---
license: cc-by-nc-4.0
pretty_name: "Do\u00f1ana National Park Dataset (DNP_DS)"
task_categories:
  - object-detection
size_categories:
  - 10K<n<100K
tags:
  - wildlife
  - camera-trap
  - yolo
---

# Doñana National Park Dataset (DNP_DS)

![License](https://img.shields.io/badge/license-CC--BY--NC--4.0-blue.svg)
[![WildINTEL](https://img.shields.io/badge/WildINTEL-project-blue)](https://wildintel.eu/)

Version: `1.0`

Camera-trap images from Doñana National Park (Spain) annotated with bounding boxes for object detection in YOLO format. It contains 33,914 images split into train, val and test, with 38,492 annotated objects of 15 animal categories (plus empty images): mammals identified to species or genus (e.g. Cervus elaphus, Dama dama, Sus scrofa, Vulpes vulpes, Lynx pardinus, Meles meles, Oryctolagus cuniculus), domestic animals (Bos taurus, Canis familiaris, Felis catus, Equus sp) and a general bird category (Ave). It is meant for training and evaluating wildlife detection models.

## Dataset format

This dataset is distributed in [YOLO](https://docs.ultralytics.com/datasets/) training format:
image files split into `train`/`val`/`test` sets, described by a `data.yaml` config.

It has 18 classes: Ave, Felis catus, Bos taurus, Canis familiaris, Herpestes ichneumon, Meles meles, Oryctolagus cuniculus, Dama dama, Genetta genetta, Equus sp, Homo sapiens, Lepus granatensis, Lynx pardinus, Cervus elaphus, Vulpes vulpes, Sus scrofa, Vehicle, Empty.

```text
.
├── data.yaml             ← YOLO dataset config (splits, classes)
├── images/
│   ├── train/            ← training images
│   ├── val/               ← validation images
│   └── test/              ← test images (if present)
├── labels/                ← training labels (if present in the source dataset)
│   ├── train/
│   ├── val/
│   └── test/
├── checksums-sha256.txt
├── CITATION.cff
└── LICENSE
```

The train split is too large
for a single Hugging Face Hub folder (10,000 files at most), so its images and labels are
spread over hash-named subfolders (e.g. `images/train/3f/img.jpg` with its label at
`labels/train/3f/img.txt`). YOLO trainers find them just the same: they look for images
recursively under each split's folder.


## Dataset statistics

| Split | Images | Labeled images | Objects |
|---|---:|---:|---:|
| train | 27467 | 27467 | 31962 |
| val | 3264 | 3264 | 3133 |
| test | 3183 | 3183 | 3397 |

| Class | Objects |
|---|---:|
| Ave | 2559 |
| Felis catus | 8 |
| Bos taurus | 6001 |
| Canis familiaris | 373 |
| Herpestes ichneumon | 844 |
| Meles meles | 2480 |
| Oryctolagus cuniculus | 1189 |
| Dama dama | 3862 |
| Genetta genetta | 398 |
| Equus sp | 7352 |
| Homo sapiens | 0 |
| Lepus granatensis | 1689 |
| Lynx pardinus | 28 |
| Cervus elaphus | 4521 |
| Vulpes vulpes | 3068 |
| Sus scrofa | 4120 |
| Vehicle | 0 |
| Empty | 0 |

## Integrity verification

`checksums-sha256.txt` lists the SHA-256 hash of every file in this export, to verify
nothing was corrupted or truncated after downloading.

## Source

Generated via [wildintel-publisher](https://github.com/wildintelproject/wildintel-publisher).

## Contributing

Questions, corrections and contributions to this dataset are welcome at https://wildintel.eu

## Funding

This work is part of the [WildINTEL project](https://wildintel.eu/), funded by the
[Biodiversa+](https://www.biodiversa.eu/) Joint Research Call 2022-2023
"Improved transnational monitoring of biodiversity and ecosystem change for science and society
(BiodivMon)". Biodiversa+ is the European co-funded biodiversity partnership supporting excellent
research on biodiversity with an impact for policy and society. Biodiversa+ is part of the European
Biodiversity Strategy for 2030 that aims to put Europe's biodiversity on a path to recovery by 2030
and is co-funded by the European Commission.

WildINTEL has been co-funded by the [European Commission](https://commission.europa.eu/) (GA No.
101052342) and the following funding organisations: [Agencia Estatal de Investigación](https://www.aei.gob.es/)
(Spain, PCI2023-145963-2, PCI2024-153489), [National Science Centre](https://www.ncn.gov.pl/?language=en)
(Poland, UMO-2023/05/Y/NZ8/00104), the [Research Council of Norway](https://www.forskningsradet.no/en/)
(Norway, NFR350962) and the [German Research Foundation](https://www.dfg.de/en/) (Germany).

Additional support was provided by Fundación Biodiversidad, Ministerio para la Transición Ecológica y el Reto Demográfico, Project AI-CENSUS and the Programa Operativo FEDER Andalucía 2014–2020, Project UHU-202028.

## License

This dataset is released under: `CC-BY-NC-4.0`. See the `LICENSE` file for the full text.

## Citation

To cite this dataset:

> Javier Calzada Samperio, Santiago Gutiérrez-Zapata, Simone Santoro, Manuel E. Gegundez-Arias, Iñaki Fernández de Viana, Lenka Straková, & Agata Kaczówka (2026). *Doñana National Park Dataset (DNP_DS)* (Version 1.0) [Data set]. University of Huelva. https://doi.org/10.5281/zenodo.616569 © 2026 University of Huelva

This citation was generated from the [`CITATION.cff`](CITATION.cff) file. See
[About CITATION files](https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-citation-files)
for more info.

## Limitations and ethical considerations

Before using this dataset, users should review possible limitations related to class
imbalance, annotation quality, environmental bias, and any privacy or sensitive
information the images may contain.