TuneSpy

TuneSpy shares similarities with the popular Shazam app, as both are designed to identify and match audio clips with songs from a database. While Shazam primarily focuses on real-time audio recognition using advanced fingerprinting algorithms optimized for mobile environments, TuneSpy is a desktop application aimed at exploring the core concepts of audio processing and music matching.

TuneSpy is a Python application that allows users to load audio files, generate spectrograms, extract MFCC features, and compare the loaded audio with a preprocessed database of songs to find the most similar match.

Features

• Load audio files in various formats (MP3, WAV, FLAC)
• Generate spectrograms and save them as PNG images
• Extract MFCC features and save them as JSON files
• Hash spectrogram images using perceptual hashing
• Compare loaded audio with a preprocessed database of songs
• Display the most similar songs with similarity percentages
• Mix two audio files with adjustable weights
• Play and stop audio playback

Requirements

• Python 3.x
• Required Python packages (install using pip):
  • librosa
  • numpy
  • matplotlib
  • imagehash
  • Pillow
  • PyQt5
  • soundfile
  • sounddevice
  • scipy
  • mutagen

Installation

1. Clone the repository:

   git clone https://github.com/HarmoniCode/TuneSpy.git
   cd TuneSpy

2. Install the required Python packages:

   pip install -r requirements.txt

Running the Application

python main.py

License

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