Project-AgML/dragonfruit_disease_classification

Dragonfruit Disease Classificatio

A dataset for disease classification of dragonfruit. The dataset contains raw and augmented versions.
The raw dataset contains 4,497 images.
Images per class:

• Bad fruit: 307
• Bad leaf: 1,615
• Good fruit: 333
• Good leaf: 2,242

The augmented dataset contains 11,024 images.
Images per class:

• Bad fruit: 921
• Bad leaf: 4,834
• Good fruit: 999
• Good leaf: 4,270

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

Citation

@article{sarkar2025udcad,
  title={UDCAD-DFL-DL: A unique dataset for classifying and detecting agricultural diseases in dragon fruits and leaves},
  author={Sarkar, Pronob Chandra and Pranta, Gourab Kumar and Mojumdar, Mayen Uddin and Mahmud, Arif and Noori, Sheak Rashed Haider and Chakraborty, Narayan Ranjan},
  journal={Data in Brief},
  volume={59},
  pages={111411},
  year={2025},
  publisher={Elsevier}
}

Sarkar, Pronob; Pranta, Gourab Kumar ; Mojumdar, Mayen Uddin (2024), “Dragon fruit & leaf Dataset from Bangladesh for Classification and Ecological Research”, Mendeley Data, V1, doi: 10.17632/cfchfdpfw5.1