Project-AgML/tea_sickness_classification

Tea Sickness Classification

This dataset contains real field images of tea leaves affected by various diseases, collected in tea gardens across Anhui Province, China. Images were captured using a handheld iPhone 14 Pro Max with RGB imaging during October 2023, providing practical examples for agricultural disease detection research. The dataset contains 885 images across 8 classes: Anthracnose, algal leaf, bird eye spot, brown blight, gray light, healthy, red leaf spot, white spot.
Images per class:

• Anthracnose: 100
• algal leaf: 113
• bird eye spot: 100
• brown blight: 113
• gray light: 100
• healthy: 74
• red leaf spot: 143
• white spot: 142

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

Citation

@article{yang2025lightweight,
  title={Lightweight wavelet-CNN tea leaf disease detection},
  author={Yang, Jing and Xu, GaoJian and Yang, MengDao and Lin, ZhengPei},
  journal={PLOS One},
  volume={20},
  pages={e0323322},
  year={2025},
  publisher={Public Library of Science}
}

The dataset itself can be cited as:

Gibson Kimutai. (2022). tea sickness dataset [Dataset]. Mendeley. https://doi.org/10.17632/J32XDT2FF5.2

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