Project-AgML/LeafNet_plant_disease_classification

Leafnet Plant Disease Classification

This dataset comprises real-world RGB images of plant leaves, capturing both diseased and healthy specimens for disease detection tasks. Collected under typical agricultural imaging conditions, it provides a practical resource for developing computer vision models in plant pathology applications. The dataset contains 4,502 images across 2 classes: diseased, healthy.
Images per class:

• diseased: 2,225
• healthy: 2,277

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

Citation

<!-- TODO: add BibTeX citation -->

The dataset itself can be cited as:

Siddharth Singh Chouhan. (2022). A Database of Leaf Images: Practice towards Plant Conservation with Plant Pathology [Dataset]. Mendeley. https://doi.org/10.17632/HB74YNKJCN.5

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