---
language: en
license: mit
tags:
- fundus
- diabetic retinopathy
- classification
datasets:
- APTOS
- EYEPACS
- IDRID
- DDR
library: timm
model-index:
- name: convnext_small
  results:
  - task:
      type: image-classification
    dataset:
      name: EYEPACS
      type: EYEPACS
    metrics:
    - type: kappa
      value: 0.789091944694519
      name: Quadratic Kappa
  - task:
      type: image-classification
    dataset:
      name: IDRID
      type: IDRID
    metrics:
    - type: kappa
      value: 0.7588151097297668
      name: Quadratic Kappa
  - task:
      type: image-classification
    dataset:
      name: DDR
      type: DDR
    metrics:
    - type: kappa
      value: 0.8041317462921143
      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.