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Fix Typo. Add Code Tags #50

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Fix Typo. Add Code Tags #50

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20 changes: 10 additions & 10 deletions README.md
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Expand Up @@ -50,22 +50,22 @@
### 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
- 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
- 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
- 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:
Expand All @@ -80,7 +80,7 @@ https://drive.google.com/file/d/1j0jDENjdwxCDb36meP6-u5xDBzmKBOjJ/view?usp=shari
- 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
- We used this repo(https://github.com/nagadomi/lbpcascade_animeface) to detect facial areas
- Manual data cleaning will greatly increace both datasets quality

## Acknowledgement
Expand All @@ -90,7 +90,7 @@ 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
- Commercial application is prohibited, please retain this license if you clone this repo

## Citation

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