Update app.py

app.py

@@ -8,10 +8,11 @@ import cv2
 # Register KerasLayer from TensorFlow Hub
 tf.keras.utils.get_custom_objects().update({'KerasLayer': hub.KerasLayer})
 
-# Load the model and specify custom objects
+# Load the model using the Functional API
 try:
+    # Load the model with custom objects
     model = tf.keras.models.load_model('bird_model4.h5', custom_objects={'KerasLayer': hub.KerasLayer})
-except ValueError as e:
+except Exception as e:
     print("Error loading the model:", e)
     exit()
 
@@ -25,7 +26,7 @@ def predict_image(image):
     # Resize and normalize the image
     img = cv2.resize(image, (224, 224))
     img = img / 255.0
-    
+
     # Make predictions
     predictions = model.predict(img[np.newaxis, ...])[0]
     top_classes = np.argsort(predictions)[-3:][::-1]  # Indices of top 3 predictions