Project-AgML/MH_SoyaHealthVision_disease_classification_uav

MH SoyaHealthVision Disease Classification UAV

A dataset for disease classification of soybean leaves. The dataset contains 2,842 images across 4 classes: Healthy, Mosaic, Rust, Semilooper_Pest.
Images per class:

• Healthy: 280
• Mosaic: 772
• Rust: 1,000
• Semilooper_Pest: 790

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

Citation

@article{shinde2025indian,
  title={An Indian UAV and leaf image dataset for integrated crop health assessment of soybean crop},
  author={Shinde, Sayali and Attar, Vahida},
  journal={Data in Brief},
  volume={60},
  pages={111517},
  year={2025},
  publisher={Elsevier}
}

Shinde, Sayali; Attar, Dr.Vahida; Technological University,Pune, COEP ; Technology Innovation Hub, Indian Statistical Institute Kolkata, IDEAS (2024), “MH-SoyaHealthVision: An Indian UAV and Leaf Image Dataset for Integrated Crop Health Assessment”, Mendeley Data, V1, doi: 10.17632/hkbgh5s3b7.1