Subtitle Generator

Upload your video and get subtitles.

Table of Contents

• Subtitle Generator
  • Table of Contents
  • Features
  • Requirements
  • Installation
    • Prepare the model file
    • Docker Installation
  • Usage
  • Project Structure
  • Contributing
  • License
  • Acknowledgments

Features

• Subtitle generation using a pre-trained model.
• Easy-to-use web interface built with Streamlit.
• Efficient processing with NVIDIA CUDA.

Requirements

• Docker
• NVIDIA GPU and drivers compatible with CUDA 12.4.1

Installation

Prepare the model file

1. Download the model and place the weight to ./model

Docker Installation

1. Clone the Repository

   git clone https://github.com/yourusername/subtitle-generator.git
   cd subtitle-generator

2. Build the Docker Image

   docker compose up -d

This will start the application, and you can access the Streamlit interface at http://localhost:8501.

Usage

1. Access the Web Interface

   Open your web browser and navigate to http://localhost:8501.

2. Upload Video

   Use the provided interface to upload your video file.

3. Generate Subtitles

   The backend will process the video, and subtitles will be generated and downloaded to your local computer.

Project Structure

.
├── Dockerfile
├── README.md
├── app.py
├── core
│   └── ... (pre-built Rust backend binary and necessary files)
├── requirements.txt
└── start.sh

• Dockerfile: The Dockerfile to build the project container.
• README.md: This README file.
• app.py: The Streamlit application code.
• core/: Directory containing the pre-built Rust backend binary.
• requirements.txt: Python dependencies file.
• start.sh: Script to start the backend and frontend.

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -am 'Add new feature').
5. Push to the branch (git push origin feature-branch).
6. Create a new Pull Request.

License

This project is for non-commercial usages. For commercial usages, please contact the author: [email protected]

Acknowledgments

• NVIDIA for providing the CUDA base image.
• Streamlit for the easy-to-use web application framework.
• Tsinghua University for their software mirror.