Face Recognition System This project implements a face recognition system using OpenCV and LBPH (Local Binary Patterns Histograms). The system is capable of detecting faces, generating datasets, training a classifier, and recognizing faces in real-time.

This project is designed to create a real-time face recognition system using Python and OpenCV. It involves three main steps:

1.Generating a dataset of faces. 2.Training a face recognizer using the dataset. 3.Recognizing faces in real-time using the trained recognizer.

Requirements Python 3.x OpenCV NumPy PIL (Python Imaging Library)

Generating Dataset Run the generate_dataset.py script to capture and save images.

Training the Classifier Run the train_classifier.py script to train the face recognizer

Recognizing Faces Run the recognize_faces.py script to start real-time face recognition

The system can detect and recognize faces in real-time. It labels recognized faces with the corresponding names "Soham" and "Maithili" based on the trained dataset.