finish

app.py

@@ -49,6 +49,19 @@ def load_submissions():
 
     return main_dict, challenges, categories
 
+def sort_by_highest_percentage(df):
+    # Convert percentage values to numeric format
+    for column in df.columns.to_list():
+        df[column] = pd.to_numeric(df[column].str.rstrip('%'))
+
+        # Sort DataFrame by highest percentage first
+        df = df.sort_values(by=column, ascending=False)
+
+        # Convert back to percentage string format
+        df[column] = df[column].astype(str) + '%'
+
+    return df
+
 def get_dataframe_all():
     main, challenges, categories = load_submissions()
     main_frame = pd.DataFrame([main])
@@ -64,6 +77,11 @@ def get_dataframe_all():
     categories_frame = categories_frame.reset_index().rename(columns={'index': 'Category'})
     challenges_frame = challenges_frame.reset_index().rename(columns={'index': 'Challenge'})
 
+    main_frame = sort_by_highest_percentage(main_frame)
+
+    categories_frame = categories_frame.reindex(columns=main_frame.columns.to_list())
+    challenges_frame = challenges_frame.reindex(columns=main_frame.columns.to_list())
+
     return main_frame, challenges_frame, categories_frame
 
 TITLE = "# Open Parti Prompts Leaderboard"
@@ -76,15 +94,16 @@ EXPLANATION = """\n\n
 
 In the [Community Parti Prompts](https://huggingface.co/spaces/OpenGenAI/open-parti-prompts), community members select for every prompt
 of [Parti Prompts](https://huggingface.co/datasets/nateraw/parti-prompts) which open-source image generation model has generated the best image.
-The community's answers are then stored and used in this space to give a human evaluation of the different models.
+The community's answers are then stored and used in this space to give a human evaluation of the different models. \n\n
+
 Currently the leaderboard includes the following models:
 - [sd-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)
 - [sd-v2-1](https://huggingface.co/stabilityai/stable-diffusion-2-1)
 - [if-v1-0](https://huggingface.co/DeepFloyd/IF-I-XL-v1.0)
-- [karlo](https://huggingface.co/kakaobrain/karlo-v1-alpha)
+- [karlo](https://huggingface.co/kakaobrain/karlo-v1-alpha) \n\n
 
 In the following you can see three result tables. The first shows you the overall preferences across all prompts. The second and third tables
-show you a breakdown analysis per category and level of difficulty ("challenge") as defined by [Parti Prompts](https://huggingface.co/datasets/nateraw/parti-prompts).
+show you a breakdown analysis per category and per type of challenge as defined by [Parti Prompts](https://huggingface.co/datasets/nateraw/parti-prompts).
 """
 
 GALLERY_COLUMN_NUM = len(SUBMISSIONS)
@@ -101,7 +120,7 @@ with gr.Blocks() as demo:
     headers = list(SUBMISSIONS.keys())
     datatype = "str"
 
-    main_df, category_df, challenge_df = get_dataframe_all()
+    main_df, challenge_df, category_df = get_dataframe_all()
 
     with gr.Column():
         gr.Markdown("# Open Parti Prompts")