Project-AgML/pomegranate_disease_classification

Pomegranate Disease Classification

A dataset for disease classification of pomegranate.
The dataset contains 2,178 images.
Images per class:

• Colletotrichum spp: 571
• Ectomyelois ceratoniae: 555
• Healthy: 661
• Sunburn: 391

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

Citation

@article{mohammed2025pomegranate,
  title={Pomegranate disease detection and classification dataset for deep learning applications: A case study from Halabja city},
  author={Mohammed, Bashdar Abdalrahman and Abdalla, Peshraw Ahmed and Aziz, Sirwan M and Hassan, Hiwa Omer},
  journal={Data in Brief},
  pages={112298},
  year={2025},
  publisher={Elsevier}
}

Mohammed, B. A., Abdalla, P. A., & Hassan, H. O. (2025). Halabja Pomegranate Fruit Disease Image Dataset. Zenodo. https://doi.org/10.5281/zenodo.15856012