zgzjdx / 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

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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

About

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

License:GNU General Public License v3.0


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Language:Python 100.0%