Emotion Recognition with DeepFace

This program utilizes the DeepFace library to perform real-time emotion recognition from webcam video feed.

Features

• Detects faces in the webcam video feed using the Haar cascade classifier.
• Analyzes the detected faces using DeepFace to determine the dominant emotion.
• Displays the bounding box around the detected face and the corresponding dominant emotion label in real-time.
• Calculates and displays the frames per second (FPS) of the video feed.

Requirements

• Python 3.x
• OpenCV (pip install opencv-python)
• DeepFace (pip install deepface)

Usage

1. Clone the repository:

   git clone https://github.com/jahnavirishikesh/Emotion-Recognition-Deepface.git

2. Navigate to the project directory:

   cd Emotion-Recognition-Deepface

3. Run the program:

   python emotion_recognition.py

4. A new window will open displaying the webcam video feed with the emotion recognition overlay.

5. Press 'q' to quit the program.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Acknowledgements

This program utilizes the DeepFace library developed by Rıza Alp Güler and the Haar cascade classifier provided by OpenCV.

Enjoy emotion recognition with DeepFace!