Facial_Expression_Recognition_FER2013
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Baticsute
Images and Videos, Real-time Facial Expession Recognition Application with Combine CNN , deep learning features extraction incorporate SIFT, FAST feature .
Facial_Expression_Recognition_FER2013
Powered by Python 3.5
Library Requirements
pip install tensorflow-gpu
pip install keras
pip install numpy
pip install sklearn
pip install pandas
pip install opencv-python==3.3.1
Dataset
FER2013
More details : Kaggle Challenge - https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data
Accuracy Achivement
Kaggle Challenge Winner 71.2%.
Model Combine CNN1 + CNN2 + CNN_FAST + CNN_SIFT 72.89%
Confusion Matrix
CNN Architectures
Build from scratch in /cnn folder .
HOW ARE YOU TODAY? Application
Run UI.py file to open application.
You can choose some image and video that include human faces to detect emotions
Click Button "Open Your Camera" for real-time detecting yourself emotions from webcam.
Highlight Results
Video Realtime
Examples will be uploaded later.
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