Datasetpublic

Project-AgML/tree_species_classification_slovak_normal_cropped

Tree Species Classification Slovak Normal Cropped This dataset provides real RGB images of tree species collected in natural field environments across Slovakia and the Czech Republic. Images were captured using handheld cameras (Sony Alpha 7 and Canon EOS 4000D) during field surveys in June and August 2022. The dataset contains 1,367 images across 4 classes: European beech, European silver fir, Norway spruce, Sessile oak.Images per class: European beech: 300 European silver… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/tree_species_classification_slovak_normal_cropped.

sourceHugging Facecc-by-4.0updated 10h agoView on Hugging Face

0likes28downloads

Dataset Card

Tree Species Classification Slovak Normal Cropped

This dataset provides real RGB images of tree species collected in natural field environments across Slovakia and the Czech Republic. Images were captured using handheld cameras (Sony Alpha 7 and Canon EOS 4000D) during field surveys in June and August 2022. The dataset contains 1,367 images across 4 classes: European beech, European silver fir, Norway spruce, Sessile oak. Images per class:

—European beech: 300
—European silver fir: 337
—Norway spruce: 396
—Sessile oak: 334

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

bibtex

@article{surendran2025forestry,
  title={A forestry investigation: Exploring factors behind improved tree species classification using bark images},
  author={Surendran, Gokul Kottilapurath and Deekshitha, and Lukac, Martin and Lukac, Martin and Vybostok, Jozef and Mokros, Martin},
  journal={Ecological Informatics},
  volume={85},
  pages={102932},
  year={2025},
  publisher={Elsevier}
}

Kottilapurath Surendran, G., & Mokroš, M. (2024). Slovak normal cropped dataset [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.14228004

This dataset was reformatted from its original format to match HuggingFace standards.