app.py

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

learn = load_learner('export.pkl')
labels = learn.dls.vocab

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

title = "Currawong vs Magpie Classifier"
description = "Distinguish between two often-confused birds - the Magpie and the Currawong"
examples = ['magpie.jpg', 'currawong.jfif']
gr.Interface(
    title=title,
    description=description,
    examples=examples,
    interpretation='default', 
    enable_queue=True,
    fn=predict,
    inputs=gr.inputs.Image(shape=(256,256)),
    outputs=gr.outputs.Label(num_top_classes=2)
).launch()