A Deep Learning powered engine to measure your Website's Aesthetics
Paper: "Calista: A deep learning-based system for understanding and evaluating website aesthetics"
Cite as:
@article{DELITZAS2023,
title = {Calista: A deep learning-based system for understanding and evaluating website aesthetics},
journal = {International Journal of Human-Computer Studies},
volume = {175},
pages = {103019},
year = {2023},
issn = {1071-5819},
doi = {https://doi.org/10.1016/j.ijhcs.2023.103019},
url = {https://www.sciencedirect.com/science/article/pii/S1071581923000253},
author = {Alexandros Delitzas and Kyriakos C. Chatzidimitriou and Andreas L. Symeonidis}
}
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Step 1: Insert the URL of the webpage that you want to evaluate its aesthetics
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Step 2: Wait a few seconds for the assessment process to complete
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Step 3: The aesthetics score is ready!
- Docker
- Docker-compose
Download the model in the folder CNN/src/cnn_model/ from here.
Add a .env file in the root folder of the project and set the following variables:
| Environment variable | Description |
|---|---|
| BASEURL | Base URL that is used for the requests |
Start:
docker-compose -f docker-compose.yml up --build
Stop:
Ctrl-C
For detached mode:
Start:
docker-compose -f docker-compose.yml up -d --build
Stop:
docker-compose down