ModRes: A modification of the ResPlan dataset ready for floor plan analysis and graph machine learning
Floor plan datasets underpin computational analysis of building layouts, spatial connectivity and graph machine learning.
ProofPaper ↗
Key points
- We present ModRes, a cleaned and enriched version of the ResPlan dataset, containing 8,431 valid and unique residential floor plans.
- For each floor plan, ModRes provides two-dimensional geometry, images, three-dimensional building representations and three complementary dual graphs in CSV and JSON formats with graph-, node- and edge-level features.
- We characterise the dataset using graph-based statistics and demonstrate its utility through a range of case studies.
- ModRes provides structured geometric, topological and semantic representations needed to automate spatial analysis and support machine learning-based workflows for building design and performance evaluation.
Sources (1)
- [1]ModRes: A modification of the ResPlan dataset ready for floor plan analysis and graph machine learningarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 12, 05:50 PM
Floor plan datasets underpin computational analysis of building layouts, spatial connectivity and graph machine learning.
We present ModRes, a cleaned and enriched version of the ResPlan dataset, containing 8,431 valid and unique residential floor plans.
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