Examify - AI-Powered Fair Exam Conduction

Examify is a Python-based Windows application developed during the Technov2K24 24-hour hackathon at VIT-AP. It ensures fair online exam conduction using AI, preventing unethical practices like screen sneaking, tab switching, or window navigation.

Developed using OpenCV, Mediapipe, FastAPI, and Selenium, the app integrates a simple Tkinter user interface to manage the entire exam process seamlessly.

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Table of Contents

1. Features
2. Technologies Used
3. How It Works
4. Installation
5. App demo
6. Contributors
7. Note
8. License

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Features

• AI-Powered Monitoring:

  • Detects gaze direction and suspicious head movements using Mediapipe’s Face Mesh.
  • Tracks actions such as sneaking glances at another screen, looking away for prolonged periods, or moving out of frame.

• Warning System:

  • Issues audible alerts if suspicious activity exceeds a threshold.
  • Warning score accumulates with continued violations.

• Secure Browser:

  • Opens the exam link in Chromium in fullscreen mode using Selenium.
  • Blocks keys and prevents switching windows or tabs.

• Automated Workflow:

  • Camera preview ensures proper monitoring setup before the exam starts.
  • Automatically closes the browser and stops the camera after the exam duration.

• Data Recording:

  • Sends student details, warning scores, and credibility scores to the server.
  • Stores all records in a CSV file for teacher evaluation.

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Technologies Used

• Python:
  • OpenCV for real-time video processing.
  • Mediapipe for face mesh detection.
  • Selenium for browser automation.
  • FastAPI for server-side processing and storage.
  • Tkinter for the graphical user interface.
• Chromium: Fullscreen exam browser.
• CSV: Used for storing student records.

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How It Works

1. User Login

• A Tkinter UI collects:
  • Name
  • Registration Number
  • Exam Link

2. Terms and Conditions

• Students are shown the rules and must agree to proceed.

3. Monitoring Setup

• A 15-second camera preview ensures proper face detection using OpenCV and Mediapipe.
• Face mesh data is processed to detect gaze direction and monitor behavior.

4. Exam Conduction

• The app opens the exam link in a Chromium browser (fullscreen).
• Background monitoring tracks the student’s activity.
• Unauthorized actions (e.g., sneaking glances, switching tabs) increase the warning score.

5. Post-Exam

• At the end of the exam duration:
  • Chromium browser and camera are closed automatically.
  • Warning scores and credibility scores are sent to the server.

6. Data Storage

• The server saves all student data (Name, Registration Number, Warning Score, Credibility Score) in a CSV file for teacher access.

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Installation

Execute the following commands in your command prompt or terminal

git clone https://github.com/prodev717/Examify.git

cd Examify

pip install -r requirements.txt

python main.py

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App demo

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Contributors

Ganesh M

• GitHub: prodev717
• Role: Backend Developer
• Contributions:
  • Developed the FastAPI server for data handling and storage.
  • Implemented real-time face detection using OpenCV and Mediapipe.
  • Managed threading and background monitoring processes.
  • Configured Selenium for secure browser automation.

VK Rohith

• GitHub: VK Rohith
• Role: Frontend Developer
• Contributions:
  • Designed the user interface using Tkinter.
  • Built the exam initiation and rules agreement workflow.

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Note

Before using the app, ensure the ChromeDriver path is set correctly in the code and the FastAPI server is running. To start server run start_server.bat

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License

This project is licensed under the MIT License. See the LICENSE file for details.