update app.py

app.py

@@ -39,20 +39,18 @@ with gr.Blocks(title="ViT ImageNet Classification - ClassCat",
     gr.HTML("""<div style="font-family:'Times New Roman', 'Serif'; font-size:16pt; font-weight:bold; text-align:center; color:royalblue;">ViT - ImageNet Classification</div>""")
 
     with gr.Row(): 
-        with gr.Column():
-            input_image = gr.Image(type="pil", image_mode="RGB", shape=(224, 224))
-
-            with gr.Row():
-                gr.Examples(['./samples/cat.jpg'], label='Sample images : cat', inputs=input_image)
-                gr.Examples(['./samples/cheetah.jpg'], label='cheetah', inputs=input_image)
-                gr.Examples(['./samples/hotdog.jpg'], label='hotdog', inputs=input_image)
-                gr.Examples(['./samples/lion.jpg'], label='lion', inputs=input_image)
-                #gr.Examples(example_files, inputs=input_image)
-        
+        input_image = gr.Image(type="pil", image_mode="RGB", shape=(224, 224))        
         output_label=gr.Label(label="Probabilities", num_top_classes=3)
 
     send_btn = gr.Button("Infer")
     send_btn.click(fn=classify_image, inputs=input_image, outputs=output_label)
 
+    with gr.Row():
+        gr.Examples(['./samples/cat.jpg'], label='Sample images : cat', inputs=input_image)
+        gr.Examples(['./samples/cheetah.jpg'], label='cheetah', inputs=input_image)
+        gr.Examples(['./samples/hotdog.jpg'], label='hotdog', inputs=input_image)
+        gr.Examples(['./samples/lion.jpg'], label='lion', inputs=input_image)
+        #gr.Examples(example_files, inputs=input_image)
+
 #demo.queue(concurrency_count=3)
 demo.launch(debug=True)