Project-AgML/cotton_leaf_disease_classification

Cotton Leaf Disease Classification

A dataset for disease classification of cotton leaves. The dataset contains both the raw data and augmented version.
The raw data contains 1373 images distributed between the classes as follows:

• Alternaria Leaf Spot: 173 images
• Bacterial Blight: 218 images
• Fusarium Wilt: 337 images
• Healthy Leaf: 333 images
• Verticillium Wilt: 312 images

The augmented data contains 4963 images, again distributed as follows:

• Alternaria_Leaf: 987 images
• Bacterial_Blight: 1027 images
• Fusarium_Wilt: 957 images
• Healthy_Leaf: 1015 images
• Verticillium_Wilt: 977 images

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

Citation

@article{ripon2025cotton,
  title={Cotton leaf image dataset for disease classification and health monitoring},
  author={Ripon, Shamim and Gani, Raiyan and Niha, Nazratan Mazumder and Rahat, Wasimul Bari and Toufiq, Shafaeat Hasan and Maisha, Mushfida Ferdous and Ahmed, Jubaer},
  journal={Data in Brief},
  pages={112142},
  year={2025},
  publisher={Elsevier}
}

Ripon, Shamim; Gani , Raiyan ; Niha, Nazratan Mazumder ; Rahat, Wasimul Bari ; Toufiq, Shafaeat Hasan ; Maisha, Mushfida Ferdous ; Ahmed, Jubaer (2025), “Cotton Leaf Image Dataset for Disease Classification ”, Mendeley Data, V1, doi: 10.17632/t9hgvk2h9p.1