{
 "id": "MedOtter/m2caiSeg",
 "owner": "MedOtter",
 "name": "m2caiSeg",
 "downloads": 134,
 "likes": 0,
 "last_modified": "2026-07-13T23:24:12.000Z",
 "stated_licence": "cc-by-nc-sa-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "image-segmentation"
 ],
 "citation": "Released under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).\nThe segmentation annotations are from the m2caiSeg dataset; the underlying video\nframes are from the m2cai16 challenge (CAMMA, University of Strasbourg), released\nunder CC BY-NC-SA 4.0. Cite both:\n\n- Maqbool, S., Riaz, A., Sajid, H., Hasan, O. \"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks.\" arXiv:2008.10134, 2020.\n- Twinanda, A. P., et al. \"EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos.\" IEEE Transactions on Medical Imaging, 36(1):86-97, 2017. (m2cai16 / Cholec source, CAMMA)\n\n**Changes made in this mirror:** the m2caiSeg images and class masks are repackaged\ninto HuggingFace parquet with train/test splits; a `class_mapping.json` index was\nadded. No pixel data or class labels were altered.",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-sa-4.0) is classified as having use restrictions.",
 "revision": "278babe5c874a334a1485bd184f8482fe5635358",
 "stated_evidence": "https://huggingface.co/datasets/MedOtter/m2caiSeg/blob/278babe5c874a334a1485bd184f8482fe5635358/README.md",
 "file_evidence": "https://huggingface.co/datasets/MedOtter/m2caiSeg/tree/278babe5c874a334a1485bd184f8482fe5635358",
 "card_nc": false
}