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
• —EarlyMildSpotting: 83
• —Fungal_Infected: 28
• —Tea Grey Blight: 53
• —Healthy: 473
• —MildEdgeDamage: 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 EarlyMildSpotting: 417
• —Hibiscus Fungal: 1,000
• —Tea Grey Blight: 1,000
• —Hibiscus Healthy: 1,000
• —Hibiscus MildEdge_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