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This project implements a dual-mode Emotion Recognition system using deep learning. It trains separate models for: Facial emotion recognition using the FER-2013 dataset Audio emotion recognition using the RAVDESS dataset Both training scripts generate h5 and png. Deployment is not yet integrated; current focus is on training and model generation.
A real-time facial expression recognition system built with CNN, TensorFlow, and OpenCV. It uses a webcam to detect faces and classify emotions like happiness, sadness, anger, and more.