Upload README.md with huggingface_hub

README.md

@@ -1,24 +1,59 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: mask
-    dtype: image
-  splits:
-  - name: train
-    num_bytes: 945634413
-    num_examples: 3040
-  - name: test
-    num_bytes: 622780532
-    num_examples: 2026
-  download_size: 1568995436
-  dataset_size: 1568414945
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+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.