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Real-Time Emotion Insights & Focus Clock Real-Time Emotion Detection and Screen Time Tracker !Emotion Detection

Real-Time Emotion Detection and Screen Time Tracker

Project Overview

The Real-Time Emotion Detection and Screen Time Tracker is a Python application that combines two powerful features:

1. Emotion Detection: It analyzes faces captured by your webcam and predicts the dominant emotion (e.g., happy, sad, surprised) using DeepFace.
2. Screen Time Tracking: It tracks how much time you spend looking at the screen (on-screen time) versus away from it (off-screen time).

Features

Emotion Analysis:

• Detects faces in real-time.
• Predicts the dominant emotion for each detected face.
• Displays the emotion on the screen.

Screen Time Tracking:

• Calculates on-screen and off-screen time.
• Alerts with a buzzer sound if off-screen time exceeds a threshold.
• Records maximum on-screen and off-screen times in an Excel sheet (timer_data.xlsx).

Results :

Real-time emotion detection is displayed on the screen. Maximum on-screen and off-screen times are saved in timer_data.xlsx.

Example Use Cases :

Screen Time Monitoring: Keep track of your screen time during work or study sessions. Emotion Tracking: Understand emotional reactions during video calls or online meetings.

How It Works

Dependencies

To run this project, you'll need the following Python libraries:

• OpenCV (cv2)
• DeepFace
• Openpyxl

You can install these using the following command:

pip install opencv-python deepface openpyxl