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 = img.resize((512, 512))
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Camel or a Llama ?"
examples = ['llama_beauty.jpg']
interpretation='default'
enable_queue=True

gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs=gr.Label(num_top_classes=3),
    title=title,
    examples=examples,
).launch(share=True)