from fastai.vision import *
import gradio as gr
from fastbook import *
import os
import glob

def classify_digit_type(img):
    name = os.path.basename(os.path.normpath(img))
    return name[0]

learn = load_learner('model.pkl')

categories = ('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')


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(shape=(512, 512)), outputs=gr.Label(num_top_classes=3)).launch(share=False)