def prepareEnvironment(self):
# People want to save time
trainingPathPositive = os.path.join(data_io.get_training_folder(), data_io.get_positive_folder())
trainingPathOldPositive = os.path.join(data_io.get_training_old_folder(), data_io.get_positive_folder())
Utils.shift(data_io.get_training_old_folder(), trainingPathOldPositive, data_io.get_positive_folder(), trainingPathPositive)
trainingPathNegative = os.path.join(data_io.get_training_folder(), data_io.get_negative_folder())
trainingPathOldNegative = os.path.join(data_io.get_training_old_folder(), data_io.get_negative_folder())
Utils.shift(data_io.get_training_old_folder(), trainingPathOldNegative, data_io.get_negative_folder(), trainingPathNegative)
os.mkdir(trainingPathPositive)
os.mkdir(trainingPathNegative)
if not self.load:
Utils.shift('.', data_io.get_savez_name(), data_io.get_savez_name(), data_io.get_savez_name())
if not self.loadWndchrm:
Utils.shift('.', data_io.get_wndchrm_dataset(), data_io.get_wndchrm_dataset(), data_io.get_wndchrm_dataset())
def executeWndchrm(self):
command = ["wndchrm", "train", data_io.get_training_folder(), data_io.get_wndchrm_datafit()]
subprocess.call(" ".join(command), shell=True)
(train, target) = self.parseWndchrmOutput()
outfile = open(data_io.get_wndchrm_dataset(), "wb")
np.savez(outfile, train=train, target=target)
return (train, target)
def prepareEnvironment(self):
# People want to save time
trainingPathPositive = os.path.join(data_io.get_training_folder(),
data_io.get_positive_folder())
trainingPathOldPositive = os.path.join(
data_io.get_training_old_folder(), data_io.get_positive_folder())
Utils.shift(data_io.get_training_old_folder(), trainingPathOldPositive,
data_io.get_positive_folder(), trainingPathPositive)
trainingPathNegative = os.path.join(data_io.get_training_folder(),
data_io.get_negative_folder())
trainingPathOldNegative = os.path.join(
data_io.get_training_old_folder(), data_io.get_negative_folder())
Utils.shift(data_io.get_training_old_folder(), trainingPathOldNegative,
data_io.get_negative_folder(), trainingPathNegative)
os.mkdir(trainingPathPositive)
os.mkdir(trainingPathNegative)
if not self.load:
Utils.shift('.', data_io.get_savez_name(),
data_io.get_savez_name(), data_io.get_savez_name())
if not self.loadWndchrm:
Utils.shift('.', data_io.get_wndchrm_dataset(),
data_io.get_wndchrm_dataset(),
data_io.get_wndchrm_dataset())
def loadWndchrmFeatures(self):
outfile = open(data_io.get_wndchrm_dataset(), "rb")
npzfile = np.load(outfile)
train = npzfile['train']
target = npzfile['target']
return (train, target)
