File size: 2,137 Bytes
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license: cc-by-4.0
pretty_name: DeepFish
task_categories:
- image-classification
- image-segmentation
- object-detection
tags:
- underwater
- fish
- marine
- counting
- localization
size_categories:
- 10K<n<100K
---
# DeepFish
A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis.
About 40 thousand underwater images (1920 × 1080) from 20 habitats in the marine environments of tropical Australia,
with classification, point-level (localization/counting) and segmentation labels.
- **Paper:** [Scientific Reports, 2020](https://www.nature.com/articles/s41598-020-71639-x)
- **Code:** https://github.com/alzayats/DeepFish
- **Project page:** https://alzayats.github.io/DeepFish/
- **Original data record:** James Cook University, https://doi.org/10.25903/5f617fb6d6e0e
This repository is a mirror of the original `DeepFish.tar` for faster downloads worldwide.
The file is byte-identical to the one on the original data portal.
## Download
```bash
pip install -U huggingface_hub
hf download Alzayats/DeepFish DeepFish.tar DeepFish.tar.sha256 --repo-type dataset --local-dir .
sha256sum -c DeepFish.tar.sha256
tar xf DeepFish.tar
```
Interrupted downloads resume when you run the command again.
| File | Size | SHA-256 |
|------|------|---------|
| `DeepFish.tar` | 7.1 GiB (7,621,627,392 bytes) | `8acabb8a314fa8eb45fa9cc6829c84bdc127b1f8f605f2e152304e98b6dbb46c` |
## Structure
```
DeepFish/
Classification/ # fish / no-fish labels, per habitat
Localization/ # point-level annotations
Segmentation/ # segmentation masks
```
## License
CC BY 4.0. Data owners: Michael Bradley, James Cook University.
## Citation
```bibtex
@article{saleh2020realistic,
title={A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis},
author={Saleh, Alzayat and Laradji, Issam H and Konovalov, Dmitry A and Bradley, Michael and Vazquez, David and Sheaves, Marcus},
journal={Scientific Reports},
volume={10},
number={1},
pages={14671},
year={2020},
publisher={Nature Publishing Group UK London},
doi={10.1038/s41598-020-71639-x}
}
```
|