/face_recognition_pca

Face recognition using PCA and some machine learning algorithm on Olivetti dataset.

Primary LanguageJupyter Notebook

Olivetti Face Recognition Using PCA

Olivetti Dataset

Brief information about Olivetti Dataset :

  • Face images taken between April 1992 and April 1994.
  • There are ten different image of each of 40 distinct people
  • There are 400 face images in the dataset
  • Face images were taken at different times, variying ligthing, facial express and facial detail
  • All face images have black background
  • The images are gray level
  • Size of each image is 64x64
  • Image pixel values were scaled to [0, 1] interval
  • Names of 40 people were encoded to an integer from 0 to 39

Principal Component Analysis

Principal component analysis is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.

Requirements

  • Python 3.7 64bit

Installation

  • Get the package from PyPi :
  • All requirement that you will need its exist in requirements.txt so you just need to run this command :
!pip install -r requirements.txt

Test

Congratulation.

  • Open the notebook main.ipynb and edit it as you want.

  • main.ipynb

Authors

Thank you.