A convolutional neural network (CNN) in Keras to recognize facial expressions. The data consists of 48x48 pixel grayscale images of faces. The faces are classified based on the emotion shown in the facial expression into one of seven categories (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral). OpenCV has been used to automatically detect faces in images and draw bounding boxes around them. A web interface is used to perform real-time facial expression recognition on video and image data.
artificialnouveau/Facial_Expression_Recognition
A convolutional neural network (CNN) in Keras to recognize facial expressions. The data consists of 48x48 pixel grayscale images of faces. The faces are classified based on the emotion shown in the facial expression into one of seven categories (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral). OpenCV has been used to automatically detect faces in images and draw bounding boxes around them. A web interface is used to perform real-time facial expression recognition on video and image data.
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