app.py

import gradio as gr
import tensorflow as tf
import keras
from keras.datasets import mnist
import matplotlib.pyplot as plt
import random

(train_images, train_labels), (test_images, test_labels) = mnist.load_data()

def get_digit(digit_choice):
  rn = 0
  while(test_labels[rn] != digit_choice):
    rn = int(random.random() * 1000)
  digit = train_images[rn]
  fig = plt.figure()
  plt.imshow(digit)
  out_txt = "digit index: %d\ndigit label: %d" % digit_choice, rn
  return fig, out_txt

iface = gr.Interface(
  fn = get_digit,
  #inputs='image',
  #inputs=[gr.inputs.Image(label="Input Image", source="webcam")],
  inputs = [ 
    gr.inputs.Dropdown([0, 1, 2, 3])
    #gr.inputs.Number()
    #'text'
  ],
  #outputs='image',
  outputs=[gr.outputs.Image(type="plot"), 'text'],
  title='page title',
  description='page description'
)
  
iface.launch()