Update app.py

app.py

@@ -460,8 +460,8 @@ def get_all_df_quality(selected_columns, dir=QUALITY_DIR):
     return df
 
 def get_all_df_i2v(selected_columns, dir=I2V_DIR):
-    # submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
-    # submission_repo.git_pull()
+    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_i2v(df, selected_columns)
     df = df.sort_values(by="Selected Score", ascending=False)
@@ -486,10 +486,12 @@ def convert_scores_to_percentage(df):
     for column in df.columns[skip_col:]:  # 假设第一列是'name'
         # if df[column].isdigit():
         # print(df[column])
-        is_numeric = pd.to_numeric(df[column], errors='coerce').notna().all()
-        if is_numeric:
+        # is_numeric = pd.to_numeric(df[column], errors='coerce').notna().all()
+        valid_numeric_count = pd.to_numeric(df[column], errors='coerce').notna().sum()
+        if valid_numeric_count > 0:
             df[column] = round(df[column] * 100,2)
-            df[column] = df[column].apply(lambda x:  f"{x:05.2f}") + '%'
+            df['column'] = df['column'].apply(lambda x: f"{x:05.2f}%" if pd.notna(x) else x)
+            # df[column] = df[column].apply(lambda x:  f"{x:05.2f}") + '%'
     return df
 
 def choose_all_quailty():