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RoCoLe: A robusta coffee leaf images dataset for evaluation of machine learning based methods in plant diseases recognition.

ABSTRACT: In this article we introduce a robusta coffee leaf images dataset called RoCoLe. The dataset contains 1560 leaf images with visible red mites and spots (denoting coffee leaf rust presence) for infection cases and images without such structures for healthy cases. In addition, the data set includes annotations regarding objects (leaves), state (healthy and unhealthy) and the severity of disease (leaf area with spots). Images were all obtained in real-world conditions in the same coffee plants field using a smartphone camera. RoCoLe data set facilitates the evaluation of the performance of machine learning algorithms used in image segmentation and classification problems related to plant diseases recognition. The current dataset is freely and publicly available at https://doi.org/10.17632/c5yvn32dzg.2.

SUBMITTER: Parraga-Alava J

PROVIDER: S-EPMC6727496 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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RoCoLe: A <i>robusta</i> coffee leaf images dataset for evaluation of machine learning based methods in plant diseases recognition.

Parraga-Alava Jorge J Cusme Kevin K Loor Angélica A Santander Esneider E

Data in brief 20190819

In this article we introduce a <i>robusta</i> coffee leaf images dataset called RoCoLe. The dataset contains 1560 leaf images with visible red mites and spots (denoting coffee leaf rust presence) for infection cases and images without such structures for healthy cases. In addition, the data set includes annotations regarding objects (leaves), state (healthy and unhealthy) and the severity of disease (leaf area with spots). Images were all obtained in real-world conditions in the same coffee plan ...[more]

PMID: 31516934

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