Audio Watermarking

A simple web application for adding watermark samples to audio files.

• Upload WAV audio files (44.1kHz or 48kHz, 16-bit or 24-bit)
• Automatically adds 16 watermark samples at the beginning of the file
• Downloads the processed audio file with format: [original-name]--WM.wav for watermarked files
• Remove watermark and download with format: [original-name]--NWM.wav for unwatermarked files
• Support for both mono and stereo audio files

• Python 3.9+
• Flask
• NumPy
• librosa (for audio metadata extraction)
• soundfile
• psycopg2-binary (for database operations)

1. Clone this repository
2. Install dependencies:

   pip install -r requirements.txt

1. Start the Flask backend server:

   python app.py

   The backend API will run on http://localhost:5000 and provides the following endpoints:
   • POST /upload - Add watermark to audio file
   • POST /remove - Remove watermark from audio file
   • GET /api/nodes - Retrieve all nodes from database
   • GET /api/artists - Retrieve all artists with collective information

2. Start the React frontend (in a separate terminal):

   cd frontend
   npm install  # First time only
   npm start

   The frontend will run on http://localhost:3000

3. Open your browser and navigate to:

   http://localhost:3000
   

4. Upload a WAV file (44.1kHz or 48kHz, 16-bit or 24-bit) and the processed file will be automatically downloaded

The original HTML interface (index.html, artists.html) is no longer served by the backend. Use the React frontend at http://localhost:3000 instead.

The application adds 16 samples at the start of the audio file with amplitudes representing a binary pattern using two dB levels:

• 0 (low): -99dB
• 1 (high): -90dB

These dB values are converted to 16-bit amplitude values using the formula:

amplitude = 10^(dB/20) × 32767

The watermark samples are prepended to the original audio data.

• Backend: Python Flask server
• Audio Processing: NumPy for array manipulation, wave module for WAV file handling
• Frontend: Single HTML page with vanilla JavaScript
• File Format: WAV (44.1kHz or 48kHz, 16-bit or 24-bit, mono or stereo)
• Max Upload Size: 500 MB
• Download Format:
  • Watermarked: [original-name]--WM.wav
  • Unwatermarked: [original-name]--NWM.wav

For production deployment:

• Use a production WSGI server (e.g., Gunicorn, uWSGI) instead of Flask's development server
• Set debug=False in the Flask app configuration
• Configure appropriate file upload limits
• Use HTTPS for secure file transfers
• Implement authentication if needed

To test the application with a sample file:

1. Create a test audio file (or use your own 44.1kHz or 48kHz, 16-bit or 24-bit WAV file)
2. Upload through the web interface
3. The watermarked file will download automatically with suffix --WM

This is an initial experimental repository looking at CoPilot and how to work closely with the ML tool to accelerate my develop throughout a more complex, holistic and useful product.

python3 -m venv venv
source venv/bin/activate
python -m pip install --upgrade pip setuptools wheel
python -m pip install flask numpy

There is more to come here, I'm expecting all PRs to be raised by CoPilot based on my prompts.