Category :
Software Projects
Project Dates :
2025-07-24 - 2025-07-24

πŸ“Έ Emotion Detection from Multiple Sources

Welcome to the Emotion Detection Application – a tool for identifying and analyzing emotions from images and live camera feeds. This project is built with an intuitive interface and powerful emotion recognition capabilities.


πŸš€ About the Project

This application uses DeepFace and OpenCV to detect and analyze human emotions in real-time or from static images. It’s equipped with a user-friendly graphical interface built with Tkinter, making it accessible for users of all levels.

🎯 Core Features

  • πŸ–ΌοΈ Image Emotion Analysis: Upload an image and detect emotions with a visual overlay of results.
  • πŸ“‚ Folder Analysis: Analyze multiple images in a folder seamlessly.
  • πŸŽ₯ Live Camera Emotion Detection: Real-time emotion analysis from your webcam feed.
  • πŸ’¬ Motivational Quotes: Receive personalized quotes based on detected emotions.
  • πŸ’Ύ Save Results: Captured images and results are automatically saved for later review.

πŸ› οΈ Technologies Used

  • Python 3
  • OpenCV – Image processing and camera interface
  • DeepFace – Emotion analysis
  • Tkinter – User interface
  • Pillow (PIL) – Image handling

Check out all dependencies in requirements.txt.


πŸ’» How to Run the Project

πŸ“₯ 1. Clone the Repository

git clone https://github.com/axbecher/emotion_detection_from_multiple_sources
cd emotion-detection

🐍 2. Install dependencies

pip install -r requirements.txt

πŸ–₯️ 3. Install dependencies

python ui.py

πŸ–ΌοΈ How the Application Looks & Works

This section provides a visual walkthrough of the Emotion Detection Application. Below are screenshots demonstrating key functionalities:

1. Home Screen

The home screen offers intuitive navigation options to analyze emotions from live captures or photos. Home Screen

2. Live Emotion Analysis

When you select "Live Emotion Analysis," the application requests camera permissions to initiate real-time emotion detection. Camera Permission Camera Starting

Once the camera is active, the system analyzes your facial expressions, highlighting the detected emotions: Live Emotion Detection

3. Photo Emotion Analysis

You can also analyze static images by selecting "Photo Emotion Analysis" and choosing an image or folder: Photo Emotion Analysis

The results display the dominant emotion and a breakdown of detected emotions, stress grades, and more: Photo Analysis Results

4. Saved Captures

The application automatically saves analyzed images and results for future reference.
Captured images from live analysis are stored in the captures folder: Live Captures Folder

Analyzed photos from the "Photo Emotion Analysis" feature are saved in the photos_captures folder: Photo Captures Folder