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()
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"
print "%i %i %i %s" % (i, known_label, label, x)
sys.stdout.flush()
i+=1
else:
img = test.get_image(idx)
label, nearest = knn(img.as_array(), train.images(as_array=True), k)
print "K-NEAREST NEIGHBORS"
print "============================================================"
print
for dist, nearpoint, nearlabel in nearest:
print MNISTImage(nearpoint, nearlabel, 28, 28).as_asciiart()
print
print "CLASSIFIED IMAGE"
print "============================================================"
print
print img.as_asciiart()
print
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"
print "%i %i %i %s" % (i, known_label, label, x)
sys.stdout.flush()
i += 1
else:
img = test.get_image(idx)
label, nearest = knn(img.as_array(), train.images(as_array=True), k)
print "K-NEAREST NEIGHBORS"
print "============================================================"
print
for dist, nearpoint, nearlabel in nearest:
print MNISTImage(nearpoint, nearlabel, 28, 28).as_asciiart()
print
print "CLASSIFIED IMAGE"
print "============================================================"
print
print img.as_asciiart()
print
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()
