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. 2022 Mar 12:42:108042.
doi: 10.1016/j.dib.2022.108042. eCollection 2022 Jun.

Dataset of manually classified images obtained from a construction site

Affiliations

Dataset of manually classified images obtained from a construction site

Alexandre Del Savio et al. Data Brief. .

Abstract

A manually classified dataset of images obtained by four static cameras located around a construction site is presented. Eight object classes, typically found in a construction environment, were considered. The dataset consists of 1046 images selected from video footage by a frame extraction algorithm and txt files containing the objects' class and coordinates information. These data can be used to develop computer vision techniques in the engineering and construction fields.

Keywords: Construction images; computer vision image classification; construction monitoring images; construction objects; neural network training images.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article.

Figures

Fig 1
Fig. 1
Construction site location. Adapted from .
Fig 2
Fig. 2
Hierarchical classification proposed.
Fig 3
Fig. 3
Extract of IMG100.jpg's objects with their respective IDs.
Fig 4
Fig. 4
Location of static cameras in construction site.

References

    1. Almeida Del Savio A., Luna A., Cárdenas-Salas D., Vergara Olivera M., Urday Ibarra G. International Conference on Artificial Intelligence and Energy System (ICAIES) in Virtual Mode, Jaipur, India. 2021. The use of artificial intelligence to identify objects in a construction site. - DOI
    1. Algorithm for frame extraction: video_to_frames_decord.py https://gist.github.com/HaydenFaulkner/3aa69130017d6405a8c0580c63bee8e6.
    1. LabelImg v.1.8.1. https://pypi.org/project/labelImg/1.8.1/.
    1. Dahua Technology, DSS Express. https://www.dahuasecurity.com/es/products/All-Products/Software/Platafor...