loading_the_data.py

# 10% of the data will automatically be used for validation
validation_size = 0.1
img_size = 48 # resize images to be 48x48
num_channels = 3 # RGB
sample_size = 8192 #We'll use 8192 pictures (2**13)

data = dataset.read_train_sets(train_path, img_size, ['cats'],
                               validation_size=validation_size, 
                               sample_size=sample_size)

x_train, _, _, _ = data.train.next_batch(7373) #no need to load them in batches
x_valid, _, _, _ = data.valid.next_batch(819)  # now that tensorflow can do it
x_train[0] # array([[[0.6784314 , 0.6784314 , 0.7019608 ], ...)