---
license: other
task_categories:
- image-classification
- zero-shot-image-classification
tags:
- face-recognition
- face-verification
- cross-pose
- cplfw
- imagefolder
pretty_name: CPLFW HF-ready
size_categories:
- 10K<n<100K
---

# CPLFW HF-ready

This folder packages the local CPLFW (Cross-Pose LFW) aligned images as a Hugging
Face `imagefolder` dataset with a verification-pairs CSV.

## Layout

```
cplfw/
├── 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/AJ_Cook_1.jpg`.
- `label`: numeric identity label.
- `label_name` / `identity`: identity name.
- `image_num`: per-identity image index from the original filename.
- `source_filename`: original CPLFW filename.

## pairs.csv columns

`pairs.csv` mirrors `pairs_CPLFW.txt` (6000 verification pairs; 3000 same-identity
cross-pose positives and 3000 negatives, split into 10 folds of 600 pairs each
following the LFW convention).

- `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_path`, `image_b_path`: paths under the `train` split.

## Local Stats

- Images: 11648
- Unique identities: 3929
- Identities with one image: 21
- Verification pairs: 6000 (3000 positive / 3000 negative)
- Folds: 10 x 600 pairs

## Skipped upstream files

These four upstream files have malformed names (typos like `_3jpg.jpg`, `.jip.jpg`,
or `-` instead of `_`). They are not referenced by any verification pair, so the
benchmark is unaffected.

- `Landon_Donovan_3jpg.jpg`
- `Leni_Bjorklund-2.jpg`
- `Leni_Bjorklund-3.jpg`
- `Mike_Montgomery_3.jip.jpg`

## Loading

```python
from datasets import load_dataset

ds = load_dataset("imagefolder", data_dir="data/evaluation/huggingface/cplfw")
train = ds["train"]
```

```python
import pandas as pd

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

## Notes

CPLFW (Cross-Pose LFW) is described by its authors as a verification benchmark
emphasizing pose variation between the two faces in each positive pair. Check the
original dataset terms before publishing or redistributing it.