Update app.py

app.py

@@ -34,8 +34,8 @@ from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, QUEUE_REPO, REP
 # import copy
 
 def load_data(data_path):
-    columns = ['Unlearned_Methods','Pre-ASR', 'Post-ASR','FID', 'Clip-Score']
-    columns_sorted = [Unlearned_Methods','Pre-ASR', 'Post-ASR','FID', 'Clip-Score']
+    columns = ['Unlearned_Methods','Pre-ASR', 'Post-ASR','FID', 'CLIP-Score']
+    columns_sorted = [Unlearned_Methods','Pre-ASR', 'Post-ASR','FID', 'CLIP-Score']
     
     df = pd.read_csv(data_path).dropna()
     df['Post-ASR'] = df['Post-ASR'].round(0)
@@ -76,10 +76,10 @@ def restart_space():
 #     pending_eval_queue_df,
 # ) = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
 
-all_columns = ['Unlearned_Methods','Source', 'Diffusion_Models','Pre-ASR','Pre-ASR','Post-FID']
-show_columns = ['Unlearned_Methods','Source', 'Diffusion_Models','Pre-ASR','Pre-ASR','Post-FID']
-TYPES = ['str', 'markdown', 'str', 'number', 'number', 'number', 'number']
-files = ['vangogh', 'nudity','church','garbage','parachute','tench', 'vangogh']
+all_columns = ['Unlearned_Methods','Pre-ASR','Pre-ASR','FID','CLIP-Score']
+show_columns = ['Unlearned_Methods',,'Pre-ASR','Pre-ASR','FID','CLIP-Score']
+TYPES = ['str', 'number', 'number', 'number', 'number']
+files = ['nudity','vangogh', 'church','garbage','parachute','tench']
 csv_path='./assets/'+files[0]+'.csv'
 df_results = load_data(csv_path)
 methods = list(set(df_results['Unlearned_Methods']))