yunusserhat/tea_sickness_dataset

Tea Sickness Dataset

This dataset contains images of tea leaves affected by seven common diseases, along with healthy examples. It is designed for use in machine learning tasks such as classification, particularly leveraging transfer learning techniques.

Dataset Summary

The dataset includes tea leaves from eight categories:

Label ID	Class Name
0	Anthracnose
1	Algal Leaf Spot
2	Bird Eye Spot
3	Brown Blight
4	Gray Blight
5	Healthy
6	Red Leaf Spot
7	White Spot

Each class contains more than 100 images, captured from tea plants in the Johnstone Boiyon farm, Koiwa location, Bomet County, using a clone of 1510. The dataset is useful for developing models that can predict the presence of diseases in tea leaves, particularly in agricultural and sustainability contexts.

Dataset Structure

Features

• image: An RGB image of a tea leaf (PIL Image format)
• label: Class label as integer (0–7) with corresponding disease names

Splits

Split	Number of Examples	Size (Bytes)
Train	708	622,082,045
Validation	88	79,334,678
Test	89	79,495,048
Total	885	780,911,771

Usage

This dataset is suitable for:

• Fine-tuning image classification models
• Research on plant disease detection
• Transfer learning and domain adaptation experiments

Citation

If you use this dataset in your research, please cite it as:

@article{kimutai2022tea,
  title     = {Tea sickness dataset},
  author    = {Kimutai, Gibson and Förster, Anna},
  journal   = {Mendeley Data},
  volume    = {2},
  year      = {2022},
  doi       = {10.17632/j32xdt2ff5.2}
}

License

CC BY 4.0 — You are free to use, share, and adapt the dataset, provided appropriate credit is given.

Acknowledgements

This dataset was collected by researchers from the University of Rwanda and the University of Bremen. We thank the contributors for making the dataset publicly available to advance agricultural AI applications.