README.md

---
configs:
- config_name: augmented
  data_files:
  - split: train
    path: augmented/train-*
- config_name: raw
  data_dir: raw
  default: true
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 10K<n<100K
dataset_info:
- config_name: augmented
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Healthy_Leaf
          '1': Leaf_Rot
          '2': Leaf_Spot
  splits:
  - name: train
    num_bytes: 1176728136
    num_examples: 10185
  download_size: 1194701007
  dataset_size: 1176728136
- config_name: raw
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Healthy_Leaf
          '1': Leaf_Rot
          '2': Leaf_Spot
  splits:
  - name: train
    num_bytes: 212668378
    num_examples: 2037
  download_size: 202720575
  dataset_size: 212668378
---

# 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