use image model

app.py

@@ -1,8 +1,16 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+learn = load_learner('cat_or_dog.pkl')
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+def predict(image):
+    img = PILImage.create(image)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+gr.Interface(
+    fn=predict, 
+    inputs=gr.inputs.Image(shape=(512, 512)), 
+    outputs=gr.outputs.Label(num_top_classes=3)
+).launch(share=True)
 
 demo.launch()