This repository accompanies the paper:
ResPlan: A Large-Scale Vector-Graph Dataset of 17,000 Residential Floor Plans
Mohamed Abouagour, Eleftherios Garyfallidis
ResPlan introduces a large-scale dataset of 17,000 structurally rich and realistic residential floor plans designed to advance research in spatial AI, robotics, and generative modeling.
- High fidelity annotations of architectural elements: walls, doors, windows, balconies.
- Functional spaces: kitchens, bedrooms, bathrooms, living rooms.
- Dual representation: vector geometries + graph structures.
- Open-source pipeline for geometry cleaning, alignment, and annotation refinement.
- Applications: reinforcement learning, robotics navigation, generative AI, VR/AR simulations, game design.
Here is a sample floor plan rendered with plot_plan:
And here is the same plan with its graph overlay:
ResPlan_demo.ipynb– Example Jupyter notebook showing how to:- Load and visualize plans
- Convert geometries to raster masks
- Apply augmentations (rotate, flip, scale)
- Convert plans into graph representations
resplan_utils.py– Helper utilities for:- Geometry operations
- Augmentations
- Mask conversions
- Plotting plans and graphs:contentReference[oaicite:0]{index=0}
ResPlan.zip– Containing the PKL file of the dataset (unzip first).
Clone the repository and install dependencies:
git clone https://github.com/m-agour/ResPlan.git
cd ResPlan
pip install shapely geopandas matplotlib networkx numpy opencv-python
then, run ResPlan_demo.ipynb
If you use ResPlan in research, please cite:
Plain text
Abouagour, M., & Garyfallidis, E. (2025). ResPlan: A Large-Scale Vector-Graph Dataset of 17,000 Residential Floor Plans. arXiv:2508.14006. https://doi.org/10.48550/arXiv.2508.14006
BibTeX (paper)
@article{AbouagourGaryfallidis2025ResPlan,
title = {ResPlan: A Large-Scale Vector-Graph Dataset of 17,000 Residential Floor Plans},
author = {Abouagour, Mohamed and Garyfallidis, Eleftherios},
journal = {arXiv preprint arXiv:2508.14006},
year = {2025},
doi = {10.48550/arXiv.2508.14006},
url = {https://arxiv.org/abs/2508.14006}
}