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


learn = load_learner('model.pkl')


labels = learn.dls.vocab
def predict(img):
    pil_img = PILImage.create(img)
    pred, pred_idx, probs = learn.predict(pil_img)
    result = {}
    for label_idx, label in enumerate(labels):
        result[label] = float(probs[label_idx])
    return result


gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(shape=(512, 512)),
    outputs=gr.outputs.Label(num_top_classes=3),
    examples=['border_collie.jpg'],
).launch()