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FER - Facial Expression Recognition

This work is to demonstrate the below problem: https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge

A real time face detector and emotion classifier is built using Convolution Neural Network and OpenCV. The CNN model is tuned for fine performance even on a low end device.

Instructions

Follow the guided tutorial for neural network training.

Files Structure:

  • FER_CNN.ipynb - Tutorial to train the CNN
  • FER.py - Uses the pre-trained model to give inferences
  • model.json - Neural network architecture
  • weights.h5 - Trained model weights

Installation

Using Python virtual environment will be advisable.

  • For model prediction

    pip install -r requirements.txt

    OR

    pip install opencv-python

    pip install tensorflow (Note here we are installing tensorflow-cpu)

    pip install keras

  • For model training, pandas numpy tensorflow keras matplotlib scikit-learn seaborn

  • Running the inference engine

Use the webcam

python FER.py webcam <fps>

Use a video file

python FER.py <video_file_name> <fps>

Contributing

  • Report issues on issue tracker
  • Fork this repo
  • Make awesome changes
  • Raise a pull request

Copyright & License

Copyright (C) 2018 Mayur Madnani

Licensed under MIT License

See the LICENSE.