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let's deploy to huggingface spaces
Browse files
app.py
CHANGED
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import gradio as gr
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iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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iface.launch()
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from fastai.vision.all import *
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import gradio as gr
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learner = load_learner('export.pkl')
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labels = learner.dls.vocab
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examples = ['tiger-lily.jpg']
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def predict(img):
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img = PILImage.create(img)
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pred,pred_idx,probs = learner.predict(img)
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return {labels[i]: float(probs[i]) for i in range(len(labels))}
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gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3),examples=examples).launch(share=True)
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