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https://github.com/SystemErrorWang/White-box-Cartoonization
Official tensorflow implementation for CVPR2020 paper “Learning to Cartoonize Using White-box Cartoon Representations”
https://github.com/SystemErrorWang/White-box-Cartoonization
Last synced: about 2 months ago
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Official tensorflow implementation for CVPR2020 paper “Learning to Cartoonize Using White-box Cartoon Representations”
- Host: GitHub
- URL: https://github.com/SystemErrorWang/White-box-Cartoonization
- Owner: SystemErrorWang
- Created: 2020-03-16T12:11:53.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2022-10-09T12:49:22.000Z (over 2 years ago)
- Last Synced: 2024-11-05T03:51:36.814Z (2 months ago)
- Language: Python
- Size: 43.6 MB
- Stars: 3,954
- Watchers: 74
- Forks: 738
- Open Issues: 73
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-tensorflow-lite - White-box CartoonGAN - model/cartoongan/dr/1)) | [Project repo](https://github.com/margaretmz/Cartoonizer-with-TFLite) \| [Android](https://github.com/margaretmz/Cartoonizer-with-TFLite/tree/master/android) \| [Tutorial](https://blog.tensorflow.org/2020/09/how-to-create-cartoonizer-with-tf-lite.html) | Community | (Models with samples / Computer vision)
README
# [CVPR2020]Learning to Cartoonize Using White-box Cartoon Representations
[project page](https://systemerrorwang.github.io/White-box-Cartoonization/) | [paper](https://github.com/SystemErrorWang/White-box-Cartoonization/blob/master/paper/06791.pdf) | [twitter](https://twitter.com/IlIIlIIIllIllII/status/1243108510423896065) | [zhihu](https://zhuanlan.zhihu.com/p/117422157) | [bilibili](https://www.bilibili.com/video/av56708333) | [facial model](https://github.com/SystemErrorWang/FacialCartoonization)
- Tensorflow implementation for CVPR2020 paper “Learning to Cartoonize Using White-box Cartoon Representations”.
- Improved method for facial images are now available:
- https://github.com/SystemErrorWang/FacialCartoonization
## Use cases
### Scenery
### Food
### Indoor Scenes
### People
### More Images Are Shown In The Supplementary Materials
## Online demo
- Some kind people made online demo for this project
- Demo link: https://cartoonize-lkqov62dia-de.a.run.app/cartoonize
- Code: https://github.com/experience-ml/cartoonize
- Sample Demo: https://www.youtube.com/watch?v=GqduSLcmhto&feature=emb_title
## Prerequisites
- Training code: Linux or Windows
- NVIDIA GPU + CUDA CuDNN for performance
- Inference code: Linux, Windows and MacOS
## How To Use
### Installation
- Assume you already have NVIDIA GPU and CUDA CuDNN installed
- Install tensorflow-gpu, we tested 1.12.0 and 1.13.0rc0
- Install scikit-image==0.14.5, other versions may cause problems
### Inference with Pre-trained Model
- Store test images in /test_code/test_images
- Run /test_code/cartoonize.py
- Results will be saved in /test_code/cartoonized_images
### Train
- Place your training data in corresponding folders in /dataset
- Run pretrain.py, results will be saved in /pretrain folder
- Run train.py, results will be saved in /train_cartoon folder
- Codes are cleaned from production environment and untested
- There may be minor problems but should be easy to resolve
- Pretrained VGG_19 model can be found at following url:
https://drive.google.com/file/d/1j0jDENjdwxCDb36meP6-u5xDBzmKBOjJ/view?usp=sharing
### Datasets
- Due to copyright issues, we cannot provide cartoon images used for training
- However, these training datasets are easy to prepare
- Scenery images are collected from Shinkai Makoto, Miyazaki Hayao and Hosoda Mamoru films
- Clip films into frames and random crop and resize to 256x256
- Portrait images are from Kyoto animations and PA Works
- We use this repo(https://github.com/nagadomi/lbpcascade_animeface) to detect facial areas
- Manual data cleaning will greatly increace both datasets quality
## Acknowledgement
We are grateful for the help from Lvmin Zhang and Style2Paints Research
## License
- Copyright (C) Xinrui Wang All rights reserved. Licensed under the CC BY-NC-SA 4.0
- license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
- Commercial application is prohibited, please remain this license if you clone this repo
## Citation
If you use this code for your research, please cite our [paper](https://systemerrorwang.github.io/White-box-Cartoonization/):
@InProceedings{Wang_2020_CVPR,
author = {Wang, Xinrui and Yu, Jinze},
title = {Learning to Cartoonize Using White-Box Cartoon Representations},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
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