def writeNomalize(mode):
if mode is 0:
# read training set
imagesPath = "train-images-idx3-ubyte-nomalized"
else:
imagesPath = "t10k-images-idx3-ubyte-nomalized"
dataset = MNISTHelper.readDatabase(mode)
lenght = len(dataset)
with open(imagesPath, "w") as f:
f.write(struct.pack(">I", 2051))
f.write(struct.pack(">I", len(dataset)))
count = 0
for data in dataset:
img = data[0] * 255
vectora = FeatureExtractor.fv(img)
for value in vectora:
f.write(struct.pack(">d", value))
print "{} / {}".format(count, lenght)
count = count + 1
