Emotion Recognition from Facial Expressions

This package is a submodule of the "Empathy in Embodied Conversational Agents" project in iVizLab @Simon Fraser University.

It is intended to provide a simple emotion recognition component to capture the facial emotions from offline images, videos as well as online web-cam data.

Prerequisites

The system is tested for:

• Python == 3.6.*

• opencv-python >= 3.4, <=4.0

• keras >= 2.0, <=2.2.* with tensorflow = 1.12.0 backend

Installing

The package and dependencies can be installed via pip with:

pip install git+https://github.com/o-n-yalcin/face_emotion_recognition

Or clone the project and:

$ git clone https://github.com/o-n-yalcin/face_emotion_recognition.git
$ pip install -e ./face_emotion_recognition

You can start using the recognizer. You only need to pass a frame for the recognizer to do its job:

from fer.recognizer.video_recognition import EmoVideoRecognizer

emo = EmoVideoRecognizer()
predictions = emo.recognize(frame)

Example Usages

The project includes three examples within the examples folder. Offline examples require video and image files to be placed in the related folders within the data folder.

test_image.py prints out the prediction results for each image in the data/images folder.

$ python -m examples.test_image

test_video_file creates a csv file of predictions per frame for every video within the data/videos folder.

$ python -m examples.test_video_file

Online example creates a thread for webcam input and shows the prediction results in real time.

$ python -m examples.test_webcam

Following these examples you can create your own version according to your needs.

Authors

• Ozge Nilay Yalcin - ony

License

This project is licensed under the MIT License - see the LICENSE.txt file for details