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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 = img.resize((512, 512))
img = PILImage.create(img)
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
title = "Camel or a Llama ?"
examples = ['llama_beauty.jpg']
interpretation='default'
enable_queue=True
gr.Interface(
fn=predict,
inputs=gr.Image(type="pil"),
outputs=gr.Label(num_top_classes=3),
title=title,
examples=examples,
).launch(share=True)
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