Update app.py

app.py

@@ -38,8 +38,10 @@ def predict_image(input_img_pil):
 
     # 1. Preprocessing: Resize and convert to NumPy array
     img_resized = input_img_pil.resize(IMAGE_SIZE)
+    print("image resized")
     img_array = keras.preprocessing.image.img_to_array(img_resized)
-    
+    print(" image converted to array")
+        
     # 2. Rescaling and Batch dimension:
     # Keras models usually expect input shapes like (Batch_Size, Height, Width, Channels)
     # and often expect pixel values to be normalized (e.g., 0-1 range).