{"url":"/dataset/wta-tla","name":"WTA/TLA","full_name":"WTA/TLA: A UAV-captured Dataset for Semantic Segmentation of Energy Infrastructure","description_markdown":"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](https://ieeexplore.ieee.org/document/9836096)).\r\n\r\nEach dataset contains multiple locations. For each location:\r\n- images/ directory contains RGB images\r\n- multi_masks/ directory contains semantic image masks, with each class encoded in a different color (0:background, 1:blade, 2:tower).\r\n- annotations/ directory contains semantic image masks, for visual inspection.\r\n\r\n<h5>Training/Testing</h5>\r\ntrain.txt/test.txt and train_gt.txt/test_gt.txt contain images and masks for training and testing respectively\r\n\r\n<h5>Citation:</h5>\r\n\r\n```\r\n@inproceedings{za2022wtatla,\r\n  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},\r\n  booktitle={2022 International Conference on Unmanned Aircraft Systems (ICUAS)}, \r\n  title={WTA/TLA: A UAV-captured Dataset for Semantic Segmentation of Energy Infrastructure}, \r\n  year={2022}\r\n```","description_withheld":null,"homepage":"https://github.com/gzamps/wta_tla_dataset","introduced_date":"2023-01-27","introduced_date_note":null,"introduced_by":null,"license":{"name":"Apache License 2.0","url":"https://github.com/gzamps/wta_tla_dataset/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"},{"name":"Aerial Video Semantic Segmentation","url":"/task/aerial-video-semantic-segmentation","datasets_with_task":"/datasets/task/aerial-video-semantic-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["WTA/TLA"],"data_loaders":[],"num_papers_in_archive":0,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}