Datasets:

Project-AgML
/

african_plum_grading_classification

configs:
  - config_name: default
    default: true
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': bruised
              '1': cracked
              '2': rotten
              '3': spotted
              '4': unaffected
              '5': unripe
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K

African Plum Grading Classification

A dataset for grade classification of plums. The dataset contains 4,507 images across 6 classes: bruised, cracked, rotten, spotted, unaffected, unripe. Images per class:

bruised: 319
cracked: 162
rotten: 720
spotted: 759
unaffected: 1,721
unripe: 826

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

Citation

@article{fadja2025dataset,
  title={A dataset of annotated African plum images from Cameroon for AI-based quality assessment},
  author={Fadja, Arnaud Nguembang and Tagni, Armel Gabin Fameni and Che, Sain Rigobert and Atemkeng, Marcellin},
  journal={Data in Brief},
  volume={59},
  pages={111351},
  year={2025},
  publisher={Elsevier}
}

Arnaud Nguembang Fadja, and Armel Gabin Fameni Tagni. (2024). African Plums Dataset [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/9694239