Hibiscus Leaf Diseases Classification Dataset

Published: 28 July 2025| Version 2 | DOI: 10.17632/k8pp8cbp8k.2
Contributors:
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Description

The Hibiscus Leaf Diseases Classification Dataset features 1,101 high-quality JPEG images (560×420 pixels) of hibiscus leaves, collected from a variety of locations across Bangladesh, including Dhaka, Khulna, Rajshahi, and other diverse growing regions. The dataset was created to help classify leaves into eight categories based on their condition: healthy (473 images), mild edge damage (226), citruspot (150), slidely disease (109), early mild spotting (83), fungal infected (28), senescent (30), and wrinkled (26). These images were captured in natural outdoor lighting using both smartphones and DSLR cameras, offering a realistic and varied visual set. By reflecting the natural diversity and challenges found in the field, this dataset provides a practical and valuable foundation for researchers and developers working on plant disease detection, image classification, and innovative agriculture tools.

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Institutions

  • Daffodil International University
  • Jahangirnagar University

Categories

Disease, Leaf Area, Convolutional Neural Network, Deep Learning, Agriculture

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