Metadata-Version: 2.1
Name: simplefeature
Version: 1.1.2
Summary: UNKNOWN
Home-page: https://github.com/joelb92/simplefeature
Author: D.D. Cox, and N. Pinto, Joel Brogan
Author-email: joelbrogan92@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: opencv-python
Requires-Dist: numpy
Requires-Dist: scikit-image

This repository provides an incredibly light-weight implementation of the gray-scale feature extractor from:
"Beyond simple features: A large-scale feature search approach to unconstrained face recognition"

## Use

`pip install simplefeature` 
   
or

   `git clone https://github.com/joelb92/simplefeature.git && cd simplefeat && python setup.py install`


~~~
   import simplefeature
   import cv2
   im = cv2.imread("/home/face.jpg")
   embedding = simplefeature.extract(im) 
~~~

Inputs will be scaled to 200x200px
The system outputs a 51200-d vector

Please cite this paper:
~~~
Cox, David, and Nicolas Pinto. "Beyond simple features: A large-scale feature search approach to unconstrained face recognition."
2011 IEEE International Conference on Automatic Face & Gesture Recognition (FG). IEEE, 2011.
~~~

