minor fix

app.py

@@ -24,89 +24,7 @@ with gr.Blocks() as block:
     
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
         # Table 1
-        with gr.TabItem("📊 MMEB (Archived)", elem_id="qa-tab-table1", id=1):
-            with gr.Row():
-                with gr.Accordion("Citation", open=False):
-                    citation_button = gr.Textbox(
-                        value=CITATION_BUTTON_TEXT,
-                        label=CITATION_BUTTON_LABEL,
-                        elem_id="citation-button",
-                        lines=10,
-                    )
-            gr.Markdown(TABLE_INTRODUCTION)
-
-            with gr.Row():
-                search_bar = gr.Textbox(
-                    placeholder="Search models...",
-                    show_label=False,
-                    elem_id="search-bar"
-                )
-            
-            df = get_df()
-            min_size, max_size = get_size_range(df)
-
-            with gr.Row():
-                min_size_slider = gr.Slider(
-                    minimum=min_size,
-                    maximum=max_size,
-                    value=min_size,
-                    step=0.1,
-                    label="Minimum number of parameters (B)",
-                )
-                max_size_slider = gr.Slider(
-                    minimum=min_size,
-                    maximum=max_size,
-                    value=max_size,
-                    step=0.1,
-                    label="Maximum number of parameters (B)",
-                )
-
-            with gr.Row():
-                tasks_select = gr.CheckboxGroup(
-                    choices=TASKS_V1,
-                    value=TASKS_V1,
-                    label="Select tasks to Display",
-                    elem_id="tasks-select"
-                )
-
-            data_component = gr.components.Dataframe(
-                value=df[COLUMN_NAMES],
-                headers=COLUMN_NAMES,
-                type="pandas",
-                datatype=DATA_TITLE_TYPE,
-                interactive=False,
-                visible=True,
-                max_height=2400, 
-            )
-            
-            refresh_button = gr.Button("Refresh")
-            
-            def update_with_tasks(*args):
-                return update_table(*args)
-
-            search_bar.change(
-                fn=update_with_tasks, 
-                inputs=[search_bar, min_size_slider, max_size_slider, tasks_select], 
-                outputs=data_component
-            )
-            min_size_slider.change(
-                fn=update_with_tasks, 
-                inputs=[search_bar, min_size_slider, max_size_slider, tasks_select], 
-                outputs=data_component
-            )
-            max_size_slider.change(
-                fn=update_with_tasks, 
-                inputs=[search_bar, min_size_slider, max_size_slider, tasks_select], 
-                outputs=data_component
-            )
-            tasks_select.change(
-                fn=update_with_tasks, 
-                inputs=[search_bar, min_size_slider, max_size_slider, tasks_select], 
-                outputs=data_component
-            )
-            refresh_button.click(fn=refresh_data, outputs=data_component)
-
-        with gr.TabItem("📊 **MMEB (V2)**", elem_id="qa-tab-table1", id=2):
+        with gr.TabItem("📊 MMEB (V2)", elem_id="qa-tab-table1", id=1):
             with gr.Row():
                 with gr.Accordion("Citation", open=False):
                     citation_button2 = gr.Textbox(
@@ -186,10 +104,10 @@ with gr.Blocks() as block:
                 inputs=[search_bar2, min_size_slider2, max_size_slider2, tasks_select2], 
                 outputs=data_component2
             )
-            refresh_button.click(fn=v2.refresh_data, outputs=data_component)
+            refresh_button2.click(fn=v2.refresh_data, outputs=data_component2)
 
-        # table 3
-        with gr.TabItem("🖼️ Image", elem_id="qa-tab-table1", id=3):
+        # table 2
+        with gr.TabItem("🖼️ Image", elem_id="qa-tab-table1", id=2):
             data_component3 = gr.components.Dataframe(
                 value=df2[v2.COLUMN_NAMES_I],
                 headers=v2.COLUMN_NAMES_I,
@@ -200,8 +118,8 @@ with gr.Blocks() as block:
                 max_height=2400, 
             )
 
-        # table 4
-        with gr.TabItem("💽 Video", elem_id="qa-tab-table1", id=4):
+        # table 3
+        with gr.TabItem("💽 Video", elem_id="qa-tab-table1", id=3):
             data_component4 = gr.components.Dataframe(
                 value=df2[v2.COLUMN_NAMES_V],
                 headers=v2.COLUMN_NAMES_V,
@@ -212,8 +130,8 @@ with gr.Blocks() as block:
                 max_height=2400, 
             )
 
-        # table 5
-        with gr.TabItem("📑 Visual Doc", elem_id="qa-tab-table1", id=5):
+        # table 4
+        with gr.TabItem("📑 Visual Doc", elem_id="qa-tab-table1", id=4):
             data_component5 = gr.components.Dataframe(
                 value=df2[v2.COLUMN_NAMES_D],
                 headers=v2.COLUMN_NAMES_D,
@@ -224,14 +142,98 @@ with gr.Blocks() as block:
                 max_height=2400, 
             )
 
-        # table 6
-        with gr.TabItem("📝 About", elem_id="qa-tab-table2", id=6):
+        # table 5
+        with gr.TabItem("📝 About", elem_id="qa-tab-table2", id=5):
             gr.Markdown(LEADERBOARD_INFO, elem_classes="markdown-text")
             gr.Image("overview.png", width=900, label="Dataset Overview")
 
-        # table 7
-        with gr.TabItem("🚀 Submit here! ", elem_id="submit-tab", id=7):
+        # table 6
+        with gr.TabItem("🚀 Submit here! ", elem_id="submit-tab", id=6):
             with gr.Row():
                 gr.Markdown(SUBMIT_INTRODUCTION, elem_classes="markdown-text")
 
+        # table 7
+        with gr.TabItem("📊 MMEB (Archived)", elem_id="qa-tab-table1", id=7):
+            with gr.Row():
+                with gr.Accordion("Citation", open=False):
+                    citation_button = gr.Textbox(
+                        value=CITATION_BUTTON_TEXT,
+                        label=CITATION_BUTTON_LABEL,
+                        elem_id="citation-button",
+                        lines=10,
+                    )
+            gr.Markdown(TABLE_INTRODUCTION)
+
+            with gr.Row():
+                search_bar = gr.Textbox(
+                    placeholder="Search models...",
+                    show_label=False,
+                    elem_id="search-bar"
+                )
+            
+            df = get_df()
+            min_size, max_size = get_size_range(df)
+
+            with gr.Row():
+                min_size_slider = gr.Slider(
+                    minimum=min_size,
+                    maximum=max_size,
+                    value=min_size,
+                    step=0.1,
+                    label="Minimum number of parameters (B)",
+                )
+                max_size_slider = gr.Slider(
+                    minimum=min_size,
+                    maximum=max_size,
+                    value=max_size,
+                    step=0.1,
+                    label="Maximum number of parameters (B)",
+                )
+
+            with gr.Row():
+                tasks_select = gr.CheckboxGroup(
+                    choices=TASKS_V1,
+                    value=TASKS_V1,
+                    label="Select tasks to Display",
+                    elem_id="tasks-select"
+                )
+
+            data_component = gr.components.Dataframe(
+                value=df[COLUMN_NAMES],
+                headers=COLUMN_NAMES,
+                type="pandas",
+                datatype=DATA_TITLE_TYPE,
+                interactive=False,
+                visible=True,
+                max_height=2400, 
+            )
+            
+            refresh_button = gr.Button("Refresh")
+            
+            def update_with_tasks(*args):
+                return update_table(*args)
+
+            search_bar.change(
+                fn=update_with_tasks, 
+                inputs=[search_bar, min_size_slider, max_size_slider, tasks_select], 
+                outputs=data_component
+            )
+            min_size_slider.change(
+                fn=update_with_tasks, 
+                inputs=[search_bar, min_size_slider, max_size_slider, tasks_select], 
+                outputs=data_component
+            )
+            max_size_slider.change(
+                fn=update_with_tasks, 
+                inputs=[search_bar, min_size_slider, max_size_slider, tasks_select], 
+                outputs=data_component
+            )
+            tasks_select.change(
+                fn=update_with_tasks, 
+                inputs=[search_bar, min_size_slider, max_size_slider, tasks_select], 
+                outputs=data_component
+            )
+            refresh_button.click(fn=refresh_data, outputs=data_component)
+
+
 block.launch(share=True)

utils.py

@@ -18,7 +18,7 @@ DATA_TITLE_TYPE = ['number', 'markdown', 'str', 'markdown'] + \
                     ['number'] * len(TASKS_V1)
 
 LEADERBOARD_INTRODUCTION = """
-# 📊 **MMEB LEADERBOARD**
+# 📊 **MMEB LEADERBOARD (VLM2Vec)**
 
 ## Introduction
 We introduce a novel benchmark, **MMEB-V1 (Massive Multimodal Embedding Benchmark)**, 

utils_v2.py

@@ -11,7 +11,7 @@ def sum_lst(lst):
         total += item
     return total
 
-SCORE_BASE_DIR = "Scores"
+SCORE_BASE_DIR = "scores"
 META_DATA = ["model_name", "model_size", "url"]
 DATASETS = {
     "image": {
@@ -41,9 +41,9 @@ BASE_COLS = ['Rank', 'Models', 'Model Size(B)']
 TASKS = ["Overall", "I-CLS", "I-QA", "I-RET", "I-VG", "VisDoc", "V-CLS", "V-QA", "V-RET", "V-MRET"]
 BASE_DATA_TITLE_TYPE = ['number', 'markdown', 'str', 'markdown']
 
-COLUMN_NAMES = BASE_COLS + TASKS
+COLUMN_NAMES = BASE_COLS + ["Overall", 'Image-Overall', 'Video-Overall', 'VisDoc']
 DATA_TITLE_TYPE = BASE_DATA_TITLE_TYPE + \
-                    ['number'] * len(TASKS)
+                    ['number'] * 3
 
 TASKS_I = ['Image-Overall'] + ALL_DATASETS_SPLITS['image']
 COLUMN_NAMES_I = BASE_COLS + TASKS_I
@@ -97,7 +97,7 @@ def load_scores(raw_scores=None):
                     if modality == 'visdoc':
                         metric = "ndcg_linear@5" if "ndcg_linear@5" in score else "ndcg@5"
                     score = score.get(metric, 0.0)
-                all_scores[dataset] = round(score, 2)
+                all_scores[dataset] = round(score, 4) * 100.0
     return all_scores
 
 def calculate_score(raw_scores=None):