Fire-ART

Introduction Fire-ART is a firefighting asset recognition dataset comprising 2,626 images and 6,627 annotated instances. The dataset integrates four image sources: (1) an enhanced FireNet image set (Boehm et al., 2019), (2) publicly available images, (3) self-captured photographs, and (4) a modified subset of the HKU Building Image Dataset (HBD) (Wong et al., 2024). The self-captured images were collected from six regions: the United Kingdom, the United States, Mainland China, Macau SAR, France, and Greece. It includes 15 common categories of firefighting equipment: fire extinguisher, fire exit sign, fire door sign, fire alarm, emergency light, smoke detector, fire hose reel, piping system, sprinkler, fire call point, emergency door release, fire blanket, fire equipment sign, firefighting lift switch, and hidden fire equipment. Fire-ART is designed to support the development of computer vision models for object detection and segmentation, with the aim of advancing automation in indoor fire safety management and smart facility management. Dataset Citation This dataset accompanies the manuscript: Wen, Y., Qiao, Y., Lam, C.C., Brilakis, I., Lee, S. and Wong, M.O.*, 2025. Semantic BIM enrichment for firefighting assets: Fire-ART dataset and panoramic image-based 3D reconstruction. ISPRS Journal of Photogrammetry and Remote Sensing 231, 679–703. https://doi.org/10.1016/j.isprsjprs.2025.11.015 External Data Source Attribution 1. The FireNet dataset (Boehm et al., 2019) is publicly available at:https://www.firenet.xyz/ Please download the FireNet dataset from the above link. 2. The HBD dataset (Wong et al., 2024) is publicly avilable at: https://github.com/EnochYing/Image2BIM/tree/main/HBD Please download the HBD dataset from the above link. Reference: Wong, M.O., Ying, H., Yin, M., Yi, X., Xiao, L., He, C., & Tang, L. (2024). 3D Semantic Reconstruction-oriented Image Dataset for Building Element Segmentation. Automation in Construction 165. How to Use This repository hosts the images and annotations of the Fire-ART dataset. Images: The collection includes (1) the FireNet dataset, (2) publicly available images, (3) self-captured photographs, and (4) a modified subset of the HBD dataset. For images from (1) the FireNet dataset, please download the originals directly from the official source: https://rdr.ucl.ac.uk/articles/dataset/FireNet/9137798 Annotations: Annotations for all four image sources are provided in this repository. Please note that for FireNet images, you should use our enhanced annotations (rather than the original ones) to ensure consistency with the 15 defined firefighting asset categories. Licensing & Terms of Use This dataset is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0). You are free to use, share, and adapt the dataset with proper attribution. Dataset Structure Fire-ART_Part 1/│├── images/ # Download address for FireNet dataset (.txt) │ ├── download_link.txt│└── labels/ # Corresponding YOLO-format annotation files with updated annotation from Fire-ART (.txt) ├── 0000.txt ├── 0001.txt └── ... Fire-ART_Part 2/│├── images/ # Image files from publicly available images, self-captured images and HBD dataset (.jpg)│ ├── 03_1_image_18_Google_5.jpg│ ├── 03_1_image_37_Google_7.jpg│ └── ...│└── labels/ # Corresponding YOLO-format annotation files (.txt) ├── 03_1_image_18_Google_5.txt ├── 03_1_image_37_Google_7.txt └── ... Annotation Format & Tool Annotation Format: YOLO format (class_id, x1, y1, x2, y2, ..., xn, yn).Annotation Tool: Labelled using X-AnyLabeling and manual QA process. Dataset Statistics Table Class No. of Instance Piping system 1146 Fire equipment sign 864 Sprinkler 629 Fire extinguisher 624 Fire call point 620 Fire exit sign 617 Fire alarm 536 Smoke detector 423 Fire door sign 309 Fire hose reel 227 Fire blanket 227 Hidden fire equipment 136 Emergency door release 135 Emergency light 76 Firefighting lift switch 58 Total 6627