Piyushkumar1307 / Facial-recognition

Facial-recognition

This project is a facial recognition system that captures images of a subject, trains a recognition model, and provides real-time facial recognition through a graphical user interface (GUI). It uses Python along with OpenCV, Pillow, NumPy, and OS for implementation.

Table of Contents

• Introduction
• Requirements
• Folder Structure
• Setup
• Steps to Run

Introduction

Provide a brief introduction to your project. Explain its purpose, features, and any important context.

Requirements

List the requirements and dependencies for your project. Include the necessary libraries:

• Python
• OpenCV (cv)
• Pillow
• NumPy
• OS (usually comes with Python)

Folder Structure

dataset/ # Contains collected data datacollect.py # Script for data collection trainingdemo.py # Script for model training testmodel.py # Script for testing the model other files and folders

Setup

1. Clone the repository to your local machine:

git clone https://github.com/YourUsername/YourRepository.git

2. Navigate to the project directory:

cd Facial-recognition

3. Install the required Python libraries:

pip install opencv-python pillow numpy

Steps to Run

1. Data Collection:

   • Run datacollect.py to capture images of the subject.
   • Capture images from various angles and expressions (around 500 images).

2. Model Training:

   • Execute trainingdemo.py to create a training.yml file.
   • This file contains the trained model for facial recognition.

3. Testing:

   • Run testmodel.py to launch the GUI for facial recognition.
   • Use the GUI to test the system in real-time.

Enjoy using the facial recognition system!