patrickvonplaten commited on
Commit
9eb3a05
1 Parent(s): 2d3a398

make style

Browse files
Files changed (2) hide show
  1. README.md +1 -1
  2. app.py +51 -17
README.md CHANGED
@@ -4,7 +4,7 @@ emoji: 📊
4
  colorFrom: blue
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  colorTo: purple
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  sdk: gradio
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- sdk_version: 3.29.0
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  app_file: app.py
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  pinned: false
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  license: apache-2.0
 
4
  colorFrom: blue
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  colorTo: purple
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  sdk: gradio
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+ sdk_version: 3.41.0
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  app_file: app.py
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  pinned: false
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  license: apache-2.0
app.py CHANGED
@@ -1,22 +1,30 @@
1
- from datasets import load_dataset
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- from collections import Counter, defaultdict
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- import pandas as pd
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- from huggingface_hub import list_datasets
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  import os
 
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  import gradio as gr
 
 
 
 
 
 
 
 
 
 
 
7
 
8
  parti_prompt_results = []
9
  ORG = "diffusers-parti-prompts"
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  SUBMISSIONS = {
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- "sd-v1-5": None,
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- "sd-v2-1": None,
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- "if-v1-0": None,
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  "karlo": None,
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  }
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  LINKS = {
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- "sd-v1-5": "https://huggingface.co/runwayml/stable-diffusion-v1-5",
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- "sd-v2-1": "https://huggingface.co/stabilityai/stable-diffusion-2-1",
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- "if-v1-0": "https://huggingface.co/DeepFloyd/IF-I-XL-v1.0",
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  "karlo": "https://huggingface.co/kakaobrain/karlo-v1-alpha",
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  }
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  MODEL_KEYS = "-".join(SUBMISSIONS.keys())
@@ -40,9 +48,26 @@ def load_submissions():
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  total_submissions = 0
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  for _id in relevant_ids:
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- ds = load_dataset(_id)["train"]
 
 
 
 
 
 
 
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  for result, image_id in zip(ds["result"], ds["id"]):
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- if result not in submission_names:
 
 
 
 
 
 
 
 
 
 
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  # Make sure that incorrect model names are not added
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  continue
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@@ -84,6 +109,10 @@ def get_dataframe_all():
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  categories_frame = categories_frame.reset_index().rename(columns={'index': 'Category'})
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  challenges_frame = challenges_frame.reset_index().rename(columns={'index': 'Challenge'})
86
 
 
 
 
 
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  return total_submissions, main_frame, challenges_frame, categories_frame
88
 
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  TITLE = "# Open Parti Prompts Leaderboard"
@@ -110,10 +139,10 @@ For more information of how the images were created, please refer to [Open Parti
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  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
111
 
112
  Currently the leaderboard includes the following models:
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- - [sd-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)
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- - [sd-v2-1](https://huggingface.co/stabilityai/stable-diffusion-2-1)
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- - [if-v1-0](https://huggingface.co/DeepFloyd/IF-I-XL-v1.0)
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- - [karlo](https://huggingface.co/kakaobrain/karlo-v1-alpha) \n\n
117
 
118
  In the following you can see three result tables. The first shows the overall comparison of the 4 models. The score states,
119
  **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:
175
 
176
  with gr.Row():
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  refresh_button = gr.Button("Refresh")
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- refresh_button.click(refresh, inputs=[], outputs=[num_submissions, main_dataframe, cat_dataframe, chal_dataframe])
 
 
 
 
 
179
 
180
  demo.launch()
 
 
 
 
 
1
  import os
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+
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  import gradio as gr
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+ import pandas as pd
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+
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+ from apscheduler.schedulers.background import BackgroundScheduler
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+ from collections import Counter, defaultdict
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+ from datasets import load_dataset
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+ import datasets
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+ from huggingface_hub import HfApi, list_datasets
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+
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+ api = HfApi(token=os.environ.get("HF_TOKEN", None))
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+ def restart_space():
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+ api.restart_space(repo_id="OpenGenAI/parti-prompts-leaderboard")
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16
  parti_prompt_results = []
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  ORG = "diffusers-parti-prompts"
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  SUBMISSIONS = {
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+ "kand2": None,
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+ "sdxl": None,
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+ "wuerst": None,
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  "karlo": None,
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  }
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  LINKS = {
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+ "kand2": "https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder",
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+ "sdxl": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0",
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+ "wuerst": "https://huggingface.co/warp-ai/wuerstchen",
28
  "karlo": "https://huggingface.co/kakaobrain/karlo-v1-alpha",
29
  }
30
  MODEL_KEYS = "-".join(SUBMISSIONS.keys())
 
48
  total_submissions = 0
49
 
50
  for _id in relevant_ids:
51
+ try:
52
+ ds = load_dataset(_id)["train"]
53
+ except:
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+ # skip dataset
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+ continue
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+
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+ all_results = []
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+ all_ids = []
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  for result, image_id in zip(ds["result"], ds["id"]):
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+ all_result = result.split(",")
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+
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+ all_results += all_result
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+ all_ids += (len(all_result) * [image_id])
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+
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+ for result, image_id in zip(all_results, all_ids):
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+ if result == "":
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+ print(f"{result} was not solved by any model.")
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+
69
+ elif result not in submission_names:
70
+ import ipdb; ipdb.set_trace()
71
  # Make sure that incorrect model names are not added
72
  continue
73
 
 
109
  categories_frame = categories_frame.reset_index().rename(columns={'index': 'Category'})
110
  challenges_frame = challenges_frame.reset_index().rename(columns={'index': 'Challenge'})
111
 
112
+ main_frame = main_frame.rename(columns={"": "NOT SOLVED"})
113
+ categories_frame = categories_frame.rename(columns={"": "NOT SOLVED"})
114
+ challenges_frame = challenges_frame.rename(columns={"": "NOT SOLVED"})
115
+
116
  return total_submissions, main_frame, challenges_frame, categories_frame
117
 
118
  TITLE = "# Open Parti Prompts Leaderboard"
 
139
  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
140
 
141
  Currently the leaderboard includes the following models:
142
+ - [kand2](https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder),
143
+ - [sdxl](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0),
144
+ - [wuerst](https://huggingface.co/warp-ai/wuerstchen),
145
+ - [karlo](https://huggingface.co/kakaobrain/karlo-v1-alpha),
146
 
147
  In the following you can see three result tables. The first shows the overall comparison of the 4 models. The score states,
148
  **the percentage at which images generated from the corresponding model are preferred over the image from all other models**. The second and third tables
 
204
 
205
  with gr.Row():
206
  refresh_button = gr.Button("Refresh")
207
+ refresh_button.click(refresh, inputs=[], outputs=[num_submissions, main_dataframe, cat_dataframe, chal_dataframe])
208
+
209
+ # Restart space every 20 minutes
210
+ scheduler = BackgroundScheduler()
211
+ scheduler.add_job(restart_space, 'interval', seconds=3600)
212
+ scheduler.start()
213
 
214
  demo.launch()