{"url":"/dataset/wfdd","name":"WFDD","full_name":"Woven Fabric Defect Detection","description_markdown":"WFDD is a dataset for benchmarking anomaly detection methods with a focus on textile inspection. It includes 4101 woven fabric images categorized into 4 categories: grey cloth, grid cloth, yellow cloth, and pink flower. The first three classes are collected from the industrial production sites of WEIQIAO Textile, while the 'pink flower' class is gathered from the publicly available Cloth Flaw Dataset. Each category contains block-shape, point-like, and line-type defects with pixel-level annotations.","description_withheld":null,"homepage":"https://github.com/cqylunlun/GLASS?tab=readme-ov-file#dataset-release","introduced_date":"2024-07-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-unified-anomaly-synthesis-strategy-with","title":"A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization","first_author":"Qiyu Chen","url":null},"license":{"name":"MIT license","url":"https://github.com/cqylunlun/GLASS/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["WFDD"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/anomaly-detection-on-wfdd","task":"Anomaly Detection","dataset_variant":"WFDD","rows":1,"metrics":["Detection AUROC","Segmentation AUPRO","Segmentation AUROC"],"first_row_in_archive_order":{"model":"GLASS","paper":"/paper/a-unified-anomaly-synthesis-strategy-with","metrics":{"Detection AUROC":"100","Segmentation AUPRO":"94.9","Segmentation AUROC":"98.9"},"code_links":[{"title":"cqylunlun/glass","url":"https://github.com/cqylunlun/glass"},{"title":"septmars/DL","url":"https://github.com/septmars/DL"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/a-unified-anomaly-synthesis-strategy-with","title":"A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization","date":"2024-07-12","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":5,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":8,"samples_ran":5,"samples_unverified":3,"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."}