app.py

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

learn = load_learner('movements_05_02_22_4pm.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))}

examples = [f"Image{n:02d}.jpg" for n in range(23)]
interpretation='default'
title = "Art Movement Classifier"
description = "What Art Movement Matches the Image Best? Expressionism | Impressionism | Hudson River School | Ukiyo-e | Pre-Raphaelite"

gr.Interface(fn=predict,
             inputs=gr.inputs.Image(shape=((512,512))),
             outputs=gr.outputs.Label(num_top_classes=5),
             title = title,
             examples =  examples,
             interpretation = interpretation,
             description = description).launch(share=True, enable_queue=True)