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import gradio as gr
from fastai.vision.all import *
import skimage
from fastai.vision.all import PILImage
learn = load_learner('model.pkl')
labels = learn.dls.vocab
def predict(img):
img = PILImage.create(img)
img = img.resize((512, 512))
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
examples = ['image.jpg']
#gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
gr.Interface(fn=predict,inputs=gr.components.Image(),outputs=gr.components.Label(num_top_classes=3),examples=examples,).launch()
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