Perth is a comprehensive Python library for audio watermarking and detection.
Perth enables you to embed imperceptible watermarks in audio files and later detect them, even after the audio has undergone various transformations or manipulations. The library implements multiple watermarking techniques including neural network-based approaches.
- Multiple Watermarking Techniques: Including the Perth-Net Implicit neural network approach
- Robust Watermarks: Watermarks can survive common audio transformations like compression, resampling, and more
- Command-Line Interface: Easy to use CLI for quick watermarking tasks
- Python API: Comprehensive API for integration into your applications
- Quality Metrics: Tools to evaluate the perceptual quality of watermarked audio
pip install resemble-perth
git clone https://github.com/resemble-ai/Perth
cd Perth
pip install -e .
# Apply a watermark to an audio file
perth input.wav -o output.wav
# Extract a watermark from an audio file
perth input.wav --extract
import perth
import librosa
import soundfile as sf
# Load audio file
wav, sr = librosa.load("input.wav", sr=None)
# Initialize watermarker
watermarker = perth.PerthImplicitWatermarker()
# Apply watermark
watermarked_audio = watermarker.apply_watermark(wav, watermark=None, sample_rate=sr)
# Save watermarked audio
sf.write("output.wav", watermarked_audio, sr)
import perth
import librosa
# Load the watermarked audio
watermarked_audio, sr = librosa.load("output.wav", sr=None)
# Initialize watermarker (same as used for embedding)
watermarker = perth.PerthImplicitWatermarker()
# Extract watermark
watermark = watermarker.get_watermark(watermarked_audio, sample_rate=sr)
print(f"Extracted watermark: {watermark}")
The Perth-Net Implicit watermarker uses a neural network-based approach for embedding and extracting watermarks. It's designed to be robust against various audio manipulations while maintaining high audio quality.
from perth.perth_net.perth_net_implicit.perth_watermarker import PerthImplicitWatermarker
watermarker = PerthImplicitWatermarker(device="cuda") # Use GPU for faster processing
A simple placeholder watermarker for testing and demonstration purposes.
from perth import DummyWatermarker
watermarker = DummyWatermarker()
The library includes utilities for evaluating the quality and robustness of watermarked audio:
import librosa
from perth.utils import calculate_audio_metrics, plot_audio_comparison
# Load original and watermarked audio
original, sr = librosa.load("input.wav", sr=None)
watermarked, _ = librosa.load("output.wav", sr=None)
# Calculate quality metrics
metrics = calculate_audio_metrics(original, watermarked)
print(f"SNR: {metrics['snr']:.2f} dB")
print(f"PSNR: {metrics['psnr']:.2f} dB")
# Visualize differences
plot_audio_comparison(original, watermarked, sr, output_path="comparison.png")
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.