The program is a realization of the main assignment for ID1214 Artificial Intelligence course at Kungliga Tekniska Högskolan (Stockholm), done in collaboration with David Rundel.

It is a a generative art-based animation portraying the user’s mood. We use two artificial-intelligence-based modules in the project - face detection (OpenCV) and emotion recognition (Convolutional Neural Network). These components serve as means for obtaining data (input in a form of face image from webcam) and processing it (evaluating the emotion). The output of the program is a generative-art-based function which takes as a parameter the determined emotion, translates it into a set of variables (color, brush weight etc.) and on this basis produces an image.

The resulting program is a simple application with two screens as a visual output, number of modules facilitating a real-time flow of data and artificial-intelligence-based logic and manipulation of the data.

When establishing the environment for the program, we recommend using Anaconda. In addition, a webcam is needed to capture images of the user. The expected output, when launching the program (integrated_system.py), is a full-screen application with start button triggering an emotion-driven animation. One quits the application with ESC button.

Examplary output:

Libraries required for the Integrated System (integrated_system.py):

• tensorflow 2.0.0
• keras 2.3.1
• numpy 1.17.3
• tkinter 8.6.8
• PIL 6.2.1
• opencv-python 4.1.2.30
• cairo 1.14.12
• pycairo 1.18.2

Necessary files for the Integrated System:

• model.h5
• model.json
• haarcascade_frontalface_default.xml

Libraries required for the Facial_Expression (facial_expression.ipynb):

• tensorflow 2.0.0
• keras 2.3.1
• numpy 1.17.3
• pandas 0.25.3
• hyperopt 0.1.2
• scipy 1.3.1
• sklearn 0.22
• matplotlib 3.1.1