---
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](https://github.com/DengPingFan/SINet)
(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:

```bibtex
@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](https://github.com/DengPingFan/SINet) for authoritative terms.