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import gradio as gr
from fastai.vision.all import *
import skimage
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 classifier that differentiates between grizzly, black, and teddy bears."
examples = [f'examples/{bear_type}.jpg' for bear_type in {'grizzly', 'black', 'teddy'}]
queue_size = 20
demo = gr.Interface(
fn=predict,
inputs=gr.Image(width=512, height=512),
outputs=gr.Label(num_top_classes=3),
title=title,
description=description,
examples=examples
)
demo.queue(max_size=queue_size)
demo.launch()
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