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app.py
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app.py
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import streamlit as st
import json
import requests
import matplotlib.pyplot as plt
import numpy as np
URI='http://127.0.0.1:5000'
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()