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from PIL import Image
import tensorflow
import gradio as gr
import numpy as np
from tensorflow.keras.models import load_model
import tensorflow as tf
model = load_model('model')
print(model)
def infer(img):
cartoonGAN = model.signatures["serving_default"]
img = np.array(img.convert("RGB"))
img = np.expand_dims(img, 0).astype(np.float32) / 127.5 - 1
out = cartoonGAN(tf.constant(img))['output_1']
out = ((out.numpy().squeeze() + 1) * 127.5).astype(np.uint8)
return out
title = "CartoonGAN"
description = "Gradio Demo for CartoonGAN. To use it, simply upload an image."
article = "<p style='text-align: center'><a href='http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_CartoonGAN_Generative_Adversarial_CVPR_2018_paper.pdf' target='_blank'>Paper</a></p> <p style='text-align: center'>samples from repo: <img src=''></p>"
examples=[['ny_street.jpg'],['husky_study.jpg'],['tube_london.jpg'],['monalisa.jpg'],['dog-sleepy.gif'],['japan_fuji.jpg']]
gr.Interface(infer, [gr.inputs.Image(type="pil")], gr.outputs.Image(type="pil"), "image",title=title,description=description,enable_queue=True,examples=examples).launch(share=True)
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