app.py

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


learn = load_learner('export.pkl')

labels = learn.dls.vocab


def predict(img):
    img = PILImage.create(img)
    pred, pred_idx, probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}


gr.Interface(fn=predict, inputs=gr.Image(type="pil"),
             outputs=gr.Label(num_top_classes=3), examples=['dog1.jfif', 'dog2.jfif']).launch(share=True)