Eye Disease Classification Fundus is a medical vision dataset built for fundus image classification tasks. It aims to improve the classification ability of computer vision models in ophthalmic disease identification and assisted diagnosis scenarios, and is widely used in research areas such as medical image analysis, CNN model training, and intelligent ophthalmic assisted diagnosis. This dataset was collected by Sylhet Eye Hospital & Laser Centre and verified by specialist physicians. It contains 6,086 images, including four types of fundus images: cataracts, diabetic retinopathy, glaucoma, and normal fundus. The images are divided into training, validation, and test sets in an 80:10:10 ratio.

Citation

DOI (Digital Object Identifier):https://doi.org/10.34740/kaggle/dsv/15402471

@misc{munshaibur_rahman_mahin_2026,
title={Eye disease Classification Fundus image dataset},
url={https://www.kaggle.com/dsv/15402471},
DOI={10.34740/KAGGLE/DSV/15402471},
publisher={Kaggle},
author={Munshaibur Rahman Mahin},
year={2026}
}