{"url":"/dataset/gf-pa66-3d-xct-composite-material-3d","name":"GF-PA66 3D XCT","full_name":"Glass fiber-reinforced polyamide 66 (GF-PA66) 3D X-ray Computed Tomography (XCT))","description_markdown":"Stack of 2D gray images of glass fiber-reinforced polyamide 66 (GF-PA66) 3D X-ray Computed Tomography (XCT) specimen.\r\n\r\nUsage: 2D/3D image segmentation\r\nFormat: HDF5\r\n\r\nLibraries to read HDF5 files:\r\n\r\n1) silx: [https://github.com/silx-kit/silx](https://github.com/silx-kit/silx)\r\n\r\n2) h5py: [https://www.h5py.org](https://www.h5py.org)\r\n\r\n3) pymicro: [https://github.com/heprom/pymicro](https://github.com/heprom/pymicro)\r\n\r\nTrained models to segment this dataset: [https://doi.org/10.5281/zenodo.4601560](https://doi.org/10.5281/zenodo.4601560)\r\n\r\nPlease cite us as\r\n\r\n```\r\n@ARTICLE{10.3389/fmats.2021.761229,\r\n    AUTHOR={Bertoldo, João P. C. and Decencière, Etienne and Ryckelynck, David and Proudhon, Henry},\r\n    TITLE={A Modular U-Net for Automated Segmentation of X-Ray Tomography Images in Composite Materials},\r\n    JOURNAL={Frontiers in Materials},\r\n    VOLUME={8},\r\n    YEAR={2021},\r\n    URL={https://www.frontiersin.org/article/10.3389/fmats.2021.761229},\r\n    DOI={10.3389/fmats.2021.761229},\r\n    ISSN={2296-8016},\r\n}\r\n```","description_withheld":null,"homepage":"https://zenodo.org/record/4587827#.YhiqwYzMJaM","introduced_date":"2021-11-25","introduced_date_note":null,"introduced_by":null,"license":{"name":"Creative Commons Attribution Share Alike 4.0 International","url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"},{"name":"3D Semantic Segmentation","url":"/task/3d-semantic-segmentation","datasets_with_task":"/datasets/task/3d-semantic-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["GF-PA66 3D XCT"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/2d-semantic-segmentation-on-gf-pa66-3d-xct","task":"2D Semantic Segmentation","dataset_variant":"GF-PA66 3D XCT","rows":1,"metrics":["Jaccard (Mean)"],"first_row_in_archive_order":{"model":"Modular U-Net (2D)","paper":"/paper/a-modular-u-net-for-automated-segmentation-of","metrics":{"Jaccard (Mean)":"87"},"code_links":[{"title":"joaopcbertoldo/tomo2seg","url":"https://github.com/joaopcbertoldo/tomo2seg"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/a-modular-u-net-for-automated-segmentation-of","title":"A modular U-Net for automated segmentation of X-ray tomography images in composite materials","date":"2021-07-15","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."}