prepare images for cnn

prepare.py

import keras
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Conv2D, MaxPooling2D
import numpy as np

#reshape images to fit into the CNN model
img_list = np.zeros(shape = (len(images), h,w,1), dtype = np.uint8)
for j in range(len(images)):
    img_list[j,:,:,0] = np.reshape(list(images[j]), (h,w))
    
img_list = img_list.astype('float32')
img_list /= 255