bear classifier

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+# def is_cat(x): return x[0].isupper()
+
+# Cell
+learn = load_learner('model.pkl')
+
+# Cell
+categories = ('Black Bear', 'Grizzly', 'Teddy')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+# Cell
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['grizzly.jpg', 'blackbear.jpg', 'teddy.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

bearmodel.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b4e20034852920aad8f5baa870c60189b896bb0138f65c77e2b947d3b2d66c2d
+size 46983265

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b4e20034852920aad8f5baa870c60189b896bb0138f65c77e2b947d3b2d66c2d
+size 46983265

requirements.txt

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+fastai