Update app.py

app.py

@@ -429,7 +429,7 @@ plt.xlabel('Epochs')
 plt.show()
 
 pre_trained = tf.keras.models.load_model("gradio_pix2pix.h5")
-
+pre_trained_2 = tf.keras.models.load_model("generatorLR-HR_300.h5")
 #pre_trained.summary()
 
 #pre_trained.optimizer
@@ -461,6 +461,16 @@ def result(Input,Choice):
       Input = cv2.resize(Input, (size1,size0), interpolation = cv2.INTER_AREA)
       return Input
     if Choice=="Enhancement":
+      size0 = Input.shape[0]
+      size1 = Input.shape[1]
+      Input = cv2.resize(Input, (256,256), interpolation = cv2.INTER_AREA)
+      Input = cv2.cvtColor(Input , cv2.COLOR_BGR2GRAY)
+      Input = np.array(Input).reshape(1,256,256,1)
+      prediction = pre_trained_2(Input,training=True)
+      Input = prediction[0]
+      Input = (Input+1)*127.5
+      Input = np.uint8(Input)
+      Input = cv2.resize(Input, (size1,size0), interpolation = cv2.INTER_AREA)
       return Input
 
 #lst = cv2.imread('/content/drive/MyDrive/ColabNotebooks/enhance/low-sat.jpg')