Add model count

app.py

@@ -184,7 +184,7 @@ def plot_acc_rate(rate_compare_results_df: pl.DataFrame, width: int = 1000, heig
 
 def update_data(
     dataset: str, benchmark: str, intermediate: bool, mim: bool, ssl: bool, dist: bool, log_x: bool, search_bar: str
-) -> tuple[alt.LayerChart, pl.DataFrame]:
+) -> tuple[alt.LayerChart, pl.DataFrame, str]:
     compare_results_df = pl.read_csv(f"results_{dataset}.csv")
     if intermediate is False:
         compare_results_df = compare_results_df.filter(pl.col("Intermediate") == intermediate)
@@ -262,7 +262,9 @@ def update_data(
         ]
     )
 
-    return (chart, output_df.drop("Mistakes", "Samples", "torch_version"))
+    model_count_text = f"{len(output_df)} models displayed"
+
+    return (chart, output_df.drop("Mistakes", "Samples", "torch_version"), model_count_text)
 
 
 def app() -> None:
@@ -340,13 +342,13 @@ def app() -> None:
                 search_bar = gr.Textbox(label="Model Filter", placeholder="e.g. convnext, efficient|mobile")
 
             with gr.Column():
-                pass
+                model_count_display = gr.Markdown()
 
         plot = gr.Plot(container=False)
         table = gr.Dataframe(show_search="search")
 
         inputs = [dataset_dropdown, benchmark_dropdown, intermediate, mim, ssl, dist, log_x, search_bar]
-        outputs = [plot, table]
+        outputs = [plot, table, model_count_display]
         leaderboard.load(update_data, inputs=inputs, outputs=outputs)
 
         dataset_dropdown.change(update_data, inputs=inputs, outputs=outputs)