make style

README.md

@@ -4,7 +4,7 @@ emoji: 📊
 colorFrom: blue
 colorTo: purple
 sdk: gradio
-sdk_version: 3.29.0
+sdk_version: 3.41.0
 app_file: app.py
 pinned: false
 license: apache-2.0

app.py

@@ -1,22 +1,30 @@
-from datasets import load_dataset
-from collections import Counter, defaultdict
-import pandas as pd
-from huggingface_hub import list_datasets
 import os
+
 import gradio as gr
+import pandas as pd
+
+from apscheduler.schedulers.background import BackgroundScheduler
+from collections import Counter, defaultdict
+from datasets import load_dataset
+import datasets
+from huggingface_hub import HfApi, list_datasets
+
+api = HfApi(token=os.environ.get("HF_TOKEN", None))
+def restart_space():
+  api.restart_space(repo_id="OpenGenAI/parti-prompts-leaderboard")
 
 parti_prompt_results = []
 ORG = "diffusers-parti-prompts"
 SUBMISSIONS = {
-    "sd-v1-5": None,
-    "sd-v2-1": None,
-    "if-v1-0": None,
+    "kand2": None,
+    "sdxl": None,
+    "wuerst": None,
     "karlo": None,
 }
 LINKS = {
-    "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",
+    "kand2": "https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder",
+    "sdxl": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0",
+    "wuerst": "https://huggingface.co/warp-ai/wuerstchen",
     "karlo": "https://huggingface.co/kakaobrain/karlo-v1-alpha",
 }
 MODEL_KEYS = "-".join(SUBMISSIONS.keys())
@@ -40,9 +48,26 @@ def load_submissions():
     total_submissions = 0
 
     for _id in relevant_ids:
-        ds = load_dataset(_id)["train"]
+        try:
+            ds = load_dataset(_id)["train"]
+        except:
+            # skip dataset
+            continue
+
+        all_results = []
+        all_ids = []
         for result, image_id in zip(ds["result"], ds["id"]):
-            if result not in submission_names:
+            all_result = result.split(",")
+
+            all_results += all_result
+            all_ids += (len(all_result) * [image_id])
+            
+        for result, image_id in zip(all_results, all_ids):
+            if result == "":
+                print(f"{result} was not solved by any model.")
+
+            elif result not in submission_names:
+                import ipdb; ipdb.set_trace()
                 # Make sure that incorrect model names are not added
                 continue
 
@@ -84,6 +109,10 @@ 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 = main_frame.rename(columns={"": "NOT SOLVED"})
+    categories_frame = categories_frame.rename(columns={"": "NOT SOLVED"})
+    challenges_frame = challenges_frame.rename(columns={"": "NOT SOLVED"})
+
     return total_submissions, main_frame, challenges_frame, categories_frame
 
 TITLE = "# Open Parti Prompts Leaderboard"
@@ -110,10 +139,10 @@ For more information of how the images were created, please refer to [Open Parti
 The community's answers are then stored and used in this space to give a human-preference-based comparison 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) \n\n
+- [kand2](https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder),
+- [sdxl](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0),
+- [wuerst](https://huggingface.co/warp-ai/wuerstchen),
+- [karlo](https://huggingface.co/kakaobrain/karlo-v1-alpha),
 
 In the following you can see three result tables. The first shows the overall comparison of the 4 models. The score states, 
 **the percentage at which images generated from the corresponding model are preferred over the image from all other models**. The second and third tables
@@ -175,6 +204,11 @@ with gr.Blocks() as demo:
 
     with gr.Row():
         refresh_button = gr.Button("Refresh")
-        refresh_button.click(refresh, inputs=[], outputs=[num_submissions, main_dataframe, cat_dataframe, chal_dataframe])
+        refresh_button.click(refresh, inputs=[], outputs=[num_submissions, main_dataframe, cat_dataframe, chal_dataframe])   
+
+# Restart space every 20 minutes
+scheduler = BackgroundScheduler()
+scheduler.add_job(restart_space, 'interval', seconds=3600)
+scheduler.start()
 
 demo.launch()