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import gradio as gr
from fastai.vision.all import *
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))}
iface = gr.Interface(
fn=predict,
inputs=gr.components.Image(shape=(512, 512)),
outputs=gr.components.Label(num_top_classes=3),
description="Pet Classifier",
article="<p style='text-align: center'><a href='google.com' target='_blank'>Blog post</a></p>",
live=True,
enable_queue=True,
)
iface.launch()
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