The Audio Genre Detection project is a robust and sophisticated system for determining the genre of audio files. Leveraging the power of Essentia, a comprehensive library for audio analysis, and TensorFlow, this system provides accurate and efficient genre classification.

It includes a Dockerized environment that streamlines the process of running the audio genre detection system, making it accessible and hassle-free.

Before you begin, ensure you have met the following requirements:

• Docker: You need to have Docker installed on your system.

1. Clone this repository to your local machine.

git clone https://github.com/cobanov/audio-genre-detection.git
cd audio-genre-detection

2. Build and run the docker image

docker build -t audio-genre-detection .
docker run -it -p 8000:8000 audio-genre-detection

Once you have set up the environment, you can easily use the audio genre detection system.

Access the SwaggerAPI interface to upload an audio file for genre detection:

http://localhost:8000/docs#/

The system will process your audio file and provide genre predictions, making it a seamless and efficient solution for genre classification.

We welcome contributions from the community. If you'd like to improve this project or report issues, please refer to our Contribution Guidelines for more information.

This project is licensed under the MIT License, which means it is open-source and free to use, modify, and distribute. Please read the license for more details.