Project-AgML/rice_disease_classification_bangladesh

Rice Disease Classification

A dataset for image classification of Rice Disease. The dataset contains raw and augmented versions.
The raw dataset contains 2,769 images.
Images per class:

• Healthy: 603
• Insect: 281
• Leaf Scald: 421
• Rice: 16
• Rice Blast: 696
• Rice Leaffolder: 247
• Rice Stripes: 266
• Rice Tungro: 239

The augmented dataset contains 18,536 images.
Images per class:

• Healthy: 3,995
• Insect: 2,084
• Leaf scald: 2,619
• Rice: 128
• Rice Blast: 4,450
• Rice Leaffolder: 1,658
• Rice Stripes: 1,818
• Rice Tungro: 1,784

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

Citation

@article{hasan2025comprehensive,
  title={A comprehensive dataset of rice leaf images for disease detection using machine learning},
  author={Hasan, Afif and Layes, Tanvir Almas and Afridi, Arafat Sahin and Rifat, Shakhawath Hossain and Nur, Fernaz Narin and Moon, Nazmun Nessa},
  journal={Data in Brief},
  pages={111977},
  year={2025},
  publisher={Elsevier}
}

Rifat, Shakhawath Hossain; Layes, Tanvir Almas; Hasan, Afif; Mojumdar, Mayen Uddin (2024), “Rice Leaf Disease and Pest Dataset Overview”, Mendeley Data, V1, doi: 10.17632/vwv3nry3wr.1