essanhaji/face_recognition_pca

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

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

• El Houcine ES SANHAJI - Initial work - essanhaji

Thank you.