WTA/TLA (WTA/TLA: A UAV-captured Dataset for Semantic Segmentation of Energy Infrastructure)

WTA (Wind Turbine Aerial) and TLA (Transmission Line Aerial) are public datasets which contain a set of RGB images from wind turbine farms and transmission towers and power lines, along with semantic ground truth for relevant classes. This is the official repository of the paper: WTA/TLA: A UAV-captured Dataset for Semantic Segmentation of Energy Infrastructure (url).

Each dataset contains multiple locations. For each location: - images/ directory contains RGB images - multi_masks/ directory contains semantic image masks, with each class encoded in a different color (0:background, 1:blade, 2:tower). - annotations/ directory contains semantic image masks, for visual inspection.

Training/Testing

train.txt/test.txt and train_gt.txt/test_gt.txt contain images and masks for training and testing respectively

Citation:

@inproceedings{za2022wtatla,
  author={Zampokas, Georgios and Skartados, Evangelos and Alexiou, Dimitrios and Tsiakas, Kosmas and Tzanakis, Ioannis and Roussos, Nikolaos and Giakoumis,   Dimitrios and Kostavelis, Ioannis and Bouganis, Christos-Savvas and Tzovaras, Dimitrios},
  booktitle={2022 International Conference on Unmanned Aircraft Systems (ICUAS)}, 
  title={WTA/TLA: A UAV-captured Dataset for Semantic Segmentation of Energy Infrastructure}, 
  year={2022}