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from fastai.vision.all import *
import gradio as gr
import pathlib
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
learn = load_learner('export.pkl')
labels = learn.dls.vocab
def predict(img):
img = PILImage.create(img)
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
title = "Bear Classifier"
description = "A bear classifier trained on downloaded images of bear dataset with fastai."
article="<p style='text-align: center'><a href='https://shuowangphd.github.io' target='_blank'>Back to my personal webpage.</a></p>"
exa = [['grizzly.jpg'],['teddy.jpg']]
interpretation='default'
enable_queue=True
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(num_top_classes=3),
title=title,description=description,article=article,examples=exa,
interpretation=interpretation,
enable_queue=enable_queue).launch()
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