Project-AgML/betel_leaf_disease_classification_2

Betel Leaf Classification

A dataset for image classification of Betel Leaf. The dataset contains raw and augmented versions.
The raw dataset contains 2,037 images.
Images per class:

• Healthy_Leaf: 1,080
• Leaf_Rot: 269
• Leaf_Spot: 688

The augmented dataset contains 10,185 images.
Images per class:

• Healthy_Leaf: 5,400
• Leaf_Rot: 1,345
• Leaf_Spot: 3,440

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

Citation

@article{hridoy2025comprehensive,
  title={A comprehensive image dataset for accurate diagnosis of betel leaf diseases using artificial intelligence in plant pathology},
  author={Hridoy, Rashidul Hasan and Habib, Md Tarek and Mahmud, Imran and Haque, Aminul and Al Mamun, Md Abdulla},
  journal={Data in Brief},
  volume={60},
  pages={111564},
  year={2025},
  publisher={Elsevier}
}```

Hridoy, Rashidul Hasan; Habib, Md Tarek; Mahmud, Imran; Haque, Aminul; Mamun, Md Abdulla Al (2025), “Comprehensive Betel Leaf Disease Dataset for Advanced Pathology Research ”, Mendeley Data, V1, doi: 10.17632/vpzkntzjty.1