Add Organization column to all tables with filters

app.py

@@ -7,6 +7,11 @@ CLASSIFICATION_DATA = {
         "ResNet-50", "ViT-Base", "Swin-T", "InceptionV3", "SqueezeNet",
         "ResNet-50", "ViT-Base", "Swin-T", "InceptionV3", "SqueezeNet",
     ],
+    "Organization": [
+        "Microsoft", "Google", "Microsoft", "Google", "DeepMind",
+        "Microsoft", "Google", "Microsoft", "Google", "DeepMind",
+        "Microsoft", "Google", "Microsoft", "Google", "DeepMind",
+    ],
     "Dataset": [
         "DoMars16", "DoMars16", "DoMars16", "DoMars16", "DoMars16",
         "Atmospheric Dust", "Atmospheric Dust", "Atmospheric Dust", "Atmospheric Dust", "Atmospheric Dust",
@@ -30,6 +35,11 @@ DETECTION_DATA = {
         "Faster R-CNN", "YOLOv5", "DETR", "RetinaNet", "SSD",
         "Faster R-CNN", "YOLOv5", "DETR", "RetinaNet", "SSD",
     ],
+    "Organization": [
+        "Meta", "Ultralytics", "Meta", "Meta", "Google",
+        "Meta", "Ultralytics", "Meta", "Meta", "Google",
+        "Meta", "Ultralytics", "Meta", "Meta", "Google",
+    ],
     "Dataset": [
         "Mars Crater", "Mars Crater", "Mars Crater", "Mars Crater", "Mars Crater",
         "Rover Component", "Rover Component", "Rover Component", "Rover Component", "Rover Component",
@@ -53,6 +63,11 @@ SEGMENTATION_DATA = {
         "U-Net", "DeepLabV3+", "Mask R-CNN", "SegFormer", "HRNet",
         "U-Net", "DeepLabV3+", "Mask R-CNN", "SegFormer", "HRNet",
     ],
+    "Organization": [
+        "OpenAI", "Google", "Meta", "NVIDIA", "Microsoft",
+        "OpenAI", "Google", "Meta", "NVIDIA", "Microsoft",
+        "OpenAI", "Google", "Meta", "NVIDIA", "Microsoft",
+    ],
     "Dataset": [
         "Mars Terrain", "Mars Terrain", "Mars Terrain", "Mars Terrain", "Mars Terrain",
         "Dust Storm", "Dust Storm", "Dust Storm", "Dust Storm", "Dust Storm",
@@ -71,7 +86,7 @@ SEGMENTATION_DATA = {
 }
 
 
-def filter_and_search(df, search, datasets, models, columns):
+def filter_and_search(df, search, datasets, models, organizations, columns):
     filtered = df.copy()
 
     if search:
@@ -82,6 +97,8 @@ def filter_and_search(df, search, datasets, models, columns):
         filtered = filtered[filtered["Dataset"].isin(datasets)]
     if models:
         filtered = filtered[filtered["Model"].isin(models)]
+    if organizations:
+        filtered = filtered[filtered["Organization"].isin(organizations)]
 
     if columns:
         display_cols = [col for col in columns if col in filtered.columns]
@@ -94,8 +111,9 @@ def build_tab(data, name):
     df = pd.DataFrame(data)
     datasets = sorted(df["Dataset"].unique().tolist())
     models = sorted(df["Model"].unique().tolist())
-    metric_cols = [col for col in df.columns if col not in ["Model", "Dataset"]]
-    all_cols = ["Model", "Dataset"] + metric_cols
+    organizations = sorted(df["Organization"].unique().tolist())
+    metric_cols = [col for col in df.columns if col not in ["Model", "Organization", "Dataset"]]
+    all_cols = ["Model", "Organization", "Dataset"] + metric_cols
 
     with gr.TabItem(name, elem_id="llm-benchmark-tab-table"):
         with gr.Row():
@@ -129,6 +147,14 @@ def build_tab(data, name):
                     elem_classes="filter-group"
                 )
 
+                gr.Markdown("**Organizations**")
+                org_filter = gr.CheckboxGroup(
+                    choices=organizations,
+                    value=organizations,
+                    label="",
+                    elem_classes="filter-group"
+                )
+
                 gr.Markdown("**Datasets**")
                 dataset_filter = gr.CheckboxGroup(
                     choices=datasets,
@@ -137,13 +163,14 @@ def build_tab(data, name):
                     elem_classes="filter-group"
                 )
 
-        def update(search, ds, md, cols):
-            return filter_and_search(df, search, ds, md, cols)
+        def update(search, ds, md, org, cols):
+            return filter_and_search(df, search, ds, md, org, cols)
 
-        search_bar.change(update, [search_bar, dataset_filter, model_filter, col_selector], table)
-        dataset_filter.change(update, [search_bar, dataset_filter, model_filter, col_selector], table)
-        model_filter.change(update, [search_bar, dataset_filter, model_filter, col_selector], table)
-        col_selector.change(update, [search_bar, dataset_filter, model_filter, col_selector], table)
+        search_bar.change(update, [search_bar, dataset_filter, model_filter, org_filter, col_selector], table)
+        dataset_filter.change(update, [search_bar, dataset_filter, model_filter, org_filter, col_selector], table)
+        model_filter.change(update, [search_bar, dataset_filter, model_filter, org_filter, col_selector], table)
+        org_filter.change(update, [search_bar, dataset_filter, model_filter, org_filter, col_selector], table)
+        col_selector.change(update, [search_bar, dataset_filter, model_filter, org_filter, col_selector], table)
 
 
 custom_css = """