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=18),
    title=title,
    description=description,
    interpretation=interpretation,
    enable_queue=enable_queue
).launch()