app.py

import streamlit as st
import json
import requests
import matplotlib.pyplot as plt
import numpy as np
st.set_option('deprecation.showPyplotGlobalUse', False)
URI = 'https://ml-server-lol-1.herokuapp.com'

st.title('Neural Network Visualizer')
st.sidebar.markdown('## Input Image')

if st.button('Get random prediction'):
    response = requests.post(URI, data={})
    response = json.loads(response.text)
    preds = response.get('prediction')
    image = response.get('image')
    image = np.reshape(image,(28,28))
    
    st.sidebar.image(image,width=150)
    
    for layer, p in enumerate(preds):
        numbers = np.squeeze(np.array(p))
        plt.figure(figsize=(32,4))
        
        if layer==2:
            row=1
            col=10
        else:
            row=2
            col=16
            
        for i,number in enumerate(numbers):
            plt.subplot(row,col,i+1)
            plt.imshow(number*np.ones((8,8,3)).astype('float32'))
            plt.xticks([])
            plt.yticks([])
            
            if layer==2:
                plt.xlabel(str(i), fontsize=40)
        plt.subplots_adjust(wspace=0.05,hspace=0.05)
        plt.tight_layout()
        st.text('Layer {}'.format(layer+1))
        st.pyplot()