REFUGE Multi-Rater — Glaucoma with Multi-Expert Annotations
1200 fundus images from REFUGE1 with optic disc/cup segmentation masks annotated by multiple expert raters.
At a glance
| Field | Value |
|---|---|
| Short name | refuge1_multirater |
| Full name | REFUGE Multi-Rater — Glaucoma with Multi-Expert Annotations |
| Primary category | fundus |
| Contained modalities | fundus |
| Tasks | classification, segmentation |
| Samples | 1,200 |
| Classes | 2 (non-glaucoma, glaucoma) |
| Splits | train, val, test |
| Size | 0.8 GB |
| Source-stated terms | CC BY-NC-SA (see HuggingFace page) |
| Normalized terms | cc-by-nc-sa |
| Descriptive screening label | Explicit noncommercial clause recorded; check source |
| Terms scope | dataset_files |
| Access friction | anonymous_direct |
| Route backend | Google Drive |
| Availability | available (checked 2026-07-21) |
| Acquisition support | loader_implemented_not_live_tested |
| Legacy sample-loader status | Standard loader included |
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download refuge1_multirater --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download refuge1_multirater --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('refuge1_multirater')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: drive.google.com/file
Source-term evidence: drive.google.com/file
Loader example
This entry includes a standard DatasetSample loader.
from pathlib import Path
from eyedatahub.datasets.registry import REGISTRY
data_dir = Path('~/.eyedatahub/data').expanduser()
ds = REGISTRY.get_dataset('refuge1_multirater')
samples = ds.load(data_dir, split='test')
for s in samples[:5]:
print(s.sample_id, s.label, s.image_path)
Citation
- BibTeX
- Plain text
@misc{refuge1_multirater,
title = { REFUGE Multi-Rater — Glaucoma with Multi-Expert Annotations },
note = { Orlando J.I. et al., 'REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs', MIA 2020 },
year = { 2020 },
url = { https://drive.google.com/file/d/1TXTrZyaZ76faXek46pEzaYQmAejLf30d/view },
}
Orlando J.I. et al., 'REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs', MIA 2020.
Source-stated terms
- Raw source string: CC BY-NC-SA (see HuggingFace page)
- Normalized category:
cc-by-nc-sa - Apparent scope:
dataset_files - Descriptive screening label: Explicit noncommercial clause recorded; check source
⚠️ Source-stated terms, scope, and normalized labels are curation metadata, not legal advice or a permission finding. Review the current official source before transfer or reuse.
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