This repo is to extract the computational aesthetic features introduced from the paper - "The Pictures we Like are our Image: Continuous Mapping of Favorite Pictures into Self-Assessed and Attributed Personality Traits". Some of the features had been removed and readapted. See the table below.
| Category | Name | dimension |
|---|---|---|
| Color | HSV statics Emotion-based Color diversity Color name |
5 3 1 11 |
| Composition | Edge pixels Level of detial Average region size Low depth of field (DOF) Rule of thirds Image size |
1 1 1 3 2 1 |
| Textural Properties | Gray distribution entropy Wavelet based textures Tamura GLCM - features |
1 12 3 3 |
The description column is omitted. To see what each feature does, please refer to the paper. Additionally, there are some changes being made.
- The Faces features was removed.
- The realization of color diversity is different from the paper.
- The GIST descriptors was removed.
- The GLCM - features used only gray image and left only 4 features.
$ pip install git+https://github.com/Justin900429/computational-aesthetics
from CA import CA
...
# Create objects
img_path = "..."
ca = CA(img_path)
res = ca.compute_ca()
...
# update image path
new_path = "..."
ca.update(new_path)
new_res = ca.compute_ca()
...See example for more details
@ARTICLE{
7378902,
author={Segalin, Crisitina and Perina, Alessandro and Cristani, Marco and Vinciarelli, Alessandro},
journal={IEEE Transactions on Affective Computing},
title={The Pictures We Like Are Our Image: Continuous Mapping of Favorite Pictures into Self-Assessed and Attributed Personality Traits},
year={2017},
volume={8},
number={2},
pages={268-285},
doi={10.1109/TAFFC.2016.2516994}
}