# Cartoonize with CartoonGAN

*author: Shiyu*



<br />



## Description

Convert an image into an cartoon image using [`CartoonGAN`](https://github.com/Yijunmaverick/CartoonGAN-Test-Pytorch-Torch).



<br />




## Code Example

Load an image from path './test.png'. 

 *Write the pipeline in simplified style*:

```python
import towhee

towhee.glob('./test.png') \
      .image_decode() \
      .img2img_translation.animegan(model_name = 'hayao') \
      .show()
```

<img src="./results1.png" height="150px"/>

*Write a pipeline with explicit inputs/outputs name specifications:*

```python
import towhee
      
towhee.glob['path']('./test.png') \
      .image_decode['path', 'origin']() \
      .img2img_translation.cartoongan['origin', 'hayao'](model_name = 'Hayao') \
      .img2img_translation.cartoongan['origin', 'hosoda'](model_name = 'Hosoda') \
      .img2img_translation.cartoongan['origin', 'paprika'](model_name = 'Paprika') \
      .img2img_translation.cartoongan['origin', 'shinkai'](model_name = 'Shinkai') \
      .select['origin', 'hayao', 'hosoda', 'paprika', 'shinkai']() \
      .show()
```

<img src="./results2.png" alt="results1" height="150px"/>



<br />



## Factory Constructor

Create the operator via the following factory method

***img2img_translation.cartoongan(model_name = 'which anime model to use')***

Model options: 

- Hayao
- Hosoda
- Paprika
- Shinkai



<br />



## Interface

Takes in a numpy rgb image in channels first. It transforms input into animated image in numpy form.


**Parameters:**

​	***model_name***: *str*

​	Which model to use for transfer.

   ***framework***: *str*

​	Which ML framework being used, for now only supports PyTorch.

  ***device***: *str*

​	Which device being used('cpu' or 'cuda'), defaults to 'cpu'.



**Returns**: *towhee.types.Image (a sub-class of numpy.ndarray)*

​	The new image.