Update API

app.py

@@ -7,7 +7,11 @@ from pathlib import Path
 from serve.constants import SERVER_PORT, ROOT_PATH, ELO_RESULTS_DIR
 
 def build_combine_demo(models, elo_results_file, leaderboard_table_file):
-
+        # gr.themes.Default(),
+        # gr.themes.Soft(),
+        # gr.Theme.from_hub('gary109/HaleyCH_Theme'),
+        # gr.Theme.from_hub('EveryPizza/Cartoony-Gradio-Theme')
+        # gr.themes.Default(primary_hue="red", secondary_hue="pink")
     with gr.Blocks(
         title="Play with Open Vision Models",
         theme=gr.themes.Default(),

model/matchmaker.py

@@ -61,7 +61,8 @@ def matchmaker(num_players, k_group=4):
     ratings, comparison_counts, total_comparisons = load_json_via_sftp()
 
     # Randomly select a player
-    selected_player = np.random.randint(0, num_players)
+    # selected_player = np.random.randint(0, num_players)
+    selected_player = np.argmin(comparison_counts.sum(axis=1))
 
     selected_trueskill_score = trueskill_env.expose(ratings[selected_player])
     trueskill_scores = np.array([trueskill_env.expose(p) for p in ratings])
@@ -75,9 +76,6 @@ def matchmaker(num_players, k_group=4):
 
     # Group players
     model_ids = [selected_player] + opponents
-
-    from serve.update_skill import Model_ID
-    Model_ID.group = model_ids
         
     return model_ids
 

model/model_manager.py

@@ -7,6 +7,7 @@ import spaces
 from PIL import Image
 from .models import IMAGE_GENERATION_MODELS, IMAGE_EDITION_MODELS, load_pipeline
 from .fetch_museum_results import draw_from_imagen_museum, draw2_from_imagen_museum
+from serve.upload import get_random_mscoco_prompt
 
 class ModelManager:
     def __init__(self):
@@ -25,7 +26,7 @@ class ModelManager:
     @spaces.GPU(duration=120)
     def generate_image_ig(self, prompt, model_name):
         pipe = self.load_model_pipe(model_name)
-        result = pipe(prompt=prompt)
+        result = pipe(prompt=prompt).images[0]
         return result
 
     def generate_image_ig_api(self, prompt, model_name):
@@ -47,18 +48,23 @@ class ModelManager:
             # model_names = random.sample([model for model in self.model_ig_list], 4)
             from .matchmaker import matchmaker
             model_ids = matchmaker(num_players=len(self.model_ig_list))
+            print(model_ids)
             model_names = [self.model_ig_list[i] for i in model_ids]
+            print(model_names)
         else:
             model_names = [model_A, model_B, model_C, model_D]
 
+        with concurrent.futures.ThreadPoolExecutor() as executor:
+            futures = [executor.submit(self.generate_image_ig, prompt, model) if model.startswith("huggingface")
+                       else executor.submit(self.generate_image_ig_api, prompt, model) for model in model_names]
+            results = [future.result() for future in futures]
+
         # with concurrent.futures.ThreadPoolExecutor() as executor:
-        #     futures = [executor.submit(self.generate_image_ig, prompt, model) if model.startswith("imagenhub")
-        #                else executor.submit(self.generate_image_ig_api, prompt, model) for model in model_names]
+        #     futures = [executor.submit(self.generate_image_ig_api, prompt, model) for model in model_names]
         #     results = [future.result() for future in futures]
 
+        # results = [self.generate_image_ig(prompt, model) for model in model_names]
 
-        results = [self.generate_image_ig(prompt, model) for model in model_names]
-        # results = [future.result() for future in futures]
         return results[0], results[1], results[2], results[3], \
             model_names[0], model_names[1], model_names[2], model_names[3]
 
@@ -67,23 +73,38 @@ class ModelManager:
             # model_names = random.sample([model for model in self.model_ig_list], 4)
             from .matchmaker import matchmaker
             model_ids = matchmaker(num_players=len(self.model_ig_list))
+            print(model_ids)
             model_names = [self.model_ig_list[i] for i in model_ids]
+            print(model_names)
         else:
             model_names = [model_A, model_B, model_C, model_D]
 
+        prompt = get_random_mscoco_prompt()
+        print(prompt)
+        # with concurrent.futures.ThreadPoolExecutor() as executor:
+        #     model_1 = model_names[0].split('_')[1]
+        #     model_2 = model_names[1].split('_')[1]
+        #     model_3 = model_names[2].split('_')[1]
+        #     model_4 = model_names[3].split('_')[1]
+
+        #     result_list = draw2_from_imagen_museum("t2i", model_1, model_2, model_3, model_4)
+        #     image_links = result_list[0]
+        #     prompt_list = result_list[1]
+        #     print(prompt_list[0])
+
         with concurrent.futures.ThreadPoolExecutor() as executor:
-            model_1 = model_names[0].split('_')[1]
-            model_2 = model_names[1].split('_')[1]
-            model_3 = model_names[2].split('_')[1]
-            model_4 = model_names[3].split('_')[1]
+            futures = [executor.submit(self.generate_image_ig, prompt, model) if model.startswith("huggingface")
+                       else executor.submit(self.generate_image_ig_api, prompt, model) for model in model_names]
+            results = [future.result() for future in futures]
+        # with concurrent.futures.ThreadPoolExecutor() as executor:
+        #     futures = [executor.submit(self.generate_image_ig_api, prompt, model) for model in model_names]
+        #     results = [future.result() for future in futures]
 
-            result_list = draw2_from_imagen_museum("t2i", model_1, model_2, model_3, model_4)
-            image_links = result_list[0]
-            prompt_list = result_list[1]
-            print(prompt_list[0])
+        # results = [self.generate_image_ig_api(prompt, model) for model in model_names]
+        # results = [future.result() for future in futures]
+        return results[0], results[1], results[2], results[3], \
+            model_names[0], model_names[1], model_names[2], model_names[3], prompt
 
-        return image_links[0], image_links[1], image_links[2], image_links[3], \
-            model_names[0], model_names[1], model_names[2], model_names[3], prompt_list[0]
     
     def generate_image_ig_parallel(self, prompt, model_A, model_B):
         model_names = [model_A, model_B]

model/models/__init__.py

@@ -2,35 +2,51 @@ from .imagenhub_models import load_imagenhub_model
 # from .playground_api import load_playground_model
 from .fal_api_models import load_fal_model
 # from .videogenhub_models import load_videogenhub_model
-# from .huggingface_models import load_huggingface_model
+from .huggingface_models import load_huggingface_model
+from .replicate_api_models import load_replicate_model
+from .openai_api_models import load_openai_model
 
 # IMAGE_GENERATION_MODELS = ['huggingface_SD-v1.5_text2image',
 #                            'huggingface_SD-v2.1_text2image',
 #                            'huggingface_SD-XL-v1.0_text2image',
 #                            'huggingface_IF-I-XL-v1.0_text2image',
 #                             ]
-IMAGE_GENERATION_MODELS = [ 'imagenhub_SD_generation',
-                            'imagenhub_SDXL_generation',
-                            'imagenhub_OpenJourney_generation',
-                            'imagenhub_LCM_generation', 
-                            'imagenhub_DeepFloydIF_generation', 
-                            'imagenhub_PixArtAlpha_generation', 
-                            'imagenhub_Kandinsky_generation', 
-                            ]
+
 # IMAGE_GENERATION_MODELS = [ 'imagenhub_SD_generation',
-#                             'imagenhub_SD_generation',
-#                             'imagenhub_SD_generation',
-#                             'imagenhub_SD_generation', 
-#                             ]
-# IMAGE_GENERATION_MODELS = ['fal_LCM(v1.5/XL)_text2image',
-#                            'fal_SDXLTurbo_text2image',
-#                            'fal_SDXL_text2image', 
-#                            'imagenhub_PixArtAlpha_generation', 
-#                            'fal_PixArtSigma_text2image',
+#                             'imagenhub_SDXL_generation',
 #                             'imagenhub_OpenJourney_generation',
-#                             'fal_SDXLLightning_text2image', 
-#                             'fal_StableCascade_text2image',
+#                             'imagenhub_LCM_generation', 
+#                             'imagenhub_DeepFloydIF_generation', 
+#                             'imagenhub_PixArtAlpha_generation', 
+#                             'imagenhub_Kandinsky_generation', 
 #                             ]
+
+IMAGE_GENERATION_MODELS = [ 
+                            'replicate_SDXL_text2image',
+                            'replicate_SD-v3.0_text2image',
+                            'replicate_SD-v2.1_text2image',
+                            'replicate_SD-v1.5_text2image',
+                            'replicate_SDXL-Lightning_text2image',
+                            'replicate_Kandinsky-v2.0_text2image',
+                            'replicate_Kandinsky-v2.2_text2image',
+                            'replicate_Proteus-v0.2_text2image',
+                            'replicate_Playground-v2.0_text2image',
+                            'replicate_Playground-v2.5_text2image',
+                            'replicate_Dreamshaper-xl-turbo_text2image',
+                            'replicate_SDXL-Deepcache_text2image',
+                            'replicate_Openjourney-v4_text2image',
+                            'replicate_LCM_text2image',
+                            'replicate_Realvisxl-v3.0_text2image',
+                            'replicate_Realvisxl-v2.0_text2image',
+                            'replicate_Pixart-Sigma_text2image',
+                            'replicate_SSD-1b_text2image',
+                            'replicate_Open-Dalle-v1.1_text2image',
+                            'replicate_Deepfloyd-IF_text2image',
+                            'huggingface_SD-turbo_text2image',
+                            'huggingface_SDXL-turbo_text2image',
+                            ]
+
+
 IMAGE_EDITION_MODELS = ['imagenhub_CycleDiffusion_edition', 'imagenhub_Pix2PixZero_edition', 'imagenhub_Prompt2prompt_edition',
                         'imagenhub_SDEdit_edition', 'imagenhub_InstructPix2Pix_edition', 
                         'imagenhub_MagicBrush_edition', 'imagenhub_PNP_edition', 
@@ -51,16 +67,18 @@ def load_pipeline(model_name):
         the type is the type of the model, either generation or edition
     """
     model_source, model_name, model_type = model_name.split("_")
-    # if model_source == "huggingface":
-    #     pipe = load_huggingface_model(model_name)
-    if model_source == "imagenhub":
-        pipe = load_imagenhub_model(model_name, model_type)
-    # elif model_source == "playground":
-    #     pipe = load_playground_model(model_name)
-    elif model_source == "fal":
-        pipe = load_fal_model(model_name, model_type)
+    # if model_source == "imagenhub":
+    #     pipe = load_imagenhub_model(model_name, model_type)
+    # elif model_source == "fal":
+    #     pipe = load_fal_model(model_name, model_type)
     # elif model_source == "videogenhub":
     #     pipe = load_videogenhub_model(model_name)
+    if model_source == "replicate":
+        pipe = load_replicate_model(model_name, model_type)
+    elif model_source == "huggingface":
+        pipe = load_huggingface_model(model_name, model_type)
+    elif model_source == "openai":
+        pipe = load_openai_model(model_name)
     else:
         raise ValueError(f"Model source {model_source} not supported")
     return pipe

model/models/huggingface_models.py

@@ -1,20 +1,25 @@
 from diffusers import DiffusionPipeline
+from diffusers import AutoPipelineForText2Image
 import torch
 
 
 
-HF_MODEl_ID = {"SD-v1.5": "runwayml/stable-diffusion-v1-5", 
-               "SD-v2.1": "runwayml/stable-diffusion-v2-1", 
-               "SD-XL-v1.0": "stabilityai/stable-diffusion-xl-base-1.0",
-               "IF-I-XL-v1.0": "DeepFloyd/IF-I-XL-v1.0"}
 
-
-def load_huggingface_model(model_name):
-    model_id = HF_MODEl_ID[model_name]
-    pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+def load_huggingface_model(model_name, model_type):
+    if model_name == "SD-turbo":
+        pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sd-turbo", torch_dtype=torch.float16, variant="fp16")
+    elif model_name == "SDXL-turbo":
+        pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
+    else:
+        raise NotImplementedError
     pipe = pipe.to("cuda")
     return pipe
 
 
-for name in ["SD-v1.5", "SD-v2.1", "SD-XL-v1.0", "IF-I-XL-v1.0"]:
-    load_huggingface_model(name)
+if __name__ == "__main__":
+    for name in ["SD-turbo", "SDXL-turbo"]:
+        load_huggingface_model(name, "text2image")
+
+    # for name in ["IF-I-XL-v1.0"]:
+    #     pipe = load_huggingface_model(name, 'text2image')
+    # pipe = DiffusionPipeline.from_pretrained("DeepFloyd/IF-I-XL-v1.0", variant="fp16", torch_dtype=torch.float16)

model/models/openai_api_models.py

@@ -0,0 +1,30 @@
+from openai import OpenAI
+
+
+def load_openai_model(model_name):
+    client = OpenAI()
+
+    if model_name == "Dalle-3":
+        response = client.images.generate(
+            model="dall-e-3",
+            prompt="a white siamese cat",
+            size="1024x1024",
+            quality="standard",
+            n=1,
+            )
+    elif model_name == "Dalle-2":
+        response = client.images.generate(
+            model="dall-e-2",
+            prompt="a white siamese cat",
+            size="512x512",
+            quality="standard",
+            n=1,
+            )
+    else:
+        raise NotImplementedError
+
+    image_url = response.data[0].url
+
+
+if __name__ == "__main__":
+    load_openai_model('Dalle-2')

model/models/replicate_api_models.py

@@ -0,0 +1,175 @@
+import replicate
+from PIL import Image
+import requests
+import io
+import os
+import base64
+
+Replicate_MODEl_NAME_MAP = {
+    "SDXL": "stability-ai/sdxl:7762fd07cf82c948538e41f63f77d685e02b063e37e496e96eefd46c929f9bdc",
+    "SD-v3.0": "stability-ai/stable-diffusion-3",
+    "SD-v2.1": "stability-ai/stable-diffusion:ac732df83cea7fff18b8472768c88ad041fa750ff7682a21affe81863cbe77e4",
+    "SD-v1.5": "stability-ai/stable-diffusion:b3d14e1cd1f9470bbb0bb68cac48e5f483e5be309551992cc33dc30654a82bb7",
+    "SDXL-Lightning": "bytedance/sdxl-lightning-4step:5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f",
+    "Kandinsky-v2.0": "ai-forever/kandinsky-2:3c6374e7a9a17e01afe306a5218cc67de55b19ea536466d6ea2602cfecea40a9",
+    "Kandinsky-v2.2": "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a",
+    "Proteus-v0.2": "lucataco/proteus-v0.2:06775cd262843edbde5abab958abdbb65a0a6b58ca301c9fd78fa55c775fc019",
+    "Playground-v2.0": "playgroundai/playground-v2-1024px-aesthetic:42fe626e41cc811eaf02c94b892774839268ce1994ea778eba97103fe1ef51b8",
+    "Playground-v2.5": "playgroundai/playground-v2.5-1024px-aesthetic:a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24",
+    "Dreamshaper-xl-turbo": "lucataco/dreamshaper-xl-turbo:0a1710e0187b01a255302738ca0158ff02a22f4638679533e111082f9dd1b615",
+    "SDXL-Deepcache": "lucataco/sdxl-deepcache:eaf678fb34006669e9a3c6dd5971e2279bf20ee0adeced464d7b6d95de16dc93",
+    "Openjourney-v4": "prompthero/openjourney:ad59ca21177f9e217b9075e7300cf6e14f7e5b4505b87b9689dbd866e9768969",
+    "LCM": "fofr/latent-consistency-model:683d19dc312f7a9f0428b04429a9ccefd28dbf7785fef083ad5cf991b65f406f",
+    "Realvisxl-v3.0": "fofr/realvisxl-v3:33279060bbbb8858700eb2146350a98d96ef334fcf817f37eb05915e1534aa1c", 
+    
+    "Realvisxl-v2.0": "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08",
+    "Pixart-Sigma": "cjwbw/pixart-sigma:5a54352c99d9fef467986bc8f3a20205e8712cbd3df1cbae4975d6254c902de1",
+    "SSD-1b": "lucataco/ssd-1b:b19e3639452c59ce8295b82aba70a231404cb062f2eb580ea894b31e8ce5bbb6",
+    "Open-Dalle-v1.1": "lucataco/open-dalle-v1.1:1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144",
+    "Deepfloyd-IF": "andreasjansson/deepfloyd-if:fb84d659df149f4515c351e394d22222a94144aa1403870c36025c8b28846c8d",
+    }
+
+class ReplicateModel():
+    def __init__(self, model_name, model_type):
+        self.model_name = model_name
+        self.model_type = model_type
+        # os.environ['FAL_KEY'] = os.environ['FalAPI']
+    
+    def __call__(self, *args, **kwargs):
+        # def decode_data_url(data_url):
+        #     # Find the start of the Base64 encoded data
+        #     base64_start = data_url.find(",") + 1
+        #     if base64_start == 0:
+        #         raise ValueError("Invalid data URL provided")
+
+        #     # Extract the Base64 encoded data
+        #     base64_string = data_url[base64_start:]
+
+        #     # Decode the Base64 string
+        #     decoded_bytes = base64.b64decode(base64_string)
+
+        #     return decoded_bytes
+
+        if self.model_type == "text2image":
+            assert "prompt" in kwargs, "prompt is required for text2image model"
+            output  = replicate.run(
+                                    f"{Replicate_MODEl_NAME_MAP[self.model_name]}",
+                                    input={
+                                            "width": 512,
+                                            "height": 512,
+                                            "prompt": kwargs["prompt"]
+                                        },
+                                )
+            if 'Openjourney' in self.model_name:
+                for item in output:
+                    result_url = item
+                    break
+            elif isinstance(output, list):
+                result_url = output[0]
+            else:
+                result_url = output
+            print(result_url)
+            response = requests.get(result_url)
+            result = Image.open(io.BytesIO(response.content))
+            # fal_client.submit(
+            #     f"fal-ai/{FAL_MODEl_NAME_MAP[self.model_name]}",
+            #     arguments={
+            #         "prompt": kwargs["prompt"]
+            #     },
+            # )
+            # for event in handler.iter_events(with_logs=True):
+            #     if isinstance(event, fal_client.InProgress):
+            #         print('Request in progress')
+            #         print(event.logs)
+            # result = handler.get()
+            # print(result)
+            # result_url = result['images'][0]['url']
+            # if self.model_name in ["SDXLTurbo", "LCM(v1.5/XL)"]:
+            #     result_url = io.BytesIO(decode_data_url(result_url))
+            #     result = Image.open(result_url)
+            # else:
+            #     response = requests.get(result_url)
+            #     result = Image.open(io.BytesIO(response.content))
+            return result
+        # elif self.model_type == "image2image":
+        #     raise NotImplementedError("image2image model is not implemented yet")
+        #     # assert "image" in kwargs or "image_url" in kwargs, "image or image_url is required for image2image model"
+        #     # if "image" in kwargs:
+        #     #     image_url = None
+        #     #     pass
+        #     # handler = fal_client.submit(
+        #     #     f"fal-ai/{self.model_name}",
+        #     #     arguments={
+        #     #         "image_url": image_url
+        #     #     },
+        #     # )
+        #     #
+        #     # for event in handler.iter_events():
+        #     #     if isinstance(event, fal_client.InProgress):
+        #     #         print('Request in progress')
+        #     #         print(event.logs)
+        #     #
+        #     # result = handler.get()
+        #     # return result
+        # elif self.model_type == "text2video":
+        #     assert "prompt" in kwargs, "prompt is required for text2video model"
+        #     if self.model_name == 'AnimateDiff':
+        #         fal_model_name = 'fast-animatediff/text-to-video'
+        #     elif self.model_name == 'AnimateDiffTurbo':
+        #         fal_model_name = 'fast-animatediff/turbo/text-to-video'
+        #     else:
+        #         raise NotImplementedError(f"text2video model of {self.model_name} in fal is not implemented yet")
+        #     handler = fal_client.submit(
+        #         f"fal-ai/{fal_model_name}",
+        #         arguments={
+        #             "prompt": kwargs["prompt"]
+        #         },
+        #     )
+
+        #     for event in handler.iter_events(with_logs=True):
+        #         if isinstance(event, fal_client.InProgress):
+        #             print('Request in progress')
+        #             print(event.logs)
+
+        #     result = handler.get()
+        #     print("result video: ====")
+        #     print(result)
+        #     result_url = result['video']['url']
+        #     return result_url
+        else:
+            raise ValueError("model_type must be text2image or image2image")
+
+def load_replicate_model(model_name, model_type):
+    return ReplicateModel(model_name, model_type)
+
+
+if __name__ == "__main__":
+    import replicate
+    import time
+    input = {
+        "seed": 1,
+        "width": 512,
+        "height": 512,
+        "grid_size": 1,
+        "prompt": "anime astronaut riding a horse on mars"
+    }
+
+
+    for name, address in Replicate_MODEl_NAME_MAP.items():
+        print('*'*50)
+        print(name)
+
+        t1 = time.time()
+        output = replicate.run(
+            address,
+            input=input
+        )
+        # for item in output:
+        #     print(item)
+        print(output)
+
+
+        t2 = time.time()
+        print(t2-t1)
+        print('*'*50)
+    

requirements.txt

@@ -69,3 +69,4 @@ timm
 pandarallel
 wandb
 trueskill
+replicate

serve/Ksort.py

@@ -2,6 +2,7 @@ import gradio as gr
 from PIL import Image, ImageDraw, ImageFont, ImageOps
 import os
 from .constants import KSORT_IMAGE_DIR
+from .constants import COLOR1, COLOR2, COLOR3, COLOR4
 from .vote_utils import save_any_image
 from .utils import disable_btn, enable_btn, invisible_btn
 from .upload import create_remote_directory, upload_image, upload_informance, upload_ssh_all
@@ -103,19 +104,20 @@ def reset_submit(rank):
 def reset_mode(mode):
 
     if mode == "Best":
-        return (gr.update(visible=False, interactive=False),) * 6 + \
+        return (gr.update(visible=False, interactive=False),) * 5 + \
                 (gr.update(visible=True, interactive=True),) * 16 + \
                 (gr.update(visible=True, interactive=True),) * 3 + \
                 (gr.Textbox(value="Rank", visible=False, interactive=False),)
     elif mode == "Rank":
-        return (gr.update(visible=True, interactive=True),) * 6 + \
+        return (gr.update(visible=True, interactive=True),) * 5 + \
                 (gr.update(visible=False, interactive=False),) * 16 + \
                 (gr.update(visible=True, interactive=False),) * 2 + \
                 (gr.update(visible=True, interactive=True),) + \
                 (gr.Textbox(value="Best", visible=False, interactive=False),)
     else:
         raise ValueError("Undefined mode")
-
+def reset_chatbot(mode, generate_ig0, generate_ig1, generate_ig2, generate_ig3):
+    return generate_ig0, generate_ig1, generate_ig2, generate_ig3
 def get_json_filename(conv_id):
     output_dir = f'{KSORT_IMAGE_DIR}/{conv_id}/json/'
     if not os.path.exists(output_dir):
@@ -155,12 +157,12 @@ def vote_ssh_submit(states, rank):
         "models_name": [x.model_name for x in states],
         "img_rank": [x for x in rank],
     }
-    output_file = os.path.join(output_dir, "informance.json")
+    output_file = os.path.join(output_dir, "result.json")
     # upload_informance(data, output_file)
     upload_ssh_all(states, output_dir, data, output_file)
 
     from .update_skill import update_skill
-    update_skill(rank)
+    update_skill(rank, [x.model_name for x in states])
 
 
 def submit_response_igm(
@@ -169,14 +171,14 @@ def submit_response_igm(
     vote_submit([state0, state1, state2, state3], rank, request)
     vote_ssh_submit([state0, state1, state2, state3], rank)
     if model_selector0 == "":
-        return (disable_btn,) * 7 + (
+        return (disable_btn,) * 6 + (
             gr.Markdown(f"### Model A: {state0.model_name.split('_')[1]}", visible=True),
             gr.Markdown(f"### Model B: {state1.model_name.split('_')[1]}", visible=True),
             gr.Markdown(f"### Model C: {state2.model_name.split('_')[1]}", visible=True),
             gr.Markdown(f"### Model D: {state3.model_name.split('_')[1]}", visible=True)
             ) + (disable_btn,)
     else:
-        return (disable_btn,) * 7 + (
+        return (disable_btn,) * 6 + (
             gr.Markdown(state0.model_name, visible=True),
             gr.Markdown(state1.model_name, visible=True),
             gr.Markdown(state2.model_name, visible=True),
@@ -217,63 +219,35 @@ def text_response_rank_igm(generate_ig0, generate_ig1, generate_ig2, generate_ig
     for num in range(len(rank_list)):
         if rank_list[num] in ['1', '2', '3', '4']:
             base_image = Image.fromarray(generate_ig[num]).convert("RGBA")
+            base_image = base_image.resize((512, 512), Image.ANTIALIAS)
             if rank_list[num] == '1':
-                border_color = (49, 139, 190)  
+                border_color = COLOR1  
             elif rank_list[num] == '2':
-                border_color = (109, 116, 187)
+                border_color = COLOR2
             elif rank_list[num] == '3':
-                border_color = (159, 84, 152)  
+                border_color = COLOR3  
             elif rank_list[num] == '4':
-                border_color = (174, 68, 125) 
+                border_color = COLOR4 
             border_size = 10  # Size of the border
             base_image = ImageOps.expand(base_image, border=border_size, fill=border_color)
 
             draw = ImageDraw.Draw(base_image)
-            font = ImageFont.truetype("./serve/Arial.ttf", 86)
-            text_position = (300, 50)
+            font = ImageFont.truetype("./serve/Arial.ttf", 66)
+            text_position = (180, 25)
             if rank_list[num] == '1':
-                text_color = (49, 139, 190, 255)  
+                text_color = COLOR1 
                 draw.text(text_position, Top1_text, font=font, fill=text_color)
             elif rank_list[num] == '2':
-                text_color = (109, 116, 187, 255)  
+                text_color = COLOR2  
                 draw.text(text_position, Top2_text, font=font, fill=text_color)
             elif rank_list[num] == '3':
-                text_color = (159, 84, 152, 255)  
+                text_color = COLOR3  
                 draw.text(text_position, Top3_text, font=font, fill=text_color)
             elif rank_list[num] == '4':
-                text_color = (174, 68, 125, 255)  
+                text_color = COLOR4  
                 draw.text(text_position, Top4_text, font=font, fill=text_color)
             base_image = base_image.convert("RGB")
             chatbot.append(base_image.copy())
-
-            # base_image = Image.fromarray(generate_ig[num]).convert("RGBA")
-            # if rank_list[num] == '1':
-            #     txt_layer = Image.new('RGBA', base_image.size, (0, 255, 0, 64))
-            # elif rank_list[num] == '2':
-            #     txt_layer = Image.new('RGBA', base_image.size, (0, 255, 255, 64))
-            # elif rank_list[num] == '3':
-            #     txt_layer = Image.new('RGBA', base_image.size, (255, 0, 255, 64))
-            # elif rank_list[num] == '4':
-            #     txt_layer = Image.new('RGBA', base_image.size, (255, 0, 0, 64))
-            # draw = ImageDraw.Draw(txt_layer)
-            # font = ImageFont.truetype("./serve/Arial.ttf", 86)
-            # text_position = (156, 212)
-            # if rank_list[num] == '1':
-            #     text_color = (0, 255, 0, 200)  
-            #     draw.text(text_position, Top1_text, font=font, fill=text_color)
-            # elif rank_list[num] == '2':
-            #     text_color = (0, 255, 255, 200)  
-            #     draw.text(text_position, Top2_text, font=font, fill=text_color)
-            # elif rank_list[num] == '3':
-            #     text_color = (255, 0, 255, 200)  
-            #     draw.text(text_position, Top3_text, font=font, fill=text_color)
-            # elif rank_list[num] == '4':
-            #     text_color = (255, 0, 0, 200)  
-            #     draw.text(text_position, Top4_text, font=font, fill=text_color)
-
-            # combined = Image.alpha_composite(base_image, txt_layer)
-            # combined = combined.convert("RGB")
-            # chatbot.append(combined.copy())
         else:
             return generate_ig + ["error rank"] + ["wrong"] + [rank]
     rank_str = ""
@@ -317,35 +291,35 @@ def text_response_rank_igm(generate_ig0, generate_ig1, generate_ig2, generate_ig
 #     return combined
 def add_foreground(image, vote_level, Top1_text, Top2_text, Top3_text, Top4_text):
     base_image = Image.fromarray(image).convert("RGBA")
+    base_image = base_image.resize((512, 512), Image.ANTIALIAS)
     if vote_level == 0:
-        border_color = (49, 139, 190)  
+        border_color = COLOR1  
     elif vote_level == 1:
-        border_color = (109, 116, 187)
+        border_color = COLOR2
     elif vote_level == 2:
-        border_color = (159, 84, 152)  
+        border_color = COLOR3 
     elif vote_level == 3:
-        border_color = (174, 68, 125) 
+        border_color = COLOR4
     border_size = 10  # Size of the border
     base_image = ImageOps.expand(base_image, border=border_size, fill=border_color)
 
     draw = ImageDraw.Draw(base_image)
-    font = ImageFont.truetype("./serve/Arial.ttf", 86)
+    font = ImageFont.truetype("./serve/Arial.ttf", 66)
     
-    text_position = (300, 50)
+    text_position = (180, 25)
     if vote_level == 0:
-        text_color = (49, 139, 190, 255)  
+        text_color = COLOR1 
         draw.text(text_position, Top1_text, font=font, fill=text_color)
     elif vote_level == 1:
-        text_color = (109, 116, 187, 255)  
+        text_color = COLOR2  
         draw.text(text_position, Top2_text, font=font, fill=text_color)
     elif vote_level == 2:
-        text_color = (159, 84, 152, 255)  
+        text_color = COLOR3 
         draw.text(text_position, Top3_text, font=font, fill=text_color)
     elif vote_level == 3:
-        text_color = (174, 68, 125, 255)  
+        text_color = COLOR4  
         draw.text(text_position, Top4_text, font=font, fill=text_color)
 
-    # combined = Image.alpha_composite(base_image, txt_layer)
     base_image = base_image.convert("RGB")
     return base_image
 def add_green_border(image):

serve/gradio_web.py

@@ -28,10 +28,12 @@ from .Ksort import (
     reset_submit,
     clear_rank,
     reset_mode,
+    reset_chatbot,
     reset_btn_rank,
     reset_vote_text,
     text_response_rank_igm,
 )
+from serve.upload import get_random_mscoco_prompt
 from functools import partial
 
 def build_side_by_side_ui_anony(models):
@@ -88,41 +90,28 @@ Find out who is the 🥇conditional image generation models! More models are goi
         with gr.Row():
             slow_warning = gr.Markdown("", elem_id="notice_markdown")
 
-        with gr.Row():
-            leftvote_btn = gr.Button(
-                value="A is Best", visible=False, interactive=False
-            )
-            left1vote_btn = gr.Button(
-                value="B is Best", visible=False, interactive=False
-            )
-            rightvote_btn = gr.Button(
-                value="C is Best", visible=False, interactive=False
-            )
-            right1vote_btn = gr.Button(
-                value="D is Best", visible=False, interactive=False
-            )
-            tie_btn = gr.Button(value="🤝  Tie", visible=False, interactive=False)
-            bothbad_btn = gr.Button(
-                value="👎  Both are bad", visible=False, interactive=False
-            )
+        with gr.Row(elem_classes="row"):
+            with gr.Column(scale=1, min_width=10):
+                leftvote_btn = gr.Button(
+                    value="A is Best", visible=False, interactive=False, elem_id="btncolor1", elem_classes="best-button"
+                )
+            with gr.Column(scale=1, min_width=10):
+                left1vote_btn = gr.Button(
+                    value="B is Best", visible=False, interactive=False, elem_id="btncolor1", elem_classes="best-button"
+                )
+            with gr.Column(scale=1, min_width=10):
+                rightvote_btn = gr.Button(
+                    value="C is Best", visible=False, interactive=False, elem_id="btncolor1", elem_classes="best-button"
+                )
+            with gr.Column(scale=1, min_width=10):
+                right1vote_btn = gr.Button(
+                    value="D is Best", visible=False, interactive=False, elem_id="btncolor1", elem_classes="best-button"
+                )
+            with gr.Column(scale=1, min_width=10):
+                tie_btn = gr.Button(
+                    value="🤝  Tie", visible=False, interactive=False, elem_id="btncolor2", elem_classes="best-button"
+                )
 
-        with gr.Row():
-            Top1_btn = gr.Button(
-                value="Top1", visible=False, interactive=False
-            )
-            Top2_btn = gr.Button(
-                value="Top2", visible=False, interactive=False
-            )
-            Top3_btn = gr.Button(
-                value="Top3", visible=False, interactive=False
-            )
-            Top4_btn = gr.Button(
-                value="Top4", visible=False, interactive=False
-            )
-            Revote_btn = gr.Button(
-                value="Re-vote", visible=False, interactive=False
-            )
-            Submit_btn = gr.Button(value="🤝  Submit", visible=False, interactive=False)
         with gr.Row():
             with gr.Blocks():
                 with gr.Row():
@@ -205,8 +194,8 @@ Find out who is the 🥇conditional image generation models! More models are goi
             elem_id="input_box",
             visible=False,
         )
-        vote_submit_btn = gr.Button(value="Submit", visible=False, interactive=False, variant="primary", scale=0)
-        vote_mode_btn = gr.Button(value="🔄 Mode", visible=False, interactive=False, variant="primary", scale=0)
+        vote_submit_btn = gr.Button(value="Submit", visible=False, interactive=False, variant="primary", scale=0, elem_id="btnpink", elem_classes="submit-button")
+        vote_mode_btn = gr.Button(value="🔄 Mode", visible=False, interactive=False, variant="primary", scale=0, elem_id="btnpink", elem_classes="submit-button")
 
     with gr.Row():
         textbox = gr.Textbox(
@@ -215,28 +204,28 @@ Find out who is the 🥇conditional image generation models! More models are goi
             container=True,
             elem_id="input_box",
         )
+        # send_btn = gr.Button(value="Send", variant="primary", scale=0, elem_id="btnblue", elem_classes="send-button")
+        # draw_btn = gr.Button(value="🎲 Random sample", variant="primary", scale=0, elem_id="btnblue", elem_classes="send-button")
         send_btn = gr.Button(value="Send", variant="primary", scale=0)
-        draw_btn = gr.Button(value="🎲 Random sample", variant="primary", scale=0)
-
+        draw_btn = gr.Button(value="🎲 Random Prompt", variant="primary", scale=0)
     with gr.Row():
         clear_btn = gr.Button(value="🎲 New Round", interactive=False)
-        regenerate_btn = gr.Button(value="🔄  Regenerate", interactive=False)
+        # regenerate_btn = gr.Button(value="🔄  Regenerate", interactive=False)
         # share_btn = gr.Button(value="📷  Share")
 
     #gr.Markdown(acknowledgment_md, elem_id="ack_markdown")
 
     dummy_img_output = gr.Image(width=512, visible=False)
     gr.Examples(
-        examples=[["a cute dog is playing a ball", os.path.join("./examples", "dog.jpg")],
-                  ["Buildings on fire, old film still", os.path.join("./examples", "fire.jpg")],
-                  ["Lonely evil bananas on a table, hard light chiaroscuro, realistic",os.path.join("./examples", "banana.jpg")],
-                  ["A futuristic hopeful busy city, purple and green color scheme", os.path.join("./examples", "city.jpg")]],
+        examples=[["A train crossing a bridge that is going over a body of water", os.path.join("./examples", "example1.jpg")],
+                  ["The man in the business suit wears a striped blue and white tie", os.path.join("./examples", "example2.jpg")],
+                  ["A skier stands on a small ledge in the snow",os.path.join("./examples", "example3.jpg")],
+                  ["The bathroom with green tile and a red shower curtain", os.path.join("./examples", "example4.jpg")]],
         inputs = [textbox, dummy_img_output])
 
-    btn_list = [leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn]
-    vote_list = [Top1_btn, Top2_btn, Top3_btn, Top4_btn, Revote_btn, Submit_btn]
-    order_btn_list = [send_btn, draw_btn, clear_btn, regenerate_btn]
-    vote_order_list = [leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn, \
+    # vote_list = [Top1_btn, Top2_btn, Top3_btn, Top4_btn, Revote_btn, Submit_btn]
+    order_btn_list = [send_btn, draw_btn, clear_btn]
+    vote_order_list = [leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, \
                        A1_btn, A2_btn, A3_btn, A4_btn, B1_btn, B2_btn, B3_btn, B4_btn, C1_btn, C2_btn, C3_btn, C4_btn, D1_btn, D2_btn, D3_btn, D4_btn, \
                        vote_textbox, vote_submit_btn, vote_mode_btn]
     # vote_rank_list = [A1_btn, A2_btn, A3_btn, A4_btn, B1_btn, B2_btn, B3_btn, B4_btn, C1_btn, C2_btn, C3_btn, C4_btn, D1_btn, D2_btn, D3_btn, D4_btn]
@@ -273,10 +262,10 @@ Find out who is the 🥇conditional image generation models! More models are goi
     window3_text = gr.Textbox(value="Model C", visible=False, interactive=False)
     window4_text = gr.Textbox(value="Model D", visible=False, interactive=False)
     vote_level = gr.Number(value=0, visible=False, interactive=False)
-    Top1_btn.click(reset_level, inputs=[Top1_text], outputs=[vote_level])
-    Top2_btn.click(reset_level, inputs=[Top2_text], outputs=[vote_level])
-    Top3_btn.click(reset_level, inputs=[Top3_text], outputs=[vote_level])
-    Top4_btn.click(reset_level, inputs=[Top4_text], outputs=[vote_level])
+    # Top1_btn.click(reset_level, inputs=[Top1_text], outputs=[vote_level])
+    # Top2_btn.click(reset_level, inputs=[Top2_text], outputs=[vote_level])
+    # Top3_btn.click(reset_level, inputs=[Top3_text], outputs=[vote_level])
+    # Top4_btn.click(reset_level, inputs=[Top4_text], outputs=[vote_level])
     vote_mode = gr.Textbox(value="Best", visible=False, interactive=False)
     right_vote_text = gr.Textbox(value="wrong", visible=False, interactive=False)
 
@@ -312,26 +301,27 @@ Find out who is the 🥇conditional image generation models! More models are goi
         outputs=vote_order_list
     )
 
+    # draw_btn.click(
+    #     gen_func_random,
+    #     inputs=[state0, state1, state2, state3, model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
+    #     outputs=[state0, state1, state2, state3, generate_ig0, generate_ig1, generate_ig2, generate_ig3, chatbot_left, chatbot_left1, chatbot_right, chatbot_right1, \
+    #              textbox, model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
+    #     api_name="draw_btn_annony"
+    # ).then(
+    #     disable_order_buttons,
+    #     inputs=None,
+    #     outputs=order_btn_list
+    # ).then(
+    #     enable_vote_mode_buttons,
+    #     inputs=[vote_mode],
+    #     outputs=vote_order_list
+    # )
     draw_btn.click(
-        gen_func_random,
-        inputs=[state0, state1, state2, state3, model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
-        outputs=[state0, state1, state2, state3, generate_ig0, generate_ig1, generate_ig2, generate_ig3, chatbot_left, chatbot_left1, chatbot_right, chatbot_right1, \
-                 textbox, model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
+        get_random_mscoco_prompt,
+        inputs=None, 
+        outputs=[textbox],
         api_name="draw_btn_annony"
-    ).then(
-        disable_order_buttons,
-        inputs=None,
-        outputs=order_btn_list
-    ).then(
-        enable_vote_mode_buttons,
-        inputs=[vote_mode],
-        outputs=vote_order_list
     )
-    # .then(
-    #     enable_vote_buttons,
-    #     inputs=None,
-    #     outputs=vote_list
-    # )
 
     clear_btn.click(
         clear_history_side_by_side_anony, 
@@ -343,10 +333,6 @@ Find out who is the 🥇conditional image generation models! More models are goi
         enable_order_buttons,
         inputs=None,
         outputs=order_btn_list
-    ).then(
-        disable_vote_buttons,
-        inputs=None,
-        outputs=vote_list
     ).then(
         clear_rank,
         inputs=[rank, vote_level],
@@ -369,16 +355,25 @@ Find out who is the 🥇conditional image generation models! More models are goi
     #     outputs=btn_list
     # )
     vote_mode_btn.click(
+        reset_chatbot,
+        inputs=[vote_mode, generate_ig0, generate_ig1, generate_ig2, generate_ig3], 
+        outputs=[chatbot_left, chatbot_left1, chatbot_right, chatbot_right1]
+    ).then(
         reset_mode, 
         inputs=[vote_mode], 
-        outputs=[leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn, \
+        outputs=[leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, \
                     A1_btn, A2_btn, A3_btn, A4_btn, B1_btn, B2_btn, B3_btn, B4_btn, C1_btn, C2_btn, C3_btn, C4_btn, D1_btn, D2_btn, D3_btn, D4_btn, \
                     vote_textbox, vote_submit_btn, vote_mode_btn, vote_mode]
-    )    
+    )
+
     vote_textbox.submit(
         text_response_rank_igm,
         inputs=[generate_ig0, generate_ig1, generate_ig2, generate_ig3, Top1_text, Top2_text, Top3_text, Top4_text, vote_textbox], 
         outputs=[chatbot_left, chatbot_left1, chatbot_right, chatbot_right1, vote_textbox, right_vote_text, rank]
+    ).then(
+        disable_vote,
+        inputs=None,
+        outputs=[vote_submit_btn, vote_mode_btn]
     ).then(
         submit_response_rank_igm,
         inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, rank, right_vote_text],
@@ -391,6 +386,10 @@ Find out who is the 🥇conditional image generation models! More models are goi
         text_response_rank_igm,
         inputs=[generate_ig0, generate_ig1, generate_ig2, generate_ig3, Top1_text, Top2_text, Top3_text, Top4_text, vote_textbox], 
         outputs=[chatbot_left, chatbot_left1, chatbot_right, chatbot_right1, vote_textbox, right_vote_text, rank]
+    ).then(
+        disable_vote,
+        inputs=None,
+        outputs=[vote_submit_btn, vote_mode_btn]
     ).then(
         submit_response_rank_igm,
         inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, rank, right_vote_text],
@@ -457,42 +456,35 @@ Find out who is the 🥇conditional image generation models! More models are goi
     leftvote_btn.click(
         submit_response_igm,
         inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, rankA],
-        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn, \
+        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, \
                  model_selector_left, model_selector_left1, model_selector_right, model_selector_right1, \
                  vote_mode_btn]
     )
     left1vote_btn.click(
         submit_response_igm,
         inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, rankB],
-        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn, \
+        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, \
                  model_selector_left, model_selector_left1, model_selector_right, model_selector_right1, \
                  vote_mode_btn]
     )
     rightvote_btn.click(
         submit_response_igm,
         inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, rankC],
-        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn, \
+        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, \
                  model_selector_left, model_selector_left1, model_selector_right, model_selector_right1, \
                  vote_mode_btn]
     )
     right1vote_btn.click(
         submit_response_igm,
         inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, rankD],
-        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn, \
+        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, \
                  model_selector_left, model_selector_left1, model_selector_right, model_selector_right1, \
                  vote_mode_btn]
     )
     tie_btn.click(
         submit_response_igm,
         inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, rankTie],
-        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn, \
-                 model_selector_left, model_selector_left1, model_selector_right, model_selector_right1, \
-                 vote_mode_btn]
-    )
-    bothbad_btn.click(
-        submit_response_igm,
-        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, rankBad],
-        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, bothbad_btn, \
+        outputs=[textbox, leftvote_btn, left1vote_btn, rightvote_btn, right1vote_btn, tie_btn, \
                  model_selector_left, model_selector_left1, model_selector_right, model_selector_right1, \
                  vote_mode_btn]
     )

serve/update_skill.py

@@ -6,9 +6,8 @@ import io, os
 import sys
 from serve.constants import SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD, SSH_SKILL
 trueskill_env = TrueSkill()
-
-class Model_ID(object):
-    group = []
+sys.path.append('../')
+from model.models import IMAGE_GENERATION_MODELS
 
 
 def ucb_score(trueskill_diff, t, n):
@@ -56,10 +55,16 @@ def load_json_via_sftp():
     return ratings, comparison_counts, total_comparisons
 
 
-def update_skill(rank, k_group=4):
+def update_skill(rank, model_names, k_group=4):
 
     ratings, comparison_counts, total_comparisons = load_json_via_sftp()
-    group = Model_ID.group
+
+    # group = Model_ID.group
+    group = []
+    for model_name in model_names:
+        group.append(IMAGE_GENERATION_MODELS.index(model_name))
+    print(group)
+
     pairwise_comparisons = [(i, j) for i in range(len(group)) for j in range(i+1, len(group))]
     for player1, player2 in pairwise_comparisons:
         if rank[player1] < rank[player2]:
@@ -73,5 +78,7 @@ def update_skill(rank, k_group=4):
             
         comparison_counts[group[player1], group[player2]] += 1
         comparison_counts[group[player2], group[player1]] += 1
+        
+    total_comparisons += 1
 
     save_json_via_sftp(ratings, comparison_counts, total_comparisons)

serve/upload.py

@@ -4,7 +4,8 @@ import io, os
 from PIL import Image
 import requests
 import json
-from .constants import SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD, SSH_LOG
+import random
+from .constants import SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD, SSH_LOG, SSH_MSCOCO
 
 def create_ssh_client(server, port, user, password):
     ssh = paramiko.SSHClient()
@@ -47,6 +48,25 @@ def upload_informance(data, data_path):
     pass
     # ssh = create_ssh_client(SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD)
     # upload_json_via_sftp(ssh, data, data_path)
+def get_random_mscoco_prompt():
+    ssh = create_ssh_client(SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD)
+    sftp = ssh.open_sftp()
+    files = sftp.listdir(SSH_MSCOCO)
+    txt_files = [file for file in files if file.endswith('.txt')]
+
+    selected_files = random.sample(txt_files, 1) # get one prompt
+
+    for file in selected_files:
+        remote_file_path = os.path.join(SSH_MSCOCO, file)
+        with sftp.file(remote_file_path, 'r') as f:
+            content = f.read().decode('utf-8')
+            print(f"Content of {file}:")
+            print("\n")
+    sftp.close()
+    ssh.close()
+
+    return content
+
 
 def create_remote_directory(remote_directory):
     ssh = create_ssh_client(SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD)

serve/utils.py

@@ -46,7 +46,6 @@ acknowledgment_md = """
     <p> Our codebase is built upon <a href="https://github.com/lm-sys/FastChat" target="_blank">FastChat</a>, <a href="https://github.com/TIGER-AI-Lab/ImagenHub" target="_blank">ImagenHub</a> and <a href="https://github.com/TIGER-AI-Lab/VideoGenHub" target="_blank">VideoGenHub</a>.</p>
 </div>
 """
-color = "rgb(49, 139, 190)"
 block_css = """
 #notice_markdown {
     font-size: 110%
@@ -100,11 +99,53 @@ footer {
 .custom-button {
     border-radius: 8px;
 }
-#btncolor1 {background: rgb(49, 139, 190);} 
-#btncolor2 {background: rgb(109, 116, 187);} 
-#btncolor3 {background: rgb(159, 84, 152);} 
-#btncolor4 {background: rgb(174, 68, 125);} 
+.best-button {
+    border-radius: 8px;
+}
+.row {
+    display: flex;
+    justify-content: space-between; 
+}
+.send-button {
+    color: white;
+}
+.submit-button {
+    color: red;
+}
+#btncolor1 {background: rgb(168, 230, 207);} 
+#btncolor2 {background: rgb(253, 255, 171);} 
+#btncolor3 {background: rgb(255, 211, 182);} 
+#btncolor4 {background: rgb(255, 170, 165);} 
+
+#btnblue {background: rgb(0, 187, 240);} 
+#btnpink {background: rgb(255, 168, 184);} 
 """
+
+#btncolor1 {background: rgb(128, 214, 255);} 
+#btncolor2 {background: rgb(237, 247, 152);} 
+#btncolor3 {background: rgb(250, 181, 122);} 
+#btncolor4 {background: rgb(240, 104, 104);} 
+
+#btncolor1 {background: rgb(112, 161, 215);} 
+#btncolor2 {background: rgb(161, 222, 147);} 
+#btncolor3 {background: rgb(247, 244, 139);} 
+#btncolor4 {background: rgb(244, 124, 124);} 
+
+#btncolor1 {background: rgb(168, 230, 207);} 
+#btncolor2 {background: rgb(253, 255, 171);} 
+#btncolor3 {background: rgb(255, 211, 182);} 
+#btncolor4 {background: rgb(255, 170, 165);} 
+
+#btncolor1 {background: rgb(255, 212, 96);} 
+#btncolor2 {background: rgb(240, 123, 63);} 
+#btncolor3 {background: rgb(234, 84, 85);} 
+#btncolor4 {background: rgb(45, 64, 89);} 
+
+#btncolor1 {background: rgb(255, 189, 57);} 
+#btncolor2 {background: rgb(230, 28, 93);} 
+#btncolor3 {background: rgb(147, 0, 119);} 
+#btncolor4 {background: rgb(58, 0, 136);} 
+# max-width: 100px;
 # .custom-button {
 #     padding: 10px 15px;
 #     text-align: center;
@@ -134,26 +175,27 @@ def enable_vote_buttons():
     return tuple(gr.update(visible=True, interactive=i<=4) for i in range(6))
 def disable_vote_buttons():
     return tuple(gr.update(visible=False, interactive=False) for i in range(6))
-
+def disable_vote():
+    return (gr.update(interactive=False), gr.update(interactive=False))
 def enable_vote_mode_buttons(mode):
     print(mode)
     if mode == "Best":
-        return (gr.update(visible=True, interactive=True),) * 6 + \
+        return (gr.update(visible=True, interactive=True),) * 5 + \
                 (gr.update(visible=False, interactive=False),) * 16 + \
                 (gr.update(visible=True, interactive=False),) * 2 + \
                 (gr.update(visible=True, interactive=True),)
     elif mode == "Rank":
-        return (gr.update(visible=False, interactive=False),) * 6 + \
+        return (gr.update(visible=False, interactive=False),) * 5 + \
                 (gr.update(visible=True, interactive=True),) * 16 + \
                 (gr.update(visible=True, interactive=True),) * 3
 def disable_vote_mode_buttons():
-        return tuple(gr.update(visible=False, interactive=False) for _ in range(25))
+        return tuple(gr.update(visible=False, interactive=False) for _ in range(24))
 
     
 def enable_order_buttons():
-    return tuple(gr.update(interactive=True) for _ in range(4))
+    return tuple(gr.update(interactive=True) for _ in range(3))
 def disable_order_buttons():
-    return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True), gr.update(interactive=False))
+    return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True))
 
 def clear_history():
     return None, "", None