Datasets:
metadata
license: other
task_categories:
- image-classification
- zero-shot-image-classification
tags:
- face-recognition
- face-verification
- cross-age
- calfw
- imagefolder
pretty_name: CALFW HF-ready
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: aligned
path: aligned/**
- split: raw
path: raw/**
CALFW HF-ready
This folder packages the local CALFW (Cross-Age LFW) images as a Hugging Face
imagefolder dataset with two splits and a verification-pairs CSV.
Splits
aligned: 112x112 ArcFace-aligned faces (fromdata/evaluation/CALFW/aligned/).raw: original 250x250 LFW-style faces (fromdata/evaluation/CALFW/raw/).
Both splits contain the same 12174 images and the same identity labels.
Layout
calfw/
├── README.md
├── pairs.csv
├── aligned/
│ ├── images/<shard>/<file>.jpg
│ └── metadata.csv
└── raw/
├── images/<shard>/<file>.jpg
└── metadata.csv
metadata.csv columns
file_name: relative image path used byImageFolder, e.g.images/000/AJ_Cook_0001.jpg.label: numeric identity label, shared across the two splits.label_name/identity: identity name corresponding tolabel.image_num: per-identity image index from the original filename (e.g.0001).variant:alignedorraw.source_filename: original CALFW filename.
pairs.csv columns
pairs.csv mirrors txts/pairs_CALFW.txt (6000 verification pairs; 3000 same-identity
cross-age positives and 3000 negatives, split into 10 folds of 600 pairs each).
pair_id(0..5999),fold_id(1..10),fold_position(0..299).is_same: 1 for positive pairs, 0 for negatives.image_a,image_b: bare filenames as in the upstream pairs file.image_a_aligned_path,image_b_aligned_path: path under thealignedsplit.image_a_raw_path,image_b_raw_path: path under therawsplit.
Local Stats
- Images per split: 12174
- Unique identities: 4025
- Identities with one image: 1
- Verification pairs: 6000 (3000 positive / 3000 negative)
- Folds: 10 x 600 pairs
Loading
from datasets import load_dataset
ds = load_dataset("imagefolder", data_dir="data/evaluation/huggingface/calfw")
ds["aligned"], ds["raw"]
import pandas as pd
pairs = pd.read_csv("data/evaluation/huggingface/calfw/pairs.csv")
Notes
CALFW (Cross-Age LFW) is described by its authors as a verification benchmark that emphasizes age variation between the two faces in each positive pair. Check the original dataset terms before publishing or redistributing it.