Update app.py

app.py

@@ -21,25 +21,23 @@ def predict(inp):
 
 import gradio as gr
 
-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>""")
+demo = gr.Blocks(title="Image Classification for 1000 Objects", css=".gradio-container {background:mintcream;}")
+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)
+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)
+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)
+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()
+demo.launch(debug=True)