Project-AgML/YOLOv8_PlantDisease_classification

Yolov8 Plantdisease Classification

This dataset provides real RGB images of tomato, potato, and pepper plants exhibiting various disease symptoms, captured in a controlled laboratory environment. It serves as a resource for training and evaluating computer vision models in agricultural disease detection applications. The dataset contains 20,638 images across 15 classes: Pepper__bell___Bacterial_spot, Pepper__bell___healthy, Potato___Early_blight, Potato___Late_blight, Potato___healthy, Tomato_Bacterial_spot, Tomato_Early_blight, Tomato_Late_blight, Tomato_Leaf_Mold, Tomato_Septoria_leaf_spot, Tomato_Spider_mites_Two_spotted_spider_mite, Tomato__Target_Spot, Tomato__Tomato_YellowLeaf__Curl_Virus, Tomato__Tomato_mosaic_virus, Tomato_healthy.
Images per class:

• Pepper__bell___Bacterial_spot: 997
• Pepper__bell___healthy: 1,478
• Potato___Early_blight: 1,000
• Potato___Late_blight: 1,000
• Potato___healthy: 152
• Tomato_Bacterial_spot: 2,127
• Tomato_Early_blight: 1,000
• Tomato_Late_blight: 1,909
• Tomato_Leaf_Mold: 952
• Tomato_Septoria_leaf_spot: 1,771
• Tomato_Spider_mites_Two_spotted_spider_mite: 1,676
• Tomato__Target_Spot: 1,404
• Tomato__Tomato_YellowLeaf__Curl_Virus: 3,208
• Tomato__Tomato_mosaic_virus: 373
• Tomato_healthy: 1,591

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

The original train/test/val split has been preserved in the split column.

Citation

@article{hasani2026comparative,
  title={Comparative evaluation of deep learning models for plant disease classification with edge-aware performance analysis},
  author={Hasani, Zirije and Fondaj, Jakup and Bytyqi, Dionesa and Misini, Sufjan},
  journal={PLOS One},
  volume={21},
  pages={e0349901},
  year={2026},
  publisher={Public Library of Science}
}

The dataset itself can be cited as:

Bytyçi, D., Hasani, Z., Fondaj, J., & Misini, S. (2026). Dataset, Source Code, and Models for: Deep Learning-based Plant Disease Detection using YOLOv8 [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.18895667

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