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# 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.
3 years ago