BraveVahid/facial-emotion-recognition
A deep learning project for facial emotion recognition using CNN architecture trained on the FER2013 dataset. The model classifies facial expressions into 7 emotion categories with comprehensive data augmentation and regularization techniques.
This project helps you automatically detect human emotions from still images of faces. You provide images of faces, and the system categorizes the expression into one of seven emotions like 'Happy,' 'Sad,' or 'Angry.' This is useful for researchers in psychology, human-computer interaction, or anyone analyzing emotional responses from visual data.
Use this if you need to classify facial expressions from static images into predefined emotional categories and are comfortable with a work-in-progress solution.
Not ideal if you need real-time emotion detection from a webcam, require a web-based interface, or demand extremely high accuracy for subtle emotions like 'Fear' or 'Sadness' in production.
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Dec 16, 2025
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