AOD: Augmented Ocular Diseases Dataset

Augmented ODIR-5K fundus photographs for 8-class ocular disease classification: Normal, Diabetes, Glaucoma, Cataract, AMD, Hypertension, Myopia, Other. Preprocessing includes CLAHE and standard augmentation.

At a glance

Field	Value
Short name	aod
Full name	AOD: Augmented Ocular Diseases Dataset
Primary category	fundus
Contained modalities	fundus
Tasks	classification
Samples	14,813
Classes	8 (Normal, Diabetes, Glaucoma, Cataract, AMD, Hypertension, Myopia, Other)
Splits	train, test
Size	2.0 GB
Source-stated terms	See Kaggle dataset page
Normalized terms	unknown
Descriptive screening label	Unknown or unclear; do not assume permission
Terms scope	unknown
Access friction	self_service_authenticated
Route backend	Kaggle
Availability	available (checked 2026-07-21)
Acquisition support	standard_platform_supported
Legacy sample-loader status	Standard loader included

Notes

OVERLAP: AOD is an augmented variant of ODIR-2019 (already in EyeDataHub as odir2019). Preprocessing (CLAHE) and augmentation explain the 14,813 vs 16,000 image count delta. Kept because the augmented split appears in downstream benchmarks separately.

Access preflight and acquisition

CLI

# Read-only preflight
eyehub download aod --data-dir ./data --dry-run --json

# Explicit transfer, only when preflight reports supported behavior
eyehub download aod --data-dir ./data

Python

from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY

ds = REGISTRY.get_dataset('aod')
print(preflight_dataset(ds, './data'))  # no transfer

Upstream page: kaggle.com/datasets

Source-term evidence: kaggle.com/datasets

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('aod')
samples = ds.load(data_dir, split='test')
for s in samples[:5]:
    print(s.sample_id, s.label, s.image_path)

Citation

BibTeX

@misc{aod,
  title  = { AOD: Augmented Ocular Diseases Dataset },
  note   = { AOD Dataset. Kaggle. https://www.kaggle.com/datasets/nurmukhammed7/augemnted-ocular-diseases },
  url    = { https://www.kaggle.com/datasets/nurmukhammed7/augemnted-ocular-diseases },
}

Plain text

AOD Dataset. Kaggle. https://www.kaggle.com/datasets/nurmukhammed7/augemnted-ocular-diseases

Source-stated terms

• Raw source string: See Kaggle dataset page
• Normalized category: unknown
• Apparent scope: unknown
• Descriptive screening label: Unknown or unclear; do not assume permission

⚠️ 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.

Related datasets with shared modalities

• airogs: AIROGS: AI for Robust Glaucoma Screening (113,893 records, cc-by-nc-nd)
• eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 records, unknown)
• justraigs: JustRAIGS: Just Referral AI Glaucoma Screening Dataset (101,442 records, cc-by-nc-nd)
• eyepacs: EyePACS — Diabetic Retinopathy Detection (Kaggle 2015) (88,702 records, research-only)
• multieye: MultiEYE: OCT-Enhanced Fundus Multi-Disease Benchmark (58,036 records, mit)
• angioreport: AngioReport Fundus Angiography Report Dataset (55,361 records, unknown)
• ffa_ir: FFA-IR Medical Report Dataset (47,247 records, unknown)
• bidr: BiDR: Diabetic Retinopathy Diagnosis Dataset (35,126 records, unknown)