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Cartoon-GAN

Original_0

Paper: https://arxiv.org/abs/2005.07702

Description

This project takes on the problem of transferring the style of cartoon images to real-life photographic images by implementing previous work done by CartoonGAN. We trained a Generative Adversial Network(GAN) on over 60 000 images from works by Hayao Miyazaki at Studio Ghibli.

Dependencies

  1. Install Anaconda from https://www.anaconda.com/

  2. Install pytorch at: https://pytorch.org/get-started/locally/

  3. Install dependencies:

    python -m pip install tqdm pillow numpy matplotlib opencv-python
    
  4. For predicting videos you will also need ffmpeg

Training

All training code can be found in experiment.ipynb

Predict

Predict by running predict.py.

Example:

python predict.py -i C:/folder/input_image.png -o ./output_folder/output_image.png

Predictions can be made on images, videos or a folder of images/videos.

Demonstration

Image # Original CartoonGAN GANILLA Our implementation
1 Original_1 CartoonGAN_1 GANILLA_1 Ours_1
2 Original_2 CartoonGAN_2 GANILLA_2 Ours_2
3 Original_3 CartoonGAN_3 GANILLA_3 Ours_3
4 Original_4 CartoonGAN_4 GANILLA_4 Ours_4
5 Original_5 CartoonGAN_5 GANILLA_5 Ours_5
6 Original_6 CartoonGAN_6 GANILLA_6 Ours_6
7 Original_7 CartoonGAN_7 GANILLA_7 Ours_7
8 Original_8 CartoonGAN_8 GANILLA_8 Ours_8
9 Original_9 CartoonGAN_9 GANILLA_9 Ours_9
10 Original_10 CartoonGAN_10 GANILLA_10 Ours_10
11 Original_11 CartoonGAN_11 GANILLA_11 Ours_11
12 Original_12 CartoonGAN_12 GANILLA_12 Ours_12
13 Original_13 CartoonGAN_13 GANILLA_13 Ours_13
14 Original_14 CartoonGAN_14 GANILLA_14 Ours_14
15 Original_15 CartoonGAN_15 GANILLA_15 Ours_15
16 Original_16 CartoonGAN_16 GANILLA_16 Ours_16
17 Original_17 CartoonGAN_17 GANILLA_17 Ours_17
18 Original_18 CartoonGAN_18 GANILLA_18 Ours_18
19 Original_19 CartoonGAN_19 GANILLA_19 Ours_19
20 Original_20 CartoonGAN_20 GANILLA_20 Ours_20

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  • Jupyter Notebook 97.6%
  • Python 2.4%