Pychorus

Pychorus is an open source library to find choruses or interesting sections in pieces of music. The algorithm is largely based on a paper by Masataka Goto with some simplifications and modifications. There is room for improvement so feel free to contribute to the project.

Check out my blog post: https://towardsdatascience.com/finding-choruses-in-songs-with-python-a925165f94a8 for a full explanation on how the library works

Getting Started

You can install the codebase easily with

pip install pychorus

Sample execution

The most straightforward way to use the module is as follows:

from pychorus import find_and_output_chorus

chorus_start_sec = find_and_output_chorus("path/to/audio_file", "path/to/output_file", clip_length)

You can also clone the repo and use main.py as a command line tool like

python main.py path/to/audio_file --output_file=path/to/output_file

Creating the chromogram, time-time, and time-lag matrices

from pychorus import create_chroma
from pychorus.similarity_matrix import TimeTimeSimilarityMatrix, TimeLagSimilarityMatrix

chroma, _, sr, _ = create_chroma("path/to/audio_file")
time_time_similarity = TimeTimeSimilarityMatrix(chroma, sr)
time_lag_similarity = TimeLagSimilarityMatrix(chroma, sr)

# Visualize the results
time_time_similarity.display()
time_lag_similarity.display()

Planned improvements for v0.2

License

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