Project-AgML/Luffa_disease_classification

Luffa Disease Classification

This dataset provides real field images of luffa plants with disease symptoms, collected in Bangladesh using a handheld smartphone during October 2023. Captured in natural agricultural environments, the images offer a practical resource for developing computer vision models focused on crop disease classification. The dataset contains 1,227 images across 5 classes: Alternaria, Angular Spot, Fresh, Holed, Mosaic Virus.
Images per class:

• Alternaria: 270
• Angular Spot: 238
• Fresh: 256
• Holed: 222
• Mosaic Virus: 241

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

Citation

@article{sheikh2024luffafolio,
  title={LuffaFolio: A Multidimensional Image Dataset of Smooth Luffa},
  author={Sheikh, Md Ripon and Islam, Md. Masudul and Himel, Galib Muhammad Shahriar},
  journal={Data in Brief},
  volume={53},
  pages={110149},
  year={2024},
  publisher={Elsevier}
}

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