---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: meter
    dtype: string
  - name: year
    dtype: string
  - name: location
    dtype: string
  splits:
  - name: train
    num_bytes: 2452931993
    num_examples: 311
  download_size: 2452976754
  dataset_size: 2452931993
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
size_categories:
- n<1K
---
# Interdupa Uav

This dataset provides real-world RGB imagery of intercropped durian and papaya trees in agricultural fields of Chau Thanh, Hau Giang, Vietnam. Captured using a DJI Phantom 4 Pro UAV equipped with a high-resolution RGB camera during multiple field campaigns in late 2023 and early 2024, it offers diverse aerial perspectives for agricultural monitoring applications. The dataset contains 311 images with no classification, segmentation, or bounding-box annotations.

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

## Citation

```bibtex
@article{ngo2025interdupa,
  title={InterDuPa-UAV: A UAV-based dataset for the classification of intercropped durian and papaya trees},
  author={Ngo, Quang Hieu and Luu, Trong Hieu and Nguyen, Phuc Vinh and El Makrini, Ilias and Vanderborght, Bram and Cao, Hoang-Long},
  journal={Data in Brief},
  volume={61},
  pages={111843},
  year={2025},
  publisher={Elsevier}
}
```

Luu, T. H., Ngo, Q. H., Cao, H.-L., Vanderborght, B., & El Makrini, I. (2025). InterDuPa-UAV: A UAV-based Dataset for the Classification of Intercropped Durian and Papaya Trees [Dataset]. In Science & Technology Asia (Vol. 29, Issue 4, pp. 128–137). Zenodo. https://doi.org/10.5281/zenodo.15664908

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