from fastai.vision.all import *
import gradio as gr
learn=load_learner('model.pkl')
is_black,_,probs = learn.predict(PILImage.create('black people.jpg'))
print(f"This is a: {is_black}.")
processed_output = print(f"Probability it's a black person: {probs[0]:.4f}")
return processed_output


#is_black(x) : return x[0].isupper()
categories=('white people','black people')
def func_classi(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=('white people','black people')
demo = gr.Interface(fn=func_classi, inputs="image", outputs="label")
demo.launch(inline=False)