app.py

import streamlit as st
import tensorflow as tf
import numpy as np
from PIL import Image
import tensorflow as tf

def model_out(model_path,img):
  model = tf.keras.models.load_model(model_path)
  img = (img-127.5)/127.5
  img = np.expand_dims(img, 0)
  pred = model.predict(img)
  pred = np.asarray(pred)
  return pred[0]

st.title("Xray Image Enhancer 'Doesnt work well' Pix2Pix")
face_input = st.file_uploader("Image input")

if face_input is not None:
  img = Image.open(face_input)
  img = img.resize((256, 256))
  img = np.array(img)
  pred = model_out('XrayEnhancer.h5', img)
  st.image(img, caption="Uploaded Image")
  st.image(((pred + 1) * 127.5).astype(np.uint8), caption="Enhanced Images")