Focus Monitor

A real-time Focus Monitor built with MediaPipe and OpenCV. It detects face, eyes, and head pose to estimate focus level — useful for online-exam monitoring or attention-tracking demos.

Features

• Real-time face & eye detection using MediaPipe Face Mesh
• Eye-closure timer (warns if eyes closed > 3 s)
• Auto-exit when no face detected > 10 s
• Concentration score bar (0-100 %)
• Detects noise and gives warning

⚠️ Setup & Installation

This project requires Python 3.11.

Note: The mediapipe library does not yet support newer Python versions (like 3.12+). To run this project, you must use a virtual environment based on Python 3.11.

Quickstart

1. Install Python 3.11

Ensure you have Python 3.11 installed on your system.

If you don't, download it from the official Python website or use your system's package manager (like apt for Debian/Ubuntu or brew for macOS).

2. Create a Virtual Environment

Navigate to this project's directory in your terminal.

Run the command that matches your Python 3.11 installation:

# On Linux/macOS (if 'python3.11' is available):
python3.11 -m venv .venv

# On Windows (if you used the official installer):
py -3.11 -m venv .venv

# If Python 3.11 is your default 'python3' command:
python3 -m venv .venv

3. Activate the Environment

Run the command for your operating system:

# On Linux/macOS:
source .venv/bin/activate

# On Windows (Command Prompt):
.\.venv\Scripts\activate.bat

# On Windows (PowerShell):
.\.venv\Scripts\Activate.ps1

4. Install Dependencies

With your virtual environment active, install the packages:

pip install -r requirements.txt

5. Run the Tracker

python ml.py

To stop, press q