Keras Image Processing

import numpy as np

from keras.preprocessing import image

# Loading images

img_path = '2.png'

# Loading grayscale image for MNIST 

img = image.load_img(img_path, target_size=(28, 28), grayscale=True)

# Loading color image for CIFAR-10 

# img = image.load_img(img_path, target_size=(32, 32))

# Converting images to numpy

x = image.img_to_array(img)

# Inverting and normalizing image

x = 255 - x

x /= 255

x = np.expand_dims(x, axis=0)

# For Dense network

x = x.reshape(1,784)

# Create a model

prediction = model.predict(x)

print(np.argmax(prediction))