OpenCV: Emotion Recognizer (Python)

This project aims to detect users' emotions by analyzing their facial expressions. We utilized OpenCV to process a dataset of 20,000 images from the CK+ database. The main approach involves classifying facial images using the Haar features-based cascades classifier. To train the model, we used the Linear Discriminant Analysis (LDA) model, which maximizes the distance between different classes while minimizing variance. For the training process, we used the Linear Discriminant Analysis (LDA) model that maximizes the distance between different classes while minimizing variance.