Assessfy Pvt. Ltd Moderate 6 milestones 50 marks

Face Recognition Attendance System for Employees

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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About this project

Face Recognition Attendance System for Employees

Objective: Build an automated attendance system for employees using face recognition technology.

Context: Traditional attendance methods are inefficient and susceptible to proxy attendance, a common issue in Indian workplaces. Face recognition offers a secure and contactless alternative.

What you'll build: You'll collect employee face datasets, implement face detection and recognition using OpenCV and the face_recognition library, and integrate real-time camera feeds for attendance logging. The system will generate attendance reports via a dashboard for easy monitoring.

Deliverables: Functional face recognition attendance system with real-time logging and reporting dashboard.

Milestones

Read the project brief and milestone descriptions carefully. Ensure you understand the requirements and deliverables for each stage before proceeding.

2. Dataset collection

10 marks 6d

Collect a labeled dataset of at least 20 employee face images per person, captured in varied lighting and angles. Submit the organized dataset in a directory structure by employee name, along with a CSV mapping file. Acceptance depends on clear labeling, sufficient image quantity, and diversity for each employee.

3. Face detection model

10 marks 6d

Train or implement a face detection model that accurately locates faces in the collected images. Submit your model code and a sample script that processes at least 10 images, outputting bounding boxes. The model must detect faces with high accuracy and minimal false positives on your dataset.

4. Real-time camera integration

10 marks 6d

Integrate a webcam or external camera to capture live video and detect faces in real-time using your model. Submit a script or application that displays the camera feed with detected faces highlighted. The integration is complete when the system reliably detects faces in varying conditions during live capture.

5. Attendance logging

10 marks 6d

Develop an attendance logging system that identifies employees from live camera input and records their entry time in a CSV or database. Submit the code and a sample log file showing at least five unique employee entries. The system must prevent duplicate entries for the same employee within a session.

6. Dashboard report generation

10 marks 6d

Generate a dashboard report summarizing daily attendance, including total present, absent, and timestamps per employee. Submit a dashboard (static or interactive) and a sample report export (PDF or CSV). The report must clearly visualize attendance data and allow easy verification of logged entries.

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Upcoming sessions

Session	Window	Enrolled
Face Recognition Attendance System for Employees	11 Jun 2026 to 10 Jun 2028	0

Skills you'll learn

OpenCV for image processingFace recognition librariesPython scripting

Tools used

Python OpenCV face_recognition library

Prerequisites

Image handling in Python Basic ML concepts

Available mentors

Priyang Kumar

Free

You'll earn — Certificate (PDF)

AICTE-aligned Project Completion Certificate

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AICTE-aligned

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Face Recognition Attendance System for Employees

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