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---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': clustered
          '1': single
          '2': undefined
  splits:
  - name: train
    num_bytes: 42747333
    num_examples: 5364
  download_size: 37739572
  dataset_size: 42747333
---

# Rice Seedling Classification

A dataset for image classification of Rice Seedlings.  The dataset contains 5,364 images across 3 classes: clustered, single, undefined.
Images per class:
- clustered: 1,437
- single: 1,367
- undefined: 2,560

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

## Citation

```bibtex
@article{luu2024rigad,
  title={RiGaD: An aerial dataset of rice seedlings for assessing germination rates and density},
  author={Luu, Trong Hieu and Cao, Hoang-Long and Ngo, Quang Hieu and Nguyen, Thanh Tam and El Makrini, Ilias and Vanderborght, Bram},
  journal={Data in Brief},
  volume={57},
  pages={111118},
  year={2024},
  publisher={Elsevier}
}
```

Luu, T. H., Cao, H. L., Ngo, Q. H., Nguyen, T. T., El Makrini, I., & Vanderborght, B. (2024). RiGaD: An aerial dataset of rice seedlings for assessing germination rates and density. Zenodo. https://doi.org/10.5281/zenodo.11658969