コード例 #1
0
ファイル: mnist_show.py プロジェクト: MSMHMA/cmsc12300
                       help='Directory containing the MNIST files')
    parser.add_argument('-d', '--dataset', dest='dataset', action='store', required=True,
                        choices = ("TEST","TRAIN"),
                        help='Dataset to use (testing or training)')
    parser.add_argument('-i', '--index', dest='index', action='store', type=int, required=True,
                       help="Image index")

    args = parser.parse_args()
    
    return args

args = parse_command_line_arguments()

datadir = args.datadir
dataset = args.dataset
idx = args.index

if dataset == "TRAIN":
    data = MNISTReader("%s/train-images-idx3-ubyte" % datadir, "%s/train-labels-idx1-ubyte" % datadir)
elif dataset == "TEST":
    data = MNISTReader("%s/t10k-images-idx3-ubyte" % datadir, "%s/t10k-labels-idx1-ubyte" % datadir)

img = data.get_image(idx)

print img.as_asciiart()
print "Labelled as %d" % img.label

img.as_image().show()


コード例 #2
0
ファイル: knn_mnist.py プロジェクト: ykaravas/cmsc12300
                        help="Image index")

    args = parser.parse_args()

    return args


args = parse_command_line_arguments()

datadir = args.datadir
k = args.k
idx = args.index

if idx == None:
    train = MNISTReader("%s/train-images-idx3-ubyte" % datadir,
                        "%s/train-labels-idx1-ubyte" % datadir,
                        preload=True)
    test = MNISTReader("%s/t10k-images-idx3-ubyte" % datadir,
                       "%s/t10k-labels-idx1-ubyte" % datadir,
                       preload=True)
else:
    train = MNISTReader("%s/train-images-idx3-ubyte" % datadir,
                        "%s/train-labels-idx1-ubyte" % datadir)
    test = MNISTReader("%s/t10k-images-idx3-ubyte" % datadir,
                       "%s/t10k-labels-idx1-ubyte" % datadir)

if idx == None:
    i = 0
    for p, known_label in test.images(as_array=True):
        label, nearest = knn(p, train.images(as_array=True), k)
コード例 #3
0
ファイル: mnist_show.py プロジェクト: ykaravas/cmsc12300
                        dest='index',
                        action='store',
                        type=int,
                        required=True,
                        help="Image index")

    args = parser.parse_args()

    return args


args = parse_command_line_arguments()

datadir = args.datadir
dataset = args.dataset
idx = args.index

if dataset == "TRAIN":
    data = MNISTReader("%s/train-images-idx3-ubyte" % datadir,
                       "%s/train-labels-idx1-ubyte" % datadir)
elif dataset == "TEST":
    data = MNISTReader("%s/t10k-images-idx3-ubyte" % datadir,
                       "%s/t10k-labels-idx1-ubyte" % datadir)

img = data.get_image(idx)

print img.as_asciiart()
print "Labelled as %d" % img.label

img.as_image().show()
コード例 #4
0
ファイル: knn_mnist.py プロジェクト: MSMHMA/cmsc12300
                       help='Number of neighbors to use')
    parser.add_argument('-i', '--index', dest='index', action='store', type=int,
                       help="Image index")

    args = parser.parse_args()
    
    return args

args = parse_command_line_arguments()

datadir = args.datadir
k = args.k
idx = args.index

if idx == None:
    train = MNISTReader("%s/train-images-idx3-ubyte" % datadir, "%s/train-labels-idx1-ubyte" % datadir, preload=True)
    test = MNISTReader("%s/t10k-images-idx3-ubyte" % datadir, "%s/t10k-labels-idx1-ubyte" % datadir, preload=True)
else:
    train = MNISTReader("%s/train-images-idx3-ubyte" % datadir, "%s/train-labels-idx1-ubyte" % datadir)
    test = MNISTReader("%s/t10k-images-idx3-ubyte" % datadir, "%s/t10k-labels-idx1-ubyte" % datadir)

if idx == None:
    i = 0
    for p, known_label in test.images(as_array=True):
        label, nearest = knn(p, train.images(as_array=True), k)
        
        if label == known_label:
            x=""
        else:
            x="XXX"
コード例 #5
0
ファイル: kmeans_mnist.py プロジェクト: ykaravas/cmsc12300
    parser.add_argument('-o', '--outfile', metavar='FILE', dest='outfile', action='store',
                       help='The file to save k-mean images to. If none is specified, the image is displayed interactively.')
    parser.add_argument('-t', '--threshold', dest='cutoff', action='store', type=float, default=100.0,
                       help="Converge once the centroids move less than this threshold.")

    args = parser.parse_args()
    
    return args

args = parse_command_line_arguments()

k = args.k
cutoff = args.cutoff

print "Loading data..."
test = MNISTReader("%s/t10k-images-idx3-ubyte" % args.datadir, "%s/t10k-labels-idx1-ubyte" % args.datadir)

points = None
for img in test.images():
    if points is None:
        points = numpy.array([img.imgdata])
    else:
        points = numpy.append(points, [img.imgdata], axis=0)

km = KMeans(points, k)

centroids = km.select_random_centroids()

iteration=1
while True:
    print "Iteration #%i" % iteration