modified app.py to include the model

app.py

@@ -1,7 +1,58 @@
-import gradio as gr
+# ---
+# jupyter:
+#   jupytext:
+#     text_representation:
+#       extension: .py
+#       format_name: light
+#       format_version: '1.5'
+#       jupytext_version: 1.15.1
+#   kernelspec:
+#     display_name: Python 3 (ipykernel)
+#     language: python
+#     name: python3
+# ---
+
+# !conda install conda=23.7.3 -y
+
+# !nbdev_migrate
+
+#|export
+# !pip install gradio
+
+#|export
+from fastai.vision.all import *
+import gradio as gd
+
+im = PILImage.create('car.jpg')
+im.thumbnail((192,192))
+im
+
+#|export
+learn = load_learner('export.pkl')
+
+# %time learn.predict(im)
+
+# +
+#|export
+categories = ('car','motorbike')
+
+def classify_images(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories,map(float,probs)))
+
+
+# -
+
+classify_images(im)
+
+# +
+#|export
+image = gd.inputs.Image(shape=(192,192))
+label = gd.outputs.Label()
+examples = ['car.jpg','bike.jpg']
+
+intf = gd.Interface(fn = classify_images,inputs = image, outputs = label, examples = examples)
+intf.launch(inline=False)
+
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()