update

README.md

@@ -4,9 +4,10 @@ emoji: 🌍
 colorFrom: red
 colorTo: gray
 sdk: gradio
-sdk_version: 3.29.0
+sdk_version: 3.41.0
 app_file: app.py
 pinned: false
+duplicated_from: OpenGenAI/open-parti-prompts
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -1,6 +1,7 @@
 from datasets import load_dataset
 from collections import Counter, defaultdict
 from random import sample, shuffle
+from collections import Counter
 import datasets
 from pandas import DataFrame
 from huggingface_hub import list_datasets
@@ -13,40 +14,41 @@ import secrets
 parti_prompt_results = []
 ORG = "diffusers-parti-prompts"
 SUBMISSIONS = {
-    "sd-v1-5": load_dataset(os.path.join(ORG, "sd-v1-5"))["train"],
-    "sd-v2-1": load_dataset(os.path.join(ORG, "sd-v2.1"))["train"],
-    "if-v1-0": load_dataset(os.path.join(ORG, "karlo-v1"))["train"],
-    "karlo": load_dataset(os.path.join(ORG, "if-v-1.0"))["train"],
-    # "Kadinsky":
+    "kand2": load_dataset(os.path.join(ORG, "kandinsky-2-2"))["train"],
+    "sdxl": load_dataset(os.path.join(ORG, "sdxl-1.0-refiner"))["train"],
+    "wuerst": load_dataset(os.path.join(ORG, "wuerstchen"))["train"],
+    "karlo": load_dataset(os.path.join(ORG, "karlo-v1"))["train"],
 }
 
 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",
 }
-SD_1_5_RESULT = """
-"## The traditional one 🔥! 
-![img](https://huggingface.co/datasets/OpenGenAI/logos/resolve/main/37351293.png)
-\n You mostly resonate with **Stable Diffusion 1-5** released by RunwayML.
-\n Stable Diffusion 1-5 is the most used open-source text-to-image model offering an amazing speed-to-image-quality trade-off!
-\n Check out your soulmate [here](https://huggingface.co/runwayml/stable-diffusion-v1-5).
+KANDINSKY = """
+"## The creative one 🎨! 
+![img](https://aeiljuispo.cloudimg.io/v7/https://cdn-uploads.huggingface.co/production/uploads/5dfcb1aada6d0311fd3d5448/rETvCyoUD5Mr9wm6OxUhe.png?w=200&h=200&f=face)
+\n You mostly resonate with **Kandinsky 2.2** released by AI Forever.
+\n Kandinsky 2.2 has a similar architecture to DALLE-2 and works extremely well for artistic, colorful generations.
+\n Check out your soulmate [here](https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder).
 """
-SD_2_1_RESULT = """
-## The creative one 🎨! 
+SDXL_RESULT = """
+## The powerful one ⚡! 
 ![img](https://huggingface.co/datasets/OpenGenAI/logos/resolve/main/7vmYr2XwVcPtkLzac_jxQ.png)
-\n You mostly resonate with **Stable Diffusion 2-1** released by Stability AI.
-\n Stable Diffusion 2-1 is the latest open-source release of Stable Diffusion and allows to render stunning images of much larger sizes than Stable Diffusion v1.
-Try it out [here](https://huggingface.co/stabilityai/stable-diffusion-2-1).
+\n You mostly resonate with **Stable Diffusion XL** released by Stability AI.
+\n Stable Diffusion XL consists of a two diffusion models that are chained together, a base model and a refiner model. Together, the system contains roughly 5 billion parameters.
+\n It's the latest open-source release of Stable Diffusion and allows to render stunning images of much larger sizes than Stable Diffusion v1.
+Try it out [here](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0).
 """
-IF_V1_0 = """
-## The powerful one ⚡! 
-![img](https://huggingface.co/datasets/OpenGenAI/logos/resolve/main/1662453741854-63170739dc97a974718be2c7.png)
-\n You mostly resonate with **IF v1-0** released by DeepFloyd.
-\n IF v1-0 is by far the largest of the open-sourced text-to-image models and is a very powerful image generator.
-\n Besides being able to generate multiple complex concepts in the same image, IF v1-0 is also extremely good at generating text in images.
-\n Check out your new best friend [here](https://huggingface.co/DeepFloyd/IF-I-XL-v1.0).
+WUERSTCHEN = """
+## The innovative one ⚗️ !
+![img](https://www.gravatar.com/avatar/3219846609129e84790fb83793998d61?d=retro&size=100)
+\n You mostly resonate with **Wuerstchen** released by the WARP team.
+\n Wuerstchen is a three stage diffusion model that proposed a very novel, innovative model architecture.
+\n Wuerstchen is able to generate very large images (up to 1024x2048) in just a few seconds.
+\n The model has an amazing image quality vs. speed trade-off.
+\n Check out your new best friend [here](https://huggingface.co/warp-ai/wuerstchen).
 """
 KARLO = """
 ## The precise one 🎯!
@@ -57,15 +59,15 @@ KARLO = """
 """
 
 RESULT = {
-    "sd-v1-5": SD_1_5_RESULT,
-    "sd-v2-1": SD_2_1_RESULT,
-    "if-v1-0": IF_V1_0,
+    "kand2": KANDINSKY,
+    "wuerst": WUERSTCHEN,
+    "sdxl": SDXL_RESULT,
     "karlo": KARLO,
 }
 NUM_QUESTIONS = 10
 MODEL_KEYS = "-".join(SUBMISSIONS.keys())
 SUBMISSION_ORG = f"results-{MODEL_KEYS}"
-PROMPT_FORMAT = " Pick the picture that best matches the prompt:"
+PROMPT_FORMAT = " Select all pictures that correctly match the prompt and click on 'Submit'. Remember that if no image matches the prompt, no image shall be selected."
 
 submission_names = list(SUBMISSIONS.keys())
 num_images = len(SUBMISSIONS[submission_names[0]])
@@ -161,31 +163,40 @@ def start():
 
 def process(dataframe, row_number=0):
     if row_number == NUM_QUESTIONS:
-        return None, None, None, None, "", ""
+        nones = len(RESULT) * [None]
+        falses = len(RESULT) * [False]
+        return *nones, *falses, "", ""
 
     image_id = dataframe.iloc[row_number]["id"]
     choices = [
         submission_names[dataframe.iloc[row_number][f"choice_{i}"]]
         for i in range(len(SUBMISSIONS))
     ]
-    images = (SUBMISSIONS[c][int(image_id)]["images"] for c in choices)
+    images = [SUBMISSIONS[c][int(image_id)]["images"] for c in choices]
 
     prompt = SUBMISSIONS[choices[0]][int(image_id)]["Prompt"]
     prompt = f'# "{prompt}"'
     counter = f"***{row_number + 1}/{NUM_QUESTIONS} {PROMPT_FORMAT}***"
+    image_buttons = len(images) * [False]
 
-    return *images, prompt, counter
+    return *images, *image_buttons, prompt, counter
 
 
 def write_result(user_choice, row_number, dataframe):
     if row_number == NUM_QUESTIONS:
         return row_number, dataframe
 
-    user_choice = int(user_choice)
-    chosen_model = submission_names[dataframe.iloc[row_number][f"choice_{user_choice}"]]
+    user_choices = []
+    for i, b in enumerate(str(user_choice)):
+        if bool(int(b)):
+            user_choices.append(i)
+
+    chosen_models = []
+    for user_choice in user_choices:
+        chosen_models.append(submission_names[dataframe.iloc[row_number][f"choice_{user_choice}"]])
 
-    dataframe.loc[row_number, "result"] = chosen_model
-    print(row_number)
+    print(chosen_models)
+    dataframe.loc[row_number, "result"] = ",".join(chosen_models)
     return row_number + 1, dataframe
 
 
@@ -196,7 +207,10 @@ def get_index(evt: gr.SelectData) -> int:
 def change_view(row_number, dataframe):
     if row_number == NUM_QUESTIONS:
 
-        favorite_model = dataframe["result"].value_counts().idxmax()
+        results = sum([x.split(",") for x in dataframe["result"].values], [])
+        results = [r for r in results if len(r) > 0]
+        favorite_model = Counter(results).most_common(1)[0][0]
+
         dataset = datasets.Dataset.from_pandas(dataframe)
         dataset = dataset.remove_columns(set(dataset.column_names) - set(["id", "result"]))
         hash = generate_random_hash()
@@ -225,7 +239,7 @@ TITLE = "# What AI model is best for you? 👩‍⚕️"
 DESCRIPTION = """
 ***How it works*** 📖 \n\n
 - Upon clicking start, you are shown image descriptions alongside four AI generated images.
-\n- Select the image that best fits the image description.
+\n- Select all images that match the prompt. **Note** that you should leave all images *unchecked* if no image matches the prompt.
 \n- Answer **10** questions to find out what AI generator most resonates with you. 
 \n- Your submissions contribute to [**Open Parti Prompts Leaderboard**](https://huggingface.co/spaces/OpenGenAI/parti-prompts-leaderboard) ❤️.
 \n\n
@@ -236,11 +250,11 @@ The prompts you are shown originate from the [Parti Prompts](https://huggingface
 Parti Prompts is designed to test text-to-image AI models on 1600+ prompts of varying difficulty and categories.
 The images you are shown have been pre-generated with 4 state-of-the-art open-sourced text-to-image models.
 You answers will be used to contribute to the official [**Open Parti Prompts Leaderboard**](https://huggingface.co/spaces/OpenGenAI/parti-prompts-leaderboard).
-Every month, the generated images will be updated with possibly improved models. The current models and code that was used to generate the images can be verified here:\n
-- [sd-v1-5](https://huggingface.co/datasets/diffusers-parti-prompts/sd-v1-5) \n
-- [sd-v2.1](https://huggingface.co/datasets/diffusers-parti-prompts/sd-v2.1) \n
-- [if-v-1.0](https://huggingface.co/datasets/diffusers-parti-prompts/if-v-1.0) \n
-- [karlo-v1](https://huggingface.co/datasets/diffusers-parti-prompts/karlo-v1) \n
+Every couple months, the generated images will be updated with possibly improved models. The current models and code that was used to generate the images can be verified here:\n
+- [kandinsky-2-2](https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder) \n
+- [wuerstchen](https://huggingface.co/warp-ai/wuerstchen) \n
+- [sdxl-1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) \n
+- [karlo](https://huggingface.co/datasets/diffusers-parti-prompts/karlo-v1) \n
 """
 
 GALLERY_COLUMN_NUM = len(SUBMISSIONS)
@@ -293,16 +307,18 @@ with gr.Blocks() as demo:
             with gr.Row():
                 with gr.Column() as c1:
                     image_1 = gr.Image(interactive=False)
-                    image_1_button = gr.Button("Select 1").style(full_width=True)
+                    image_1_button = gr.Checkbox(False, label="Image 1").style(full_width=True)
                 with gr.Column() as c2:
                     image_2 = gr.Image(interactive=False)
-                    image_2_button = gr.Button("Select 2").style(full_width=True)
+                    image_2_button = gr.Checkbox(False, label="Image 2").style(full_width=True)
                 with gr.Column() as c3:
                     image_3 = gr.Image(interactive=False)
-                    image_3_button = gr.Button("Select 3").style(full_width=True)
+                    image_3_button = gr.Checkbox(False, label="Image 3").style(full_width=True)
                 with gr.Column() as c4:
                     image_4 = gr.Image(interactive=False)
-                    image_4_button = gr.Button("Select 4").style(full_width=True)         
+                    image_4_button = gr.Checkbox(False, label="Image 4").style(full_width=True)         
+            with gr.Row():
+                submit_button = gr.Button("Submit").style(full_width=True)         
 
     start_button.click(
         fn=start,
@@ -316,92 +332,20 @@ with gr.Blocks() as demo:
     ).then(
         fn=change_view,
         inputs=[row_number, dataframe],
-        outputs=[intro_view, result_view, gallery_view, start_view, result]
+        outputs=[intro_view, result_view, gallery_view, start_view, result],
     ).then(
-        fn=process, inputs=[dataframe], outputs=[image_1, image_2, image_3, image_4, prompt, counter]
+        fn=process, 
+        inputs=[dataframe],
+        outputs=[image_1, image_2, image_3, image_4, image_1_button, image_2_button, image_3_button, image_4_button, prompt, counter]
     )
 
-    image_1_button.click(
-        fn=lambda: 0,
-        inputs=[],
-        outputs=[selected_image],
-    ).then(
-        fn=write_result,
-        inputs=[selected_image, row_number, dataframe],
-        outputs=[row_number, dataframe],
-    ).then(
-        fn=change_view,
-        inputs=[row_number, dataframe],
-        outputs=[intro_view, result_view, gallery_view, start_view, result]
-    ).then(
-        fn=process,
-        inputs=[dataframe, row_number],
-        outputs=[image_1, image_2, image_3, image_4, prompt, counter]
-    ).then(
-        fn=lambda x: 0 if x == NUM_QUESTIONS else x,
-        inputs=[row_number],
-        outputs=[row_number],
-    ).then(
-        fn=refresh,
-        inputs=[row_number, dataframe],
-        outputs=[dataframe],
-    )
+    def integerize(x1, x2, x3, x4):
+        number = f"{int(x1)}{int(x2)}{int(x3)}{int(x4)}"
+        return int(number)
 
-    image_2_button.click(
-        fn=lambda: 1,
-        inputs=[],
-        outputs=[selected_image],
-    ).then(
-        fn=write_result,
-        inputs=[selected_image, row_number, dataframe],
-        outputs=[row_number, dataframe],
-    ).then(
-        fn=change_view,
-        inputs=[row_number, dataframe],
-        outputs=[intro_view, result_view, gallery_view, start_view, result]
-    ).then(
-        fn=process,
-        inputs=[dataframe, row_number],
-        outputs=[image_1, image_2, image_3, image_4, prompt, counter]
-    ).then(
-        fn=lambda x: 0 if x == NUM_QUESTIONS else x,
-        inputs=[row_number],
-        outputs=[row_number],
-    ).then(
-        fn=refresh,
-        inputs=[row_number, dataframe],
-        outputs=[dataframe],
-    )
-
-    image_3_button.click(
-        fn=lambda: 2,
-        inputs=[],
-        outputs=[selected_image],
-    ).then(
-        fn=write_result,
-        inputs=[selected_image, row_number, dataframe],
-        outputs=[row_number, dataframe],
-    ).then(
-        fn=change_view,
-        inputs=[row_number, dataframe],
-        outputs=[intro_view, result_view, gallery_view, start_view, result]
-    ).then(
-        fn=process,
-        inputs=[dataframe, row_number],
-        outputs=[image_1, image_2, image_3, image_4, prompt, counter]
-    ).then(
-        fn=lambda x: 0 if x == NUM_QUESTIONS else x,
-        inputs=[row_number],
-        outputs=[row_number],
-    ).then(
-        fn=refresh,
-        inputs=[row_number, dataframe],
-        outputs=[dataframe],
-    )
-
-    image_4_button.click(
-        fn=lambda: 3,
-        inputs=[],
+    submit_button.click(
+        fn=integerize,
+        inputs=[image_1_button, image_2_button, image_3_button, image_4_button],
         outputs=[selected_image],
     ).then(
         fn=write_result,
@@ -414,7 +358,7 @@ with gr.Blocks() as demo:
     ).then(
         fn=process,
         inputs=[dataframe, row_number],
-        outputs=[image_1, image_2, image_3, image_4, prompt, counter]
+        outputs=[image_1, image_2, image_3, image_4, image_1_button, image_2_button, image_3_button, image_4_button, prompt, counter],
     ).then(
         fn=lambda x: 0 if x == NUM_QUESTIONS else x,
         inputs=[row_number],