README.md

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 (link coming soon).

Contents: Please find and download the datasets with their annotations:

• WTA Dataset: https://drive.google.com/file/d/16k1lGQ1veMgXauzmakV2A1Y_C0StnsNn/view?usp=sharing
• TLA Dataset: https://drive.google.com/file/d/1wNCyy4UT3fMRu5z6XBlrLPBVhwRp9uTO/view?usp=sharing

Format

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

Code

Coming soon.

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}

Contact:

For information/questions about the paper or code, please contact Giorgos Zampokas.