Facial Expression Recognition

• Tech Stack: OpenCV, CNN, Keras, Flask
• Github URL: Project Link

Key Features of the Project:

1. Facial Expression Recognition: Build and train a convolutional neural network (CNN) in Keras from scratch to recognize facial expressions in images.
2. Emotion Classification: Classify facial expressions into seven emotion categories: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral.
3. Face Detection: Utilize OpenCV to automatically detect faces in images and draw bounding boxes around them.
4. CNN Model Export: Save and export the trained CNN model for future use and deployment.
5. Real-time Facial Expression Recognition: Serve the trained model predictions to a web interface, enabling real-time facial expression recognition on video streams and image data.
6. Flask Web Interface: Deploy the trained model to a Flask web interface, providing a user-friendly platform for interacting with the facial expression recognition system.