🎬 SubLab — Professional Subtitle Studio

Auto-generate, translate, and burn subtitles into videos — all offline-capable.

---

✨ Features

Feature	Details
🗣️ Speech Recognition	OpenAI Whisper (7 model sizes) + Vosk (40+ languages, offline)
🌐 Translation	Google Translate (online) + Argos Translate (offline)
🎥 Video Maker	Burn subtitles directly into video with custom styles
📂 Batch Processing	Process multiple video files at once
📤 Export Formats	SRT, VTT, CSV, JSON
🌍 UI Languages	English, Arabic, Russian, French, German, Spanish, Portuguese, Chinese, Japanese, Korean
🌙 Dark / Light Mode	Full theme support
⚡ GPU Acceleration	CUDA support for Whisper
🛠️ First-Run Wizard	Auto-installs FFmpeg and required packages

---

📸 Screenshots

Coming soon

---

🚀 Quick Start

1. Clone the repository

git clone https://github.com/Hayder-IRAQ/SubLab.git
cd SubLab

2. Create a virtual environment (recommended)

python -m venv venv

# Windows
venv\Scripts\activate

# Linux / macOS
source venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

GPU users: Install PyTorch with CUDA support first:

pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu121

4. Run SubLab

python main.py

On first launch, the Setup Wizard will automatically:

• Detect your system
• Download FFmpeg if needed
• Verify all required packages
• Let you choose your preferred UI language

---

📦 Dependencies

Package	Purpose
PyQt5	GUI framework
openai-whisper	AI speech recognition
vosk	Offline speech recognition
googletrans	Online translation
argostranslate	Offline translation
moviepy	Video processing
opencv-python	Video frame handling
arabic-reshaper + python-bidi	Arabic text rendering
torch (optional)	GPU acceleration

---

🗂️ Project Structure

SubLab/
├── main.py                  # Entry point & setup wizard
├── requirements.txt
├── audio/
│   └── extractor.py         # FFmpeg / OpenCV audio extraction
├── engines/
│   ├── whisper_engine.py    # OpenAI Whisper engine (GPU-accelerated)
│   └── vosk_engine.py       # Vosk offline engine (40+ languages)
├── translation/
│   ├── translator.py        # Unified translation manager
│   ├── google_translator.py # Google Translate backend
│   └── argos_translator.py  # Argos Translate backend (offline)
├── ui/
│   ├── main_window.py       # Main application window
│   ├── subtitle_editor.py   # Subtitle editing widget
│   ├── subtitle_translator_tab.py
│   ├── video_maker_tab.py
│   ├── video_generator.py
│   └── template_manager.py
├── utils/
│   ├── config.py            # Configuration management
│   ├── export.py            # SRT / VTT / CSV / JSON export
│   ├── i18n.py              # Internationalization (10 languages)
│   ├── logger.py            # Logging setup
│   ├── setup_wizard.py      # First-run wizard
│   └── time_utils.py        # Subtitle timestamp utilities
├── models/
│   ├── whisper/             # Whisper model cache
│   └── vosk/                # Vosk model files
├── icons/                   # Application icons
└── tests/                   # Unit & integration tests

---

🧪 Running Tests

pip install pytest
pytest tests/ -v

---

🎙️ Speech Engine Comparison

	Whisper	Vosk
Accuracy	⭐⭐⭐⭐⭐	⭐⭐⭐⭐
Speed	Medium (GPU: Fast)	Fast
Offline	✅	✅
Languages	99+	40+
GPU Support	✅ CUDA	❌
Model Size	39 MB – 1.5 GB	32 MB – 2.3 GB

---

🌐 Translation Engines

	Google Translate	Argos Translate
Internet Required	✅	❌ (fully offline)
Languages	130+	30+ pairs
Quality	Excellent	Good
Cost	Free (unofficial API)	Free & open source

---

🗣️ Supported Vosk Languages

English · Arabic · Chinese · Russian · French · German · Spanish · Portuguese · Italian · Dutch · Turkish · Japanese · Korean · Hindi · Polish · Ukrainian · Greek · Vietnamese · Farsi · Filipino · Kazakh · Swedish · Uzbek · and more…

---

⚙️ Configuration

Settings are saved automatically to:

• Windows: %APPDATA%\VideoSubtitleGenerator\Settings.json
• Linux/macOS: ~/.config/VideoSubtitleGenerator/Settings.json

---

🤝 Contributing

Contributions are welcome! Please open an issue or submit a pull request.

1. Fork the repository
2. Create a feature branch: git checkout -b feature/my-feature
3. Commit your changes: git commit -m "Add my feature"
4. Push to the branch: git push origin feature/my-feature
5. Open a Pull Request

---

📄 License

This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

You may use, share, and adapt this work for non-commercial purposes only, with appropriate credit.

View License · CC BY-NC 4.0

---

👤 Author

Hayder Odhafa
GitHub: @Hayder-IRAQ

---

Made with ❤️ — SubLab v3.0 © 2025 Hayder Odhafa