# Animating using AnimeGanV2
*author: Filip Haltmayer*
## Description
Convert an image into an animated image using [`AnimeganV2`](https://github.com/TachibanaYoshino/AnimeGANv2).
## 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()
```
*Write a pipeline with explicit inputs/outputs name specifications:*
```python
import towhee
towhee.glob['path']('./test.png') \
.image_decode['path', 'origin']() \
.img2img_translation.animegan['origin', 'facepaintv2'](model_name = 'facepaintv2') \
.img2img_translation.animegan['origin', 'hayao'](model_name = 'hayao') \
.img2img_translation.animegan['origin', 'paprika'](model_name = 'paprika') \
.img2img_translation.animegan['origin', 'shinkai'](model_name = 'shinkai') \
.select['origin', 'facepaintv2', 'hayao', 'paprika', 'shinkai']() \
.show()
```
## Factory Constructor
Create the operator via the following factory method
***img2img_translation.animegan(model_name = 'which anime model to use')***
Model options:
- celeba
- facepaintv1
- facepaintv2
- hayao
- paprika
- shinkai
## 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.
**Returns**: *towhee.types.Image (a sub-class of dumpy.ndarray)*
The new image.
## Reference
Jie Chen, Gang Liu, Xin Chen
"AnimeGAN: A Novel Lightweight GAN for Photo Animation."
ISICA 2019: Artificial Intelligence Algorithms and Applications pp 242-256, 2019.