Project-AgML/tea_leaf_disease_classification_bangladesh_2

Tea Leaf Disease Classification Bangladesh 2

This dataset provides real field images of tea leaves from Habiganj district, Sylhet, Bangladesh, capturing various disease conditions affecting tea crops in natural agricultural settings. Images were collected using a handheld iPhone 12 Pro Max with RGB sensors during the spring and early summer of 2025, reflecting typical field conditions in tea gardens. The dataset contains 2,500 images across 4 classes: Blight, Healthy_Leaf, Helopeltis, Red_Rust.
Images per class:

• Blight: 555
• Healthy_Leaf: 650
• Helopeltis: 675
• Red_Rust: 620

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

Citation

@article{chowdhury2026curated,
  title={A curated dataset and lightweight deep learning framework for tea leaf disease classification},
  author={Chowdhury, Sakibul Hasan and Arman, Md Shohel and Siam, Masrafe Bin Hannan and Khan, Md Rayhan and Hasan, Afia and Fahim, Parvez Ahmed Moju},
  journal={PLOS One},
  volume={21},
  pages={e0349210},
  year={2026},
  publisher={Public Library of Science}
}

The dataset itself can be cited as:

Chowdhury, S. H., & Arman, M. S. (2025). Tea Leaf Disease Image Dataset for Automated Classification of Tea Garden Diseases [Dataset]. Mendeley Data. https://doi.org/10.17632/3X42RBJ8YV.1

This dataset was reformatted from its original format to match HuggingFace standards.