Facial Emotion Recognition System

A facial emotion recognition system developed using deep learning techniques to accurately detect and classify human emotions in real-time. This project utilizes Python, OpenCV, Tensorflow, and DeepFace libraries.

Features

• Real-time emotion detection through video feed or static images.
• Recognizes various emotions such as happiness, sadness, anger, surprise, and more.
• High accuracy achieved by fine-tuning the neural network and optimizing model architecture.

Technologies Used

• Python
• OpenCV
• Tensorflow
• DeepFace

Installation

1. Clone the repository:

   https://github.com/rajkrsingh9/Facial-Emotion-Recognition.git
   cd Facial-Emotion-Recognition

2. Create a virtual environment and activate it:

3. Install the required libraries:

Usage

1. Ensure you have a webcam connected for real-time emotion detection.
2. Run the emotion recognition script:

   python main.py

3. The system will start capturing video from your webcam and display the detected emotions in real-time.

How It Works

• The system uses OpenCV for image processing and capturing video feed from the webcam.
• DeepFace library is used for face detection and emotion recognition.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

Acknowledgements

• OpenCV
• Keras
• DeepFace

Contact

For any questions or inquiries, please contact:

• Raj Kumar Singh
• Email: [email protected]