from fastai.vision.all import *
from huggingface_hub import push_to_hub_fastai, from_pretrained_fastai
import gradio as gr

learn = from_pretrained_fastai("robinsk8a/exotic_cars_classifier")

categories = ('Dog', 'Cat''ferrari','lamborghini','mclaren','aston martin','koenigsegg','porsche','pagani')

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))


image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples=['bmw.jpg', 'lamborghini.jpg', 'koenigsegg.jpg'],

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch()