GlenGGG / FaceRecognition

Facial recognition using support vector machine (SVM) and principle component anaysis (PCA).

faceRecognition

Course project, facial recognition using support vector machine (SVM) and principle component analysis (PCA).

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

This project is written in python and used scipy.

python		3.6
scipy		1.2.1

Installing

Clone this repository.

git clone [e-mail]:GlenGGG/FaceRecognition.git
cd FaceRecognition

Download dataset

https://drive.google.com/file/d/1d_L0lQcSK5Lj6ZCxYRx4mQTCA_ArrJjF/view?usp=sharing

Decompress data.zip

unzip data.zip

Usage

Simply run the code.

python faceRecognition.py

Then you should be able to see some helpful information about the dataset and the result of PCA. In the end, a confusion matrix will be displayed, as well as information about precision, f1-score, recall and support.