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


def is_cat(x):
    return x[0].isupper()


learn = load_learner("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))}


iface = gr.Interface(
    fn=predict,
    inputs=gr.Image(width=512, height=512),
    outputs=gr.Label(num_top_classes=3),
)
iface.launch(share=True)