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A very lite version of The Deezer source separation library with very low RAM usage.

Project description

lite-spleeter: Lightweight musical instruments removing library

About

This is a lightweight Spleeter (a library that uses AI/ML to extract vocals from audio files) version that works with media files of any length, with very low and fixed RAM usage (around 1.5 GB RAM usage on my computer).

Features

• Progress indicator

• Very lightweight on low-end Computers

• Smaller package and simpler

• No numpy errors

How does it work?

It processes 30-second segments sequentially. After processing all segments, it concatenates them. This approach of processing chunks instead of the whole audio file helps keep memory usage low.

Get started

Make sure you have ffmpeg installed.

Download package:

pip install lite-spleeter

Usage

lite-spleeter separate audio_example.mp3  -o audio_output_path

You can provide either a single or a list of files for batch processing

Batch processing

separate command builds the model each time it is called, this process may be long, in this case If you have several files to separate, it is then recommended to perform all separation with a single call to separate:

lite-spleeter separate <path/to/audio1.mp3> <path/to/audio2.wav> <path/to/audio3.ogg> -o audio_output_path

To get help on the different options available with the separate command, type:

lite-spleeter separate --help

Read the original Spleeter repo for more info.

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lite_spleeter-2.1.0.tar.gz (73.1 MB view details)

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