Project-AgML/RoseNet_leaf_disease_classification

RoseNet Leaf Disease Classification

A dataset for disease classification of rose leaves. The dataset contains raw and augmented versions.
The raw dataset contains 917 images.
Images per class:

• Black Spot: 313
• Downy Mildew: 200
• Fresh Leaf: 404

The augmented dataset contains 4,342 images.
Images per class:

• Black Spot: 1,434
• Downy mildew: 1,478
• Fresh Leaf: 1,430

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

Citation

@article{sazzad2022rosenet,
  title={RoseNet: Rose leave dataset for the development of an automation system to recognize the diseases of rose},
  author={Sazzad, Sadia and Rajbongshi, Aditya and Shakil, Rashiduzzaman and Akter, Bonna and Kaiser, M Shamim},
  journal={Data in Brief},
  volume={44},
  pages={108497},
  year={2022},
  publisher={Elsevier}
}

Rajbongshi, Aditya; Sazzad, Sadia ; Shakil, Rashiduzzaman ; Akter, Bonna ; Kaiser, M Shamim (2022), “FlowerNet: An extensive rose leaves dataset for disease recognition applying machine learning and deep learning models”, Mendeley Data, V2, doi: 10.17632/7z67nyc57w.2