wildintelproject/examplewildlifedetectiondataset

Example Wildlife Detection Dataset

Version: 3.0

A small, synthetic camera-trap object-detection dataset (deer/fox/bird) used as a wildintel-publisher example. Not real field data; the images are generated placeholders, not photographs.

Dataset format

This dataset is distributed in YOLO training format: image files split into train/val/test sets, described by a data.yaml config.

It has 3 classes: deer, fox, bird.

.
├── 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

Dataset statistics

Split	Images	Labeled images	Objects
train	4	4	4
val	2	2	2
test	2	2	2

Class	Objects
deer	4
fox	2
bird	2

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.

Contributing

Questions, corrections and contributions to this dataset are welcome at https://github.com/wildintelproject/wildintel-publisher

Funding

This work is part of the WildINTEL project, funded by the Biodiversa+ 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 (GA No. 101052342) and the following funding organisations: Agencia Estatal de Investigación (Spain, PCI2023-145963-2, PCI2024-153489), National Science Centre (Poland, UMO-2023/05/Y/NZ8/00104), the Research Council of Norway (Norway, NFR350962) and the German Research Foundation (Germany).

License

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

Citation

To cite this dataset:

Jane Researcher (2026). Example Wildlife Detection Dataset (Version 3.0) [Data set]. Institute of Nature Conservation PAS. https://doi.org/10.5281/zenodo.609082 © 2026 University of Huelva

This citation was generated from the CITATION.cff file. See 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.