nateraw/fairface
Dataset Card for FairFace Usage from io import BytesIO from PIL import Image import datasets def bytes_to_pil(example_batch): example_batch['img'] = [ Image.open(BytesIO(b)) for b in example_batch.pop('img_bytes') ] return example_batch ds = datasets.load_dataset('nateraw/fairface') ds = ds.with_transform(bytes_to_pil) Dataset Summary Existing public face datasets are strongly biased toward Caucasian faces, and other races… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/fairface.
| Author / organization | nateraw |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 319 (as reported by Hugging Face) |
| Likes | 5 |
| Created | 2 March 2022 |
| Last updated at source | 28 July 2024 |
Popularity, last 4 days
319 now (+15 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- dima806/fairface_age_image_detectionModel · used to train
- dima806/fairface_gender_image_detectionModel · used to train
- nateraw/vit-age-classifierModel · used to train
- wolf1280/vit-age-classifierModel · used to train
Recent changes
- 17 Oct 2026 Description: Dataset Card for FairFace Usage from io import BytesIO from PIL import Image import datasets def bytes_to_pil(example_batch): example_batch['img'] = [ Image.open(BytesIO(b)) for b in example_batch.pop('img_bytes') ] return example_batch ds → Dataset Card for FairFace Usage from io import BytesIO from PIL import Image import datasets def bytes_to_pil(example_batch): example_batch['img'] = [ Image.open(BytesIO(b)) for b in example_batch.pop('img_bytes') ] return example_batch ds
Changes detected by Silytics between refreshes of the source.
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