This innovative toolbox, developped by KU Leuven Geomatics, jointly processes close-range sensing resources (point clouds, images) and BIM models for the AEC industry. More specifically, we combine semantic web technologies with state-of-the-art open source geomatics APIs to process and analyse big data in construction applications.
Use the package manager pip to install geomapi as a user.
conda create --name geomapi_user python=3.10
pip install geomapi
Or as a developer, install the dependencies from the root folder through the command line.
pip install -r requirements.txt
You can read the full API reference here:
import geomapi
from geomapi.nodes import Node
newNode = Node()
The master branch is protected and you can only make changes by submitting a merge request. Please create a new branch if you would like to make changes and submit them for approval.
If you want to cite us, refer to the following publication (accepted).
@article{GEOMAPI,
title = {GEOMAPI: Processing close-range sensing data of construction scenes with semantic web technologies},
journal = {Automation in Construction},
volume = {164},
pages = {105454},
year = {2024},
issn = {0926-5805},
doi = {https://doi.org/10.1016/j.autcon.2024.105454},
url = {https://www.sciencedirect.com/science/article/pii/S0926580524001900},
author = {Maarten Bassier and Jelle Vermandere and Sam De Geyter and Heinder De Winter},
keywords = {Geomatics, Semantic Web Technologies, Construction, Close-range sensing, BIM, Point clouds, Photogrammetry}
}
The code in this project is licensed under MIT license.
FAQs
A standard library to manage geomatic data
We found that geomapi demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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