Face Recognition

Simple face recognition program written in python, using the face_recognition library (https://github.com/ageitgey/face_recognition). Able to read faces from webcam and compare them to all faces in the images folder and identify any matches, and track attendance.

Installation

1. Clone the repository:

git clone https://github.com/sweetbix/facerecognition.git
cd facerecognition

2. Install project dependencies:

pip install -r requirements.txt

⚠️ Windows Setup Note

If you're on Windows, you may need to install:

👉 Visual Studio

Make sure to check:

• ✅ "Desktop development with C++"

This is required for installing dlib, which powers face detection.

3. Add known faces:

• Upload images of people you want to recognise into the images/ folder.
• Use clear front-facing images.
• File names (e.g. john.png) will be displayed

Also make sure your webcam is turned on!

Usage

python attendance.py

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Web app (fullstack)

Live webcam recognition, known-face management, and attendance logging via FastAPI + React (Vite). Known faces are stored under backend/storage/known_faces/ (seeded from images/ the first time the server starts if that folder is empty). Attendance is stored in backend/data.db (SQLite), one row per person per UTC calendar day.

Prerequisites

• Same Python deps as the CLI (including dlib / Visual Studio C++ on Windows — see above).
• Node.js 20+ and npm for the frontend.

1. Backend

From the backend/ directory:

cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload --host 127.0.0.1 --port 8000

Optional environment variables:

Variable	Default	Purpose
FACE_TOLERANCE	0.5	face_recognition.compare_faces tolerance
CORS_ORIGINS	http://localhost:5173	Comma-separated allowed browser origins

2. Frontend

In a second terminal, from frontend/:

cd frontend
npm install
npm run dev

Open http://localhost:5173. The dev server proxies /api and /ws to the backend on port 8000.

• Live — Start the camera; JPEG frames are sent over a WebSocket to /ws/recognize. Matches are drawn on the video and logged to attendance (deduplicated per UTC day).
• Faces — Upload or delete known faces (exactly one face per image).
• Attendance — View or clear the log.

For production, build the frontend (npm run build) and serve frontend/dist with any static host, configuring CORS and API/WebSocket URLs accordingly.