Create app.py

app.py

@@ -0,0 +1,24 @@
+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")