{"url":"/dataset/swinseg","name":"SWINSEG","full_name":"Singapore Whole sky Nighttime Image SEGmentation Database","description_markdown":"The SWINSEG dataset contains 115 nighttime images of sky/cloud patches along with their corresponding binary ground truth maps. The ground truth annotation was done in consultation with experts from Singapore Meteorological Services. All images were captured in Singapore using WAHRSIS, a calibrated ground-based whole sky imager, over a period of 12 months from January to December 2016. All image patches are 500x500 pixels in size, and were selected considering several factors such as time of the image capture, cloud coverage, and seasonal variations.\r\n\r\nSource: [Nighttime sky/cloud image segmentation](https://stefan.winkler.site/Publications/icip2017b.pdf)","description_withheld":null,"homepage":"http://vintage.winklerbros.net/swinseg.html","introduced_date":"2017-05-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/nighttime-skycloud-image-segmentation","title":"Nighttime sky/cloud image segmentation","first_author":"Soumyabrata Dev","url":null},"license":{"name":"Creative Commons License","url":"https://creativecommons.org/licenses/by-nc/4.0/"},"modalities":[],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["SWINSEG"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semantic-segmentation-on-swinseg","task":"Semantic Segmentation","dataset_variant":"SWINSEG","rows":1,"metrics":["Average Precision","Average Recall","F1-Score","MCC","Mean IoU"],"first_row_in_archive_order":{"model":"ACLNet","paper":"/paper/aclnet-an-attention-and-clustering-based","metrics":{"Average Precision":"0.917","Average Recall":"0.982","F1-Score":"0.947","MCC":"0.930","Mean IoU":"0.985"},"code_links":[{"title":"ckmvigil/aclnet","url":"https://github.com/ckmvigil/aclnet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/aclnet-an-attention-and-clustering-based","title":"ACLNet: An Attention and Clustering-based Cloud Segmentation Network","date":"2022-07-13","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+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."}