Update app.py

app.py

@@ -98,6 +98,7 @@ def load_model():
     model.eval()
     return model
 
+
 def load_class_names():
     with open(config.CLASS_NAMES_PATH, "r") as f:
         return json.load(f)
@@ -151,6 +152,7 @@ class GradCAM:
         cam = cam / (cam.max() + 1e-8)
         return cam.cpu().numpy()
 
+
 def overlay_heatmap(image, heatmap):
     image = np.array(image.resize((config.IMAGE_SIZE, config.IMAGE_SIZE)))
     heatmap = cv2.resize(heatmap, (image.shape[1], image.shape[0]))
@@ -252,18 +254,32 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
     )
 
     with gr.Row():
+
         with gr.Column():
-            with gr.Box(elem_classes=["section-card"]):
-                input_image = gr.Image(type="pil", label="Upload Image", height=380)
-                classify_btn = gr.Button("Run Classification", variant="primary")
+            with gr.Group(elem_classes=["section-card"]):
+                input_image = gr.Image(
+                    type="pil",
+                    label="Upload Image",
+                    height=380
+                )
+                classify_btn = gr.Button(
+                    "Run Classification",
+                    variant="primary"
+                )
 
         with gr.Column():
             with gr.Tab("Results"):
-                predictions = gr.Label(label="Top Predictions", num_top_classes=3)
+                predictions = gr.Label(
+                    label="Top Predictions",
+                    num_top_classes=3
+                )
                 recycling_info = gr.Markdown()
 
             with gr.Tab("Model Interpretation"):
-                heatmap = gr.Image(label="Grad-CAM Visualization", height=380)
+                heatmap = gr.Image(
+                    label="Grad-CAM Visualization",
+                    height=380
+                )
 
     classify_btn.click(
         classify_image,