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

learn = load_learner('movements_05_02_22_4pm.pkl')

def predict(img):
    labels = learn.dls.vocab
    im = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(im)
    return {label: float(prob) for (label,prob) in zip(labels,probs)}

examples = [f"Image{n:02d}" for n in range(25)]

gr.Interface(fn=predict,
             inputs=gr.inputs.Image(shape=((512,512))),
             outputs=gr.outputs.Label(num_top_classes=5),
             title = "Art Movements",
             examples =  examples
             description= "What Art Movement Matches the Image Best? Expressionism | Impressionism | Hudson River School | Ukiyo-e | Pre-Raphaelite").launch(share=True, enable_queue=True)