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A implementation for facial expression recognition on fer2013 dataset using a single convolutional neural network architecture

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FER-SN-FER2013

Usage

Step 1. Install libraries

conda env create -f environment.yml

Step 2. Download fer2013 CSV file

https://www.kaggle.com/competitions/challenges-in-representation-learning-facial-expression-recognition-challenge/data

Step 3. Download pre-trained models from this link

https://1drv.ms/u/s!AmeTT2EpSz40hFjOlVmzrTr7h_8N?e=kLQcpv

Step 4. Set the correct paths in the following files

Evaluation.ipynb
train.py
data/fer2013.py

To train the model from scratch, run the following

python train.py network=vgg name=my_vgg

For evaluation open the following jupyter notebook

Evaluation.ipynb

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A implementation for facial expression recognition on fer2013 dataset using a single convolutional neural network architecture

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