This repository is the out project about mood recognition using convolutional neural network for the course Seminar Neural Networks at TU Delft.
We use the FER-2013 Faces Database, a set of 28,709 pictures of people displaying 7 emotional expressions (angry, disgusted, fearful, happy, sad, surprised and neutral). The dataset quality and image diversity is not very good and you will probably get a model with bad accuracy in other applications!
You have to request for access to the dataset or you can get it on Kaggle. Download
fer2013.tar.gz and decompress
fer2013.csv in the
Install all the dependencies using
virtualenv -p python3 ./ source ./bin/activate pip install -r requirements.txt
The data is in CSV and we need to transform it using the script
csv_to_numpy.py that generates the image and label data in the
$ python3 csv_to_numpy.py
By default this is using AlexNet architectures, but in the paper we propose different ones.
# To train a model $ python3 emotion_recognition.py train # To use it live $ python3 emotion_recognition.py poc