/Lfw_face_recognition_svm_ensemble

LFW face recognition with svm and some ensemble methods,including Adaboost, Random Forest, Boosting, Voting and so on. PCA is used to extract features. Implemented with scikit-learn

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

Lfw_face_recognition_svm_ensemble

LFW face recognition with svm and some ensemble methods,including Adaboost, Random Forest, Boosting, Voting and so on. PCA is used to extract features. Implemented with scikit-learn(http://scikit-learn.org/stable/modules/ensemble.html#adaboost)

face_recognition_Adaboost.py Using Adaboost as classifier and two algorithm SAMME and SAMME.R is compared

face_recognition_other_ensemble.py Using other ensemble methods,including Adaboost, Random Forest, Boosting, Voting and so on.

To run this two file,just type

python face_recognition_Adaboost.py
python face_recognition_other_ensemble.py

Usage

python face_recognition.py

Results

  1. eigenface
    image

  2. recognition results image

  3. comparision between SAMME and SAMME.R image