akesling · August 15, 2024 03:08 · Aug 11, 2022 · Apr 11, 2013 · Apr 11, 2013 · Apr 10, 2013
diff --git a/mnist.py b/mnist.py
@@ -3,6 +3,10 @@
 import numpy as np
 
 """
+MNist loading helper for Python 2.7.
+
+For Python 3.x, see https://gist.github.com/akesling/42393ccb868125071fdea77d98a0d2f0
+
 Loosely inspired by http://abel.ee.ucla.edu/cvxopt/_downloads/mnist.py
 which is GPL licensed.
 """

diff --git a/mnist.py b/mnist.py
@@ -42,11 +42,12 @@ def show(image):
     """
     Render a given numpy.uint8 2D array of pixel data.
     """
+    from matplotlib import pyplot
     import matplotlib as mpl
-    fig = figure()
+    fig = pyplot.figure()
     ax = fig.add_subplot(1,1,1)
     imgplot = ax.imshow(image, cmap=mpl.cm.Greys)
     imgplot.set_interpolation('nearest')
     ax.xaxis.set_ticks_position('top')
     ax.yaxis.set_ticks_position('left')
-    mpl.pyplot.show()
+    pyplot.show()
diff --git a/mnist.py b/mnist.py
@@ -43,7 +43,7 @@ def show(image):
     Render a given numpy.uint8 2D array of pixel data.
     """
     import matplotlib as mpl
-    fig = mpl.pyplot.figure()
+    fig = figure()
     ax = fig.add_subplot(1,1,1)
     imgplot = ax.imshow(image, cmap=mpl.cm.Greys)
     imgplot.set_interpolation('nearest')

diff --git a/mnist.py b/mnist.py
@@ -0,0 +1,52 @@
+import os
+import struct
+import numpy as np
+
+"""
+Loosely inspired by http://abel.ee.ucla.edu/cvxopt/_downloads/mnist.py
+which is GPL licensed.
+"""
+
+def read(dataset = "training", path = "."):
+    """
+    Python function for importing the MNIST data set.  It returns an iterator
+    of 2-tuples with the first element being the label and the second element
+    being a numpy.uint8 2D array of pixel data for the given image.
+    """
+
+    if dataset is "training":
+        fname_img = os.path.join(path, 'train-images-idx3-ubyte')
+        fname_lbl = os.path.join(path, 'train-labels-idx1-ubyte')
+    elif dataset is "testing":
+        fname_img = os.path.join(path, 't10k-images-idx3-ubyte')
+        fname_lbl = os.path.join(path, 't10k-labels-idx1-ubyte')
+    else:
+        raise ValueError, "dataset must be 'testing' or 'training'"
+
+    # Load everything in some numpy arrays
+    with open(fname_lbl, 'rb') as flbl:
+        magic, num = struct.unpack(">II", flbl.read(8))
+        lbl = np.fromfile(flbl, dtype=np.int8)
+
+    with open(fname_img, 'rb') as fimg:
+        magic, num, rows, cols = struct.unpack(">IIII", fimg.read(16))
+        img = np.fromfile(fimg, dtype=np.uint8).reshape(len(lbl), rows, cols)
+
+    get_img = lambda idx: (lbl[idx], img[idx])
+
+    # Create an iterator which returns each image in turn
+    for i in xrange(len(lbl)):
+        yield get_img(i)
+
+def show(image):
+    """
+    Render a given numpy.uint8 2D array of pixel data.
+    """
+    import matplotlib as mpl
+    fig = mpl.pyplot.figure()
+    ax = fig.add_subplot(1,1,1)
+    imgplot = ax.imshow(image, cmap=mpl.cm.Greys)
+    imgplot.set_interpolation('nearest')
+    ax.xaxis.set_ticks_position('top')
+    ax.yaxis.set_ticks_position('left')
+    mpl.pyplot.show()
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