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

learner = load_learner('export.pkl')
labels = learner.dls.vocab
examples = ['tiger-lily.jpg']
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learner.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3),examples=examples).launch()