Project-AgML/pepper_disease_pest_classification

Pepper Disease Pest Classification

The dataset comprises real RGB images of pepper plants in field environments, collected over two years (2022-2023) in Shouguang City, China. Captured using a fixed platform setup, the images provide consistent visual data for computer vision research focused on agricultural disease detection in pepper crops. The dataset contains 26,377 images across 5 classes: Alternaria_Boltch, Brown_Spot, Grey_spot, Mosaic, Rust.
Images per class:

• Alternaria_Boltch: 5,343
• Brown_Spot: 5,655
• Grey_spot: 4,810
• Mosaic: 4,875
• Rust: 5,694

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

Citation

@article{wang2025advanced,
  title={An advanced deep learning method for pepper diseases and pests detection},
  author={Wang, Xuewei and Liu, Jun and Chen, Qian},
  journal={Plant Methods},
  volume={21},
  pages={70},
  year={2025},
  publisher={BioMed Central}
}

liu, jun (2024), “vegetable disease”, Mendeley Data, V1, doi: 10.17632/tg3z7xxkdb.1

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