The Facial Emotions Classifier, is a model that accurately predicts facial expressions.
The datasets were collected from one of Kaggle's FER competitions, (https://www.kaggle.com/aspiring1/fer2013-images) as images and then manually cleaned to remove bad images that could affect the model's performance.
Three frameworks were used: PyTorch, fastai library and Tensorflow. After which PyTorch attained the highest accuracy, using se_resnext50_32x4d with a validation accuracy of 98% and Testing accuracy of 76%.
On the other hand, fastai made a Validation accuracy of 76%, using vgg19_bn.
Group Members:
Ojeifo Oziegbe
Ayodele Adebayo
'Kayode Akanni
Praise Taiwo
Sharon Ibejih