Benchmarks of MLSTRUCT-FP dataset.
This repo contains the segmentation and vectorization models for processing our MLSTRUCT-FP dataset. See the following jupyter notebook files for more information and a quick start (in order):
- create_data: Creates a dataset, assembles crops, and export data session
- fp_unet: Creates U-Net model for wall segmentation
- vectorization: Vectorizes a model using Egiazarian et al. method
The weights for the best model (no_rot_256_50) can be downloaded at this link. For the vectorization model, follow the following links to download the weights for model_curves and model_lines; check the vectorization original repo for more details.
@article{Pizarro2023,
title = {Large-scale multi-unit floor plan dataset for architectural plan analysis and
recognition},
journal = {Automation in Construction},
volume = {156},
pages = {105132},
year = {2023},
issn = {0926-5805},
doi = {https://doi.org/10.1016/j.autcon.2023.105132},
url = {https://www.sciencedirect.com/science/article/pii/S0926580523003928},
author = {Pablo N. Pizarro and Nancy Hitschfeld and Ivan Sipiran}
}
Pablo Pizarro R. | 2023 - 2024