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import fastai.vision.all import *
import gradio as gr
learn = load_learner('model.pkl')
categories = ('wet','tawny','horned')
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
image = gr.inputs.Image(shape=(224,224))
label = gr.outputs.label()
examples = ['harpy.jpg','horned.jpg']
iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
iface.launch()
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