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

def label_func(x):
    return x.parent.name

learn = load_learner('model.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 = "MNIST"
description = "Fast.ai Lesson 2"
interpretation = 'default'
enable_queue = True

gr.Interface(
    fn = predict,
    inputs = gr.inputs.Image(shape= (512,512)),
    outputs = gr.outputs.Label(num_top_classes = 10),
    title = title,
    description = description,
    interpretation = interpretation,
    enable_queue = enable_queue    
).launch()