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- Dokumenttyp:
- Forschungsdaten
- Veröffentlichungsdatum:
- 11.05.2022
- Verantwortlich:
- Krapf Sebastian
- Autorinnen / Autoren:
- Krapf Sebastian, Bogenrieder Lukas, Netzler Fabian, Balke Georg, Lienkamp Markus
- Institutionszugehörigkeit:
- TUM
- Herausgeber:
- TUM
- Titel:
- RID – Roof Information Dataset for Computer Vision-Based Photovoltaic Potential Assessment
- Identifikator:
- doi:10.14459/2022mp1655470
- Enddatum der Datenerzeugung:
- 06.10.2021
- Fachgebiet:
- DAT Datenverarbeitung, Informatik
- zusätzliche Fachgebiete:
- Remote Sensing
- Quellen der Daten:
- Abbildungen von Objekten / image of objects
- Andere Quellen der Daten:
- Google aerial images
- Datentyp:
- Bilder / images; Texte / texts
- Methode der Datenerhebung:
- 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... »
- Beschreibung:
- 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.
- Links:
Code: https://github.com/TUMFTM/RID
This dataset relates to the publication: https://doi.org/10.3390/rs14102299- Schlagworte:
- roof information, roof superstructures, roof segments, computer vision, deep learning, semantic segmentation, aerial images, remote sensing, annotation, labeling, photovoltaic potential
- Technische Hinweise:
- 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/ - Sprache:
- en
- Rechte:
- by-nc, http://creativecommons.org/licenses/by-nc/4.0
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