using gradio blocks

app.py

@@ -18,6 +18,19 @@ def sashimiIentifer(input_imgFilePath):
     (pred,idx,probs) = learner.predict(input_imgFilePath)
     return dict(zip(categories, map(float, probs)))
   
-img_examples = ["Hotate_Scallops.jpg", "Ahi_YellowfinAndBigeyeTuna_Sashimi.jpg", "dalle_EngawaAndHotate.png"]
-iface = gr.Interface(fn=sashimiIentifer, inputs="image", outputs="label", examples =img_examples, title="Sashimi Identier", description="This app identifies which sashimi it is based on the given image")
-iface.launch()
+img_examples1 = ["Hotate_Scallops.jpg", "Ahi_YellowfinAndBigeyeTuna_Sashimi.jpg"]
+img_examples2 = [ "dalle_EngawaAndHotate.png"]
+
+demo = gr.Blocks()
+
+with demo:
+  with gr.Row():
+    input = gr.inputs.Image(shape=(192,192))
+    output = gr.outputs.Label()
+  with gr.Tab("Example Images from Web"):
+    examplesFromBrowser = gr.Examples(examples=img_examples1, inputs=input)
+  with gr.Tab("Example Images generated by AI"):
+    examplesFromAI = gr.Examples(examples=img_examples2,inputs=input)
+  input.change(fn=sashimiIentifer, inputs=input, outputs=output)
+
+demo.launch()