Luminar - Adaptive Screen Brightness & Productivity Tool

Overview

Luminar is an advanced screen brightness and productivity management tool designed to enhance user comfort and efficiency. It utilizes real-time image processing to dynamically adjust screen brightness and integrates a Pomodoro timer for improved workflow. With profile management and health reminders, Luminar ensures an optimal screen experience.

Features

• Adaptive Brightness: Adjusts screen brightness based on ambient lighting using image processing.
• Image Processing: Enhances images with brightness and contrast adjustments.
• Pomodoro Timer: Boosts productivity with structured work and break intervals.
• Profile Management: Saves preferred brightness and color settings for different activities.
• Health Monitoring: Notifies users to take breaks for eye health.
• Energy Efficiency Mode: Dims screen brightness after inactivity.

Installation

Prerequisites:

• Python 3.x
• Required Python packages (install using the command below):

  pip install numpy opencv-python pyautogui screen-brightness-control plyer pillow

Running the Application:

1. Clone or download the repository.
2. Navigate to the project directory.
3. Run the script using:

   python Luminar.py

Usage

• Start: Begins adaptive brightness monitoring.
• Stop: Ends the session.
• Profile Settings: Manage saved brightness and color preferences.
• Pomodoro On: Activates the Pomodoro timer.
• Screen Usage History: Tracks screen time for better time management.
• About Us: Learn more about the team and the application.

Security & Privacy

• Local Processing: Data is processed locally to ensure privacy.
• No Data Storage: Images and data are not saved or transmitted.
• Transparent Permissions: The application only accesses necessary system components.

Troubleshooting

• Camera Not Detected: Ensure your camera is connected and functional.
• Brightness Adjustment Issues: Some systems may require admin permissions for brightness control.
• Pomodoro Timer Not Working: Restart the application and ensure there are no background conflicts.

Contributors

• Adviser: Roma Bondoc Pare
• Developers:
  • Tanedo, Connerry L.
  • Villareal, Genesis D.
  • Tolentino, Ian D.

License

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

Contact

For support or contributions, please reach out to the development team.