Update app.py

app.py

@@ -71,7 +71,6 @@ def get_normalized_df(df):
     for column in normalize_df.columns[1:]:
         min_val = NORMALIZE_DIC[column]['Min']
         max_val = NORMALIZE_DIC[column]['Max']
-        print(normalize_df[column], min_val, max_val)
         normalize_df[column] = (normalize_df[column] - min_val) / (max_val - min_val)
     return normalize_df
 
@@ -157,13 +156,22 @@ def get_baseline_df_quality():
     df = convert_scores_to_percentage(df)
     return df
 
-def get_all_df(selected_columns):
+def get_all_df(selected_columns, dir=CSV_DIR):
     submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
     submission_repo.git_pull()
-    df = pd.read_csv(CSV_DIR)
+    df = pd.read_csv(dir)
     df = get_final_score(df, selected_columns)
     df = df.sort_values(by="Selected Score", ascending=False)
     return df
+    
+def get_all_df_quality(selected_columns, dir=QUALITY_DIR):
+    submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
+    submission_repo.git_pull()
+    df = pd.read_csv(dir)
+    df = get_final_score_quality(df, selected_columns)
+    df = df.sort_values(by="Selected Score", ascending=False)
+    return df
+
 
 def convert_scores_to_percentage(df):
     # 对DataFrame中的每一列（除了'name'列）进行操作
@@ -185,7 +193,7 @@ def enable_all():
     return gr.update(value=TASK_INFO)
 
 def on_filter_model_size_method_change(selected_columns):
-    updated_data = get_all_df(selected_columns)
+    updated_data = get_all_df(selected_columns, CSV_DIR)
     #print(updated_data)
     # columns:
     selected_columns = [item for item in TASK_INFO if item in selected_columns]
@@ -207,7 +215,7 @@ def on_filter_model_size_method_change(selected_columns):
     return filter_component#.value
 
 def on_filter_model_size_method_change_quality(selected_columns):
-    updated_data = get_baseline_df_quality()
+    updated_data = get_all_df(selected_columns, QUALITY_DIR)
     #print(updated_data)
     # columns:
     selected_columns = [item for item in QUALITY_TAB if item in selected_columns]