Jackfruit Leaf Disease Image Dataset: Four-Class Classification (Burn, Healthy, Red Rust, and Spot)

Published: 29 October 2025| Version 3 | DOI: 10.17632/kgcvfv63h2.3
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Description

This is the JackfruitVision Dataset, a comprehensive collection of 9,949 annotated images of jackfruit leaves and trees for machine learning-based disease detection. The dataset is organized into four distinct categories: Healthy Leaf, Red Rust (caused by Cephaleuros sp.), Spot Disease (caused by multiple fungi including Colletotrichum orbiculare) and burn. The collection includes an Original Set (approximately 2,020 images) and an Augmented Set (approximately 8,340 files) of resized images, making it immediately suitable for Deep Learning, Computer Vision, and transfer learning tasks like automated disease classification and image segmentation in agricultural AI applications. Dataset BreakDown: Original dataset: - burn leaf: 547 files - healthy leaf: 443 files - red rust: 503 files - spot: 569 files Augmented Data - burn resize: 2188 files - healthy resize: 1748 files - red rust resize: 2012 files - spot resize: 2392 files

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Institutions

  • Daffodil International University

Categories

Computer Vision, Image Processing, Machine Learning, Sustainable Agriculture, Deep Learning, Data Augmentation, Agriculture

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