def saveImages(self):
for index in range(self.length):
image = self.getImageFromName(self.namesObservations[index])
imageWorker = RGBImageWorker(image, self.rows, self.columns)
patch = imageWorker.getPatch(self.coordinates[index], self.patchSize)
reducedFileName = "%s_%d.tif" % (Utils.getFolderName(self.namesObservations[index]), index)
if self.targetVector is None:
fileName = os.path.join(data_io.get_testing_folder(), data_io.get_test_folder(), reducedFileName)
elif self.targetVector[index] == 1:
fileName = os.path.join(data_io.get_training_folder(), data_io.get_positive_folder(), reducedFileName)
else:
fileName = os.path.join(data_io.get_training_folder(), data_io.get_negative_folder(), reducedFileName)
io.imsave(fileName, patch.image)
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 saveImages(self):
for index in range(self.length):
image = self.getImageFromName(self.namesObservations[index])
imageWorker = RGBImageWorker(image, self.rows, self.columns)
patch = imageWorker.getPatch(self.coordinates[index],
self.patchSize)
reducedFileName = "%s_%d.tif" % (Utils.getFolderName(
self.namesObservations[index]), index)
if self.targetVector is None:
fileName = os.path.join(data_io.get_testing_folder(),
data_io.get_test_folder(),
reducedFileName)
elif self.targetVector[index] == 1:
fileName = os.path.join(data_io.get_training_folder(),
data_io.get_positive_folder(),
reducedFileName)
else:
fileName = os.path.join(data_io.get_training_folder(),
data_io.get_negative_folder(),
reducedFileName)
io.imsave(fileName, patch.image)
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())
