Update app.py

app.py

@@ -35,6 +35,22 @@ submission_names = list(SUBMISSIONS.keys())
 num_images = len(SUBMISSIONS[submission_names[0]])
 
 
+def load_submissions():
+    all_datasets = list_datasets(author=SUBMISSION_ORG)
+    relevant_ids = [d.id for d in all_datasets]
+    
+    submitted_ids = []
+    for _id in relevant_ids:
+        ds = load_dataset(_id)["train"]
+        submitted_ids += ds["id"]
+    
+    submitted_ids = Counter(submitted_ids)
+    return submitted_ids
+
+
+SUBMITTED_IDS = load_submissions()
+
+
 def generate_random_hash(length=8):
     """
     Generates a random hash of specified length.
@@ -53,18 +69,7 @@ def generate_random_hash(length=8):
     random_hash = secrets.token_hex(num_bytes)
     
     return random_hash
-
-def load_submissions():
-    all_datasets = list_datasets(author=SUBMISSION_ORG)
-    relevant_ids = [d.id for d in all_datasets]
-    
-    submitted_ids = []
-    for _id in relevant_ids:
-        ds = load_dataset(_id)["train"]
-        submitted_ids += ds["id"]
     
-    submitted_ids = Counter(submitted_ids)
-    return submitted_ids
 
 def refresh(row_number, dataframe):
     if row_number == NUM_QUESTIONS:
@@ -73,12 +78,9 @@ def refresh(row_number, dataframe):
     else:
         return dataframe
 
-def start(submitted_ids=None):
-    if submitted_ids is None:
-        submitted_ids = load_submissions()
-        
+def start():
     ids = {id: 0 for id in range(num_images)}
-    ids = {**ids, **submitted_ids}
+    ids = {**ids, **SUBMITTED_IDS}
 
     # sort by count
     ids = sorted(ids.items(), key=lambda x: x[1])