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Document type:
Forschungsdaten
Publication date:
11.05.2022
Responsible:
Krapf Sebastian
Authors:
Krapf Sebastian, Bogenrieder Lukas, Netzler Fabian, Balke Georg, Lienkamp Markus
Author affiliation:
TUM
Publisher:
TUM
Title:
RID – Roof Information Dataset for Computer Vision-Based Photovoltaic Potential Assessment
Identifier:
doi:10.14459/2022mp1655470
End date of data production:
06.10.2021
Subject area:
DAT Datenverarbeitung, Informatik
Other subject areas:
Remote Sensing
Resource type:
Abbildungen von Objekten / image of objects
Other resource types:
Google aerial images
Data type:
Bilder / images; Texte / texts
Description:
Labeled aerial images for semantic segmentation of roof segments and roof superstructures. Data set contains 1880 annotated buildings and 1880 roof centered images. Roof segments are labeled with azimuth value or as flat. Roof superstructure classes are pvmodule, dormer, window, ladder, chimney, shadow, tree and unknown.
Method of data assessment:
An initial version of labels has been annotated by university members according to a labeling guideline which is accessible through the github repository. Subsequently, masks of each image have been reviewed and adapted where necessary to improve label quality. This dataset contains reviewed masks only. Initial label quality is evaluated by an annotation experiment conducted with five labelers on 26 buildings. Masks of annotation experiment are part of this dataset. Effect of annotation errors i...     »
Links:

Code: https://github.com/TUMFTM/RID

This dataset relates to the publication: https://doi.org/10.3390/rs14102299
Key words:
roof information, roof superstructures, roof segments, computer vision, deep learning, semantic segmentation, aerial images, remote sensing, annotation, labeling, photovoltaic potential
Technical remarks:
View and download (1,5 GB total, 5812 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1655470):
rsync rsync:// m1655470@dataserv.ub.tum.de/m1655470/
Language:
en
Rights:
by-nc, http://creativecommons.org/licenses/by-nc/4.0
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