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Python implementation for "Simplification of Indoor Space Footprints"

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Simplification of Indoor Space Footprints

This project is developed for the simplification algorithm presented in the paper, titled "Simplification of Indoor Space Footprints" by Joon-Seok Kim and Carola Wenk, one of the accepted papers of 1st ACM SIGSPATIAL International Workshop on Spatial Gems (SpatialGems 2019). Although it is designed to simplify footprints of indoor spaces such as a room and a corridor, it works with footprints of buildings very well. This library can be utilized for 2/3D building simplification and generalization.

The original code was developed by Joon-Seok Kim in C# and presented in "Simplification of geometric objects in an indoor space" 1. However, the original implementation has the strong dependency on many libraries including CGAL (Computational Geometry Algorithms Library) to compute 3D operations. In order to provide a light weight version, the code is ported in Python based on Shapely. Please make sure that Shapely and Numpy has been installed when you use the simplification.

The following code shows an example of how to use the library.

import prism
from shapely.wkt import loads

polygon = loads('POLYGON ((0 0, 2 0, 2 -1.1, 2.1 -1.1, 2.1 0, 4 0, 1 1.001, 0 2, -1 1, -1 0.99, -2 0, 0 0))')
simplified_polygon = prism.simplify(polygon, tau=1)
print(simplified_polygon.wkt)

Copyright by Joon-Seok Kim (jkim258 at gmu.edu)

[1]: Joon-Seok Kim, and Ki-Joune Li, "Simplification of geometric objects in an indoor space", ISPRS Journal of Photogrammetry and Remote Sensing 147 (2019): 146-162

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