feat(gradio): improvements + examples

app.py

@@ -40,13 +40,13 @@ def freeze(model):
 def run(
     model_name: str,
     input_image: Image,
-    do_resize: bool,
-    do_center_crop: bool,
-    normalization_mode: str,
-    smooth: int,
-    alpha_percentile: Union[int, float],
-    plot_dpi: int,
-    topk: int = 5,
+    do_resize: bool = True,
+    do_center_crop: bool = False,
+    normalization_mode: str = NormalizationMode.WRT_PREDICTION,
+    smooth: int = 15,
+    alpha_percentile: Union[int, float] = 99.99,
+    plot_dpi: int = 120,
+    topk: int = 3,
 ) -> Tuple[dict, plt.Figure]:
     # cleanup previous stuff
     plt.close("all")
@@ -128,7 +128,9 @@ with gr.Blocks() as demo:
     # basic info
     gr.Markdown(
         """# B-cos Explanation Generation Demo
-        [Repository](https://github.com/B-cos/B-cos-v2/)
+        This demo generates explanations for images using the B-cos models.
+        
+        GitHub: [link](https://github.com/B-cos/B-cos-v2/)
         """
     )
 
@@ -147,7 +149,7 @@ with gr.Blocks() as demo:
             normalization_mode = gr.Radio(
                 NormalizationMode.all(),
                 value=NormalizationMode.WRT_PREDICTION,
-                label="Normalization Mode",
+                label="Explanation Normalization Mode",
             )
 
             smooth = gr.Slider(1, 51, value=15, step=2, label="Smoothing kernel size")
@@ -178,6 +180,44 @@ with gr.Blocks() as demo:
         scroll_to_output=True,
     )
 
+    gr.Examples(
+        fn=run,
+        examples=[
+            [
+                "resnet50",
+                "./examples/polizeifahrzeug-zebra.png",
+                True,
+                False,
+                NormalizationMode.WRT_PREDICTION,
+                15,
+                99.99,
+                120,
+            ],
+            [
+                "resnet50",
+                "./examples/cat-dog.png",
+                True,
+                False,
+                NormalizationMode.WRT_PREDICTION,
+                15,
+                99.99,
+                120,
+            ]
+        ],
+        inputs=[
+            selected_model,
+            input_image,
+            do_resize,
+            do_center_crop,
+            normalization_mode,
+            smooth,
+            alpha_percentile,
+            plot_dpi,
+        ],
+        outputs=[output_labels, output],
+        cache_examples=True,
+    )
+
 
 demo.launch()