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import gradio as gr | |
''' | |
@paper: GAN Prior Embedded Network for Blind Face Restoration in the Wild (CVPR2021) | |
@author: yangxy ([email protected]) | |
''' | |
import os | |
import cv2 | |
def inference(file): | |
im = cv2.imread(file, cv2.IMREAD_COLOR) | |
cv2.imwrite(os.path.join("input.png"), im) | |
from rembg import remove | |
input_path = 'input.png' | |
output_path = 'output.png' | |
with open(input_path, 'rb') as i: | |
with open(output_path, 'wb') as o: | |
input = i.read() | |
output = remove(input) | |
o.write(output) | |
return os.path.join("output.png") | |
title = "RemBG" | |
description = "Gradio demo for RemBG. To use it, simply upload your image and wait. Read more at the link below." | |
article = "<p style='text-align: center;'><a href='https://github.com/danielgatis/rembg' target='_blank'>Github Repo</a></p>" | |
gr.Interface( | |
inference, | |
[gr.inputs.Image(type="filepath", label="Input")], | |
gr.outputs.Image(type="file", label="Output"), | |
title=title, | |
description=description, | |
article=article, | |
examples=[], | |
enable_queue=True | |
).launch() |