A dataset for window and blind states detection

A dataset for window and blind states detection

The data was constructed for detecting window and blind states. All images were annotated in XML format using LabelImg for object detection tasks. The results of applying the Faster R-CNN based model include detected images and loss graphs for both training and validation in this dataset. Additional...

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Bibliographische Detailangaben
1. Verfasser: Wang, Seunghyeon
Format: Dataset
Sprache:eng
Schlagworte:
Architectural computing and visualisation methods
Architectural design
Architectural heritage and conservation
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Beschreibung
Zusammenfassung:The data was constructed for detecting window and blind states. All images were annotated in XML format using LabelImg for object detection tasks. The results of applying the Faster R-CNN based model include detected images and loss graphs for both training and validation in this dataset. Additionally, the raw data with other annotations can be used for applications such as semantic segmentation and image captioning.
DOI:10.6084/m9.figshare.26403004