from ByteDance/LatentSync-1.6
• Face detection: Automatic face detection and cropping
• Audio processing: Audio separation, upsampling
• Multiple outputs: Step-by-step processing visualization

HuggingFace Spaces Deployment

1. Tạo Space mới trên HuggingFace

• Vào https://huggingface.co/new-space
• Chọn:
  • Owner: Username của bạn
  • Space name: Tên bạn muốn (ví dụ: lipsync-demo)
  • SDK: Gradio
  • Hardware: GPU (cần ít nhất 18GB VRAM cho LatentSync 1.6)
  • Visibility: Public hoặc Private

2. Đẩy code lên Space

Cách 1: Dùng Git

git clone https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME
cd YOUR_SPACE_NAME
git remote add origin https://github.com/naicoi/OutofLipSync
git pull origin main
git push origin main

Cách 2: Dùng HuggingFace CLI

# Install huggingface-cli nếu chưa có
pip install huggingface_hub

# Login
huggingface-cli login

# Push code lên Space
git push https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME main

3. Đợi build và deploy

• HuggingFace sẽ tự động build và deploy
• Check status ở tab "Settings" → "Build"
• Khi build xong, app sẽ chạy tại: https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME

4. Yêu cầu

• GPU: Space cần có GPU (tối thiểu 18GB VRAM cho LatentSync 1.6)
• Runtime: Python 3.10
• Disk space: ~5GB cho checkpoints

5. Lưu ý

• Checkpoint được tải tự động từ ByteDance/LatentSync-1.6 khi khởi động
• Quá trình tải checkpoint có thể mất vài phút
• Audio target chỉ hỗ trợ tiếng Anh

---

🚀 Deployment

HuggingFace Spaces

1. Create a Space on HuggingFace
2. Push this repository to your Space
3. Done! HuggingFace will automatically:
   • Create Python environment
   • Install dependencies from requirements.txt
   • Start the application

Requirements:

• Hardware: A10G GPU (recommended, 24GB VRAM)
• Python: 3.10

💻 Local Development

Option 1: Using uv (Fast - Recommended)

# Install uv (macOS/Linux)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Or: brew install uv

# Setup and install
./setup_local.sh

# Run application
uv run python app.py

Why uv? 10-100x faster than pip for dependency management!

Option 2: Using pip (Standard)

# Create venv
python3 -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run application
python app.py

📦 Dependencies

• requirements.txt: All dependencies for application
• Packages are installed in .venv/ (ignored by git)
• Git dependencies: LatentSync, FastAudioSR, tigersound, descript-audiotools

⚠️ Important Notes

Flash-attn-3 for Local Testing

The flash-attn-3 package only provides wheels for Linux x86_64:

• HuggingFace (Linux): ✅ Works automatically
• Local (macOS): ❌ Will fail during installation

Workaround for local testing:

# Comment out flash-attn-3 in requirements.txt for local testing
# Uncomment before pushing to HuggingFace

Checkpoints

Checkpoints are automatically downloaded from ByteDance/LatentSync-1.6 on startup.

Audio Language

Target audio supports English only.

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference