pyfaceau 1.3.3

Pure Python OpenFace 2.2 AU extraction with CLNF landmark refinement

pyfaceau

Python implementation of OpenFace 2.2's Facial Action Unit extraction pipeline.

Installation

pip install pyfaceau

Usage

from pyfaceau import FaceAnalyzer

analyzer = FaceAnalyzer()
result = analyzer.analyze(image)

print(result.au_intensities)  # 17 action unit intensities
print(result.landmarks)       # 68 facial landmarks
print(result.pose)            # head pose

What it does

• Extracts 17 facial action units (AU01, AU02, AU04, AU05, AU06, AU07, AU09, AU10, AU12, AU14, AU15, AU17, AU20, AU23, AU25, AU26, AU45)
• Detects 68 facial landmarks via pyclnf
• Estimates 3D head pose
• No C++ compilation required

Citation

If you use this in research, please cite:

Wilson IV, J., Rosenberg, J., Gray, M. L., & Razavi, C. R. (2025). A split-face computer vision/machine learning assessment of facial paralysis using facial action units. Facial Plastic Surgery & Aesthetic Medicine. https://doi.org/10.1177/26893614251394382

License

CC BY-NC 4.0 — free for non-commercial use with attribution.