Update app.py

app.py

@@ -11,6 +11,7 @@ model = load_model('crack_prediction-2.h5')
 poly = PolynomialFeatures(degree=5, include_bias=False)
 scaler = StandardScaler()
 
+# 
 def preprocess_input(flange_width, beam_width, geometric_factor):
     """
     Preprocess the input data: apply polynomial features and then scale.
@@ -19,11 +20,12 @@ def preprocess_input(flange_width, beam_width, geometric_factor):
     input_data = np.reshape( [flange_width, beam_width, geometric_factor], (1,-1))
     
     # # Apply Polynomial Features
-    X_train_poly = poly.fit_transform(input_data)
-    poly_features = poly.transform(X_train_poly)
-    
-    # Scale the features
-    X_train_poly_scaled = scaler.fit_transform(X_train_poly)
+    poly = PolynomialFeatures(degree=5, include_bias=False)
+    X_test_poly = poly.fit_transform(input_data)
+
+    # Standardize the polynomial features
+    scaler = StandardScaler()
+    X_train_poly_scaled = scaler.fit_transform(X_test_poly)
     scaled_features = scaler.transform(X_train_poly_scaled)
     
     return scaled_features