Apache Spark Deep Learning Cookbook

How to do it...

This section walks through the steps to convert a sample of MNIST arrays to files in a local folder.

1. Create a subfolder to save our images to our main folder of MNIST/ using the following script:

if not os.path.exists('MNIST/images'):   os.makedirs('MNIST/images/')os.chdir('MNIST/images/')

2. Loop through the first 10 samples of MNIST arrays and convert them to .png files using the following script:

from matplotlib import imagefor i in range(1,10):     png = data.train.images[i]     png = np.array(png, dtype='float')     pixels = png.reshape((28, 28))     image.imsave('image_no_{}.png'.format(i), pixels, cmap = 'gray')

3. Execute the following script to see the list of images from image_no_1.png to image_no_9.png:

print(os.listdir())