Face Recognition System

A real-time Face Recognition System built using Python and OpenCV.
The project detects faces from a webcam feed, collects training data, trains a recognizer model, and performs real-time identification.

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Features

• Real-time face detection using Haar Cascade
• Face dataset collection from webcam
• Image preprocessing (resize, grayscale, normalization)
• Face recognition using LBPH algorithm
• Confidence score-based prediction
• Support for unknown face detection
• Simple and modular pipeline

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Project Pipeline

1. Data Collection

   • Capture face images using webcam
   • Store dataset per person in labeled folders

2. Preprocessing

   • Convert to grayscale
   • Resize images to fixed dimensions
   • Apply histogram equalization / filtering

3. Feature Extraction

   • LBPH (Local Binary Pattern Histogram)

4. Model Training

   • Train LBPH recognizer on collected dataset

5. Real-Time Recognition

   • Detect face from webcam stream
   • Predict identity and display confidence score

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Technologies Used

• Python
• OpenCV
• NumPy
• LBPH Face Recognizer

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Installation

git clone https://github.com/your-username/face-recognition-system.git
cd face-recognition-system

pip install opencv-python numpy opencv-contrib-python