Music Genre Classification App

This application uses machine learning to classify music genres. It provides a user-friendly interface through Streamlit where users can upload audio files and get genre predictions along with confidence scores.

Features

• Upload audio files (MP3 or WAV format)
• Real-time genre prediction
• Confidence scores for each genre
• Visual representation of predictions
• Support for multiple music genres

Installation

1. Clone this repository:

git clone https://github.com/VishnuRam16/Music-Genre-Classification.git
cd Music-Genre-Classification

2. Install the required dependencies:

pip install -r requirements.txt

Usage

1. Start the Streamlit app:

streamlit run app.py

2. Open your web browser and navigate to the URL shown in the terminal (usually http://localhost:8501)

3. Upload an audio file using the file uploader

4. Click the "Predict Genre" button to get the genre prediction and confidence scores

How it Works

The application:

1. Extracts audio features using librosa:

   • MFCC (Mel-frequency cepstral coefficients)
   • Spectral Centroid
   • Chroma features

2. Uses a Random Forest Classifier to predict the genre

3. Provides confidence scores for each possible genre

Requirements

• Python 3.7+
• Dependencies listed in requirements.txt

License

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