This is a Essentia-based Python backend for processing audio files and providing analysis results. It allows you to process audio files and obtain complete music-related features such as BPM, mood, key, timbre, and more.
- Process audio files to extract music-related features.
- Analyze audio files to determine BPM, mood, key, timbre, and more.
- Store analysis results in JSON format.
- Provides a JSON file explaining how to read the data.
- Provides RESTful API endpoints to access analysis results.
Follow these instructions to get the project up and running on your local machine.
Before you begin, follow these steps:
- create a virtual environment
python -m venv venv
- activate the virtual environment (on Windows)
venv\Scripts\activate
- Install packages from requirements.txt
pip install -r requirements.txt
-
Clone the repository to your local machine:
git clone https://github.com/albedimaria/backend_thesis.git
- Start the Flask application:
python main.py
- Access the application in your web browser at http://localhost:5000.
- Select the audio folder containing files for processing and retrieve the analysis results.
The applicationprovides the following endpoint:
/process_audio
: process audio files and retrieve analysis results.
Contributions are welcome! If you'd like to contribute to this project, please follow these steps:
Fork the repository. Create a new branch for your feature or bug fix. Make your changes and commit them. Push your changes onto your fork. Open a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.