Upload app.py

app.py

@@ -61,9 +61,28 @@ def load_model():
                 cache_dir=None  # Use default cache
             )
             print(f"Model downloaded to: {model_path}")
-            # Load the model using TensorFlow's Keras (not standalone Keras)
-            # This is needed because the model was saved with tf_keras
-            model = tf.keras.models.load_model(model_path, compile=False)
+            
+            # Define a dummy weighted_binary_crossentropy function for loading
+            # (not used during inference since compile=False)
+            def weighted_binary_crossentropy(y_true, y_pred):
+                # Dummy implementation - not used during inference
+                epsilon = tf.keras.backend.epsilon()
+                y_pred = tf.clip_by_value(y_pred, epsilon, 1.0 - epsilon)
+                bce = -(y_true * tf.math.log(y_pred) + (1.0 - y_true) * tf.math.log(1.0 - y_pred))
+                return tf.reduce_mean(bce)
+            
+            # Provide custom_objects to handle the custom loss function
+            custom_objects = {
+                'weighted_binary_crossentropy': weighted_binary_crossentropy
+            }
+            
+            # Load the model using TensorFlow's Keras with custom_objects
+            # This is needed because the model was saved with tf_keras and a custom loss
+            model = tf.keras.models.load_model(
+                model_path, 
+                compile=False,
+                custom_objects=custom_objects
+            )
             print("Model loaded successfully!")
         return model
     except Exception as e: