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

learn = load_learner("house_model.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))}


title = "House Style Classifier"
description = (
    "Classifier that will classify a style of house into modern, ranch or victorian."
)
examples = ["modern_house.jpg", "ranch_house.jpg", "victorian_house.jpg"]
interpretation = "default"
gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(shape=(512, 512)),
    outputs=gr.outputs.Label(num_top_classes=3),
    title=title,
    description=description,
    examples=examples,
    interpretation=interpretation,
).launch()