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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)))
with gr.Blocks() as demo:
image = gr.Image(type="pil")
label = gr.Label()
examples = gr.Examples(['dog.jpg', 'cat.jpg', 'dunno.jpg'], image)
classify_btn = gr.Button("Classify")
classify_btn.click(fn=classify_image, inputs=image, outputs=label)
# Launch the interface
demo.launch(inline=False)
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