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

learn = load_learner('model.pth')

def classify_image(img):
    celebrity_name,_,probs = learn.predict(img)
    results = dict(zip(list(learn.dls.vocab),probs))
    best_results = sorted(results, key=results.get, reverse=True)[:5]
    probabilities = {key: float(results[key]) for key in best_results}
    return probabilities

image = gr.inputs.Image(shape=(224,224))
label = gr.outputs.Label()
examples = ['emma_watson.jpg', "tom_hanks.jpeg"]

iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
iface.launch(inline=False)