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Project-AgML/RoCoLe_disease_detection

RoCoLe Disease Detection A dataset for detection of Robusta coffee leaf diseases. The dataset contains 1,560 images with 1,560 bounding box annotations across 6 categories, as well as segmentation masks. This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. Citation @article{parraga2019rocole, title={RoCoLe: A robusta coffee leaf images dataset for evaluation of machine learning based methods in plant diseases… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/RoCoLe_disease_detection.

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RoCoLe Disease Detection

A dataset for detection of Robusta coffee leaf diseases. The dataset contains 1,560 images with 1,560 bounding box annotations across 6 categories, as well as segmentation masks.

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

Citation

bibtex

@article{parraga2019rocole,
  title={RoCoLe: A robusta coffee leaf images dataset for evaluation of machine learning based methods in plant diseases recognition},
  author={Parraga-Alava, Jorge and Cusme, Kevin and Loor, Ang{\'e}lica and Santander, Esneider},
  journal={Data in brief},
  volume={25},
  pages={104414},
  year={2019},
  publisher={Elsevier}
}

Parraga-Alava, Jorge; Cusme, Kevin; Loor, Angélica; Santander, Esneider (2019), “RoCoLe: A robusta coffee leaf images dataset ”, Mendeley Data, V2, doi: 10.17632/c5yvn32dzg.2

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