Update app.py
Browse files
app.py
CHANGED
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@@ -10,7 +10,7 @@ learn = load_learner("resnet152_fit_one_cycle_freeze_91acc.pkl", cpu=True)
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categories = ('arbanasi', 'filibe', 'gjirokoster', 'iskodra', 'kula', 'kuzguncuk', 'larissa_ampelakia', 'mardin', 'ohrid', 'pristina', 'safranbolu', 'selanik', 'sozopol_suzebolu', 'tiran', 'varna')
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def classify_img(img):
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pred,idx,probs=learn.predict(img)
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return dict(zip(categories, map(float, probs)))
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image=gr.inputs.Image(shape=(128,128))
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label=gr.outputs.Label()
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@@ -24,6 +24,6 @@ examples=["filibe-1-1.jpg",
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"varna-1-1.jpg"]
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demo = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples_)
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demo.launch(inline=False)
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categories = ('arbanasi', 'filibe', 'gjirokoster', 'iskodra', 'kula', 'kuzguncuk', 'larissa_ampelakia', 'mardin', 'ohrid', 'pristina', 'safranbolu', 'selanik', 'sozopol_suzebolu', 'tiran', 'varna')
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def classify_img(img):
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pred,idx,probs=learn.predict(img)
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return dict(zip(categories, map(float, probs))), img.split("/")[2]
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image=gr.inputs.Image(shape=(128,128))
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label=gr.outputs.Label()
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"varna-1-1.jpg"]
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demo = gr.Interface(fn=classify_img, inputs=image, outputs=[label,"text"], examples=examples_)
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demo.launch(inline=False)
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