LFW HF-ready

This folder packages the local LFW (Labeled Faces in the Wild) images as a Hugging Face imagefolder dataset with the canonical 10-fold verification pairs file.

Layout

lfw/
├── README.md
├── pairs.csv
└── train/
    ├── images/<shard>/<file>.jpg
    └── metadata.csv

metadata.csv columns

• file_name: relative image path used by ImageFolder, e.g. images/000/Aaron_Eckhart_0001.jpg.
• label: numeric identity label.
• label_name / identity: identity name.
• image_num: per-identity image index from the original filename (1-based).
• source_filename: original LFW filename.

pairs.csv columns

pairs.csv mirrors the official LFW pairs.txt (10 folds x 300 positive + 300 negative = 6000 verification pairs).

• pair_id (0..5999), fold_id (1..10), fold_position (0..299).
• is_same: 1 for positive pairs (same identity), 0 for negatives.
• image_a, image_b: bare filenames (e.g. Abel_Pacheco_0001.jpg).
• image_a_path, image_b_path: paths under the train split.

Local Stats

• Images: 13233
• Unique identities: 5749
• Identities with one image: 4069
• 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/lfw")
train = ds["train"]

import pandas as pd

pairs = pd.read_csv("data/evaluation/huggingface/lfw/pairs.csv")

Notes

LFW is described by its authors as an unconstrained face verification benchmark. The images here are the original (non-aligned) drop. Check the original dataset terms before publishing or redistributing it.