/facial-expression-classifier

Learn facial expressions from an image, using the FER-2013 Dataset.

Primary LanguageJupyter NotebookMIT LicenseMIT

facial-expression-classifier

Learn facial expressions from an image, using FER-2013 Dataset. The data consists of 48x48 pixel grayscale images of faces. The faces have been automatically registered so that the face is more or less centred and occupies about the same amount of space in each image.

The task is to categorize each face 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). The training set consists of 28,709 examples and the public test set consists of 3,589 examples.

Plot of number of images in training set

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Plot of number of images in test set

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Visualize images from each category

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Loss and Accuracy plot

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Confusion Matrix and Classification on training set

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Confusion Matrix and Classification on test set

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