Project-AgML/banana_disease_classification_tanzania

Banana Disease Classification Tanzania

A dataset for classification of banana leaf diseases. The dataset contains 16,092 images across 3 classes: black_sigatoka, fusarium_wilt, healthy.
Images per class:

• black_sigatoka: 5,767
• fusarium_wilt: 4,697
• healthy: 5,628

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

Citation

@article{mduma2023dataset,
  title={Dataset of banana leaves and stem images for object detection, classification and segmentation: A case of Tanzania},
  author={Mduma, Neema and Leo, Judith},
  journal={Data in Brief},
  volume={49},
  pages={109322},
  year={2023},
  publisher={Elsevier}
}

Mduma, N., Laizer, H., Loyani, L., Macheli, M., Msengi, Z., Karama, A., Msaki, I., Sanga, S., Jomanga, K., & Judith, L. (2022). The Nelson Mandela African Institution of Science and Technology Bananas dataset (Version V6) [dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/LQUWXW

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