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# Cartoonize with CartoonGAN
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*author: Shiyu*
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<br />
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## Description
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Convert an image into an cartoon image using [`CartoonGAN`](https://github.com/Yijunmaverick/CartoonGAN-Test-Pytorch-Torch).
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<br />
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## Code Example
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Load an image from path './test.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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towhee.glob('./test.png') \
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.image_decode() \
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.img2img_translation.animegan(model_name = 'hayao') \
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.show()
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```
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<img src="./results1.png" height="150px"/>
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*Write a pipeline with explicit inputs/outputs name specifications:*
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```python
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import towhee
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towhee.glob['path']('./test.png') \
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.image_decode['path', 'origin']() \
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.img2img_translation.cartoongan['origin', 'hayao'](model_name = 'Hayao') \
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.img2img_translation.cartoongan['origin', 'hosoda'](model_name = 'Hosoda') \
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.img2img_translation.cartoongan['origin', 'paprika'](model_name = 'Paprika') \
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.img2img_translation.cartoongan['origin', 'shinkai'](model_name = 'Shinkai') \
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.select['origin', 'hayao', 'hosoda', 'paprika', 'shinkai']() \
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.show()
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```
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<img src="./results2.png" alt="results1" height="150px"/>
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<br />
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## Factory Constructor
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Create the operator via the following factory method
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***img2img_translation.cartoongan(model_name = 'which anime model to use')***
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Model options:
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- Hayao
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- Hosoda
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- Paprika
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- Shinkai
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<br />
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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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***device***: *str*
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Which device being used('cpu' or 'cuda'), defaults to 'cpu'.
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**Returns**: *towhee.types.Image (a sub-class of numpy.ndarray)*
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The new image.
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