# from fastbook import *
from fastai.vision.all import *

path = Path()
path.ls(file_exts='.pkl')

learn_inf = load_learner(path/'export.pkl')

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

p = predict('images/grizzly.jpg')

print(p)

import gradio as gr
gr.Interface(examples=['images/grizzly.jpg'],fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)

# print(learn_inf.dls.vocab)