import gradio as gr
import numpy as np
from keras.models import load_model

model = load_model("MNIST_model.h5")

def MNIST(arr):
    arr = arr.reshape((1,28,28,1))
    output = model(arr)
    return {idx: float(val) for idx, val in enumerate(output[0])}

iface = gr.Interface(fn=MNIST, inputs="sketchpad", outputs="label")
iface.launch()