61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
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"""expand_mnist.py
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~~~~~~~~~~~~~~~~~~
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Take the 50,000 MNIST training images, and create an expanded set of
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250,000 images, by displacing each training image up, down, left and
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right, by one pixel. Save the resulting file to
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../data/mnist_expanded.pkl.gz.
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Note that this program is memory intensive, and may not run on small
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systems.
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"""
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from __future__ import print_function
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#### Libraries
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# Standard library
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import cPickle
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import gzip
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import os.path
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import random
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# Third-party libraries
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import numpy as np
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print("Expanding the MNIST training set")
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if os.path.exists("../data/mnist_expanded.pkl.gz"):
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print("The expanded training set already exists. Exiting.")
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else:
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f = gzip.open("../data/mnist.pkl.gz", 'rb')
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training_data, validation_data, test_data = cPickle.load(f)
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f.close()
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expanded_training_pairs = []
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j = 0 # counter
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for x, y in zip(training_data[0], training_data[1]):
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expanded_training_pairs.append((x, y))
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image = np.reshape(x, (-1, 28))
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j += 1
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if j % 1000 == 0: print("Expanding image number", j)
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# iterate over data telling us the details of how to
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# do the displacement
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for d, axis, index_position, index in [
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(1, 0, "first", 0),
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(-1, 0, "first", 27),
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(1, 1, "last", 0),
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(-1, 1, "last", 27)]:
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new_img = np.roll(image, d, axis)
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if index_position == "first":
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new_img[index, :] = np.zeros(28)
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else:
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new_img[:, index] = np.zeros(28)
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expanded_training_pairs.append((np.reshape(new_img, 784), y))
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random.shuffle(expanded_training_pairs)
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expanded_training_data = [list(d) for d in zip(*expanded_training_pairs)]
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print("Saving expanded data. This may take a few minutes.")
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f = gzip.open("../data/mnist_expanded.pkl.gz", "w")
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cPickle.dump((expanded_training_data, validation_data, test_data), f)
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f.close()
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