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---
language: en
license: mit
tags:
- fundus
- diabetic retinopathy
- classification
datasets:
- APTOS
- EYEPACS
- IDRID
- DDR
library: timm
model-index:
- name: vit_base_patch14_reg4_dinov2.lvd142m
results:
- task:
type: image-classification
dataset:
name: EYEPACS
type: EYEPACS
metrics:
- type: kappa
value: 0.778820276260376
name: Quadratic Kappa
- task:
type: image-classification
dataset:
name: IDRID
type: IDRID
metrics:
- type: kappa
value: 0.7805078029632568
name: Quadratic Kappa
- task:
type: image-classification
dataset:
name: DDR
type: DDR
metrics:
- type: kappa
value: 0.7986723184585571
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.