MGT-python

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The Musical Gestures Toolbox for Python (musicalgestures) is a collection of tools for visualising and analysing motion in video recordings, together with the sound that accompanies them. It was developed for research on music-related body motion, but it works on any video or audio file.

MGT python

Installation

pip install musicalgestures

You also need FFmpeg on your system; everything else installs automatically. The installation guide covers optional extras such as pose estimation.

Quickstart

import musicalgestures as mg

v = mg.MgVideo(mg.examples.dance)   # or your own file: mg.MgVideo('dance.mp4')
v.motiongrams().show()

This draws motiongrams: images that trace where in the frame movement happens over time, like a spectrogram for the body. Analysis methods return result objects, and .show() displays them.

You can also try the toolbox in the browser, with no installation:

Open In Colab

Documentation

  • Documentation site — installation, quickstart, user guide, and full API reference
  • Wiki — worked examples and discussion of the methods
  • Contributing — how to report issues and submit changes

Related toolboxes

These come out of the same lab, as separate packages with separate release cycles. They are built to be used together and share several implementations, so a measure computed in one agrees with the same measure computed in another.

  • micromotion—human micromotion: quantity of motion from optical markers, accelerometers, respiration belts and force plates. This package re-exports its corrected group_qom and requires it
  • ambiscape—soundscapes: the sonic ambience of a place
  • musiscape—music collections: comparing many tracks and albums held as audio files in folders

The boundary is the input rather than the question: this package starts from a VIDEO file, and the other three from motion series, a room recording and a music collection.

Credits

This toolbox builds on the Musical Gestures Toolbox for Matlab, which again builds on the Musical Gestures Toolbox for Max. Many researchers and research assistants have helped its development over the years, including Balint Laczko, Joachim Poutaraud, Frida Furmyr, Marcus Widmer, and Alexander Refsum Jensenius.

The software is maintained by the fourMs lab at RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo.

If you use this toolbox in your research, please cite:

License

This toolbox is released under the GNU General Public License 3.0.

Citing

Cite the CONCEPT DOI, which always resolves to the newest version:

Jensenius, A. R., Laczkó, B., Poutaraud, J., Widmer, M., & Furmyr, F. (2026). Musical Gestures Toolbox for Python (Version 1.11.1) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.21949007

Where the exact behaviour matters, cite the version you ran instead. Version 1.11.1 is https://doi.org/10.5281/zenodo.21949008.

CITATION.cff in this repository carries the same information in machine-readable form.

Project links

Data verified by PyPI on Aug 16, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Newer release available (1.18.0)

2 maintainers

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Data sourced directly from PyPI's database.
Avatar for fisheggg from gravatar.com fisheggg Avatar for fourMs from gravatar.com fourMs

Credits

Author: University of Oslo fourMs Lab

GitHub Statistics

Data verified by PyPI on Aug 16, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

GNU General Public License v3 (GPLv3) (GPL-3.0-or-later)

Requires

Python >=3.10

Provides Extra

pose c3d ml cli dev soundscape full

Tags

computer vision motion analysis musical gestures video analysis

Classifiers

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