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# Animating using AnimeGanV2
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*author: Filip Haltmayer*
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## Description
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Convert an image into an animated image using [`AnimeganV2`](https://github.com/TachibanaYoshino/AnimeGANv2).
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## Code Example
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Load an image from path './image.png'.
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*Write the pipeline in simplified style*:
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```python
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import towhee
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from PIL import Image
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import numpy
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pipeline = towhee.glob('./image.png').image_decode.cv2().img2img_translation.animegan(model_name = 'hayao')
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img = pipeline.to_list()[0]
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img = numpy.transpose(img, (1,2,0))
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img = Image.fromarray((img * 255).astype(numpy.uint8))
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img.show()
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```
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## Factory Constructor
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Create the operator via the following factory method
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***img2img_translation.animegan(model_name = 'which anime model to use')***
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Model options:
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- celeba
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- facepaintv1
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- facepaintv2
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- hayao
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- paprika
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- shinkai
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## Interface
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Takes in a numpy rgb image in channels first. It transforms input into animated image in numpy form.
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**Parameters:**
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***model_name***: *str*
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Which model to use for transfer.
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***framework***: *str*
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Which ML framework being used, for now only supports PyTorch.
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**Returns**: *numpy.ndarray*
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The new image.
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## Reference
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Jie Chen, Gang Liu, Xin Chen
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"AnimeGAN: A Novel Lightweight GAN for Photo Animation."
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ISICA 2019: Artificial Intelligence Algorithms and Applications pp 242-256, 2019.
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