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from PIL import Image
import tensorflow
import gradio as gr
from tensorflow.keras.models import load_model
model = load_model('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 AnimeGanv2 Face Portrait. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please use a cropped portrait picture for best results similar to the examples below."
#description = "Gradio Demo for AnimeGanv2 Face Portrait. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please use a cropped portrait picture for best results similar to the examples below."
iface = gr.Interface(infer, gr.inputs.Image(type="pil"), "image",title=title,description=description)
iface.launch()
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