Eggplant Leaf Disease Classification Dataset

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.