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FaceDection/FaceDetection/doc/FilesDescirption.md

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E-Face

This project name as E-Face which is a implementation of face detection algorithm.

My nick name is EOF. For convenient, I name it as E-Face.

The archtecture of this project.

The following list show the files in this awesome project.

  • adaboost.py Implmentation of Adaptive Boosting algorithm

  • cascade.py Cascade Decision Tree

  • config.py All parameters of configuration in this project are stored in this file.

  • image.py The initialization of images. class Image and class ImageSet are in this file.

  • haarFeature.py Stuff with Haar-Features.

  • vecProduct.py A simple function to do production of two vectors.

  • weakClassifier.py The detail about Weak classifier.

  • testing.py Script for testing.

  • training.py Script for training the model.

  • getCachedAdaBoost.py

directories:

  • model/ cache files for adaboost model.

  • featuers/ values for different feaures with different samples.

  • doc/ documents with this project.

###Programming Style:

I used basic OOP(Object Oriented Programming) tricks to build my program. Something like... I put all about `AdaBoost` into a class(AdaBoost) which you can find in file `adaboost.py`. Everytime you want to do something with adaboost, just create a object instance of that class.

Adavantages of this style: Higher level of abstraction and easy to be used. With this style, green hand will easy to build good archtecture with our project.

Disadvantages of this style: Without optimalization, it will cost a lot of memory. This will be obvious when the scale of project goes more and more large.