Real-Life Dataset of Tea Plant Leaf Disease Classification

Published: 20 November 2025| Version 2 | DOI: 10.17632/rrff4vb35m.2
Contributors:
Md Masum Billah,
,
,

Description

This dataset includes 967 images of tea leaves, categorised into five groups: Algal Leaf Spot (198 images), Brown Blight (192 images), Grey Blight (186 images), Healthy (200 images), and Red Leaf Spot (192 images). The images show tea leaves in various conditions, from healthy, disease-free leaves to those affected by different diseases. Algal Leaf Spot appears as yellowish lesions, Brown Blight causes brown, necrotic spots, Grey Blight shows greyish lesions, and Red Leaf Spot creates red circular spots. The healthy leaves are free from any visible issues. This diverse collection of images will help build a model that can accurately identify and classify different leaf diseases, contributing to better monitoring and care of tea plants. Additionally, the dataset includes a CSV file that contains the corresponding labels and metadata for all 967 images, making it easier to organise, analyse, and train machine learning models efficiently.

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Institutions

  • Daffodil International University
  • Jahangirnagar University

Categories

Disease, Machine Learning, Leaf Area, Deep Learning, Transfer Learning

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