Betel Leaf Image Dataset from Bangladesh

Published: 18 March 2024| Version 1 | DOI: 10.17632/g7fpgj57wc.1
Mohammad Rifat Ahmmad Rashid,


This dataset presents collection of images focused on betel leaves, aimed at categorizing them into four distinct conditions: healthy, dried, afflicted by bacterial disease, and suffering from fungal brown spot disease. Captured in Camperhat, Raipur, Lakshmipur, Bangladesh, this collection underscores a meticulous approach to data gathering for disease identification and classification in betel leaves. Organized into two primary folders, Original and Augmented, the dataset contains a total of 3589 images. The Original folder houses 1000 images, evenly distributed across the four leaf conditions to ensure a balanced representation. The Augmented folder, on the other hand, expands this dataset to include 2589 images, which are then divided into training (2388 images) and testing (201 images) subsets. This structure is designed to support the training of both deep learning and machine learning algorithms, with a clear aim towards the precise classification and recognition of the various states of betel leaf health.



East-West University


Agricultural Science, Computer Vision, Image Classification, Plant Diseases