import gradio as gr
from fastai.vision.widgets import PILImage
from huggingface_hub import from_pretrained_fastai

hf_learn = from_pretrained_fastai("admarhi/towerificator")
labels = hf_learn.dls.vocab

pisa_dest = 'pisa.jpg'
burj_dest = 'burj.jpg'
eiffel_dest = 'eiffel.jpg'


def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = hf_learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Towerificator 3000"
desc = '''Introducing the Towerificator 3000 – the AI-powered marvel that can tell a tower from a flower, a skyscraper from a skysquawker, and a spire from a satire! Our image classifier is so advanced, it can spot a tower in a haystack or even distinguish between a castle tower and a tower of pizza. 

Equipped with the latest in artificial intelligence, our Towerificator has a PhD in Towerology (the study of towers, obviously) and a black belt in "Tower-fu." It can identify towers faster than you can say, "Why did the tower apply for a job? Because it needed a high-rise!" 

So, if you've ever looked at a skyline and thought, "What in the name of pixelated panoramas is that?" – fear not! The Towerificator 3000 is here to sort your towers from your troubles, all while sprinkling a dash of wit on your image classification journey. Because when it comes to towers, our AI doesn't just classify; it towerfies!'''

iface = gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(num_top_classes=6), examples = [burj_dest, pisa_dest, eiffel_dest], title=title, description=desc)
iface.launch()