Eggplant Leaf Disease Classification Dataset

Published: 21 November 2024| Version 2 | DOI: 10.17632/pvsv534ccg.2
Contributors:
Rakibul Haque Rabbi,
,
,

Description

Dataset Overview: It contains 2991 high-resolution images of eggplant leaves. Images were collected from the Changao, Paragram, Ashulia, Dhaka, and Narsingdi regions of Bangladesh. Data was gathered between October 20 and November 2, 2024, over a period of 13 days. Classes: Cercospora: 628 images Curl: 284 images Flea Beetles: 84 images Hadda Beetles: 530 images Healthy: 188 images LeafhopperJassids: 38 images Magnesium Deficiency: 50 images Phomposist Blast: 218 images TMV (Tobacco Mosaic Virus): 356 images Tobacco Caterpillar: 452 images Verticillium Wilt: 163 images Purpose: Supports the advancement of automated agricultural disease detection systems. It aims to assist in the early detection and management of eggplant leaf diseases. Enables the development of reliable diagnostic tools using machine learning and image processing techniques. Promotes better crop management, increased yield, and reduced pesticide use, contributing to sustainable agricultural practices. Serves as a resource for developing and evaluating image-based disease recognition models and deep learning applications in agriculture.

Files

Institutions

Daffodil International University

Categories

Image Classification, Agriculture

Licence