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app.py

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+__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+
+from fastai.vision.all import *
+import gradio as gr
+
+def is_cat(x): return x[0].isupper()
+
+learn = load_learner('model.pkl')
+
+categories = ('Dog', 'Cat')
+
+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 = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9a5ab7a99bd9dbf6a61154075a5169375f9dbf14e32df6db5c49adef846b1e8d
+size 47061419

requirements.txt

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+fastai
+torch
+gradio
+numpy
+pandas <2.0.0