QSRlib is a library that allows the computation of Qualitative Spatial Relations and Calculi, as well as a development framework for rapid implementation of new QSRs.
QSRlib is a library that allows the computation of Qualitative Spatial Relations and Calculi, as well as a development framework for rapid implementation of new QSRs. The aims of QSRlib are to:
- provide a number of Qualitative Spatial Representations (QSRs) that are well known, and in common use in the scientific community;
- expose these QSRs via a standard IO interface that allows quick and easy re-usability, including a ROS interface to allow use in cognitive robotic systems;
- provide a flexible and easy to use infrastructure that allows rapid development of new QSRs that extend the library;
- deliver abstracted QSRs overtime in an aggregated representation that facilitates further inference.
Language of the library: Python
More information: A typical usage of QSRlib would be an intelligent system, such as a robot for example, which acquires visual data via an RGB-D camera, such as a Kinect, and via object recognition and skeleton tracking is able to perceive the individual entities in the world. The system can then make calls to QSRlib in order to abstract this input data and form a qualitative representation of the perceived world scene. This could then be used to recognise activities in natural scenes using already learnt models expressed using QSRs in the QSRlib library.
- a Python library that can be imported to any Python application;
- a number of QSRs that are well known to the scientific community;
- tandard IO interface (including a ROS interface) for quick use of QSRs;
- tools to allow rapid development of new QSRs that extend the library;
- abstracted QSRs overtime in an aggregated representation that facilitates further inference.
QSRlib has been used in various research and teaching projects, and it is available as a standalone python package or as a ROS package. This resource is a collaborative work by the Universities of Leeds, Lincoln and Birmingham (see list of authors below) and has received funds from the EC under FP7 project STRANDS, 600623. QSRlib is released under MIT license. See further details in https://qsrlib.readthedocs.io/en/latest/rsts/handwritten/license.html.
- Installation details and example: https://qsrlib.readthedocs.io/en/latest/rsts/handwritten/install.html
- List of authors: https://qsrlib.readthedocs.io/en/latest/rsts/handwritten/people.html
- Additional documentation: https://qsrlib.readthedocs.io
- Github page: https://github.com/strands-project/strands_qsr_lib