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---
language: en
license: mit
tags:
- fundus
- diabetic retinopathy
- classification
datasets:
- APTOS
- EYEPACS
- IDRID
- DDR
library: timm
model-index:
- name: swinv2_large_window12to16_192to256.ms_in22k_ft_in1k
results:
- task:
type: image-classification
dataset:
name: EYEPACS
type: EYEPACS
metrics:
- type: kappa
value: 0.7938311696052551
name: Quadratic Kappa
- task:
type: image-classification
dataset:
name: IDRID
type: IDRID
metrics:
- type: kappa
value: 0.768999457359314
name: Quadratic Kappa
- task:
type: image-classification
dataset:
name: DDR
type: DDR
metrics:
- type: kappa
value: 0.7947348952293396
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.
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