# 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() ``` results1
## 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.