#Import necessary libraries
import gradio as gr
from fastai.vision.all import *
import skimage


bear_learner = load_learner('export.pkl')

#Create function that accepth image path and 
labels = bear_learner.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred, idx, probs = bear_learner.predict(img)
    return {labels[i]: round(float(probs[i]), 2) for i in range(len(labels))}

examples = ["black_bear.jpg", "teddy_bear.jpg"]
#interface = 
gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label()).launch()