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Sophie98
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Parent(s):
de4d926
app
Browse files
app.py
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import numpy as np
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import gradio as gr
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from segmentation import get_mask,replace_sofa
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from styleTransfer import resize_sofa,resize_style,create_styledSofa
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from PIL import Image
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def style_sofa(input_img: np.ndarray, style_img: np.ndarray):
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"""
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Styles (all) the sofas in the image to the given style.
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This function uses a transformer to combine the image with the desired style according
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to a generated mask of the sofas in the image.
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Input:
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input_img = image containing a sofa
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style_img = image containing a style
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Return:
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new_sofa = image containing the styled sofa
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"""
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# preprocess input images to be (640,640) squares to fit requirements of the segmentation model
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resized_img = resize_sofa(input_img)
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resized_style = resize_style(style_img)
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# generate mask for image
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mask = get_mask(resized_img)
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styled_sofa = create_styledSofa(resized_img,resized_style)
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new_sofa = replace_sofa(resized_img,mask,styled_sofa)
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return new_sofa
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image = gr.inputs.Image()
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style = gr.inputs.Image()
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demo = gr.Interface(
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style_sofa,
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[image,style],
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'image',
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examples=[
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['sofa_example1.jpg','style_example1.jpg'],
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['sofa_example1.jpg','style_example2.jpg'],
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['sofa_example1.jpg','style_example3.jpg'],
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['sofa_example1.jpg','style_example4.jpg'],
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['sofa_example1.jpg','style_example5.jpg'],
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],
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title="Style your sofa",
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description="π Customize your sofa to your wildest dreams! π",
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)
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if __name__ == "__main__":
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demo.launch(share=True)
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#https://github.com/dhawan98/Post-Processing-of-Image-Segmentation-using-CRF
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