Update app.py

app.py

@@ -1,5 +1,7 @@
 import keras.backend as K
 import gradio as gr
+import numpy as np
+
 
 def psnr(y_true, y_pred):
     return -10*K.log(K.mean(K.flatten((y_true - y_pred))**2)) / np.log(10)
@@ -8,6 +10,9 @@ from keras.models import load_model
 model = load_model("./MyNet.h5", custom_objects={'psnr': psnr, 'val_psnr': psnr})
 
 image = gr.inputs.Image(shape=(256,256))
+image = np.asarray(image)
+image = image.astype('float32')
+image = image / 255.0
 decoded_imgs = model.predict(image)
 
 #decoded_imgs.reshape(256,256,3)