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MedOtter/m2caiSeg

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Use restrictions

The declared licence (cc-by-nc-sa-4.0) is classified as having use restrictions.

Declared licence: cc-by-nc-sa-4.0, from the tagEvidence: README.md at 278babe
Licence files: No licence file at the top level of the repositoryEvidence: file list at 278babe
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Tasks

image-segmentation

Citation text from the card

Released under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).
The segmentation annotations are from the m2caiSeg dataset; the underlying video
frames are from the m2cai16 challenge (CAMMA, University of Strasbourg), released
under CC BY-NC-SA 4.0. Cite both:

- Maqbool, S., Riaz, A., Sajid, H., Hasan, O. "m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks." arXiv:2008.10134, 2020.
- 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)

**Changes made in this mirror:** the m2caiSeg images and class masks are repackaged
into HuggingFace parquet with train/test splits; a `class_mapping.json` index was
added. No pixel data or class labels were altered.

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dataset_licence({ "id": "MedOtter/m2caiSeg" })
signal: "restrictive"
stated_licence: "cc-by-nc-sa-4.0"
sources: 0