Project-AgML/Hibiscus_Tea_disease_classification

Hibiscus Tea Disease Classification

A dataset for disease classification of Hibiscus and Tea leaves. The dataset contains raw and augmented versions.
The raw dataset contains 1,411 images.
Images per class:

• Tea Algal Spot: 54
• Tea Brown Blight: 48
• Citruspot: 150
• Early_Mild_Spotting: 83
• Fungal_Infected: 28
• Tea Grey Blight: 53
• Healthy: 473
• Mild_Edge_Damage: 226
• Tea Red Spot: 44
• Senescent: 40
• Slightly_Diseased: 109
• Wrinkled_Leaf: 55

The augmented dataset contains 12,417 images.
Images per class:

• Tea Algal Spotout: 1,000
• Tea Brown Blight: 1,000
• Hibiscus Citruspot: 1,000
• Hibiscus Early_Mild_Spotting: 417
• Hibiscus Fungal: 1,000
• Tea Grey Blight: 1,000
• Hibiscus Healthy: 1,000
• Hibiscus Mild_Edge__Damage: 1,000
• Tea Red Spot: 1,000
• Hibiscus Senescent: 1,000
• Hibiscus Slightly_Diseased: 1,000
• Hibiscus Wrinkled_Leaf: 1,000

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

Citation

@article{billah2025comprehensive,
  title={A comprehensive combined dataset on Hibiscus and Tea plant leaf disease images for classifications.},
  author={Billah, Md Masum and Sagor, Saifuddin and Uddin, Mohammad Shorif},
  journal={Data in Brief},
  pages={112357},
  year={2025},
  publisher={Elsevier}
}

Billah, Md Masum; Sagor, Saifuddin ; Shorif Uddin, Mohammad; Hossain, Shahariar (2025), “A Real-World Hibiscus and Tea Leaf Image Dataset for Classification”, Mendeley Data, V4, doi: 10.17632/5bzy89brkv.4