vnhwd / jointCascade_py

Joint Cascade Face Detection and Alignment

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Joint Cascade Face Detection and Alignment in Python

Implementing the joint cascade face detector on AFW dataset. And this implementation is based on landmark_py. All the things have benn tested on Ubuntu 14.04.

Dependencies


All of the following modules can be easily installed by pip

PIL
numpy
scipy
scikit-learn
OpenCV

Install script on Ubuntu 14.04

sudo aptitude install python-pip gfortran
sudo pip install pillow numpy scipy sklearn
sudo aptitude install python-opencv

Demo on AFW


Because AFW only contain 337 faces. If you want get a good result, please train on the big trainSet

  1. Download the AFW dataset here
  2. Replace the location of afw by yourself in afw_test.lst, afw_train.lst and neg.txt in config folder(Mine is /home/samuel/data)
  3. Change afw_config.py:dataPara:posList, negList by yourself
  • Train on AFW

python -W ignore ./demo_train.py ../config/afw_config.py

  • Evaluate on AFW(Coming Soon...)

./demo_evaluate.py ../config/afw_model/train.model ../config/afw_test.lst

References


  1. Face Alignment at 3000 FPS via Regressing Local Binary Features
  2. Joint Cascade Face Detection and Alignment

Contact


If you have any questions, please email shenfei1208@gmail.com or creating an issue on GitHub.

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Joint Cascade Face Detection and Alignment


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