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Emotion recognition using DNN with tensorflow
| Date | Stars |
|---|---|
| 2026-07-24 | 846 |
| 2026-07-25 | 846 |
| 2026-07-28 | 846 |
| 2026-07-30 | 846 |
| 2026-07-31 | 846 |
| 2026-08-06 | 846 |
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# Emotion recognition with CNN # DO NOT USE: Currently I think the code is not even running and I really don't have time to fix it This repository is the out project about mood recognition using convolutional neural network for the course Seminar Neural Networks at TU Delft.  67% Accuracy  ## Dataset We use the [FER-2013 Faces Database](http://www.socsci.ru.nl:8180/RaFD2/RaFD?p=main), 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](https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data). Download `fer2013.tar.gz` and decompress `fer2013.csv` in the `./data` folder. Install all the dependencies using `virtualenv`. ```bash 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 `data` folder. ```bash $ python3 csv_to_numpy.py ``` By default this is using AlexNet architectures, but in the paper we propose different ones. ## Usage ```bash # To train a model $ python3 emotion_recognition.py train # To use it live $ python3 emotion_recognition.py poc ``` ## Paper [Link](https://github.com/isseu/emotion-recognition-neural-networks/blob/master/paper/Report_NN.pdf)
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Justin Shenk · Germany
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:8fc13791802c2042, topic:tensorflow