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Wavee Backend

Python NumPy Flask scikit-learn SciPy

This is a demo Python-Flask backend implementation for Music Identification. Implements Shazam algorithm as described in An Industrial-Strength Audio Search Algorithm.

Quick Start with Pip

Important

Built with Python 3.10, using other versions might lead to incompatibility issues. Use Docker instead.

1. Clone the repository

root@user:~$ git clone https://github.com/daniel-lujan/Wavee-Backend.git
root@user:~$ cd Wavee-Backend

2. Create virtual environment

You can now optionally create a virtual environment.

root@user:~$ python -m venv venv
root@user:~$ venv/Scripts/activate.bat

3. Install dependencies

root@user:~$ pip install -r "requirements.txt"

4. Start server

root@user:~$ python app.py

The API is should now be available at http://localhost:5000.

Quick Start with Docker

1. Clone the repository

root@user:~$ git clone https://github.com/daniel-lujan/Wavee-Backend.git
root@user:~$ cd Wavee-Backend

2. Build and start container

root@user:~$ docker build -t wavee-backend .
root@user:~$ docker run -p 8080:8080 wavee-backend

The API is should now be available at http://localhost:8080.

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Audio fingerprinting for Music Identification API

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