Metadata-Version: 2.1
Name: pyfhog
Version: 0.1.5
Summary: Fast FHOG feature extraction for Python
Home-page: https://github.com/johnwilsoniv/pyfhog
Author: SplitFace Project
Author-email: 
License: Boost Software License 1.0
Project-URL: Homepage, https://github.com/johnwilsoniv/pyfhog
Project-URL: Documentation, https://github.com/johnwilsoniv/pyfhog#readme
Project-URL: Repository, https://github.com/johnwilsoniv/pyfhog.git
Project-URL: Issues, https://github.com/johnwilsoniv/pyfhog/issues
Keywords: hog,fhog,feature-extraction,computer-vision,facial-analysis
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.20.0

# pyfhog

Python wrapper for dlib's FHOG (Felzenszwalb HOG) feature extraction.

## Installation

```bash
pip install pyfhog
```

## Usage

```python
import pyfhog

features = pyfhog.extract(image, cell_size=8)
```

## What it does

Extracts FHOG features identical to OpenFace 2.2 (validated r=1.0, RMSE=0.0). Uses dlib's optimized C++ SIMD implementation under the hood.

## 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.
