import numpy as np

import keras.models

from keras.models import model_from_json

from scipy.misc import imread, imresize,imshow

json_file = open('model.json','r')

loaded_model_json = json_file.read()

json_file.close()

loaded_model = model_from_json(loaded_model_json)

loaded_model.load_weights("model.h5")

print("Loaded Model from disk")

loaded_model.compile(loss='categorical_crossentropy',optimizer='adam',metrics=['accuracy'])

x = imread('output.png',mode='L')

x = np.invert(x)

x = imresize(x,(28,28))

imshow(x)

x = x.reshape(1,28,28,1)

out = loaded_model.predict(x)

print(out)

print(np.argmax(out,axis=1))