Facial_Expression_Recognition

This system utilises Convolutional Neural Network (CNN) methodology and the OpenCV framework, leveraging TensorFlow and Keras libraries to predict and recognize facial emotions in images. It demonstrates proficiency in classifying facial emotion recognition (FER) from static photos, employing preprocessing methods for enhanced accuracy. Feature extraction isolates vital facial features such as the jawline, mouth, eyes, nose, and eyebrows. Achieving a classification accuracy of 96.16% and a validation accuracy of 62.02%, it effectively distinguishes seven distinct emotions based on facial expressions.