Datasets:

Project-AgML
/

rice_seedling_classification

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

@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