XiaoSanchez/Facial_Expression_Recognition
Convolutional Neural Network in Keras Recognize Facial Expressions
This helps automatically identify the emotional expression on faces in images or live video. It takes a facial image or video feed as input and outputs a classification of the emotion shown, choosing from seven categories like happy, sad, or angry. This is useful for researchers studying human behavior, marketers analyzing audience reactions, or anyone needing to quantify emotional responses.
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Use this if you need to automatically detect faces and categorize their expressions in images or real-time video streams.
Not ideal if you require nuanced emotional intensity scores beyond simple categories or need to recognize emotions from body language.
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Language
Python
License
MIT
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Last pushed
Oct 12, 2022
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