Official implementation of Color Recommendation for Vector Graphic Documents based on Multi-Palette Representation, WACV 2023
- Python:3.8
- Poetry: 1.2.*
Install requirements and run jupyter.
poetry install
poetry run jupyter lab
notebooks/recomm_colors.ipynb
: recommend colors for multiple palettes in a design
- Trained model of color prediction are in trained_models/.
- Json files for test are pre-created in data/model_test_input/crello_samples/.
You can train a color model on a notebook notebooks/train_model.ipynb
. We recommended GPU resources to train this model (e.g. Tesla T4 * 1).
You can also create a json file for test from crello dataset on a notebook notebooks/create_json_file.ipynb
.
data/training_data/metadata_colors
: extracted color palettes for Image-SVG-Text elements from Crello-dataset-v1 (the lastest Crello-dataset)
data/training_data/data_bert/data_color
: color corpus of train, validation, and test dataset, and color vocabulary from train dataset
data/trained_models
: trained model for color recommendation
model_test_input
: json sample files for testing the results of color recommendation
@misc{Qiu_2022,
author = {Qiu Qianru, Wang Xueting, Otani Mayu, and Iwazaki Yuki},
title = {Color Recommendation for Vector Graphic Documents based on Multi-Palette Representation},
doi = {10.48550/ARXIV.2209.10820},
url = {https://arxiv.org/abs/2209.10820},
year = {2022},
}