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)
    _, _, probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

gr.Interface(
    fn=predict,
    inputs=gr.components.Image(shape=(400, 400)),
    outputs=gr.components.Label(num_top_classes=2),
    title="Does my sighthound have a corn?",
    description="Given a picture of a paw, does it have a corn?",
    examples=[
        "corn_01.jpg",
        "corn_02.jpg",
        "corn_03.jpg",
        "no_corn_01.jpg",
        "no_corn_02.jpg",
    ],
).launch(enable_queue=True)