Facial-Recognition

This repository contains files related to an image classification and face detection system. Below is an overview of the included files and their purposes.

Repository Structure

File/Folder	Description
Image classification (practice)-2.ipynb	Jupyter Notebook containing image classification practice code.
best_trained_model.pkl	Pretrained model file for image classification/face detection.
haarcascade_eye.xml	Haar Cascade classifier file for eye detection.
haarcascade_frontalface.xml	Haar Cascade classifier file for frontal face detection.
number_person_file.json	JSON file containing data about numbers/persons (likely for classification).
README.md	Project documentation (this file).

Quick Start

1. Prerequisites:

   • Python 3.x
   • OpenCV (for Haar Cascade files)
   • Jupyter Notebook (to run the practice file)

2. Usage:

   • Run the Jupyter Notebook Image classification (practice)-2.ipynb to explore the image classification implementation.
   • Use the .pkl model file for predictions in your application.
   • The Haar Cascade XML files can be used with OpenCV for real-time face/eye detection.

Dependencies

Install required packages:

pip install opencv-python numpy pandas scikit-learn jupyter