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Upload 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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+
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+ learn = load_learner('export.pkl')
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+
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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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+
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+ title = "Laboratory Equipment Classifier"
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+ description = "Basice laboratory classifier trained on the images from duckduckgo with fastai. Created as a demo for Gradio and HuggingFace Spaces."
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+ examples = ['dropper.jpg']
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+ interpretation='default'
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+ enable_queue=True
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+
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+ gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()