from fastai.vision.all import *
import gradio as gr
from gradio.components import Image, Label
import glob

learn = load_learner('export.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 = Image(size = (128, 128)),
             outputs = Label(num_top_classes = 3),
             examples = ['0001_0170.jpg', '0003_0179.jpg', '0005_0268.jpg', '0008_0148.jpg', '0015_0123.jpg', '0016_0118.jpg', '0019_0276.jpg', '0020_0271.jpg']).launch(share=False)