Awesome

LineCloser

Unofficial Keras implementation of Joint Gap Detection and Inpainting of Line Drawings.

Overview

Joint gap for line-drawings. Model1 uses network from the paper. For stable training, BN was added for all Conv2D. Model2 uses common network for inpaint.

Dependencies

• Keras2 (Tensorflow backend)
• OpenCV3
• CairoSVG

Usage

1. Set up directories.

2. Download the model from release and put it in the same folder with code.

3. Run predict.py for prediction. Run model{NUM}.py for train.

Data Preparation

There are 3 methods for data generation, DATA_GEN, DATA_GAP and DATA_THIN.

0. Use DATA_GEN for training, the data is generated online.

1. Collect line-drawings with LineDistiller.

2. Put line-drawings into data/line, using DATA_GAP for training.

3. Thin(normalize) the line-drawings with LineNormalizer or tranditional thinning method.

4. Manually processe line-drawings and thinning results(threshold etc.), then crop them into pieces.

5. Put line-drawings into data/line and put thinning results into data/thin, using DATA_THIN for training.

Models

Models are licensed under a CC-BY-NC-SA 4.0 international license.

• LineCloser Release Page

From Project HAT by Hepesu With :heart: