Update app.py

app.py

@@ -78,8 +78,8 @@ def calculate_selected_score(df, selected_columns):
     # selected_score = df[selected_columns].sum(axis=1)
     selected_QUALITY = [i for i in selected_columns if i in QUALITY_LIST]
     selected_SEMANTIC = [i for i in selected_columns if i in SEMANTIC_LIST]
-    selected_quality_score = normalize_df[selected_QUALITY].sum(axis=1)/sum([DIM_WEIGHT[i] for i in selected_QUALITY])
-    selected_semantic_score = normalize_df[selected_SEMANTIC].sum(axis=1)/sum([DIM_WEIGHT[i] for i in selected_SEMANTIC ])
+    selected_quality_score = df[selected_QUALITY].sum(axis=1)/sum([DIM_WEIGHT[i] for i in selected_QUALITY])
+    selected_semantic_score = df[selected_SEMANTIC].sum(axis=1)/sum([DIM_WEIGHT[i] for i in selected_SEMANTIC ])
     selected_score =  (selected_quality_score * QUALITY_WEIGHT + selected_semantic_score * SEMANTIC_WEIGHT) / (QUALITY_WEIGHT + SEMANTIC_WEIGHT)
     return selected_score