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app.py
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import gradio as gr
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from fastai.vision.all import *
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import skimage
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learn load_learner('export.pkl')
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labels = learn.dls.vocab
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def predict(img):
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img = PILImage.create(img)
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pred, pred_idx, probs = learn.predict(img)
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return {labels[i]: float(probs[i]) for i in range(len(labels))}
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title = 'NYC Iconic Buildings Classifier'
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description = 'This is a classifier based on fastai course, lesson 2.'
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examples = []
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interpretation = 'default'
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enable_queue = True
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gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),
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outputs=gr.outputs.Label(num_top_classes=3), title=title,
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description=description, examples=examples,
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interpretation=interpretation, enable_queue=enable_queue).launch()
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