This project is a collection of jupyter-based, akori-project reports regarding saliency tests on a free-viewing web-page/user environment. Our main objective is to explore and create a machine-learning oriented algorithms able to predict user's eye-behaviour that are specifically optimized for different environments such as webpage behaviour.

If you don't know much about python or jupyter it's highly recommended to paste this repository link to binder and interact with the code, you can do that if you press this pink button:

To run and modify this project locally, know that this project is updated to always work with the latest version of Python 3 with modules such as numpy, scipy, pillow... the usual stuff. Every package needed can be found on it's requirements.txt file, because of this all you need is pip to start.

It's highly advised to make your own virtual environment with pip, you con follow the step listed in their docs here.

• Sweat, blood and tears.

I'm alone and single.

TODO

• Kristofher M. Rojas - Initial work - Eye-tracking

TODO

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

• PurpleBooth's Readme template
• God, for not existing.
• TODO