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app.py

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+
+import gradio as gr
+from fastai.vision.all import *
+
+def is_cat(x): return x[0].isupper()
+
+learn = load_learner('zebra_model.pkl')
+
+categories = ('Zebra', 'Zebra_crossing')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['zebra.jpg', 'zebra_crossing.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)