Quevedo: Annotation and Processing of Graphical Languages

Antonio F. G. Sevilla
Alberto Díaz Esteban
José María Lahoz-Bengoechea

Universidad Complutense de Madrid

Graphical languages, such as musical notation, use the 2D arrangement of symbols to convey meaning, using convention, abstraction and the fundamental sign-signified relationship of language.

The relative location of symbols is meaningful, such as in this UML diagram example, as well as their shape or direction, which can alter meaning.

SignWriting is a graphical language used to transcribe the gestures and movements of Sign Languages, using the 2D page to capture the multimodal 3D reality of signing.


Quevedo is a python library and command line application for creating, annotating and managing datasets of graphical languages, with a focus on the training and evaluation of machine learning algorithms for their recognition.


Install & Use

$ pip install quevedo[web]
$ quevedo -D new/dataset create ; cd new/dataset
$ quevedo web
$ quevedo -N network_name prepare train test

Deep Learning

Machine learning techniques developed in the field of computer vision are necessary to adequately process graphical languages. While the researcher can use any toolkit and algorithm they prefer, Quevedo includes a module to facilitate the use of deep learning neural networks with Quevedo datasets.


Quevedo allows you to train different neural networks to recognize different objects and features. These networks can then be composed into a pipeline to build an expert system, capable of performing a bigger task than each of the networks by themselves.

For example, a detection network can first locate the graphemes within a logogram, and then specialist networks be used to classify each of the graphemes.