app.py

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."

examples=[['ny_street.jpg'],['husky_study.jpg'],['tube_london.jpg'],['monalisa.jpg'],['dog-sleepy.gif'],['japan_fuji.jpg'],['victoria.jpg'],['venice.jpg'],['london_bridge.jpg'],['tuscany.jpg'],['egypt.jpg'],['taj.jpg'],['messi.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)