In [1]:

    

import os
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
from keras.datasets import mnist
from keras.models import load_model
from keras.utils import np_utils
import matplotlib.pyplot as plt
import numpy as np

(X_train, y_train), (X_test, y_test) = mnist.load_data()


    

    




Using TensorFlow backend.
/usr/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  return f(*args, **kwds)
/usr/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  return f(*args, **kwds)

In [16]:

    

model = load_model("perceptron.h5")
is_five_test = False
image = X_test[y_test != 5][10]
pred = model.predict(np.array([image]))[0][0]
plt.axis("off")
plt.title("label {}".format(pred))
plt.imshow(image, cmap='gray', interpolation='none')


    

    
Out[16]:





<matplotlib.image.AxesImage at 0x7f45bafffc18>






    

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