deploy my dogvcat model

app.py

@@ -1,5 +1,28 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: gradio_model_app.ipynb.
+
+# %% auto 0
+__all__ = ['categories', 'examples', 'inft', 'is_cat', 'classify_image']
+
+# %% gradio_model_app.ipynb 2
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(n): return f"Hello {n}!"
+def is_cat(x): return x[0].isupper()
+
+# %% gradio_model_app.ipynb 6
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# %% gradio_model_app.ipynb 8
+# image = gr.inputs.Image(shape=(192, 192))
+# label = gr.outputs.Label()
+examples = ['dog.jpg', 'cat.jpg', 'dunno.png']
 
-gr.Interface(fn=greet, inputs="text", outputs="text").launch()
+inft = gr.Interface(fn=classify_image, 
+                    inputs=gr.Image(shape=(192, 192)), 
+                    outputs=gr.Label(),
+                    examples=examples)
+inft.launch(inline=False)