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


def classify(the_image):
    prediction, index, probs = learn.predict(the_image)
    probs_floats = map(float, probs)
    cat_probs = zip(categories, probs_floats)
    return dict(cat_probs)


learn = load_learner('architecture_model.pkl')
categories = learn.dls.vocab

image = gr.Image(type='pil')
label = gr.Label()
examples = ['tudor_cottage.jpg', 'georgian_terrace.jpg']

intf = gr.Interface(fn=classify, inputs=image, outputs=label, examples=examples, title="Architecture Classifier")
intf.launch(inline=False)