/XCI-Sketch

Official implementation of https://arxiv.org/abs/2108.11554 paper

Primary LanguageJupyter Notebook

XCI-Sketch: Extraction of Color Information from Images for Generation of Colored Outlines and Sketches

Harsh Rathod, Manisimha Varma, Parna Chowdhury, Sameer Saxena, V Manushree, Ankita Ghosh, Sahil Khose


Official implementation of https://arxiv.org/abs/2108.11554 paper. This paper was submitted in SKETCHING FOR HUMAN EXPRESSIVITY 2021 workshop (ICCV 2021).

Checkout our model predictions!

  • It is available here on Streamlit Sharing.

Methodology

Our work aims to convert photographic images into colored sketches.

We use the Contour Drawing Dataset presented in the Photo-Sketching paper and propose two ways to extract color information from the images and amalgamate it with the corresponding sketches:

  • Rendering Colored Outlines in Sketches:
    • We formulate a process to transfer color onto the existing black and white sketches in the dataset to produce colored outline sketches.
    • We first select an optimal threshold value (TryingDifferentThresholdValues.ipynb) based on which we perform preprocessing and K-Means Color Clustering (GeneratingImagesBasedOnKVals.ipynb) on the images.
    • Using the post-processing image and grayscale sketches we generate colored outlines (GeneratingOutlines.ipynb).
  • Generating Colored Sketches:
    • We propose another method to produce color-filled sketches by performing colorspace manipulation (data_preprocessing.ipynb).
    • We go a step further to use these sketches as the training dataset for a Generative Adversarial Network and develop a model which can generate colored sketches from unseen images (Sketch_gan.ipynb).

Download the data here

License: This work has been apadted from dataset which is licensed under CC BY-NC-SA (Attribution-NonCommercial-ShareAlike). That means you can use this dataset for non-commerical purposes and your adapted work should be shared under similar conditions.