😊 Real-Time Emotion Detection❤️

A powerful and intuitive real-time facial emotion detection system using OpenCV and MediaPipe. Detects emotions such as Happy, Sad, Angry, Fear, and Neutral from live webcam video feeds 🎥 — with smooth performance and high accuracy.

✨ Features:

✅ Real-time emotion detection from your webcam. 😀 Detects 4 core emotions: Happy, Sad, Angry, Neutral. 📊 Displays confidence/probability for each emotion. 😄 High accuracy for smile/happy detection. 🎛️ Clean UI with dynamic confidence bars.
⚡ Real-time FPS (Frames Per Second) counter for performance monitoring.

🛠 Requirements:

• Python 3.7 or above 🐍
• Functional Webcam 🎥
• Libraries listed in requirements.txt

🚀 Installation:

1. Clone the repository 📥

   git clone https://github.com/your-username/real-time-emotion-detector.git
   cd real-time-emotion-detector

2. Install required packages 📦

   pip install -r requirements.txt

▶️ How to Use:

1. Run the application 💻

   python main.py

2. Your webcam will activate and begin real-time emotion detection 🧠
3. Press 'q' to quit the application ❌

🧠 How It Works:

This system uses a hybrid approach combining facial geometry with fallback image analysis:

1. Face Detection

🔍 Powered by MediaPipe Face Mesh to detect and track 468 facial landmarks in real-time.

2. Facial Feature Analysis

Analyzes geometrical features like:

• 👄 Mouth shape and curvature (key for detecting smiles)
• 👁 Eye aspect ratio
• 🙄 Eyebrow positioning
• 😊 Cheek area landmarks

3. Fallback Detection Logic

When landmark detection is weak, the system uses:

• 🖍 Edge detection in facial regions
• 💡 Brightness/intensity patterns
• 🔲 Region-based texture analysis

⚠️ Limitations:

• Works best in good lighting conditions 💡
• Accuracy may vary depending on webcam quality 📸