pre-release

.gitignore

@@ -167,4 +167,8 @@ cython_debug/
 /*.ipynb
 
 GenAI-Arena-hf-logs/vote_log/*
-ksort-logs/
+ksort-logs/
+
+
+*.mp4
+cache_video/

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import os
 from serve.gradio_web import *
 from serve.gradio_web_video import build_side_by_side_video_ui_anony
-from serve.leaderboard import build_leaderboard_tab, build_leaderboard_video_tab
+from serve.leaderboard import build_leaderboard_tab, build_leaderboard_video_tab, build_leaderboard_contributor
 from model.model_manager import ModelManager
 from pathlib import Path
 from serve.constants import SERVER_PORT, ROOT_PATH, ELO_RESULTS_DIR
@@ -35,6 +35,8 @@ def build_combine_demo(models, elo_results_file, leaderboard_table_file):
                     
                     with gr.Tab("Generation Arena (battle)", id=1):
                         build_side_by_side_video_ui_anony(models)
+            with gr.Tab("Contributor", id=2):
+                build_leaderboard_contributor()
     return demo
 
 

contributor.json

@@ -0,0 +1,70 @@
+{
+    "contributor": [
+        {
+            "Rank": 1,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Jing",
+            "\ud83c\udfdb\ufe0f Affiliation": "CASIA",
+            "\ud83d\uddf3\ufe0f Votes": 200
+        },
+        {
+            "Rank": 2,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Zhikai",
+            "\ud83c\udfdb\ufe0f Affiliation": "CASIA",
+            "\ud83d\uddf3\ufe0f Votes": 180
+        },
+        {
+            "Rank": 3,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Xuewen",
+            "\ud83c\udfdb\ufe0f Affiliation": "CASIA",
+            "\ud83d\uddf3\ufe0f Votes": 180
+        },
+        {
+            "Rank": 4,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Joe",
+            "\ud83c\udfdb\ufe0f Affiliation": "Berkeley",
+            "\ud83d\uddf3\ufe0f Votes": 150
+        },
+        {
+            "Rank": 5,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Jianquan",
+            "\ud83c\udfdb\ufe0f Affiliation": "CASIA",
+            "\ud83d\uddf3\ufe0f Votes": 100
+        },
+        {
+            "Rank": 6,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Zhen",
+            "\ud83c\udfdb\ufe0f Affiliation": "Berkeley",
+            "\ud83d\uddf3\ufe0f Votes": 50
+        },
+        {
+            "Rank": 7,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Collov Labs",
+            "\ud83c\udfdb\ufe0f Affiliation": "Collov Labs",
+            "\ud83d\uddf3\ufe0f Votes": 12
+        },
+        {
+            "Rank": 8,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Jinbin Bai",
+            "\ud83c\udfdb\ufe0f Affiliation": "NUS",
+            "\ud83d\uddf3\ufe0f Votes": 3
+        },
+        {
+            "Rank": 9,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Yinglong",
+            "\ud83c\udfdb\ufe0f Affiliation": "Meituan",
+            "\ud83d\uddf3\ufe0f Votes": 3
+        },
+        {
+            "Rank": 10,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Gray_squirrel",
+            "\ud83c\udfdb\ufe0f Affiliation": "",
+            "\ud83d\uddf3\ufe0f Votes": 2
+        },
+        {
+            "Rank": 11,
+            "\ud83d\udc68\u200d\u2696\ufe0f Name": "Mingfei Guo",
+            "\ud83c\udfdb\ufe0f Affiliation": "",
+            "\ud83d\uddf3\ufe0f Votes": 1
+        }
+    ]
+}

model/matchmaker.py

@@ -4,6 +4,8 @@ from trueskill import TrueSkill
 import paramiko
 import io, os
 import sys
+import random
+
 sys.path.append('../')
 from serve.constants import SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD, SSH_SKILL
 trueskill_env = TrueSkill()
@@ -79,7 +81,7 @@ def load_json_via_sftp():
 class RunningPivot(object):
     running_pivot = []
 
-not_run = [20,21,22]
+not_run = [12,13,14,15,16,17,18,19,20,21,22, 25,26] #23,24,
 
 def matchmaker(num_players, k_group=4):
     trueskill_env = TrueSkill()
@@ -112,6 +114,8 @@ def matchmaker(num_players, k_group=4):
 
     # Group players
     model_ids = [selected_player] + opponents
+
+    random.shuffle(model_ids)
         
     return model_ids
 

model/matchmaker_video.py

@@ -4,6 +4,8 @@ from trueskill import TrueSkill
 import paramiko
 import io, os
 import sys
+import random
+
 sys.path.append('../')
 from serve.constants import SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD, SSH_VIDEO_SKILL
 trueskill_env = TrueSkill()
@@ -94,10 +96,34 @@ def matchmaker_video(num_players, k_group=4):
 
     # Exclude self, select opponent with highest UCB score
     ucb_scores[selected_player] = -float('inf')  # minimize the score for the selected player to exclude it
+
+    excluded_players_1 = [num_players-1, num_players-4]
+    excluded_players_2 = [num_players-2, num_players-3, num_players-5]
+    excluded_players = excluded_players_1 + excluded_players_2
+    if selected_player in excluded_players_1:
+        for player in excluded_players:
+            ucb_scores[player] = -float('inf')
+    if selected_player in excluded_players_2:
+        for player in excluded_players_1:
+            ucb_scores[player] = -float('inf')
+    else:
+        excluded_ucb_scores = {player: ucb_scores[player] for player in excluded_players}
+        max_player = max(excluded_ucb_scores, key=excluded_ucb_scores.get)
+        if max_player in excluded_players_1:
+            for player in excluded_players:
+                if player != max_player:
+                    ucb_scores[player] = -float('inf')
+        else:
+            for player in excluded_players_1:
+                ucb_scores[player] = -float('inf')
+
+
     opponents = np.argsort(ucb_scores)[-k_group + 1:].tolist()
 
     # Group players
     model_ids = [selected_player] + opponents
+
+    random.shuffle(model_ids)
         
     return model_ids
 

model/model_manager.py

@@ -9,7 +9,9 @@ from PIL import Image
 from openai import OpenAI
 from .models import IMAGE_GENERATION_MODELS, IMAGE_EDITION_MODELS, VIDEO_GENERATION_MODELS, load_pipeline
 from .fetch_museum_results import draw_from_imagen_museum, draw2_from_imagen_museum
-from serve.upload import get_random_mscoco_prompt
+from serve.upload import get_random_mscoco_prompt, get_random_video_prompt, get_ssh_random_video_prompt
+from serve.constants import SSH_CACHE_OPENSOURCE, SSH_CACHE_ADVANCE, SSH_CACHE_PIKA, SSH_CACHE_SORA, SSH_CACHE_IMAGE
+
 
 class ModelManager:
     def __init__(self):
@@ -85,15 +87,17 @@ class ModelManager:
         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]
+                    else executor.submit(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]
 
-    def generate_video_ig_parallel_anony(self, prompt_num, model_A, model_B, model_C, model_D):
+    def generate_video_vg_parallel_anony(self, model_A, model_B, model_C, model_D):
         if model_A == "" and model_B == "" and model_C == "" and model_D == "":
             # model_names = random.sample([model for model in self.model_vg_list], 4)
 
@@ -104,14 +108,31 @@ class ModelManager:
             print(model_names)
         else:
             model_names = [model_A, model_B, model_C, model_D]
-
-        cache_dir = os.path.join("/mnt/data/lizhikai/ksort_video_cache/", f'cache_{prompt_num}')
-        results = []
+        
+        root_dir = SSH_CACHE_OPENSOURCE
         for name in model_names:
-            model_source, model_name, model_type = name.split("_")
-            video_path = os.path.join(cache_dir, f'{model_name}.mp4')
-            print(video_path)
-            results.append(video_path)
+            if "Runway-Gen3" in name or "Runway-Gen2" in name or "Pika-v1.0" in name:
+                root_dir = SSH_CACHE_ADVANCE
+            elif "Pika-beta" in name:
+                root_dir = SSH_CACHE_PIKA      
+            elif "Sora" in name and "OpenSora" not in name: 
+                root_dir = SSH_CACHE_SORA  
+        
+        local_dir = "./cache_video"
+        prompt, results = get_ssh_random_video_prompt(root_dir, local_dir, model_names)
+        cache_dir = local_dir
+        # cache_dir, prompt = get_random_video_prompt(root_dir)
+        # results = []
+        # for name in model_names:
+        #     model_source, model_name, model_type = name.split("_")
+        #     # if model_name in ["Runway-Gen3", "Pika-beta", "Pika-v1.0"]:
+        #     #     file_name = cache_dir.split("/")[-1]
+        #     #     video_path = os.path.join(cache_dir, f'{file_name}.mp4')
+        #     # else:
+        #     #     video_path = os.path.join(cache_dir, f'{model_name}.mp4')
+        #     video_path = os.path.join(cache_dir, f'{model_name}.mp4')
+        #     print(video_path)
+        #     results.append(video_path)
 
         # with concurrent.futures.ThreadPoolExecutor() as executor:
         #     futures = [executor.submit(self.generate_image_ig, prompt, model) if model.startswith("huggingface")
@@ -119,7 +140,7 @@ class ModelManager:
         #     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]
+            model_names[0], model_names[1], model_names[2], model_names[3], prompt, cache_dir
 
     def generate_image_ig_museum_parallel_anony(self, model_A, model_B, model_C, model_D):
         if model_A == "" and model_B == "" and model_C == "" and model_D == "":

model/models/__init__.py

@@ -1,6 +1,6 @@
-from .imagenhub_models import load_imagenhub_model
+# from .imagenhub_models import load_imagenhub_model
 # from .playground_api import load_playground_model
-from .fal_api_models import load_fal_model
+# from .fal_api_models import load_fal_model
 # from .videogenhub_models import load_videogenhub_model
 from .huggingface_models import load_huggingface_model
 from .replicate_api_models import load_replicate_model
@@ -36,6 +36,9 @@ IMAGE_GENERATION_MODELS = [
                             'openai_Dalle-3_text2image',
                             'other_Midjourney-v6.0_text2image',
                             'other_Midjourney-v5.0_text2image',
+                            "replicate_FLUX.1-schnell_text2image",
+                            "replicate_FLUX.1-pro_text2image",
+                            "replicate_FLUX.1-dev_text2image",
                             ]
 
 
@@ -48,12 +51,16 @@ IMAGE_EDITION_MODELS = ['imagenhub_CycleDiffusion_edition', 'imagenhub_Pix2PixZe
 #                            'videogenhub_LaVie_generation', 'videogenhub_VideoCrafter2_generation',
 #                            'videogenhub_ModelScope_generation', 'videogenhub_OpenSora_generation']
 VIDEO_GENERATION_MODELS = ['replicate_Zeroscope-v2-xl_text2video',
-                        #    'replicate_Damo-Text-to-Video_text2video',
-                           'replicate_Animate-Diff_text2video',
-                           'replicate_OpenSora_text2video',
-                           'replicate_LaVie_text2video',
-                           'replicate_VideoCrafter2_text2video',
-                           'replicate_Stable-Video-Diffusion_text2video',
+                            'replicate_Animate-Diff_text2video',
+                            'replicate_OpenSora_text2video',
+                            'replicate_LaVie_text2video',
+                            'replicate_VideoCrafter2_text2video',
+                            'replicate_Stable-Video-Diffusion_text2video',
+                            'other_Runway-Gen3_text2video',
+                            'other_Pika-beta_text2video',
+                            'other_Pika-v1.0_text2video',
+                            'other_Runway-Gen2_text2video',
+                            'other_Sora_text2video',
                            ]
 
 def load_pipeline(model_name):

model/models/generate_image_cache.py

@@ -0,0 +1,99 @@
+from huggingface_models import load_huggingface_model
+from replicate_api_models import load_replicate_model
+from openai_api_models import load_openai_model
+from other_api_models import load_other_model
+import concurrent.futures 
+import os
+import io, time
+import requests
+import json
+from PIL import Image
+
+
+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-v1.5_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',
+                            # 'huggingface_Stable-cascade_text2image',
+                            # 'openai_Dalle-2_text2image',
+                            # 'openai_Dalle-3_text2image',
+                            'other_Midjourney-v6.0_text2image',
+                            'other_Midjourney-v5.0_text2image',
+                            # "replicate_FLUX.1-schnell_text2image",
+                            # "replicate_FLUX.1-pro_text2image",
+                            # "replicate_FLUX.1-dev_text2image",
+                            ]
+
+Prompts = [
+    # 'An aerial view of someone walking through a forest alone in the style of Romanticism.',
+    # 'With dark tones and backlit resolution, this oil painting depicts a thunderstorm over a cityscape.',
+    # 'The rendering depicts a futuristic train station with volumetric lighting in an Art Nouveau style.',
+    # 'An Impressionist illustration depicts a river winding through a meadow.', # featuring a thick black outline
+    # 'Photo of a black and white picture of a person facing the sunset from a bench.',
+    # 'The skyline of a city is painted in bright, high-resolution colors.',
+    # 'A sketch shows two robots talking to each other, featuring a surreal look and narrow aspect ratio.',
+    # 'An abstract Dadaist collage in neon tones and 4K resolutions of a post-apocalyptic world.',
+    # 'With abstract elements and a rococo style, the painting depicts a garden in high resolution.',
+    # 'A picture of a senior man walking in the rain and looking directly at the camera from a medium distance.',
+]
+
+def load_pipeline(model_name):
+    model_source, model_name, model_type = model_name.split("_")
+    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, model_type)
+    elif model_source == "other":
+        pipe = load_other_model(model_name, model_type)
+    else:
+        raise ValueError(f"Model source {model_source} not supported")
+    return pipe
+
+def generate_image_ig_api(prompt, model_name):
+        pipe = load_pipeline(model_name)
+        result = pipe(prompt=prompt)
+        return result
+
+save_names = []
+for name in IMAGE_GENERATION_MODELS:
+    model_source, model_name, model_type = name.split("_")
+    save_names.append(model_name)
+
+for i, prompt in enumerate(Prompts):
+    print("save the {} prompt".format(i+1))
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        futures = [executor.submit(generate_image_ig_api, prompt, model) for model in IMAGE_GENERATION_MODELS]
+        results = [future.result() for future in futures]
+
+    root_dir = '/rscratch/zhendong/lizhikai/ksort/ksort_image_cache/'
+    save_dir = os.path.join(root_dir, f'output-{i+4}')
+    if not os.path.exists(save_dir):
+        os.makedirs(save_dir, exist_ok=True)
+    with open(os.path.join(save_dir, "prompt.txt"), 'w', encoding='utf-8') as file:
+        file.write(prompt)
+
+    for j, result in enumerate(results):
+        result = result.resize((512, 512))
+        file_path = os.path.join(save_dir, f'{save_names[j]}.jpg')
+        result.save(file_path, format="JPEG")

model/models/generate_video_cache.py

@@ -0,0 +1,62 @@
+
+
+file_path = '/home/lizhikai/webvid_prompt100.txt'
+str_list = []
+with open(file_path, 'r', encoding='utf-8') as file:
+    for line in file:
+        str_list.append(line.strip())
+        if len(str_list) == 100:
+            break
+
+def generate_image_ig_api(prompt, model_name):
+    model_source, model_name, model_type = model_name.split("_")
+    pipe = load_replicate_model(model_name, model_type)
+    result = pipe(prompt=prompt)
+    return result
+model_names = ['replicate_Zeroscope-v2-xl_text2video',
+                    #    'replicate_Damo-Text-to-Video_text2video',
+                        'replicate_Animate-Diff_text2video',
+                        'replicate_OpenSora_text2video',
+                        'replicate_LaVie_text2video',
+                        'replicate_VideoCrafter2_text2video',
+                        'replicate_Stable-Video-Diffusion_text2video',
+                        ]
+save_names = []
+for name in model_names:
+    model_source, model_name, model_type = name.split("_")
+    save_names.append(model_name)
+
+for i, prompt in enumerate(str_list):
+    print("save the {} prompt".format(i+1))
+    # if i+1 < 97:
+    #     continue
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        futures = [executor.submit(generate_image_ig_api, prompt, model) for model in model_names]
+        results = [future.result() for future in futures]
+
+    root_dir = '/mnt/data/lizhikai/ksort_video_cache/'
+    save_dir = os.path.join(root_dir, f'cache_{i+1}')
+    if not os.path.exists(save_dir):
+        os.makedirs(save_dir, exist_ok=True)
+    with open(os.path.join(save_dir, "prompt.txt"), 'w', encoding='utf-8') as file:
+        file.write(prompt)
+
+    # 下载视频并保存
+    repeat_num = 5
+    for j, url in enumerate(results):
+        while 1:
+            time.sleep(1)
+            response = requests.get(url, stream=True)
+            if response.status_code == 200:
+                file_path = os.path.join(save_dir, f'{save_names[j]}.mp4')
+                with open(file_path, 'wb') as file:
+                    for chunk in response.iter_content(chunk_size=8192):
+                        file.write(chunk)
+                print(f"视频 {j} 已保存到 {file_path}")
+                break
+            else:
+                repeat_num = repeat_num - 1
+                if repeat_num == 0:
+                    print(f"视频 {j} 保存失败")
+                    # raise ValueError("Video request failed.")
+                continue

model/models/openai_api_models.py

@@ -53,7 +53,7 @@ def load_openai_model(model_name, model_type):
 
 
 if __name__ == "__main__":
-    pipe = load_openai_model('Dalle-2', 'text2image')
+    pipe = load_openai_model('Dalle-3', 'text2image')
     result = pipe(prompt='draw a tiger')
     print(result)
 

model/models/other_api_models.py

@@ -79,35 +79,37 @@ def load_other_model(model_name, model_type):
     return OtherModel(model_name, model_type)
 
 if __name__ == "__main__":
-
-    # pipe = load_other_model("Midjourney-v5.0", "text2image")
-    # result = pipe(prompt="a good girl")
-    # print(result)
-
     import http.client
     import json
-    key = os.environ.get('MIDJOURNEY_KEY')
-    prompt = "a good girl"
 
-    conn = http.client.HTTPSConnection("xdai.online")
-    payload = json.dumps({
-    "messages": [
-        {
-            "role": "user",
-            "content": "{}".format(prompt)
-        }
-    ],
-    "stream": True,
-    "model": "luma-video",
-    # "model": "pika-text-to-video",
-    })
-    headers = {
-        'Authorization': "Bearer {}".format(key),
-        'Content-Type': 'application/json'
-    }
-    conn.request("POST", "/v1/chat/completions", payload, headers)
-    res = conn.getresponse()
-    data = res.read()
-    info = data.decode("utf-8")
-    print(data.decode("utf-8"))
+    pipe = load_other_model("Midjourney-v6.0", "text2image")
+    result = pipe(prompt="An Impressionist illustration depicts a river winding through a meadow ")
+    print(result)
+    exit()
+
+
+    # key = os.environ.get('MIDJOURNEY_KEY')
+    # prompt = "a good girl"
+
+    # conn = http.client.HTTPSConnection("xdai.online")
+    # payload = json.dumps({
+    # "messages": [
+    #     {
+    #         "role": "user",
+    #         "content": "{}".format(prompt)
+    #     }
+    # ],
+    # "stream": True,
+    # "model": "luma-video",
+    # # "model": "pika-text-to-video",
+    # })
+    # headers = {
+    #     'Authorization': "Bearer {}".format(key),
+    #     'Content-Type': 'application/json'
+    # }
+    # conn.request("POST", "/v1/chat/completions", payload, headers)
+    # res = conn.getresponse()
+    # data = res.read()
+    # info = data.decode("utf-8")
+    # print(data.decode("utf-8"))
     

model/models/replicate_api_models.py

@@ -35,6 +35,9 @@ Replicate_MODEl_NAME_MAP = {
     "LaVie": "cjwbw/lavie:0bca850c4928b6c30052541fa002f24cbb4b677259c461dd041d271ba9d3c517",
     "VideoCrafter2": "lucataco/video-crafter:7757c5775e962c618053e7df4343052a21075676d6234e8ede5fa67c9e43bce0",
     "Stable-Video-Diffusion": "sunfjun/stable-video-diffusion:d68b6e09eedbac7a49e3d8644999d93579c386a083768235cabca88796d70d82",
+    "FLUX.1-schnell": "black-forest-labs/flux-schnell",
+    "FLUX.1-pro": "black-forest-labs/flux-pro",
+    "FLUX.1-dev": "black-forest-labs/flux-dev",
     }
 
 class ReplicateModel():
@@ -62,10 +65,11 @@ class ReplicateModel():
                 result_url = output[0]
             else:
                 result_url = output
-            print(result_url)
+            print(self.model_name, result_url)
             response = requests.get(result_url)
             result = Image.open(io.BytesIO(response.content))
             return result
+
         elif self.model_type == "text2video":
             assert "prompt" in kwargs, "prompt is required for text2image model"
             if self.model_name == "Zeroscope-v2-xl":
@@ -183,8 +187,10 @@ if __name__ == "__main__":
     import replicate
     import time
     import concurrent.futures 
-    import os
+    import os, shutil, re
     import requests
+    from moviepy.editor import VideoFileClip
+
     # model_name = 'replicate_zeroscope-v2-xl_text2video'
     # model_name = 'replicate_Damo-Text-to-Video_text2video'
     # model_name = 'replicate_Animate-Diff_text2video'
@@ -197,101 +203,131 @@ if __name__ == "__main__":
     # prompt = "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic"
     # result = pipe(prompt=prompt)
 
-    # url = "https://replicate.delivery/yhqm/ucuUNHBetmQVJiogeNiDpxJoccKxPvxzTXQPZO53azfHfwvMB/out.mp4"
-    # response = requests.get(url, stream=True)
-    # if response.status_code == 200:
-    #     file_path = os.path.join("/mnt/data/lizhikai/ksort_video_cache/", '1.mp4')
-    #     with open(file_path, 'wb') as file:
-    #         for chunk in response.iter_content(chunk_size=8192):
-    #             file.write(chunk)
-    #     print(f"视频 {j} 已保存到 {file_path}")
+    # # 文件复制
+    source_folder = '/mnt/data/lizhikai/ksort_video_cache/Pika-v1.0add/'
+    destination_folder = '/mnt/data/lizhikai/ksort_video_cache/Advance/'
 
-    file_path = '/home/lizhikai/webvid_prompt100.txt'
-    str_list = []
-    with open(file_path, 'r', encoding='utf-8') as file:
-        for line in file:
-            str_list.append(line.strip())
-            if len(str_list) == 100:
-                break
+    special_char = 'output'
+    for dirpath, dirnames, filenames in os.walk(source_folder):
+        for dirname in dirnames:
+            des_dirname = "output-"+dirname[-3:]
+            print(des_dirname)
+            if special_char in dirname:
+                model_name = ["Pika-v1.0"]
+                for name in model_name:
+                    source_file_path = os.path.join(source_folder, os.path.join(dirname, name+".mp4"))
+                    print(source_file_path)
+                    destination_file_path = os.path.join(destination_folder, os.path.join(des_dirname, name+".mp4"))
+                    print(destination_file_path)
+                    shutil.copy(source_file_path, destination_file_path)
 
-    def generate_image_ig_api(prompt, model_name):
-        model_source, model_name, model_type = model_name.split("_")
-        pipe = load_replicate_model(model_name, model_type)
-        result = pipe(prompt=prompt)
-        return result
-    model_names = ['replicate_Zeroscope-v2-xl_text2video',
-                        #    'replicate_Damo-Text-to-Video_text2video',
-                           'replicate_Animate-Diff_text2video',
-                           'replicate_OpenSora_text2video',
-                           'replicate_LaVie_text2video',
-                           'replicate_VideoCrafter2_text2video',
-                           'replicate_Stable-Video-Diffusion_text2video',
-                           ]
-    save_names = []
-    for name in model_names:
-        model_source, model_name, model_type = name.split("_")
-        save_names.append(model_name)
 
-    for i, prompt in enumerate(str_list):
-        print("save the {} prompt".format(i+1))
-        # if i+1 < 97:
-        #     continue
-        with concurrent.futures.ThreadPoolExecutor() as executor:
-            futures = [executor.submit(generate_image_ig_api, prompt, model) for model in model_names]
-            results = [future.result() for future in futures]
+    # 视频裁剪
+    # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Runway-Gen3/'
+    # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Runway-Gen2/'
+    # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Pika-Beta/'
+    # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Pika-v1/'
+    # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Sora/'
+    # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Pika-v1.0add/'
+    # special_char = 'output'
+    # num = 0
+    # for dirpath, dirnames, filenames in os.walk(root_dir):
+    #     for dirname in dirnames:
+    #         # 如果文件夹名称中包含指定的特殊字符
+    #         if special_char in dirname:
+    #             num = num+1
+    #             print(num)
+    #             if num < 0:
+    #                 continue
+    #             video_path = os.path.join(root_dir, (os.path.join(dirname, f"{dirname}.mp4")))
+    #             out_video_path = os.path.join(root_dir, (os.path.join(dirname, f"Pika-v1.0.mp4")))
+    #             print(video_path)
+    #             print(out_video_path)
 
-        root_dir = '/mnt/data/lizhikai/ksort_video_cache/'
-        save_dir = os.path.join(root_dir, f'cache_{i+1}')
-        if not os.path.exists(save_dir):
-            os.makedirs(save_dir, exist_ok=True)
-        with open(os.path.join(save_dir, "prompt.txt"), 'w', encoding='utf-8') as file:
-            file.write(prompt)
+    #             video = VideoFileClip(video_path)
+    #             width, height = video.size
+    #             center_x, center_y = width // 2, height // 2
+    #             new_width, new_height = 512, 512
+    #             cropped_video = video.crop(x_center=center_x, y_center=center_y, width=min(width, height), height=min(width, height))
+    #             resized_video = cropped_video.resize(newsize=(new_width, new_height))
+    #             resized_video.write_videofile(out_video_path, codec='libx264', fps=video.fps)
+    #             os.remove(video_path)
 
-        # 下载视频并保存
-        repeat_num = 5
-        for j, url in enumerate(results):
-            while 1:
-                time.sleep(1)
-                response = requests.get(url, stream=True)
-                if response.status_code == 200:
-                    file_path = os.path.join(save_dir, f'{save_names[j]}.mp4')
-                    with open(file_path, 'wb') as file:
-                        for chunk in response.iter_content(chunk_size=8192):
-                            file.write(chunk)
-                    print(f"视频 {j} 已保存到 {file_path}")
-                    break
-                else:
-                    repeat_num = repeat_num - 1
-                    if repeat_num == 0:
-                        print(f"视频 {j} 保存失败")
-                        # raise ValueError("Video request failed.")
-                    continue
 
 
-    # input = {
-    #     "seed": 1,
-    #     "width": 512,
-    #     "height": 512,
-    #     "grid_size": 1,
-    #     "prompt": "anime astronaut riding a horse on mars"
-    # }
+    # file_path = '/home/lizhikai/webvid_prompt100.txt'
+    # str_list = []
+    # with open(file_path, 'r', encoding='utf-8') as file:
+    #     for line in file:
+    #         str_list.append(line.strip())
+    #         if len(str_list) == 100:
+    #             break
 
+    # 生成代码
+    # def generate_image_ig_api(prompt, model_name):
+    #     model_source, model_name, model_type = model_name.split("_")
+    #     pipe = load_replicate_model(model_name, model_type)
+    #     result = pipe(prompt=prompt)
+    #     return result
+    # model_names = ['replicate_Zeroscope-v2-xl_text2video',
+    #                     #    'replicate_Damo-Text-to-Video_text2video',
+    #                        'replicate_Animate-Diff_text2video',
+    #                        'replicate_OpenSora_text2video',
+    #                        'replicate_LaVie_text2video',
+    #                        'replicate_VideoCrafter2_text2video',
+    #                        'replicate_Stable-Video-Diffusion_text2video',
+    #                        ]
+    # save_names = []
+    # for name in model_names:
+    #     model_source, model_name, model_type = name.split("_")
+    #     save_names.append(model_name)
 
-    # for name, address in Replicate_MODEl_NAME_MAP.items():
-    #     print('*'*50)
-    #     print(name)
+    # # 遍历根目录及其子目录
+    # # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Runway-Gen3/'
+    # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Runway-Gen2/'
+    # # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Pika-Beta/'
+    # # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Pika-v1/'
+    # # root_dir = '/mnt/data/lizhikai/ksort_video_cache/Sora/'
+    # special_char = 'output'
+    # num = 0
+    # for dirpath, dirnames, filenames in os.walk(root_dir):
+    #     for dirname in dirnames:
+    #         # 如果文件夹名称中包含指定的特殊字符
+    #         if special_char in dirname:
+    #             num = num+1
+    #             print(num)
+    #             if num < 0:
+    #                 continue
+    #             str_list = []
+    #             prompt_path = os.path.join(root_dir, (os.path.join(dirname, "prompt.txt")))
+    #             print(prompt_path)
+    #             with open(prompt_path, 'r', encoding='utf-8') as file:
+    #                 for line in file:
+    #                     str_list.append(line.strip())
+    #             prompt = str_list[0]
+    #             print(prompt)
 
-    #     t1 = time.time()
-    #     output = replicate.run(
-    #         address,
-    #         input=input
-    #     )
-    #     # for item in output:
-    #     #     print(item)
-    #     print(output)
+    #             with concurrent.futures.ThreadPoolExecutor() as executor:
+    #                 futures = [executor.submit(generate_image_ig_api, prompt, model) for model in model_names]
+    #                 results = [future.result() for future in futures]
 
+    #             # 下载视频并保存
+    #             repeat_num = 5
+    #             for j, url in enumerate(results):
+    #                 while 1:
+    #                     time.sleep(1)
+    #                     response = requests.get(url, stream=True)
+    #                     if response.status_code == 200:
+    #                         file_path = os.path.join(os.path.join(root_dir, dirname), f'{save_names[j]}.mp4')
+    #                         with open(file_path, 'wb') as file:
+    #                             for chunk in response.iter_content(chunk_size=8192):
+    #                                 file.write(chunk)
+    #                         print(f"视频 {j} 已保存到 {file_path}")
+    #                         break
+    #                     else:
+    #                         repeat_num = repeat_num - 1
+    #                         if repeat_num == 0:
+    #                             print(f"视频 {j} 保存失败")
+    #                             # raise ValueError("Video request failed.")
+    #                         continue
 
-    #     t2 = time.time()
-    #     print(t2-t1)
-    #     print('*'*50)
-    

serve/Ksort.py

@@ -167,7 +167,7 @@ def vote_ssh_submit(states, textbox, rank, user_name, user_institution):
     from .update_skill import update_skill
     update_skill(rank, [x.model_name for x in states])
 
-def vote_video_ssh_submit(states, textbox, prompt_num, rank, user_name, user_institution):
+def vote_video_ssh_submit(states, textbox, prompt_path, rank, user_name, user_institution):
     conv_id = states[0].conv_id
     output_dir = create_remote_directory(conv_id, video=True)
 
@@ -175,7 +175,7 @@ def vote_video_ssh_submit(states, textbox, prompt_num, rank, user_name, user_ins
         "models_name": [x.model_name for x in states],
         "video_rank": [x for x in rank],
         "prompt": [textbox],
-        "prompt_num": [prompt_num],
+        "prompt_path": [prompt_path],
         "video_path": [x.output for x in states],
         "user_info": {"name": [user_name], "institution": [user_institution]}, 
     }
@@ -206,9 +206,9 @@ def submit_response_igm(
             gr.Markdown(state3.model_name, visible=True)
             ) + (disable_btn,)
 def submit_response_vg(
-    state0, state1, state2, state3, model_selector0, model_selector1, model_selector2, model_selector3, textbox, prompt_num, rank, user_name, user_institution, request: gr.Request
+    state0, state1, state2, state3, model_selector0, model_selector1, model_selector2, model_selector3, textbox, prompt_path, rank, user_name, user_institution, request: gr.Request
 ):
-    vote_video_ssh_submit([state0, state1, state2, state3], textbox, prompt_num, rank, user_name, user_institution)
+    vote_video_ssh_submit([state0, state1, state2, state3], textbox, prompt_path, rank, user_name, user_institution)
     if model_selector0 == "":
         return (disable_btn,) * 6 + (
             gr.Markdown(f"### Model A: {state0.model_name.split('_')[1]}", visible=True),
@@ -247,11 +247,11 @@ def submit_response_rank_igm(
     else:
         return (enable_btn,) * 16 + (enable_btn,) * 3 + ("wrong",) + (gr.Markdown("", visible=False),) * 4
 def submit_response_rank_vg(
-    state0, state1, state2, state3, model_selector0, model_selector1, model_selector2, model_selector3, textbox, prompt_num, rank, right_vote_text, user_name, user_institution, request: gr.Request
+    state0, state1, state2, state3, model_selector0, model_selector1, model_selector2, model_selector3, textbox, prompt_path, rank, right_vote_text, user_name, user_institution, request: gr.Request
 ):
     print(rank)
     if right_vote_text == "right":
-        vote_video_ssh_submit([state0, state1, state2, state3], textbox, prompt_num, rank, user_name, user_institution)
+        vote_video_ssh_submit([state0, state1, state2, state3], textbox, prompt_path, rank, user_name, user_institution)
         if model_selector0 == "":
             return (disable_btn,) * 16 + (disable_btn,) * 3 + ("wrong",) + (
                 gr.Markdown(f"### Model A: {state0.model_name.split('_')[1]}", visible=True),

serve/gradio_web.py

@@ -48,11 +48,11 @@ def set_ssh():
 
 def build_side_by_side_ui_anony(models):
     notice_markdown = """
-# ⚔️  K-Sort-Arena (Text-to-Image) ⚔️
+# ⚔️  K-Sort Arena (Text-to-Image Generation) ⚔️
 ## 📜 Rules
-- Input prompt to Four anonymous models (e.g., SD, SDXL, OpenJourney in Text-guided Image Generation Model) and vote on the outputs!
-- Two voting mode: Rand Mode and Best Mode. Please feel free to switch them!
-- Users are encouraged to make evaluations based on subjective preferences. As an aid, they can refer to the following criteria: Alignment (50%) + Aesthetics (50%).
+- Input a prompt for four anonymized models (e.g., SD, SDXL, OpenJourney for Text-guided Image Generation) and vote on their outputs.
+- Two voting modes available: Rank Mode and Best Mode. Switch freely between modes. Please note that ties are always allowed. In ranking mode, users can input rankings like 1 3 3 1. Any invalid rankings, such as 1 4 4 1, will be automatically corrected during post-processing.
+- Users are encouraged to make evaluations based on subjective preferences. Evaluation criteria: Alignment (50%) + Aesthetics (50%).
     - Alignment includes: Entity Matching (30%) + Style Matching (20%);
     - Aesthetics includes: Photorealism (30%) + Light and Shadow (10%) + Absence of Artifacts (10%).
 
@@ -197,7 +197,7 @@ def build_side_by_side_ui_anony(models):
     with gr.Row():
         vote_textbox = gr.Textbox(
             show_label=False,
-            placeholder="👉 Enter your rank",
+            placeholder="👉 Enter your rank (you can use buttons above, or directly type here, e.g. 1 2 3 4)",
             container=True,
             elem_id="input_box",
             visible=False,
@@ -222,7 +222,7 @@ def build_side_by_side_ui_anony(models):
         # share_btn = gr.Button(value="📷  Share")
     with gr.Blocks(): 
         with gr.Row(elem_id="centered-text"): # 
-            user_info = gr.Markdown("User information", visible=True, elem_id="centered-text") #, elem_id="centered-text"
+            user_info = gr.Markdown("User information (to appear on the contributor leaderboard)", visible=True, elem_id="centered-text") #, elem_id="centered-text"
             # with gr.Blocks(): 
             # name = gr.Markdown("Name", visible=True)
             user_name = gr.Textbox(show_label=False,placeholder="👉 Enter your name (optional)", elem_classes="custom-width")

serve/gradio_web_video.py

@@ -10,7 +10,7 @@ from .vote_utils import (
     tievote_last_response_igm as tievote_last_response,
     bothbad_vote_last_response_igm as bothbad_vote_last_response,
     share_click_igm as share_click,
-    generate_igv_annoy,
+    generate_vg_annoy,
     share_js
 )
 from .Ksort import (
@@ -32,19 +32,20 @@ from .Ksort import (
 
 from functools import partial
 from serve.constants import SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD
-from serve.upload import get_random_webvid_prompt, create_ssh_client
+from serve.upload import create_ssh_client
 from serve.update_skill import create_ssh_skill_client
 from model.matchmaker import create_ssh_matchmaker_client
 
 def build_side_by_side_video_ui_anony(models):
     notice_markdown = """
-# ⚔️  K-Sort-Arena (Text-to-Video) ⚔️
+# ⚔️  K-Sort Arena (Text-to-Video Generation) ⚔️
 ## 📜 Rules
-- Input prompt to Four anonymous models (e.g., OpenSora, StableVideoDiffusion in Text-guided Video Generation Model) and vote on the outputs!
-- Two voting mode: Rand Mode and Best Mode. Please feel free to switch them!
-- Users are encouraged to make evaluations based on subjective preferences. As an aid, they can refer to the following criteria: Alignment (50%) + Aesthetics (50%).
-    - Alignment includes: Video Content Matching (30%) + Inter-frame Consistency (20%);
+- Input a prompt for four anonymized models (e.g., Sora, Pika, OpenSora, StableVideoDiffusion for Text-guided Video Generation) and vote on their outputs.
+- Two voting modes available: Rank Mode and Best Mode. Switch freely between modes. Please note that ties are always allowed. In ranking mode, users can input rankings like 1 3 3 1. Any invalid rankings, such as 1 4 4 1, will be automatically corrected during post-processing.
+- Users are encouraged to make evaluations based on subjective preferences. Evaluation criteria: Alignment (50%) + Aesthetics (50%).
+    - Alignment includes:  Video Content Matching (20%) + Movement Matching (15%) + Inter-frame Consistency (15%);
     - Aesthetics includes: Photorealism (30%) + Physical Correctness (10%) + Absence of Artifacts (10%).
+- Users can hover over the videos to see a replay button and click to zoom out to full-screen.
 
 ## 👇 Generating now!
 
@@ -57,7 +58,7 @@ def build_side_by_side_video_ui_anony(models):
     state2 = gr.State()
     state3 = gr.State()
 
-    gen_func = partial(generate_igv_annoy, models.generate_video_ig_parallel_anony)
+    gen_func = partial(generate_vg_annoy, models.generate_video_vg_parallel_anony)
     # gen_func_random = partial(generate_igm_annoy_museum, models.generate_image_ig_museum_parallel_anony)
     
     gr.Markdown(notice_markdown, elem_id="notice_markdown")
@@ -187,7 +188,7 @@ def build_side_by_side_video_ui_anony(models):
     with gr.Row():
         vote_textbox = gr.Textbox(
             show_label=False,
-            placeholder="👉 Enter your rank",
+            placeholder="👉 Enter your rank (you can use buttons above, or directly type here, e.g. 1 2 3 4)",
             container=True,
             elem_id="input_box",
             visible=False,
@@ -198,19 +199,19 @@ def build_side_by_side_video_ui_anony(models):
     with gr.Row():
         textbox = gr.Textbox(
             show_label=False,
-            placeholder="👉 Generate the rand prompt and Send",
+            placeholder="👉 Generate a random prompt and send to video generation",
             container=True,
             elem_id="input_box",
             interactive=False,
         )
 
-        send_btn = gr.Button(value="Send", variant="primary", scale=0, elem_id="btnblue")
-        draw_btn = gr.Button(value="🎲 Random Prompt", variant="primary", scale=0, elem_id="btnblue")
+        send_btn = gr.Button(value="Send", variant="primary", scale=0, elem_id="btnblue", visible=False, interactive=False)
+        draw_btn = gr.Button(value="🎲 Random Sample", variant="primary", scale=0, elem_id="btnblue")
     with gr.Row():
         clear_btn = gr.Button(value="🎲 New Round", interactive=False)
     with gr.Blocks(): 
         with gr.Row(elem_id="centered-text"): # 
-            user_info = gr.Markdown("User information", visible=True, elem_id="centered-text") #, elem_id="centered-text"
+            user_info = gr.Markdown("User information (to appear on the contributor leaderboard)", visible=True, elem_id="centered-text") #, elem_id="centered-text"
             # with gr.Blocks(): 
             # name = gr.Markdown("Name", visible=True)
             user_name = gr.Textbox(show_label=False,placeholder="👉 Enter your name (optional)", elem_classes="custom-width")
@@ -218,7 +219,7 @@ def build_side_by_side_video_ui_anony(models):
             # institution = gr.Markdown("Institution", visible=True)
             user_institution = gr.Textbox(show_label=False,placeholder="👉 Enter your affiliation (optional)", elem_classes="custom-width")
 
-    prompt_num = gr.Number(value=0, visible=False, interactive=False) # record the num of prompt
+    prompt_path = gr.Textbox(value="", visible=False, interactive=False)
     #gr.Markdown(acknowledgment_md, elem_id="ack_markdown")
     example1_text = gr.Textbox(value="Chef with recipe book watching young cook preparing dish in the kitchen.", visible=False, interactive=False)
     example2_text = gr.Textbox(value="A baker turns freshly baked loaves of sourdough bread.", visible=False, interactive=False)
@@ -270,15 +271,31 @@ def build_side_by_side_video_ui_anony(models):
     vote_mode = gr.Textbox(value="Rank", visible=False, interactive=False)
     right_vote_text = gr.Textbox(value="wrong", visible=False, interactive=False)
 
-    send_btn.click(
+    # send_btn.click(
+    #     disable_video_order_buttons,
+    #     inputs=[textbox, example1_text, example2_text, example3_text, example4_text],
+    #     outputs=[textbox, send_btn, draw_btn, clear_btn, prompt_path]
+    # ).then(
+    #     gen_func, # 修改为调取函数而不是生成函数
+    #     inputs=[state0, state1, state2, state3, textbox, prompt_path, 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, \
+    #              model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
+    #     api_name="send_btn_annony"
+    # ).then(
+    #     enable_vote_mode_buttons,
+    #     inputs=[vote_mode, textbox],
+    #     outputs=vote_order_list
+    # )
+
+    draw_btn.click(
         disable_video_order_buttons,
-        inputs=[textbox, example1_text, example2_text, example3_text, example4_text],
-        outputs=[textbox, send_btn, draw_btn, clear_btn, prompt_num]
+        inputs=[],
+        outputs=[textbox, send_btn, draw_btn, clear_btn]
     ).then(
-        gen_func, # 修改为调取函数而不是生成函数
-        inputs=[state0, state1, state2, state3, textbox, prompt_num, model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
+        gen_func, 
+        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, \
-                 model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
+                 model_selector_left, model_selector_left1, model_selector_right, model_selector_right1, textbox, prompt_path],
         api_name="send_btn_annony"
     ).then(
         enable_vote_mode_buttons,
@@ -286,13 +303,6 @@ def build_side_by_side_video_ui_anony(models):
         outputs=vote_order_list
     )
 
-    draw_btn.click(
-        get_random_webvid_prompt,
-        inputs=None, 
-        outputs=[prompt_num, textbox],
-        api_name="draw_btn_annony"
-    )
-
     clear_btn.click(
         clear_history_side_by_side_anony, 
         inputs=None, 
@@ -336,7 +346,7 @@ def build_side_by_side_video_ui_anony(models):
         outputs=[vote_textbox, right_vote_text, rank]
     ).then(
         submit_response_rank_vg,
-        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_num, rank, right_vote_text, user_name, user_institution],
+        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_path, rank, right_vote_text, user_name, user_institution],
         outputs=[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, right_vote_text, \
                     model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
@@ -354,7 +364,7 @@ def build_side_by_side_video_ui_anony(models):
         outputs=[vote_textbox, right_vote_text, rank]
     ).then(
         submit_response_rank_vg,
-        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_num, rank, right_vote_text, user_name, user_institution],
+        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_path, rank, right_vote_text, user_name, user_institution],
         outputs=[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, right_vote_text, \
                     model_selector_left, model_selector_left1, model_selector_right, model_selector_right1],
@@ -364,35 +374,35 @@ def build_side_by_side_video_ui_anony(models):
 
     leftvote_btn.click(
         submit_response_vg,
-        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_num, rankA, user_name, user_institution],
+        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_path, rankA, user_name, user_institution],
         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_vg,
-        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_num, rankB, user_name, user_institution],
+        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_path, rankB, user_name, user_institution],
         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_vg,
-        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_num, rankC, user_name, user_institution],
+        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_path, rankC, user_name, user_institution],
         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_vg,
-        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_num, rankD, user_name, user_institution],
+        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_path, rankD, user_name, user_institution],
         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_vg,
-        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_num, rankTie, user_name, user_institution],
+        inputs=[state0, state1, state2, state3, dummy_left_model, dummy_left1_model, dummy_right_model, dummy_right1_model, textbox, prompt_path, rankTie, user_name, user_institution],
         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]
@@ -411,6 +421,7 @@ def build_side_by_side_video_ui_anony(models):
         inputs = [rank],
         outputs = [vote_textbox]
     )
+
     A2_btn.click(
         reset_btn_rank, 
         inputs=[window1_text, rank, A2_btn, vote_level], 

serve/leaderboard.py

@@ -36,13 +36,13 @@ from datetime import datetime
 
 def make_leaderboard_md():
     leaderboard_md = f"""
-# 🏆 K-Sort-Arena Leaderboard (Text-to-Image)
+# 🏆 K-Sort Arena Leaderboard (Text-to-Image Generation)
 """
     return leaderboard_md
 
 def make_leaderboard_video_md():
     leaderboard_md = f"""
-# 🏆 K-Sort-Arena Leaderboard (Text-to-Video)
+# 🏆 K-Sort Arena Leaderboard (Text-to-Video Generation)
 """
     return leaderboard_md
 
@@ -55,15 +55,15 @@ def make_arena_leaderboard_md(total_models, total_votes, last_updated):
     # last_updated = last_updated.strftime("%Y-%m-%d")
 
     leaderboard_md = f"""
-Total #models: **{total_models}** (anonymous). Total #votes: **{total_votes}** (Equivalent to **{total_votes*6}** votes for one-on-one games). 
-\n Last updated: {last_updated}.
+Total models: **{total_models}** (anonymized), Total votes: **{total_votes}** (equivalent to **{total_votes*6}** pairwise comparisons)
+\n Last updated: {last_updated}
 """
 
     return leaderboard_md
 
 
 def make_disclaimer_md():
-    disclaimer_md = f'''
+    disclaimer_md = '''
         <div id="modal" style="display:none; position:fixed; top:50%; left:50%; transform:translate(-50%, -50%); padding:20px; background:white; box-shadow:0 0 10px rgba(0,0,0,0.5); z-index:1000;">
             <p style="font-size:24px;"><strong>Disclaimer</strong></p>
             <p style="font-size:18px;"><b>Purpose and Scope</b></b></p>
@@ -85,12 +85,10 @@ def make_disclaimer_md():
             <p><b>For any questions or to report issues, please contact us at [email protected].</b></p>
         </div>
         <div id="overlay" style="display:none; position:fixed; top:0; left:0; width:100%; height:100%; background:rgba(0,0,0,0.5); z-index:999;" onclick="document.getElementById('modal').style.display='none'; document.getElementById('overlay').style.display='none'"></div>
-        <p> ⚠️ This platform is designed for academic usage, for details please refer to <a href="#" id="open_link" onclick="document.getElementById('modal').style.display='block'; document.getElementById('overlay').style.display='block'">disclaimer</a>.</p>
+        <p> This platform is designed for academic usage, for details please refer to <a href="#" id="open_link" onclick="document.getElementById('modal').style.display='block'; document.getElementById('overlay').style.display='block'">disclaimer</a>.</p>
         '''
-    
     return disclaimer_md
 
-
 def make_arena_leaderboard_data(results):
     import pandas as pd
     df = pd.DataFrame(results)
@@ -106,19 +104,20 @@ def build_leaderboard_tab(score_result_file = 'sorted_score_list.json'):
 
     md = make_leaderboard_md()
     md_1 = gr.Markdown(md, elem_id="leaderboard_markdown")
-    gr.HTML(make_disclaimer_md)
 
-    with gr.Tab("Arena Score", id=0):
-        md = make_arena_leaderboard_md(total_models, total_votes, last_updated)
-        gr.Markdown(md, elem_id="leaderboard_markdown")
-        md = make_arena_leaderboard_data(score_results)
-        gr.Dataframe(md)
+    # with gr.Tab("Arena Score", id=0):
+    md = make_arena_leaderboard_md(total_models, total_votes, last_updated)
+    gr.Markdown(md, elem_id="leaderboard_markdown")
+    md = make_arena_leaderboard_data(score_results)
+    gr.Dataframe(md)
     
     gr.Markdown(
-                """ ## The leaderboard is updated frequently and continues to incorporate new models. 
+                """ ### The leaderboard is regularly updated and continuously incorporates new models. 
                 """,
                 elem_id="leaderboard_markdown",
             )
+    with gr.Blocks():
+        gr.HTML(make_disclaimer_md)
     from .utils import acknowledgment_md, html_code
     with gr.Blocks():
         gr.Markdown(acknowledgment_md)
@@ -134,19 +133,50 @@ def build_leaderboard_video_tab(score_result_file = 'sorted_score_list_video.jso
 
     md = make_leaderboard_video_md()
     md_1 = gr.Markdown(md, elem_id="leaderboard_markdown")
-    gr.HTML(make_disclaimer_md)
+    # with gr.Blocks():
+    #     gr.HTML(make_disclaimer_md)
+
+    # with gr.Tab("Arena Score", id=0):
+    md = make_arena_leaderboard_md(total_models, total_votes, last_updated)
+    gr.Markdown(md, elem_id="leaderboard_markdown")
+    md = make_arena_leaderboard_data(score_results)
+    gr.Dataframe(md)
 
-    with gr.Tab("Arena Score", id=0):
-        md = make_arena_leaderboard_md(total_models, total_votes, last_updated)
-        gr.Markdown(md, elem_id="leaderboard_markdown")
-        md = make_arena_leaderboard_data(score_results)
-        gr.Dataframe(md)
+    notice_markdown_sora = """
+    - Note: As Sora's video generation function is not publicly available, we used sample videos from their official website. This may lead to a biased assessment of Sora's capabilities, as these samples likely represent Sora's best outputs. Therefore, Sora's position on our leaderboard should be considered as its upper bound. We are working on methods to conduct more comprehensive and fair comparisons in the future.
+    """
+
+    gr.Markdown(notice_markdown_sora, elem_id="notice_markdown_sora")
     
     gr.Markdown(
-                """ ## The leaderboard is updated frequently and continues to incorporate new models. 
+                """ ### The leaderboard is regularly updated and continuously incorporates new models. 
                 """,
                 elem_id="leaderboard_markdown",
             )
     from .utils import acknowledgment_md, html_code
     with gr.Blocks():
         gr.Markdown(acknowledgment_md)
+
+
+def build_leaderboard_contributor(file = 'contributor.json'):
+    md = f"""
+# 🏆 Contributor Leaderboard
+The submission of user information is entirely optional. This information is used solely for contribution statistics. We respect and safeguard users' privacy choices. 
+To maintain a clean and concise leaderboard, please ensure consistency in submitted names and affiliations. For example, use 'Berkeley' consistently rather than alternating with 'UC Berkeley'.
+"""
+    md_1 = gr.Markdown(md, elem_id="leaderboard_markdown")
+
+    # md = make_arena_leaderboard_md(total_models, total_votes, last_updated)
+    # gr.Markdown(md, elem_id="leaderboard_markdown")
+
+    with open(file, "r") as json_file:
+        data = json.load(json_file)
+    score_results = data["contributor"]
+    md = make_arena_leaderboard_data(score_results)
+    gr.Dataframe(md)
+    
+    gr.Markdown(
+                """ ### The leaderboard is regularly updated. 
+                """,
+                elem_id="leaderboard_markdown",
+            )

serve/upload.py

@@ -1,6 +1,6 @@
 import paramiko
 import numpy as np
-import io, os
+import io, os, stat
 import gradio as gr
 from PIL import Image
 import requests
@@ -78,16 +78,75 @@ def get_random_mscoco_prompt():
 
     random_line = random.choice(lines).strip()
     return random_line
-def get_random_webvid_prompt():
 
-    file_path = './webvid_prompt.txt'
-    with open(file_path, 'r', encoding='utf-8') as file:
-        lines = file.readlines()
-    line_number = random.randint(0, len(lines) - 1)
-    print(line_number + 1)
-    random_line = lines[line_number].strip()
-    print(random_line)
-    return line_number + 1, random_line
+def get_random_video_prompt(root_dir):
+    subdirs = [os.path.join(root_dir, d) for d in os.listdir(root_dir) if os.path.isdir(os.path.join(root_dir, d))]
+    if not subdirs:
+        raise NotImplementedError
+    selected_dir = random.choice(subdirs)
+    prompt_path = os.path.join(selected_dir, 'prompt.txt')
+
+    if os.path.exists(prompt_path):
+        str_list = []
+        with open(prompt_path, 'r', encoding='utf-8') as file:
+            for line in file:
+                str_list.append(line.strip())
+        prompt = str_list[0]
+    else:
+        raise NotImplementedError
+    return selected_dir, prompt
+
+def get_ssh_random_video_prompt(root_dir, local_dir, model_names):
+    def is_directory(sftp, path):
+        try:
+            return stat.S_ISDIR(sftp.stat(path).st_mode)
+        except IOError:
+            return False
+    ssh = paramiko.SSHClient()
+    ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
+    try:
+        ssh.connect(SSH_SERVER, SSH_PORT, SSH_USER, SSH_PASSWORD)
+        sftp = ssh.open_sftp()
+
+        remote_subdirs = sftp.listdir(root_dir)
+        remote_subdirs = [d for d in remote_subdirs if is_directory(sftp, os.path.join(root_dir, d))]
+        
+        if not remote_subdirs:
+            print(f"No subdirectories found in {root_dir}")
+            raise NotImplementedError
+
+        chosen_subdir = random.choice(remote_subdirs)
+        chosen_subdir_path = os.path.join(root_dir, chosen_subdir)
+        print(f"Chosen subdirectory: {chosen_subdir_path}")
+        
+        prompt_path = 'prompt.txt'
+        results = [prompt_path]
+        for name in model_names:
+            model_source, model_name, model_type = name.split("_")
+            video_path = f'{model_name}.mp4'
+            print(video_path)
+            results.append(video_path)
+
+        local_path = []
+        for tar_file in results:
+            remote_file_path = os.path.join(chosen_subdir_path, tar_file)
+            local_file_path = os.path.join(local_dir, tar_file)
+            sftp.get(remote_file_path, local_file_path)
+            local_path.append(local_file_path)
+            print(f"Downloaded {remote_file_path} to {local_file_path}")
+
+        if os.path.exists(local_path[0]):
+            str_list = []
+            with open(local_path[0], 'r', encoding='utf-8') as file:
+                for line in file:
+                    str_list.append(line.strip())
+            prompt = str_list[0]
+        else:
+            raise NotImplementedError
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        raise NotImplementedError
+    return prompt, local_path[1:]
 
 def create_remote_directory(remote_directory, video=False):
     global ssh_client

serve/utils.py

@@ -209,20 +209,8 @@ def disable_order_buttons(textbox, video=False):
         return (gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True))
     else:
         return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True))
-def disable_video_order_buttons(textbox, example1_text, example2_text, example3_text, example4_text):
-    example_list = [example1_text, example2_text, example3_text, example4_text]
-    if not textbox.strip():
-        return (gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(visible=False))
-    else:
-        if textbox == example_list[0]:
-            return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True), gr.update(value=8))
-        elif textbox == example_list[1]:
-            return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True), gr.update(value=3))
-        elif textbox == example_list[2]:
-            return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True), gr.update(value=93))
-        elif textbox == example_list[3]:
-            return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True), gr.update(value=84))
-        return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True), gr.update(visible=False))
+def disable_video_order_buttons():
+    return (gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=True))
 
 def clear_history():
     return None, "", None

serve/vote_utils.py

@@ -871,9 +871,8 @@ def generate_igm_annoy(gen_func, state0, state1, state2, state3, text, model_nam
     #         save_any_image(state.output, f)
     #     save_image_file_on_log_server(output_file)
 
-def generate_igv_annoy(gen_func, state0, state1, state2, state3, text, prompt_num, model_name0, model_name1, model_name2, model_name3, request: gr.Request):
-    if not text.strip():
-        return (gr.update(visible=False),) * 16
+def generate_vg_annoy(gen_func, state0, state1, state2, state3, model_name0, model_name1, model_name2, model_name3, request: gr.Request):
+
     if state0 is None:
         state0 = ImageStateIG(model_name0)
     if state1 is None:
@@ -892,8 +891,8 @@ def generate_igv_annoy(gen_func, state0, state1, state2, state3, text, prompt_nu
     model_name2 = ""
     model_name3 = ""
 
-    generated_video0, generated_video1, generated_video2, generated_video3, model_name0, model_name1, model_name2, model_name3 \
-        = gen_func(prompt_num, model_name0, model_name1, model_name2, model_name3)
+    generated_video0, generated_video1, generated_video2, generated_video3, model_name0, model_name1, model_name2, model_name3, text, prompt_path \
+        = gen_func(model_name0, model_name1, model_name2, model_name3)
     state0.prompt = text
     state1.prompt = text
     state2.prompt = text
@@ -912,7 +911,8 @@ def generate_igv_annoy(gen_func, state0, state1, state2, state3, text, prompt_nu
     yield state0, state1, state2, state3, generated_video0, generated_video1, generated_video2, generated_video3, \
         generated_video0, generated_video1, generated_video2, generated_video3, \
         gr.Markdown(f"### Model A: {model_name0}", visible=False), gr.Markdown(f"### Model B: {model_name1}", visible=False), \
-        gr.Markdown(f"### Model C: {model_name2}", visible=False), gr.Markdown(f"### Model D: {model_name3}", visible=False)
+        gr.Markdown(f"### Model C: {model_name2}", visible=False), gr.Markdown(f"### Model D: {model_name3}", visible=False), \
+        text, prompt_path
             
 
 def generate_igm_annoy_museum(gen_func, state0, state1, state2, state3, model_name0, model_name1, model_name2, model_name3, request: gr.Request):

sorted_score_list.json

@@ -1,196 +1,217 @@
 {
-    "total_models": 27,
-    "total_votes": 965,
-    "last_updated": "2024-07-29",
+    "total_models": 30,
+    "total_votes": 966,
+    "last_updated": "2024-08-12",
     "sorted_score_list": [
         {
-            "Rank": 0,
+            "Rank": 1,
             "\ud83e\udd16 Model": "Midjourney-v6.0",
             "\u2b50 Score (\u03bc/\u03c3)": "32.36 (34.75/0.796)",
             "\ud83d\uddf3\ufe0f Votes": 425.0,
-            "Organization": "Midjourney"
+            "\ud83c\udfdb\ufe0f Organization": "Midjourney"
         },
         {
-            "Rank": 1,
+            "Rank": 2,
             "\ud83e\udd16 Model": "Midjourney-v5.0",
             "\u2b50 Score (\u03bc/\u03c3)": "31.36 (33.74/0.791)",
             "\ud83d\uddf3\ufe0f Votes": 438.0,
-            "Organization": "Midjourney"
+            "\ud83c\udfdb\ufe0f Organization": "Midjourney"
         },
         {
-            "Rank": 2,
+            "Rank": 3,
             "\ud83e\udd16 Model": "SD-v3.0",
             "\u2b50 Score (\u03bc/\u03c3)": "29.33 (31.7/0.788)",
             "\ud83d\uddf3\ufe0f Votes": 426.0,
-            "Organization": "Stability AI"
+            "\ud83c\udfdb\ufe0f Organization": "Stability AI"
         },
         {
-            "Rank": 3,
+            "Rank": 4,
             "\ud83e\udd16 Model": "Dalle-3",
             "\u2b50 Score (\u03bc/\u03c3)": "28.55 (30.94/0.795)",
             "\ud83d\uddf3\ufe0f Votes": 427.0,
-            "Organization": "OpenAI"
-        },
-        {
-            "Rank": 4,
-            "\ud83e\udd16 Model": "Pixart-Sigma",
-            "\u2b50 Score (\u03bc/\u03c3)": "26.33 (28.7/0.79)",
-            "\ud83d\uddf3\ufe0f Votes": 441.0,
-            "Organization": "PixArt-Alpha"
+            "\ud83c\udfdb\ufe0f Organization": "OpenAI"
         },
         {
             "Rank": 5,
             "\ud83e\udd16 Model": "Proteus-v0.2",
-            "\u2b50 Score (\u03bc/\u03c3)": "26.15 (28.52/0.79)",
-            "\ud83d\uddf3\ufe0f Votes": 423.0,
-            "Organization": "DataAutoGPT3"
+            "\u2b50 Score (\u03bc/\u03c3)": "26.42 (28.78/0.789)",
+            "\ud83d\uddf3\ufe0f Votes": 426.0,
+            "\ud83c\udfdb\ufe0f Organization": "DataAutoGPT3"
         },
         {
             "Rank": 6,
-            "\ud83e\udd16 Model": "Dreamshaper-xl",
-            "\u2b50 Score (\u03bc/\u03c3)": "25.66 (28.02/0.786)",
-            "\ud83d\uddf3\ufe0f Votes": 434.0,
-            "Organization": "Lykon"
+            "\ud83e\udd16 Model": "Pixart-Sigma",
+            "\u2b50 Score (\u03bc/\u03c3)": "26.32 (28.69/0.79)",
+            "\ud83d\uddf3\ufe0f Votes": 444.0,
+            "\ud83c\udfdb\ufe0f Organization": "PixArt-Alpha"
         },
         {
             "Rank": 7,
             "\ud83e\udd16 Model": "Open-Dalle-v1.1",
-            "\u2b50 Score (\u03bc/\u03c3)": "25.51 (27.85/0.782)",
-            "\ud83d\uddf3\ufe0f Votes": 429.0,
-            "Organization": "DataAutoGPT3"
+            "\u2b50 Score (\u03bc/\u03c3)": "25.52 (27.86/0.782)",
+            "\ud83d\uddf3\ufe0f Votes": 432.0,
+            "\ud83c\udfdb\ufe0f Organization": "DataAutoGPT3"
         },
         {
             "Rank": 8,
+            "\ud83e\udd16 Model": "Dreamshaper-xl",
+            "\u2b50 Score (\u03bc/\u03c3)": "25.4 (27.76/0.786)",
+            "\ud83d\uddf3\ufe0f Votes": 437.0,
+            "\ud83c\udfdb\ufe0f Organization": "Lykon"
+        },
+        {
+            "Rank": 9,
             "\ud83e\udd16 Model": "Deepfloyd-IF",
             "\u2b50 Score (\u03bc/\u03c3)": "25.22 (27.58/0.789)",
             "\ud83d\uddf3\ufe0f Votes": 426.0,
-            "Organization": "DeepFloyd"
+            "\ud83c\udfdb\ufe0f Organization": "DeepFloyd"
         },
         {
-            "Rank": 9,
+            "Rank": 10,
             "\ud83e\udd16 Model": "Realvisxl-v3.0",
             "\u2b50 Score (\u03bc/\u03c3)": "24.9 (27.26/0.785)",
             "\ud83d\uddf3\ufe0f Votes": 424.0,
-            "Organization": "Realistic Vision"
+            "\ud83c\udfdb\ufe0f Organization": "Realistic Vision"
         },
         {
-            "Rank": 10,
+            "Rank": 11,
             "\ud83e\udd16 Model": "Realvisxl-v2.0",
             "\u2b50 Score (\u03bc/\u03c3)": "24.75 (27.11/0.785)",
             "\ud83d\uddf3\ufe0f Votes": 436.0,
-            "Organization": "Realistic Vision"
+            "\ud83c\udfdb\ufe0f Organization": "Realistic Vision"
         },
         {
-            "Rank": 11,
+            "Rank": 12,
             "\ud83e\udd16 Model": "Kandinsky-v2.2",
             "\u2b50 Score (\u03bc/\u03c3)": "24.48 (26.83/0.786)",
             "\ud83d\uddf3\ufe0f Votes": 426.0,
-            "Organization": "AI-Forever"
+            "\ud83c\udfdb\ufe0f Organization": "AI-Forever"
         },
         {
-            "Rank": 12,
+            "Rank": 13,
             "\ud83e\udd16 Model": "Dalle-2",
             "\u2b50 Score (\u03bc/\u03c3)": "23.04 (25.4/0.787)",
             "\ud83d\uddf3\ufe0f Votes": 423.0,
-            "Organization": "OpenAI"
+            "\ud83c\udfdb\ufe0f Organization": "OpenAI"
         },
         {
-            "Rank": 13,
+            "Rank": 14,
             "\ud83e\udd16 Model": "Playground-v2.5",
             "\u2b50 Score (\u03bc/\u03c3)": "21.98 (24.36/0.795)",
             "\ud83d\uddf3\ufe0f Votes": 430.0,
-            "Organization": "Playground AI"
+            "\ud83c\udfdb\ufe0f Organization": "Playground AI"
         },
         {
-            "Rank": 14,
+            "Rank": 15,
             "\ud83e\udd16 Model": "Kandinsky-v2.0",
             "\u2b50 Score (\u03bc/\u03c3)": "21.86 (24.23/0.791)",
             "\ud83d\uddf3\ufe0f Votes": 427.0,
-            "Organization": "AI-Forever"
+            "\ud83c\udfdb\ufe0f Organization": "AI-Forever"
         },
         {
-            "Rank": 15,
+            "Rank": 16,
             "\ud83e\udd16 Model": "SDXL-turbo",
             "\u2b50 Score (\u03bc/\u03c3)": "21.05 (23.42/0.79)",
             "\ud83d\uddf3\ufe0f Votes": 436.0,
-            "Organization": "Stability AI"
+            "\ud83c\udfdb\ufe0f Organization": "Stability AI"
         },
         {
-            "Rank": 16,
+            "Rank": 17,
             "\ud83e\udd16 Model": "Playground-v2.0",
             "\u2b50 Score (\u03bc/\u03c3)": "20.71 (23.1/0.795)",
             "\ud83d\uddf3\ufe0f Votes": 449.0,
-            "Organization": "Playground AI"
+            "\ud83c\udfdb\ufe0f Organization": "Playground AI"
         },
         {
-            "Rank": 17,
+            "Rank": 18,
             "\ud83e\udd16 Model": "Openjourney-v4",
             "\u2b50 Score (\u03bc/\u03c3)": "20.4 (22.76/0.789)",
             "\ud83d\uddf3\ufe0f Votes": 426.0,
-            "Organization": "Prompthero"
+            "\ud83c\udfdb\ufe0f Organization": "Prompthero"
         },
         {
-            "Rank": 18,
+            "Rank": 19,
             "\ud83e\udd16 Model": "SD-v2.1",
             "\u2b50 Score (\u03bc/\u03c3)": "20.19 (22.57/0.792)",
             "\ud83d\uddf3\ufe0f Votes": 424.0,
-            "Organization": "Stability AI"
+            "\ud83c\udfdb\ufe0f Organization": "Stability AI"
         },
         {
-            "Rank": 19,
+            "Rank": 20,
             "\ud83e\udd16 Model": "LCM-v1.5",
             "\u2b50 Score (\u03bc/\u03c3)": "19.79 (22.18/0.797)",
             "\ud83d\uddf3\ufe0f Votes": 429.0,
-            "Organization": "Tsinghua"
+            "\ud83c\udfdb\ufe0f Organization": "Tsinghua"
         },
         {
-            "Rank": 20,
+            "Rank": 21,
             "\ud83e\udd16 Model": "SDXL",
             "\u2b50 Score (\u03bc/\u03c3)": "19.78 (22.15/0.789)",
             "\ud83d\uddf3\ufe0f Votes": 441.0,
-            "Organization": "Stability AI"
+            "\ud83c\udfdb\ufe0f Organization": "Stability AI"
         },
         {
-            "Rank": 21,
+            "Rank": 22,
             "\ud83e\udd16 Model": "SSD-1b",
             "\u2b50 Score (\u03bc/\u03c3)": "18.53 (20.91/0.794)",
             "\ud83d\uddf3\ufe0f Votes": 427.0,
-            "Organization": "Segmind"
+            "\ud83c\udfdb\ufe0f Organization": "Segmind"
         },
         {
-            "Rank": 22,
+            "Rank": 23,
             "\ud83e\udd16 Model": "SD-v1.5",
             "\u2b50 Score (\u03bc/\u03c3)": "18.52 (20.92/0.799)",
             "\ud83d\uddf3\ufe0f Votes": 437.0,
-            "Organization": "Stability AI"
+            "\ud83c\udfdb\ufe0f Organization": "Stability AI"
         },
         {
-            "Rank": 23,
+            "Rank": 24,
             "\ud83e\udd16 Model": "SD-turbo",
             "\u2b50 Score (\u03bc/\u03c3)": "18.41 (20.8/0.794)",
             "\ud83d\uddf3\ufe0f Votes": 423.0,
-            "Organization": "Stability AI"
+            "\ud83c\udfdb\ufe0f Organization": "Stability AI"
         },
         {
-            "Rank": 24,
+            "Rank": 25,
             "\ud83e\udd16 Model": "Stable-cascade",
             "\u2b50 Score (\u03bc/\u03c3)": "15.27 (17.64/0.789)",
             "\ud83d\uddf3\ufe0f Votes": 426.0,
-            "Organization": "Stability AI"
+            "\ud83c\udfdb\ufe0f Organization": "Stability AI"
         },
         {
-            "Rank": 25,
+            "Rank": 26,
             "\ud83e\udd16 Model": "SDXL-Lightning",
             "\u2b50 Score (\u03bc/\u03c3)": "15.05 (17.43/0.794)",
             "\ud83d\uddf3\ufe0f Votes": 428.0,
-            "Organization": "ByteDance"
+            "\ud83c\udfdb\ufe0f Organization": "ByteDance"
         },
         {
-            "Rank": 26,
+            "Rank": 27,
             "\ud83e\udd16 Model": "SDXL-Deepcache",
             "\u2b50 Score (\u03bc/\u03c3)": "10.0 (12.46/0.821)",
             "\ud83d\uddf3\ufe0f Votes": 423.0,
-            "Organization": "NUS"
+            "\ud83c\udfdb\ufe0f Organization": "NUS"
+        },
+        {
+            "Rank": 28,
+            "\ud83e\udd16 Model": "FLUX.1-schnell",
+            "\u2b50 Score (\u03bc/\u03c3)": "0.0 (25.0/8.333)",
+            "\ud83d\uddf3\ufe0f Votes": 0.0,
+            "\ud83c\udfdb\ufe0f Organization": "Black Forest Labs"
+        },
+        {
+            "Rank": 29,
+            "\ud83e\udd16 Model": "FLUX.1-pro",
+            "\u2b50 Score (\u03bc/\u03c3)": "0.0 (25.0/8.333)",
+            "\ud83d\uddf3\ufe0f Votes": 0.0,
+            "\ud83c\udfdb\ufe0f Organization": "Black Forest Labs"
+        },
+        {
+            "Rank": 30,
+            "\ud83e\udd16 Model": "FLUX.1-dev",
+            "\u2b50 Score (\u03bc/\u03c3)": "0.0 (25.0/8.333)",
+            "\ud83d\uddf3\ufe0f Votes": 0.0,
+            "\ud83c\udfdb\ufe0f Organization": "Black Forest Labs"
         }
     ]
 }

sorted_score_list_video.json

@@ -1,49 +1,84 @@
 {
-    "total_models": 6,
-    "total_votes": 143,
-    "last_updated": "2024-07-31",
+    "total_models": 11,
+    "total_votes": 332,
+    "last_updated": "2024-08-13",
     "sorted_score_list": [
-        {
-            "Rank": 0,
-            "\ud83e\udd16 Model": "OpenSora",
-            "\u2b50 Score (\u03bc/\u03c3)": "26.15 (28.54/0.796)",
-            "\ud83d\uddf3\ufe0f Votes": 264.0,
-            "Organization": "HPC-AI"
-        },
         {
             "Rank": 1,
-            "\ud83e\udd16 Model": "LaVie",
-            "\u2b50 Score (\u03bc/\u03c3)": "25.85 (28.23/0.793)",
-            "\ud83d\uddf3\ufe0f Votes": 243.0,
-            "Organization": "Shanghai AI Lab"
+            "\ud83e\udd16 Model": "Sora",
+            "\u2b50 Score (\u03bc/\u03c3)": "35.95 (40.65/1.565)",
+            "\ud83d\uddf3\ufe0f Votes": 105.0,
+            "\ud83c\udfdb\ufe0f Organization": "OpenAI"
         },
         {
             "Rank": 2,
-            "\ud83e\udd16 Model": "VideoCrafter2",
-            "\u2b50 Score (\u03bc/\u03c3)": "23.8 (26.23/0.811)",
-            "\ud83d\uddf3\ufe0f Votes": 321.0,
-            "Organization": "Tencent"
+            "\ud83e\udd16 Model": "Runway-Gen3",
+            "\u2b50 Score (\u03bc/\u03c3)": "32.5 (35.75/1.086)",
+            "\ud83d\uddf3\ufe0f Votes": 122.0,
+            "\ud83c\udfdb\ufe0f Organization": "Runway"
         },
         {
             "Rank": 3,
-            "\ud83e\udd16 Model": "AnimateDiff",
-            "\u2b50 Score (\u03bc/\u03c3)": "23.06 (25.5/0.813)",
-            "\ud83d\uddf3\ufe0f Votes": 375.0,
-            "Organization": "CUHK etc."
+            "\ud83e\udd16 Model": "Pika-v1.0",
+            "\u2b50 Score (\u03bc/\u03c3)": "29.89 (32.7/0.94)",
+            "\ud83d\uddf3\ufe0f Votes": 119.0,
+            "\ud83c\udfdb\ufe0f Organization": "Pika"
         },
         {
             "Rank": 4,
-            "\ud83e\udd16 Model": "StableVideoDiffusion",
-            "\u2b50 Score (\u03bc/\u03c3)": "23.03 (25.51/0.827)",
-            "\ud83d\uddf3\ufe0f Votes": 267.0,
-            "Organization": "Stability AI"
+            "\ud83e\udd16 Model": "Pika-beta",
+            "\u2b50 Score (\u03bc/\u03c3)": "28.52 (31.28/0.919)",
+            "\ud83d\uddf3\ufe0f Votes": 119.0,
+            "\ud83c\udfdb\ufe0f Organization": "Pika"
         },
         {
             "Rank": 5,
+            "\ud83e\udd16 Model": "Runway-Gen2",
+            "\u2b50 Score (\u03bc/\u03c3)": "27.8 (30.44/0.879)",
+            "\ud83d\uddf3\ufe0f Votes": 111.0,
+            "\ud83c\udfdb\ufe0f Organization": "Runway"
+        },
+        {
+            "Rank": 6,
+            "\ud83e\udd16 Model": "OpenSora",
+            "\u2b50 Score (\u03bc/\u03c3)": "27.11 (29.57/0.818)",
+            "\ud83d\uddf3\ufe0f Votes": 709.0,
+            "\ud83c\udfdb\ufe0f Organization": "HPC-AI"
+        },
+        {
+            "Rank": 7,
+            "\ud83e\udd16 Model": "LaVie",
+            "\u2b50 Score (\u03bc/\u03c3)": "25.67 (28.13/0.818)",
+            "\ud83d\uddf3\ufe0f Votes": 664.0,
+            "\ud83c\udfdb\ufe0f Organization": "Shanghai AI Lab"
+        },
+        {
+            "Rank": 8,
+            "\ud83e\udd16 Model": "VideoCrafter2",
+            "\u2b50 Score (\u03bc/\u03c3)": "22.36 (24.88/0.842)",
+            "\ud83d\uddf3\ufe0f Votes": 717.0,
+            "\ud83c\udfdb\ufe0f Organization": "Tencent"
+        },
+        {
+            "Rank": 9,
+            "\ud83e\udd16 Model": "StableVideoDiffusion",
+            "\u2b50 Score (\u03bc/\u03c3)": "21.87 (24.39/0.841)",
+            "\ud83d\uddf3\ufe0f Votes": 510.0,
+            "\ud83c\udfdb\ufe0f Organization": "Stability AI"
+        },
+        {
+            "Rank": 10,
+            "\ud83e\udd16 Model": "AnimateDiff",
+            "\u2b50 Score (\u03bc/\u03c3)": "21.03 (23.56/0.844)",
+            "\ud83d\uddf3\ufe0f Votes": 480.0,
+            "\ud83c\udfdb\ufe0f Organization": "CUHK etc."
+        },
+        {
+            "Rank": 11,
             "\ud83e\udd16 Model": "Zeroscope-v2-xl",
-            "\u2b50 Score (\u03bc/\u03c3)": "11.91 (15.16/1.084)",
-            "\ud83d\uddf3\ufe0f Votes": 246.0,
-            "Organization": "Cerspense"
+            "\u2b50 Score (\u03bc/\u03c3)": "12.54 (15.71/1.055)",
+            "\ud83d\uddf3\ufe0f Votes": 348.0,
+            "\ud83c\udfdb\ufe0f Organization": "Cerspense"
         }
     ]
 }

webvid_prompt.txt

@@ -1,100 +0,0 @@
-Cloudy moscow kremlin time lapse
-Sharp knife to cut delicious smoked fish
-A baker turns freshly baked loaves of sourdough bread
-Shot of beautiful dinnerware and cutlery on a banquet table at restaurant
-Corn husks in field for agriculture farming
-Pear fruits hanging on a branch of a tree rulevogo
-Peaceful girl doing yoga meditate virabhasana sunrise coast slow motion
-Chef with recipe book watching young cook preparing dish in the kitchen
-Man walking in deep snow under the branches
-Fist patting down sand in an orange bucket
-Old decrepit house in the center of the city surrounded by new buildings
-Green grape plants in the middle of nature
-Climbers go up to the mountain pass
-Bodrum holiday resort seashore marina
-A flight over a beautiful stream in the forest
-Attractive young couple at home laughing at funny internet joke online using digital tablet having fun
-A small animation for the design video about redcurrant
-Time lapse of sky clouds storm
-Happy young caucasian baby boy playing toy bucket spade sandy beach with father while mother takes photograph sun lens flare shot on red epic
-A young woman having dental treatment
-Huge waterfall in chilean scenery huilo huilo
-Yellow bird and nest on the branch
-Little girl playing in the garden in summer
-Hands of girl fall out sweets from bowl on white floor
-Woman hairdresser put on curlers to long hair plus size woman
-Pov of two hands and young woman putting the propellers on a drone
-Video of watering a flower pot
-Woman look at the city in hong kong
-Sexy woman posing sitting on chair
-Coconat palm tree on sky tropical view
-Dog sitting tied to a post and waiting for the owner
-Asian female cyclist blogger live stream happily to show her ride on the road
-Pretty student learning in computer class at the university
-Storm clouds and rainbow  over bordeaux vineyards
-Aerial view of roof tops of old city
-Mountain area with fog and mist time lapse
-The famous waterfall of niagara falls in canada
-Low section of ice fisherman fishing in tent
-Medical students in training assisting surgeon in hospital operating room
-Passing by a cruise ship in the evening in ha long bay
-London skyline with building site at sunset
-The red deer female close up in the summertime
-Chinese new year flat icon chinese decor lantern
-The waiters in the restaurant put the glasses on buffet table
-Makeup artist dips brush into a makeup kit
-Panning down on team of businesswomen and businessmen in an office working and talking about new projects
-Time lapse in the mountains of brazil tree line
-Sick man in bed measuring temperature feeling fever medium shot
-Santa claus sitting in a chair with a little girl dreaming about her christmas presents
-Abused woman lying in the bathtub screams in despair
-Young mime is juggling in the park
-Countryside timelapse in spain
-Green branches of a coniferous tree with needles fill the entire screen
-Closeup of pouring healthy black chia seeds into a bowl 
-South korea high resolution victory concept
-Inspecting south african passport
-Attractive business woman reading documents in busy office female executive working on company project deadline
-Slow dolly in towards beautiful waterfall through bright fall colors
-Digital animation of american flag waving while background shows silhouette of hill with tree during sunset
-Hud multipath target monitoring
-Happy young businessman thinking while using phone
-Thick morning fog in the summer forest
-Group of children play a game of reaction speed in scientific museum
-Abstract chrisanthemum background
-Inside processor of a battery chip 
-Big and small frog sitting in the water and  swimming away
-Street lamp fallen down on ground with shattered glass from snow storm
-Rustic cabin in early autumn in the great smoky mountains with dark shadows and some autumn color as seen from a window pane from another historical cabin
-Night vision view of timber wolf
-Pseudo galena by pyrrhotite hematitiziran 
-Gorgeous couple in love have a romantic walk in magnificent budapest blurred background at night
-Close up thoughtful pretty young woman relaxing at the beach resort
-Happy senior woman working on laptop computer 
-Singing nightingale on a tree branch
-Pouring of rice water from jug into glass on table
-Flaming gorge national park in summer in utah with handheld shot of brown cow grazing closeup on grass herd near ranch
-Aerial flyby miami beach condominiums
-Jungle covered mountain on panay island in the philippines
-Close up portrait of two caucasian young girl and boy playing together on digital tablet
-White spools are getting wound by textile equipment
-The wedge newport beach california waves crashing aerial footage
-Peak at kaengkrachan national park thailand
-Christmas bauble dropping and bouncing beside crackers and presents in slow motion
-Happy extended family on the sofa at home
-Closeup shot of young female confectioner decorating delicious handmade cake placed on rotating stand with freshly baked meringues
-Non smoking sign in the airplane cabin
-Swan opening up wings and flapping them to dry off while grooming
-A series of explosions in the winter tundra
-Man actor wearing a tiger clothe preparing his acting with a tambourine
-Abstract shape pattern texture moving background
-Above the thermal station two pipes smoking in the gray sky
-Vacation water villas on tropical island
-Dense fog glows orange and covers hills at dawn
-People walking on the beach in timelapse 
-Aerial view of wind turbines energy production in yellow fields
-Preparing and mixing a fresh salad
-A jetsurfer taking various turns while jet surfing on water
-Happy little girl jumping in swimming pool and learning how to swim with help of father
-Student boy wash the school board
-Office workers showing work on laptop