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---
language: en
license: mit
tags:
- fundus
- diabetic retinopathy
- classification
datasets:
- APTOS
- EYEPACS
- IDRID
- DDR
library: timm
model-index:
- name: vit_large_patch14_dinov2
results:
- task:
type: image-classification
dataset:
name: EYEPACS
type: EYEPACS
metrics:
- type: kappa
value: 0.7660728693008423
name: Quadratic Kappa
- task:
type: image-classification
dataset:
name: IDRID
type: IDRID
metrics:
- type: kappa
value: 0.7999367713928223
name: Quadratic Kappa
- task:
type: image-classification
dataset:
name: DDR
type: DDR
metrics:
- type: kappa
value: 0.7271304130554199
name: Quadratic Kappa
---
# Fundus DR Grading
[![Rye](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/rye/main/artwork/badge.json)](https://rye-up.com)
[![PyTorch](https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white)](https://pytorch.org/docs/stable/index.html)
[![Lightning](https://img.shields.io/badge/Lightning-792ee5?logo=lightning&logoColor=white)](https://lightning.ai/docs/pytorch/stable/)
## Description
This project aims to evaluate the performance of different models for the classification of diabetic retinopathy (DR) in fundus images. The reported perfomance metrics are not always consistent in the literature. Our goal is to provide a fair comparison between different models using the same datasets and evaluation protocol.