Cartoongan

author: Shiyu

Description

Convert an image into an cartoon image using CartoonGAN.

Code Example

Load an image from path './test.png'.

Write the pipeline in simplified style:

import towhee

towhee.glob('./test.png') \
      .image_decode() \
      .img2img_translation.animegan(model_name = 'hayao') \
      .show()

Write a pipeline with explicit inputs/outputs name specifications:

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()

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

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.