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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… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/betel_leaf_disease_classification_2.

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Dataset Card

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

bibtex

@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