https://github.com/parap1uie-s/synfundus-1m
SynFundus-1M is a synthetic fundus image dataset consisting of millions of images and extensive annotations that can help improve the performance of diagnostic models.
https://github.com/parap1uie-s/synfundus-1m
Last synced: 5 months ago
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SynFundus-1M is a synthetic fundus image dataset consisting of millions of images and extensive annotations that can help improve the performance of diagnostic models.
- Host: GitHub
- URL: https://github.com/parap1uie-s/synfundus-1m
- Owner: parap1uie-s
- License: other
- Created: 2023-12-13T06:20:18.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-11T08:02:09.000Z (almost 2 years ago)
- Last Synced: 2025-02-01T13:24:50.544Z (over 1 year ago)
- Size: 2.66 MB
- Stars: 17
- Watchers: 1
- Forks: 2
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SynFundus-1M
[](./LICENSE)
SynFundus-1M is a synthetic fundus image dataset consisting of millions of images and extensive annotations that can help improve the performance of diagnostic models.
Usage and License Notices: The data is intended and licensed for research use only.
# News
We have uploaded the dataset to huggingface dataset.
Researchers who cannot access BaiduNetDisk please provide huggingface username (re-fill in the application form).
Thanks for the help from [Alen Li](https://huggingface.co/chknug)!
# Demo visualize

SynFundus-1M images are annotated with 11 diseases types and 4 types of quality score.
# Request SynFundus-1M
SynFundus-1M is for research purposes only, and researchers must comply with the CC-BY-NC-SA 4.0 agreement.
Researchers may send request via the [application form](https://forms.gle/FHRxZoAwFGGs1mEs8).
# Citation
If you find SynFundus-1M useful for your research and applications, please cite using this BibTeX:
```
@misc{shang2023synfundus,
title={SynFundus: A synthetic fundus images dataset with millions of samples and multi-disease annotations},
author={Fangxin Shang and Jie Fu and Yehui Yang and Haifeng Huang and Junwei Liu and Lei Ma},
year={2023},
eprint={2312.00377},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```
# License
The dataset is [CC-BY-NC-SA 4.0](./LICENSE) (allowing only non-commercial use) and models trained using the dataset should not be used outside of research purposes.