app.py

#!/usr/bin/env python3

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

learn = load_learner("hotdog.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))}


title = "Hotdog or Not?"
description = "Upload a picture of a hotdog or hamburger and be amazed!"
examples = ["hotdog.jpg"]
interpretation = "default"
enable_queue = True

gr.Interface(
    fn=predict,
    inputs=gr.components.Image(shape=(512, 512)),
    outputs=gr.components.Label(num_top_classes=3),
    title=title,
    description=description,
    # examples=examples,
    interpretation=interpretation,
).launch(enable_queue=enable_queue)