Skip to content

Latest commit

 

History

History
49 lines (35 loc) · 1.75 KB

README.md

File metadata and controls

49 lines (35 loc) · 1.75 KB

Face Recognition System

This is a Face Recognition System built using Python and various machine learning algorithms. The system detects and recognizes faces in real-time or from images, utilizing OpenCV for face detection and machine learning techniques for face recognition.

Table of Contents

Introduction

This Face Recognition System identifies human faces using machine learning algorithms. It detects faces in real-time from a webcam feed or from an image file and compares the detected face with a pre-existing dataset to identify the person.

Features

  • Real-time face detection using OpenCV.
  • Face recognition through machine learning algorithms.
  • Supports image-based face recognition.
  • Easy integration and extensibility with different datasets.

Technologies Used

  • Python 3.x: The programming language used for the project.
  • OpenCV: Library for image processing and face detection.
  • NumPy: Used for numerical operations.
  • Machine Learning Algorithms: Includes techniques like KNN, SVM, and deep learning for face recognition.
  • Haar Cascade Classifier: For face detection.
  • CSV: Used to store the attendance list in CSV format.

Setup Instructions

Prerequisites

  • Python 3.x
  • Git (for cloning the repository)
  • Required Python libraries: Install via requirements.txt.

Installation

  1. Clone the repository: 
    git clone https://github.com/Samima-Nasrin/Face-Recognition-System.git