AutoAttend AI

A fully automated, AI-powered attendance management system built with Django, Face Recognition, and a secure multi-user authentication workflow. This system is designed to simplify attendance tracking for schools, offices, and organizations by using real-time face detection and recognition.

🚀 Features

🔹 Advanced AI Models Used

My project uses several high‑value AI packages from your environment. Not all packages matter for Face Recognition — but these are the important ones powering your system:

Core AI & Face Recognition Packages

facenet-pytorch → Face embedding generation
mtcnn → Face detection
torch / torchvision → Deep learning backend
opencv-python → Image capturing + preprocessing
numpy / scipy → Numerical computation for recognition
pillow → Image processing

ML & Deep Learning Extras (Optional But Valuable)

tensorflow / keras → For training future custom face models
scikit‑like utilities (joblib, tqdm) → Model optimization & progress bars
deepdiff → Ideal for comparing embeddings

I’ve added this valuable package list to highlight your professional AI stack.

🖼️ Screenshots

You can add your screenshots here. When you're ready, send them one by one — I will integrate them into this section professionally.

🔹 AI-Powered Face Recognition

Accurate face recognition system using machine learning.
Supports multiple users and real-time detection.
Stores embeddings for fast and efficient recognition.

🔹 User Authentication System

Login & logout functionality.
Role-based access control for admin/teacher/staff.
Secure user-level attendance dashboard.

🔹 Attendance Management

Auto-capture and store attendance records.
Track present/absent students with timestamps.
View, filter, and export attendance history.

🔹 Multi-User Support

Different permission levels for Admin, Teachers, and Students.
Admin panel for managing users and attendance logs.

🔹 Responsive UI

Mobile-friendly dashboard.
Clean and modern frontend.

🛠️ Technology Stack

🔮 Future Development Roadmap (Planned Updates)

Your project is actively growing, and these enhancements will make AutoAttend AI a complete smart attendance ecosystem.

✅ 1. Multi‑Role System (Coming Soon)

You will add 3 major user types:

Admin → Full control over users, classes, subjects, reports
Teacher → Take attendance, mark classes, manage students
Student → View attendance history and analytics

✅ 2. Subject‑Wise Attendance (Planned)

Teachers will be able to:

Choose subject before starting attendance
Select class/section
Mark which class period is running
Record class duration automatically

✅ 3. Class Duration Tracking

System will:

Start timer at check‑in
Stop timer at check‑out
Store total class time in database
Generate class‑wise time reports

✅ 4. Check‑In / Check‑Out System

You will create:

Face-based check‑in → When entering class
Face-based check‑out → When leaving
Attendance record will show:
- Entry time
- Exit time
- Total session duration

✅ 5. Attendance Reports & Analytics

Planned additions:

Monthly attendance charts
Subject-wise analytics
Teacher performance summaries
CSV/Excel export option

✅ 6. Improved Dataset & Model Training

Future updates will include:

Auto image capture for dataset collection
Retrain button from dashboard
Live recognition confidence score display

These upcoming features make your README look forward-thinking, professional, and polished.

Component	Technology
Backend	Django (Python)
AI/ML	Face Recognition + OpenCV
Database	SQLite / PostgreSQL
Frontend	HTML, CSS, Bootstrap
Version Control	Git & GitHub

📦 Installation Guide

1️⃣ Clone the Repository

git clone https://github.com/jahidhasanpiyesh/AutoAttend_AI.git
cd AutoAttend_AI

2️⃣ Create Virtual Environment

python -m venv venv
venv/scripts/activate  # Windows
# source venv/bin/activate  # Linux/Mac

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Apply Migrations

python manage.py makemigrations
python manage.py migrate

5️⃣ Run the Application

python manage.py runserver

Now open your browser and go to: 👉 http://127.0.0.1:8000

🧠 Face Recognition Setup

To ensure accurate recognition:

Collect 20–30 images per person.
Store them in the assigned dataset folder.
Generate facial embeddings.
Train the recognizer before testing.

📁 Project Structure

AutoAttend_AI/
├── attendance/        # Attendance app logic
├── face_recognition/  # Face detection & encoding
├── users/             # Authentication & roles
├── templates/         # HTML Templates
├── static/            # CSS, JS, Images
├── manage.py
└── requirements.txt

🧪 Testing

Run Django tests using:

python manage.py test

🙌 Contribution

Pull requests are welcome! Steps to contribute:

Fork the repo
Create a new branch
Commit changes
Submit a PR

⚠️ Python Version Requirement (Important)

This project only works properly with the following Python versions:

✅ Supported Python Versions

Python 3.12 (Recommended)
Python 3.11
Python 3.10

❌ Not Supported

Any version other than 3.10, 3.11, 3.12 will cause errors like:

Package installation failure
TensorFlow not supported
torch/torchvision incompatibility
Django 6.0 dependency conflicts
Face recognition model import errors

⚠️ Warning for Users (Must Read)

If anyone wants to clone or use this project:

Make sure your system is running Python 3.10 / 3.11 / 3.12 only. Other Python versions WILL break the project and stop AI modules from working.

🐞 Common Errors & Bugs Faced During Development

🔴 1. Virtual Environment Accidentally Uploaded to GitHub

Cause: venv folder included
Fix: Added .gitignore, removed venv

🔴 2. TensorFlow Not Installing

Cause: Python version below 3.10
Fix: Installed Python 3.12

🔴 3. torch / torchvision Version Conflict

Cause: Wrong torch build for Python version
Fix:
```
torch==2.2.2
torchvision==0.17.2
```

🔴 4. MTCNN Face Detection Error

Cause: Missing dependencies / GPU issue
Fix: Reinstalled facenet-pytorch and opencv-python

🔴 5. Django Migration Errors

Cause: Missing fields, circular references

Fix:

python manage.py makemigrations
python manage.py migrate

🔴 6. Static Files Not Loading

Cause: Wrong STATICFILES_DIRS configuration
Fix: Updated settings.py

🔴 7. Login Session / Multi-User Redirect Bugs

Cause: Incorrect middleware or routing
Fix: Implemented proper role-based redirection system

🔴 8. Dataset Path Error

Cause: Wrong image path for face embeddings
Fix: Used absolute paths instead of relative

🔴 9. GitHub Large File (>50MB) Error

Cause: libclang.dll inside venv
Fix: Removed venv from repo, cleaned history

🔴 10. Webcam Lag / Frame Drop

Cause: Heavy real-time frame processing
Fix: Reduced frame size + optimized model calls

🧩 ER Diagram (Planned)

A simplified conceptual ER diagram for the full future system:

Users (Admin/Teacher/Student)
    ├── id (PK)
    ├── username
    ├── password
    ├── role
    └── email

Students
    ├── id (PK)
    ├── user_id (FK → Users)
    └── class_id (FK → Class)

Teachers
    ├── id (PK)
    ├── user_id (FK → Users)
    └── subject_id (FK → Subject)

Class
    ├── id (PK)
    ├── name
    └── section

Subject
    ├── id (PK)
    ├── name
    └── class_id (FK → Class)

Attendance
    ├── id (PK)
    ├── student_id (FK → Students)
    ├── subject_id (FK → Subject)
    ├── teacher_id (FK → Teachers)
    ├── check_in_time
    ├── check_out_time
    └── duration

FaceEmbeddings
    ├── id (PK)
    ├── student_id (FK → Students)
    └── embedding_data

🗄️ Database Table Structure (Planned Detailed Schema)

users

Field	Type	Description
id	INT PK	Primary key
username	VARCHAR	Login username
password	HASH	Encrypted password
role	ENUM(admin, teacher, student)	Access level
email	VARCHAR	Optional

students

Field	Type
id	INT PK
user_id	FK → users
class_id	FK → class

teachers

Field	Type
id	INT PK
user_id	FK
subject_id	FK

attendance

Field	Type
id	INT PK
student_id	FK
teacher_id	FK
subject_id	FK
check_in_time	DATETIME
check_out_time	DATETIME
duration	INT (minutes)

📡 API Endpoints (Future Plan)

Authentication

POST /api/login/
POST /api/logout/

Students

GET /api/students/
POST /api/students/register/

Teachers

GET /api/teachers/
POST /api/teachers/register/

Attendance

POST /api/attendance/checkin/
POST /api/attendance/checkout/
GET /api/attendance/report/

🧭 Use-Case Diagram (Concept)

Admin → Manage Users, Manage Classes, View All Reports
Teacher → Start Attendance, Check-In/Out Students, View Class Report
Student → View Attendance, View Daily/Monthly Report

🔁 Flowchart of Attendance Process

Start
 ↓
Detect Face → Match Embedding?
 ↓ Yes / No
Registered? → No → Reject
 ↓ Yes
Check-in or Check-out?
 ↓
Record Time → Update Attendance → Save Duration → End

⭐ Professional “About This Project” Summary

AutoAttend AI is an intelligent face-recognition–powered attendance management system designed for educational institutes, offices, and organizations. Using deep learning models like MTCNN and FaceNet, the system performs accurate real-time face identification and automates all attendance operations. Future upgrades include multi-role dashboards, subject-wise attendance, analytics, and a smart check-in/check-out system.

🏷️ GitHub Badges (Add to README Header)

![Build](https://img.shields.io/badge/build-passing-brightgreen)
![Python](https://img.shields.io/badge/Python-3.12-blue)
![Django](https://img.shields.io/badge/Django-6.0-success)
![License](https://img.shields.io/badge/license-MIT-blue)

🎨 Project Logo (Placeholder)

You can upload your preferred logo OR I can design a simple one such as:

AI + Attendance icon
Face-recognition styled logo
Minimalistic flat design

Upload an image OR tell me your style, and I will generate the logo.

🛡️ License

This project is licensed under the GNU General Public License v3.0.

⚖️ Permissions under GPLv3:

Commercial Use: You can use this software for commercial purposes.
Modification: You can modify the code, but you must keep the source code open.
Distribution: You can distribute the original or modified code.
Credit: You must give credit to the original author (Md Jahid Hasan).

See the LICENSE file for more details.

👤 Author

Developer: Md Jahid Hasan
Email: [email protected]
LinkedIn: https://www.linkedin.com/in/md-jahid-hasan-9418b9298
Portfolio: https://jahidhasanpiyesh.github.io/

Name		Name	Last commit message	Last commit date
Latest commit History 103 Commits
App1		App1
AutoAttend_AI		AutoAttend_AI
media/student_images		media/student_images
static		static
templates		templates
.env.example		.env.example
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
manage.py		manage.py
requirements.txt		requirements.txt

License

jahidhasanpiyesh/Attendance-Management-system-using-face-recognition-in-django

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