Update app.py

app.py

@@ -4,13 +4,9 @@ from tensorflow.keras.models import load_model
 import numpy as np
 from tensorflow.keras.preprocessing import image
 
-my_model = load_model('Brain_Tumor_Model.h5')
 
-# Set a threshold for binary classification
-threshold = 0.5
 
 def predict_input_image(img):
-    # Normalize the image by cropping (center crop)
     # Normalize the image by cropping (center crop)
     h, w = img.size
     crop_start_x = (w - 224) // 2
@@ -19,6 +15,11 @@ def predict_input_image(img):
     img = tf.image.resize(img, [224,224])
     img = np.expand_dims(img, axis = 0)
 
+    my_model = load_model('Brain_Tumor_Model.h5')
+
+    # Set a threshold for binary classification
+    threshold = 0.5
+    
     # Make predictions using your model
     predictions = my_model.predict(img)