README.md

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  This dataset contains images of primates with facial landmark annotations.
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# PrimateFace

Cross-species primate face analysis dataset with facial landmark annotations
for non-human primates. The dataset provides annotations in two landmark
conventions, enabling landmark conversion across schemes.

## Landmark Conventions

PrimateFace supports two facial landmark configurations on the same images:

- **COCO 68-landmark** (`dlib68`): The standard dlib/COCO Whole-Body face
  keypoint layout (jaw contour, eyebrows, nose, eyes, mouth).
- **PrimateFace 48-landmark** (`pf48`): A custom primate-optimized landmark
  set.

## Configs

Each config corresponds to a data source and annotation variant:

| Config | Keypoints | Description |
|--------|-----------|-------------|
| `mac-au-68kpt` | 68 (dlib/COCO) | Cayo Santiago action-unit videos, COCO Whole-Body face landmarks |
| `mac-au-48kpt` | 48 (PrimateFace) | Cayo Santiago action-unit videos, PrimateFace custom landmarks |

Both configs contain the same images annotated with different landmark sets.

## Usage

```python
from datasets import load_dataset

# Load 68-keypoint annotations (dlib/COCO convention)
ds_68 = load_dataset("fparodi/PrimateFace", "mac-au-68kpt")

# Load 48-keypoint annotations (PrimateFace convention)
ds_48 = load_dataset("fparodi/PrimateFace", "mac-au-48kpt")
```

## Citation

If you use this dataset, please cite:

```bibtex
@article{parodi2025primateface,
  title={PrimateFace: A Machine Learning Resource for Automated Face Analysis in Human and Non-human Primates},
  url={https://www.biorxiv.org/content/10.1101/2025.08.12.669927},
  year={2025}
}
```

## Links

- **Paper**: [PrimateFace (bioRxiv)](https://www.biorxiv.org/content/10.1101/2025.08.12.669927)
- **Code**: [KordingLab/PrimateFace (GitHub)](https://github.com/KordingLab/PrimateFace)

## License

CC-BY-NC-4.0 — non-commercial research use only.