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

def label_func(x):
    if x.name[0] == 'm':
        return "Mustang"
    elif x.name[1] == "a":
        return "Camaro"
    elif x.name[1] == "h":
        return "Challenger" 

learn = load_learner('export-2.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))}

gr.Interface(fn=predict, inputs=gr.Image(type='pil'), outputs=gr.Label(num_top_classes=3)).launch(share=True)