wyn-wav2lip 0.1.5

A simple package to run Wav2Lip for lip synchronization with quality enhancements.

Wav2Lip Package

Wav2Lip is a Python package that simplifies the setup and execution of the Wav2Lip model, a deep learning tool for lip synchronization with enhanced quality options.

wav2lip_project/
├── wav2lip/
│   ├── __init__.py
│   └── wav2lip.py  # Refactored class-based script with the correct name
├── pyproject.toml  # Poetry configuration file
├── README.md  # Project description and usage instructions
├── LICENSE  # License file (e.g., MIT License)
├── tests/
│   └── test_wav2lip.py  # Unit tests for the package
├── dist/  # Will contain build files after 'poetry build'
├── .gitignore  # Files to ignore in version control (optional)
└── setup.cfg  # Optional: You can include a setup.cfg for backward compatibility

Features

setup for Google Colab environments.

• Supports multiple quality settings (Fast, Improved, Enhanced).
• Integrated with GFPGAN for face upscaling.
• Easy configuration through INI files for customizable options.

Installation

To install the Wav2Lip package, you can use Poetry to manage dependencies.

pip install wav2lip

Usage

Here's an example of how to use the Wav2Lip package:

from wav2lip.wav2lip import Wav2Lip

# Initialize Wav2Lip
wav2lip = Wav2Lip()

# Setup environment (ensure that you have GPU enabled)
wav2lip.setup()

# Run the model with video and audio input
wav2lip.run(video_file="/content/your_video.mp4", vocal_file="/content/your_audio.wav")

Options

You can specify different options for the model, such as:

• Quality: "Fast", "Improved", or "Enhanced".
• Output Height: "half resolution", "full resolution", or "480".
• Padding and Mask: Customize mouth tracking, padding, and mask settings.

Contributing

Feel free to open issues or contribute by submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.