fix

app.py

@@ -230,29 +230,29 @@ with demo:
                     #        value=[],
                     #        interactive=True
                     #    )
-                with gr.Column(min_width=320):
-                    #with gr.Box(elem_id="box-filter"):
-                    filter_columns_type = gr.CheckboxGroup(
-                        label="Model types",
-                        choices=[t.to_str() for t in ModelType],
-                        value=[t.to_str() for t in ModelType],
-                        interactive=True,
-                        elem_id="filter-columns-type",
-                    )
-                    filter_columns_precision = gr.CheckboxGroup(
-                        label="Precision",
-                        choices=[i.value.name for i in Precision],
-                        value=[i.value.name for i in Precision],
-                        interactive=True,
-                        elem_id="filter-columns-precision",
-                    )
-                    filter_columns_size = gr.CheckboxGroup(
-                        label="Model sizes (in billions of parameters)",
-                        choices=list(NUMERIC_INTERVALS.keys()),
-                        value=list(NUMERIC_INTERVALS.keys()),
-                        interactive=True,
-                        elem_id="filter-columns-size",
-                    )
+                #with gr.Column(min_width=320):
+                #    #with gr.Box(elem_id="box-filter"):
+                #    filter_columns_type = gr.CheckboxGroup(
+                #        label="Model types",
+                #        choices=[t.to_str() for t in ModelType],
+                #        value=[t.to_str() for t in ModelType],
+                #        interactive=True,
+                #        elem_id="filter-columns-type",
+                #    )
+                #    filter_columns_precision = gr.CheckboxGroup(
+                #        label="Precision",
+                #        choices=[i.value.name for i in Precision],
+                #        value=[i.value.name for i in Precision],
+                #        interactive=True,
+                #        elem_id="filter-columns-precision",
+                #    )
+                #    filter_columns_size = gr.CheckboxGroup(
+                #        label="Model sizes (in billions of parameters)",
+                #        choices=list(NUMERIC_INTERVALS.keys()),
+                #        value=list(NUMERIC_INTERVALS.keys()),
+                #        interactive=True,
+                #        elem_id="filter-columns-size",
+                #    )
 
 
             leaderboard_table = gr.components.Dataframe(
@@ -359,29 +359,29 @@ with demo:
                     #        value=[],
                     #        interactive=True
                     #    )
-                with gr.Column(min_width=320):
-                    #with gr.Box(elem_id="box-filter"):
-                    filter_columns_type = gr.CheckboxGroup(
-                        label="Model types",
-                        choices=[t.to_str() for t in ModelType],
-                        value=[t.to_str() for t in ModelType],
-                        interactive=True,
-                        elem_id="filter-columns-type",
-                    )
-                    filter_columns_precision = gr.CheckboxGroup(
-                        label="Precision",
-                        choices=[i.value.name for i in Precision],
-                        value=[i.value.name for i in Precision],
-                        interactive=True,
-                        elem_id="filter-columns-precision",
-                    )
-                    filter_columns_size = gr.CheckboxGroup(
-                        label="Model sizes (in billions of parameters)",
-                        choices=list(NUMERIC_INTERVALS.keys()),
-                        value=list(NUMERIC_INTERVALS.keys()),
-                        interactive=True,
-                        elem_id="filter-columns-size",
-                    )
+                #with gr.Column(min_width=320):
+                #    #with gr.Box(elem_id="box-filter"):
+                #    filter_columns_type = gr.CheckboxGroup(
+                #        label="Model types",
+                #        choices=[t.to_str() for t in ModelType],
+                #        value=[t.to_str() for t in ModelType],
+                #        interactive=True,
+                #        elem_id="filter-columns-type",
+                #    )
+                #    filter_columns_precision = gr.CheckboxGroup(
+                #        label="Precision",
+                #        choices=[i.value.name for i in Precision],
+                #        value=[i.value.name for i in Precision],
+                #        interactive=True,
+                #        elem_id="filter-columns-precision",
+                #    )
+                #    filter_columns_size = gr.CheckboxGroup(
+                #        label="Model sizes (in billions of parameters)",
+                #        choices=list(NUMERIC_INTERVALS.keys()),
+                #        value=list(NUMERIC_INTERVALS.keys()),
+                #        interactive=True,
+                #        elem_id="filter-columns-size",
+                #    )
 
 
             leaderboard_table = gr.components.Dataframe(

src/about.py

@@ -13,15 +13,15 @@ class Task:
 class Tasks(Enum):
     # task_key in the json file, metric_key in the json file, name to display in the leaderboard 
     Where2Place = Task("Where2Place", "overall", "Where2Place")
-    blink_val_ev= Task("blink_val_ev", "overall", "blink_val_ev")
-    cv_bench_test = Task("cv_bench_test", "overall", "cv_bench_test")
-    robo_spatial_home_all = Task("robo_spatial_home_all", "overall", "robo_spatial_home_all")
-    embspatial_bench = Task("embspatial_bench", "overall", "embspatial_bench")
-    all_angles_bench = Task("all_angles_bench", "overall", "all_angles_bench")
-    vsi_bench_tiny = Task("vsi_bench_tiny", "overall", "vsi_bench_tiny")
+    blink_val_ev= Task("blink_val_ev", "overall", "Blink")
+    cv_bench_test = Task("cv_bench_test", "overall", "CVBench")
+    robo_spatial_home_all = Task("robo_spatial_home_all", "overall", "RoboSpatial-Home")
+    embspatial_bench = Task("embspatial_bench", "overall", "EmbspatialBench")
+    all_angles_bench = Task("all_angles_bench", "overall", "All-Angles Bench")
+    vsi_bench_tiny = Task("vsi_bench_tiny", "overall", "VSI-Bench")
     SAT = Task("SAT", "overall", "SAT")
-    egoplan_bench2 = Task("egoplan_bench2", "overall", "egoplan_bench2")
-    erqa = Task("erqa", "overall", "erqa")
+    egoplan_bench2 = Task("egoplan_bench2", "overall", "EgoPlan-Bench2")
+    erqa = Task("erqa", "overall", "ERQA")
 
 class Quotas(Enum):
     Perception = Task("Perception", "overall", "Perception")
@@ -38,7 +38,7 @@ class Quotas(Enum):
     SpatialReasoning_se = Task("SpatialReasoning", "Size estimation", "SR_Se")
     Prediction = Task("Prediction", "overall", "Prediction")
     Prediction_T = Task("Prediction", "Trajectory", "P_T")
-    Prediction_F = Task("Prediction", "Future prediction",P_Fp")
+    Prediction_F = Task("Prediction", "Future prediction","P_Fp")
     Planning = Task("Planning", "overall", "Planning")
     Planning_G = Task("Planning", "Goal Decomposition", "P_GD")
     Planning_N = Task("Planning", "Navigation", "P_N")
@@ -80,7 +80,7 @@ We hope to promote a more open ecosystem for embodied model developers to partic
 
 # How it works 
 
-## Embodied verse tool - FlagEvalMM
+## Embodied Verse tool - FlagEvalMM
 FlagEvalMM是一个开源评估框架，旨在全面评估多模态模型，其提供了一种标准化的方法来评估跨各种任务和指标使用多种模式（文本、图像、视频）的模型。
 
 - 灵活的架构：支持多个多模态模型和评估任务，包括VQA、图像检索、文本到图像等。