towhee
/
anime-transfer-gradio
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53 lines
2.0 KiB
53 lines
2.0 KiB
import gradio
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import numpy
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from PIL import Image
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from pathlib import Path
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from typing import NamedTuple
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from towhee.operator import Operator
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from towhee import pipeline
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path = str(Path.cwd() / 'test.jpg')
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class AnimeTransferGradio(Operator):
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"""
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AnimeTransferGradio operator
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"""
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def __init__(self) -> None:
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super().__init__()
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def __call__(self, source: str = 'upload') -> NamedTuple('Outputs', [('img_path', str)]):
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interface = gradio.Interface(self.trans_img, [gradio.inputs.Image(type="pil", source=source),
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gradio.inputs.Radio(["celeba", "facepaintv1","facepaintv2", "hayao", "paprika", 'shinkai'])],
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gradio.outputs.Image(type="pil"), allow_flagging='never', allow_screenshot=False)
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interface.launch(enable_queue=True)
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Outputs = NamedTuple('Outputs', [('img_path', str)])
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return Outputs(path)
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@staticmethod
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def trans_img(input, version):
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trans_pipeline = 'filip-halt/style-transfer-animegan'
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# Resizing the image while keeping aspect ratio.
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size = (512, 512)
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input.thumbnail(size, Image.ANTIALIAS)
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input.save(path)
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if version == 'celeba':
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x = pipeline(trans_pipeline, tag='celeba')(path)
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elif version == 'facepaintv1':
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x = pipeline(trans_pipeline, tag='facepaintv1')(path)
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elif version == 'facepaintv2':
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x = pipeline(trans_pipeline, tag='facepaintv2')(path)
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elif version == 'hayao':
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x = pipeline(trans_pipeline, tag='hayao')(path)
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elif version == 'paprika':
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x = pipeline(trans_pipeline, tag='paprika')(path)
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elif version == 'shinkai':
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x = pipeline(trans_pipeline, tag='shinkai')(path)
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# Converting from channel-first, [0,1] value RGB, numpy array to PIL image.
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x = numpy.transpose(x[0][0], (1, 2, 0))
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x = Image.fromarray((x * 255).astype(numpy.uint8))
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return x
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