MahmoudAbdelRahman/build2Vec

Building representation in the vector space

29
/ 100
Experimental

This tool helps architects, urban planners, and facility managers translate complex building data, often from Building Information Models (BIM) or IFC files, into a structured format for analysis. It takes your building's components and their relationships, represented as a graph, and outputs numerical representations (vectors) that capture semantic similarities. These vectors can then be used to identify patterns or differences between building parts, helping professionals understand building structures better.

No commits in the last 6 months.

Use this if you need to derive numerical features from building component relationships to apply machine learning for tasks like semantic search, classification, or anomaly detection within building models.

Not ideal if you're looking for a direct visualization tool or a complete suite for building performance simulation, as it focuses specifically on data representation rather than end-user applications.

building-information-modeling architectural-analysis facility-management urban-planning smart-buildings
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 8 / 25

How are scores calculated?

Stars

9

Forks

1

Language

Python

License

MIT

Last pushed

Nov 04, 2021

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/MahmoudAbdelRahman/build2Vec"

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