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

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))}


title = "Car classifier"
description = "A car classifier in which I've being spending so much time to make a working prototype online"
examples = ['lamborghini.jpg', 'koenigsegg.jpg']
interpretation='default'
enable_queue=True

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,enable_queue=enable_queue).launch()