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data and checkpoints

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BENCHMARK.md
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## RETFound - Benckmark data split and model checkpoints
Here we provide data split and model checkpoints to facilitate model comparison. Please remember to accordingly change the data_path, task, and nb_classes for model fine-tuning and evaluation.
We provide data split and model checkpoints to facilitate model comparison. Please remember to adjust the data_path, task, and nb_classes for model fine-tuning and evaluation.
### Data split
| Dataset | Download Link 1 | Download Link 2 |
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### Official websites
APTOS2019: https://www.kaggle.com/competitions/aptos2019-blindness-detection/data
MESSIDOR2: https://www.adcis.net/en/third-party/messidor2/
IDRID: https://ieee-dataport.org/open-access/indian-diabetic-retinopathy-image-dataset-idrid
PAPILA: https://figshare.com/articles/dataset/PAPILA/14798004/1
Glaucoma_fundus: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/1YRRAC
JSIEC: https://zenodo.org/records/3477553
Retina: https://www.kaggle.com/datasets/jr2ngb/cataractdataset
OCTID: https://borealisdata.ca/dataverse/OCTID
- APTOS2019: https://www.kaggle.com/competitions/aptos2019-blindness-detection/data
- MESSIDOR2: https://www.adcis.net/en/third-party/messidor2/
- IDRID: https://ieee-dataport.org/open-access/indian-diabetic-retinopathy-image-dataset-idrid
- PAPILA: https://figshare.com/articles/dataset/PAPILA/14798004/1
- Glaucoma_fundus: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/1YRRAC
- JSIEC: https://zenodo.org/records/3477553
- Retina: https://www.kaggle.com/datasets/jr2ngb/cataractdataset
- OCTID: https://borealisdata.ca/dataverse/OCTID
README.md
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## RETFound - A foundation model for retinal imaging
This is the official repo for [RETFound: a foundation model for generalizable disease detection from retinal images](https://www.nature.com/articles/s41586-023-06555-x), which is based on [MAE](https://github.com/facebookresearch/mae):
Official repo for [RETFound: a foundation model for generalizable disease detection from retinal images](https://www.nature.com/articles/s41586-023-06555-x), which is based on [MAE](https://github.com/facebookresearch/mae):
Please contact **ykzhoua@gmail.com** or **yukun.zhou.19@ucl.ac.uk** if you have questions.