Update app.py

app.py

@@ -21,9 +21,25 @@ def predict(inp):
 
 import gradio as gr
 
-gr.Interface(fn=predict,
-             inputs=gr.Image(type="pil"),
-             outputs=gr.Label(num_top_classes=3),
-             examples=["lion.jpg", "cheetah.jpg"]).launch()
+with gr.Blocks(title="Image Classification for 1000 Objects",
+            css=".gradio-container {background:mintcream;}"
+        ) as demo:
+    gr.HTML("""<div style="font-family:'Times New Roman', 'Serif'; font-size:16pt; font-weight:bold; text-align:center; color:royalblue;">Image Classification for 1000 Objects</div>""")
+
+    with gr.Row(): 
+        input_image  = gr.Image(type="filepath", image_mode="L", shape=(224, 224))        
+        output_label = gr.Label(label="Probabilities", num_top_classes=3)
+
+    send_btn = gr.Button("Infer")
+    send_btn.click(fn=predict, inputs=input_image, outputs=output_label)
+
+    with gr.Row():
+        gr.Examples(['./lion.jpg']   , label='Sample images : Lion', inputs=input_image)
+        gr.Examples(['./cheetah.jpg'], label='Cheetah'             , inputs=input_image)
+
+# gr.Interface(fn=predict,
+#              inputs=gr.Image(type="pil"),
+#              outputs=gr.Label(num_top_classes=3),
+#              examples=["lion.jpg", "cheetah.jpg"]).launch()
 
 demo.launch()