This repository contains the PyTorch implementation for ICCV 2021 Paper "Neural Strokes: Stylized Line Drawing of 3D Shapes" by Difan Liu, Matthew Fisher, Aaron Hertzmann, Evangelos Kalogerakis.
- The project is developed on Ubuntu 16.04 with cuda10.0 + cudnn7.6. The code has been tested with PyTorch 1.2.0 (GPU version) and Python 3.7.6.
- Python packages:
- diffvg
- OpenCV (tested with 4.3.0)
- PyYAML (tested with 5.3.1)
- scikit-image (tested with 0.17.2)
- scipy (tested with 1.4.1)
-
Pre-trained model is available here, please put it in
weights
:cd weights unzip weights.zip
-
Dataset is available here, please put it in
datasets
:cd datasets unzip datasets.zip
- Preprocess raw data:
python preprocess.py -s datasets/style_01
-s
: path to the data of a single style.
- Test:
python test.py -d datasets/style_01/test_2 -g weights/style_01/SG.pth -t weights/style_01/ST.pth -s results/style_01__test_2.png
-d
: path to testing data.
-g
: path to Stroke Geometry checkpoint.
-t
: path to Stroke Texture checkpoint.
-s
: path to save the synthesized image.
- Start the Stroke Geometry (SG) training:
python train_SG.py -d datasets/style_01/train -n style_01__SG
- After the Stroke Geometry (SG) training is finished, start the Stroke Texture (ST) training:
python train_ST.py -d datasets/style_01/train -n style_01__ST
-d
: path to training data.
-n
: name of the experiment.
@InProceedings{Liu_2021_ICCV,
author={Liu, Difan and Fisher, Matthew and Hertzmann, Aaron and Kalogerakis, Evangelos},
title={Neural Strokes: Stylized Line Drawing of 3D Shapes},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
year = {2021}
}
To ask questions, please email.