app.py

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

title = "Homer or Peter"
examples = ["homer_1.jpg",
            "homer_2.jpg",
            "homer_3.jpg",
            "peter_1.jpg",
            "peter_2.jpg"]
interpretation='default'
enable_queue=True

learn = load_learner('homer-or-peter.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.components.Image(shape=(512, 512)),
             outputs=gr.components.Label(num_top_classes=3),
             title=title,
             examples=examples,
             interpretation=interpretation
            ).launch(enable_queue=enable_queue)