app.py

from fastai.vision.all import *
import gradio as gr


#is_black(x) : return x[0].isupper()
categories=('Black people','White people')
def func_classi(image):
    learn=load_learner('model.pkl')
    race,_,probs = learn.predict(PILImage.create(image))
    print(f"This is a: {race}.")
    print(f"Probability it's a black person: {probs[0]:.4f}.\nProbability it's a white person: {probs[1]:.4f}")

    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=('Black people','White people')
demo = gr.Interface(fn=func_classi, inputs=[gr.func_classi()], outputs=[gr.Textbook(label="Results")])
demo.launch(inline=False)