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from fastai.vision.all import *
import gradio as gr
def is_cat(x): return x[0].isupper()
learn = load_learner('model.pkl')
categories = ('Dog', 'Cat')
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['dog.jpeg', 'cat.jpeg', 'elephant.jpeg']
intf = gr.Interface(fn=classify_image,inputs=gr.Image(type="pil"), outputs=gr.Label(), examples=examples)
intf.launch(inline=False)
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