README.md

metadata

license: cc-by-nc-4.0
pretty_name: COD10K
task_categories:
  - image-segmentation
tags:
  - camouflaged-object-detection
  - binary-segmentation
  - saliency
size_categories:
  - 1K<n<10K

COD10K (Camouflaged Object Detection 10K)

This dataset contains the COD10K subset for camouflaged object detection, packaged from the SINet repository (DengPingFan/SINet). Each example is a natural image paired with a binary ground-truth object mask.

Contents

Only the COD10K portion of the SINet train/test bundles is included here. The SINet distribution also ships CAMO and CHAMELEON samples; those were excluded:

• train: 3040 COD10K samples (the 1000 CAMO camourflage_* samples bundled in the SINet TrainDataset were filtered out).
• test: 2026 COD10K samples (the CAMO (251) and CHAMELEON (77) test sets bundled in the SINet TestDataset were filtered out).

Features

• image: the RGB input image (datasets.Image).
• mask: the binary ground-truth object segmentation mask (datasets.Image, mode L).

Edge/instance maps that ship with COD10K are not included; only the binary object mask is provided as mask.

Citation

If you use this dataset, please cite the COD10K paper:

@inproceedings{fan2020camouflaged,
  title={Camouflaged Object Detection},
  author={Fan, Deng-Ping and Ji, Ge-Peng and Sun, Guolei and Cheng, Ming-Ming and Shen, Jianbing and Shao, Ling},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2020}
}

License

Released for academic / research (non-commercial) use, following the terms of the original COD10K / SINet release. No explicit SPDX license is provided by the authors; this repository is tagged cc-by-nc-4.0 to reflect the non-commercial, attribution-based terms. Please refer to the original repository for authoritative terms.